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hinh anh nguoi nong dan lam ruong - Yahoo Image Search Results

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How Smart Farming Is Renovating Traditional Farming Methods And Tools?

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Smart Farming is focussed on the use of data acquired through various sources (historical, geographical and instrumental) in the management of farm activities. Technologically advanced doesn't essentially mean that it is a smart system. Smart systems differentiate themselves through their ability to record the data and make sense out of it. Smart farming employs hardware (IoT) and software (SaaS) to capture the data and give actionable insights to manage all the operations on the farm, both pre and post harvest. The data is organized, accessible all the time and full of data on every aspect of finance and field operations that can be monitored from anywhere in the world.

DIFFERENCES BETWEEN TRADITIONAL AND SMART FARMING

Same set of practices for cultivation of a crop throughout the region

Manual maintenance of all the field and finance data separately leading to errors

Application of fertilizers and pesticides throughout the field

Geo-tagging and zone detection not possible

No way to predict weather

Each farm is analysed to see the suitable crops and water requirements for optimization

Early detection and application at the affected region only, saving costs

Field and finance data available in same place showing the profilts, yields and patterns with simple reports.

Satellite imagery detects the different zones in farms

Weather analysis and prediction

HOW AUTOMATION AND ROBOTICS HELP?

IoT (Internet of Things) in agriculture involves sensors, drones and robots connected through internet which function automatically and semi automatically performing operations and gathering data aimed at increasing efficiency and predictability. With increasing demands and shortage of labor across the globe, agriculture automation and robots or commonly known as Agribots are starting to gain attention among farmers. Crop production decreased by an estimated 213 crores approx ($3.1 billion) a year due to labor shortages in the USA alone. Recent advancements in sensors and AI technology that lets machines to train on their surroundings has made agrobots more notable. The world is in the early stages of an ag robotics revolution with most of the products still in trial phases and R&D mode.

Semi automatic robots with arms can detect weeds and spray pesticides in the affected plants, saving up the plants as well as over all pesticide costs. These robots can also be used in harvesting and lifting. Heavy farming vehicles can also be navigated from the comfort of homes through phone screens to perform tasks and GPS can track their positions at every time.

Drones equipped with sensors and cameras are used for imaging, mapping and surveying the farms. They can be remotely controlled or they can fly automatically through software-controlled flight plans in their embedded systems, working in coordination with sensors and GPS. From the drone data, insights can be drawn regarding crop health, irrigation, spraying, planting, soil and field, plant counting and yield prediction and much more.

IoT based remote sensing utilizes sensors placed along the farms like weather stations for gathering data which is transmitted to analytical tool for analysis. They monitor the crops for changes in light, humidity, temperature, shape and size. The data collected by sensors in terms of humidity, temperature, moisture precipitation and dew detection helps in determining the weather pattern in farms so that cultivation is done for suitable crops. The analysis of quality of soil helps in determining the nutrient value and drier areas of farms, soil drainage capacity or acidity, which allows to adjust the amount of water needed for irrigation and the opt most beneficial type of cultivation. Computer imaging involves the use of sensor cameras installed at different corners of the farm or drones equipped with cameras to produce images which undergo digital image processing. The images are used for quality control, disease detection, sorting and grading yield and irrigation monitoring through Image processing combined with machine learning which uses images from database to compare with images of crops to determine the size, shape, color and growth therefore controlling the quality.

Cloud based software is used for the management of financial and field activities of farms. Prior to computers, farmers maintained data manually by keeping lengthy records on papers. This method was prone to human calculation errors. After the computer boom in the 1980s, it was not long before finance softwares such as Money Counts came to market. They used spreadsheets to maintain the financial data. The biggest challenge that farmers faced was the inability to manage field data. These softwares were used to maintain finance data only. Around mid 2000s, satellite image use with tools like Raven Receiver for field zone tracking became widely used. Farmers had to implement and coordinate different tools to manage complete farm operation. With constant improvements through the years Agritech SaaS has become all in one tool for management of all these activities and more at one place through a single tool. A good example would be CropIn, that is working with Government of Karnataka and leading multinational agri corporations utilizing data analytics and satellite imagery to collect, analyze data and manage all the activities from farm to fork.

One of the biggest applications of cloud software in agriculture is for data collection and retrievement. Cloud software store tonnes of data relating to weather cycles, crop patterns, soil quality, harvesting and satellite imagery to provide insights with sharp accuracy and speed. All the data related to farm is stored in cloud and hence readily accessible. So if in future, crops are infected with the same symptoms as 10 years ago, the data can be used to find the remedy used at that time.

Database management in cloud software tie up all the loose ends of every type of data available with respect to farm to enable higher level of decision-making. Meteorological data, market data, farm data, GIS and water availability - all the data from past and present is analysed thoroughly before giving optimum value of seeding, water and pesticide requirements for a farm. The systems also have an alert system whenever discrepancies in crop growth are detected. Hence these systems work efficiently in case of pest attack informing farmers with actionable data.

Data storage is the backbone of predictive analysis. Earlier the data storage was hardware based, hence hardware needed to be carefully maintained and stored. Loss of hardware meant the data was gone forever. Nowadays the agritech systems are cloud based, which means that one need not invest in purchase and maintenance of hardware. All the data is available all the time and can be accessed through phone, PCs and tablets. Data storage is significant also in accurate analysis. The more data is available relating to farms, the more accurate detection of weather phenomena, pests, crop yield and profits will be.

Cloud-based software finds applications with

Smart Farming focuses on application of acquired data and combining it from various data sources to show the bigger picture to manage all the activities of the farm. Smart farming is a big leap from traditional farming as it brings certainty and predictability to table. Robotics, automation and cloud software systems are tools for smart farming. Robotics, drones and sensor equipment placed throughout the farms can collect data and this data is processed to produce farm insights. Cloud based software can be used to collect the data on farm and process the data relative to weather patterns, yields, irrigation and satellite imagery, and off farm - such as markets and dealer availability to perform predictive analysis. Cloud based software finds the applications for farmers, banks, food processing companies, insurance providers, seed production and government.

Has IoT or Cloud-based SaaS (Software as a Service) solutions been applied for 'smarter agriculture' scenarios in agriculture dominated developing economies?

Although IoT is still at a nascent stage, the governments of agriculture dominant developing economies do invest in cutting-edge technologies like IoT, AI and Machine Learning for making smarter agriculture solutions. In agri-based economies like India, the implementation of IoT in agriculture has its own set of unique benefits and challenges.

Firstly, the farmers fear upgrading to agtech as they lack the knowledge about the applicability of technology in agriculture. Besides this, the sensors, robots and drones that are used in the development of IoT solutions are expensive and high maintenance and require technically trained labor for operating them. The data collected needs to be analysed - this can be done by taking them to a lab or by using instruments on farm. Also a variety of sensors are required for collecting data on different parameters which needs to be analysed separately, hence making them high-ticket budget items. Therefore, the designed solutions must be cost-effective and highly scalable, considering the various farm sizes.

What are the benefits of smart farming using SaaS solutions?

Readily available and accessible management through smartphones, tablets and PCs

Alert Log & Management (pest infestation, diseases etc.)

Incorporates end-to-end solutions from farm to fork traceability

Robust & flexible system for Farm Management

Satellite and weather input based advisory

Higher yield as inputs are optimized and constantly monitored

Traceability & Output Predictability

Crop reports & insights - easy reporting on-the-go

Better quality due to compliance of food standards and nutrition tracking

Accountable & Efficient Operations

Geo tagging for accountability & accurate predictability

Less waste due to customized practices accounting for precise application of resources and thus reduction in production costs

Standard package of practices

Adherence to Compliance & Certification

As a multinational farming company, it is only natural that we switch to smart farming to optimize productivity. What are the differences between IoT and SaaS solutions that we should consider before investing in one?

High skilled labor not required

No equipment required on farms

Labor logs and chemical usage data available

No physical equipment required to be placed on farms.

No hardware maintenance costs, Insights are accessible on laptop or PC screens and data stored in clouds

High resolution satellite images for monitoring and weather analysis

One stop solution for managing all the operations pre and post harvest

Very scalable for multi-country implementation, Single application for the management of multiple farms around the globe

Can be integrated with existing devices and IoTs

Yearly or Monthly subscription plans available at low cost, low risk

Holitistic supply chain management

Can be integrated with existing devices and IoTs

Requires high skilled field staff to implement and manage bots

Equipments are expensive and fragile

Sensors, robots, drones and cameras required to be placed on farms to monitor and operate.

Recurring maintenance costs for hardware

Computer imaging is done via sensor cameras and drones with manual operators

Each equipment has a defined set of operation, not one can show all stats

Not scalable, each farm data has to be managed separately

Difficult to integration with already implemented devices

Heavy initial investments

No supply chain management

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Smart Farming Technology - Advanced Agriculture Solution | Cropin

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Smart Farming is focussed on the use of data acquired through various sources (historical, geographical and instrumental) in the management of farm activities. Technologically advanced doesn't essentially mean that it is a smart system. Smart systems differentiate themselves through their ability to record the data and make sense out of it.

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Traditional Farming and Smart Farming. What are the differences?

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Traditional Farming and Smart Farming. What are the differences?

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NEW Farming vs OLD Farming.. Whats The Difference?

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1. Traditional farming
2. Smart farming with ICT

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1. Robotics
- Weeding Robots
- Machine Navigation
- Harvesting Robotics
- Material Handling
2. Remote Sensing
- Crop Monitoring
- Weather conditions
- Soil quality
3. Computer Imaging
4. Drones

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IoT Application in Agriculture for Smart Farming | Cropin

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The IoT applications in farming target conventional farming operations, and helps to implement smart farming to meet the increasing demands. Know more.

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IoT (Internet of Things)

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Ground Drone? Leica Geosystems, Milrem Launch Unmanned Ground Vehicle

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Milrem and Leica Geosystems today announced Pegasus:Multiscope, the first unmanned ground vehicle (UGV) for off-road use, opening new applications in

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Drone Applications, Advantages and Disadvantages of Drone Applications in Farming

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Drone Applications, Advantages and Disadvantages of Drone Applications in Farming

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Applications of Drone Technology in Farming?
1. Terrain Mapping
2. Solar Panel Inspection
3. Livestock Monitoring
4. Soil and Field Analysis
5. Seed Planting
6. Crop Spraying
7. Crop Mapping and Surveying
8. Irrigation Monitoring
9. Health assessment

Drones Application in Farming  Advantages and Disadvantages?
Advantages
1.  Efficient Agriculture Practice
2.  Prevents Infestation
3. Moisture Monitoring
4. Analyzes Crop Quality
Disadvantages
1. Legal Restriction
2. Flight Route Limitations
3. Knowledge limitations
4. Expensive

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Unmanned aerial vehicles (UAVs) or Drones have been used extensively in the commercial industry for the past many decades. The earliest commercial use of the ai drone technology may be traced back to the early 1980s, however, it is only in the past two decades that the practical applications of drones have expanded considerably. Owing to the advancement in technology, especially in futuristic technologies like artificial intelligence (AI), machine learning (ML), and others, today drones are widely used across various industries; enabling faster, better, and more cost-effective operations of various industries.

Today, the total value of the drone technology used across all industries including commercial and public applications amounts to nearly $ 150 billion, which is expected to continue increasing in foreseeable future. Agriculture is one of the top industries among the various others where drones will continue to increase its application. Drones in agriculture can help in overcoming various persistent challenges while enabling better agriculture practices to address future challenges as well. Farming drones are seen as the next futuristic technology that will be crucial to feed the growing population, which is expected to reach 9 billion by 2050, increasing the demand for food by over 70% for the same period. Moreover, drones in agriculture will also be crucial to fighting against the extreme weather events which are constantly wreaking havoc for the farmers and creating food security situations across many regions in the world.

It is imperative for farmers across the world to embrace the drones in agriculture and exploit its potential to improve their agricultural practices, as well as, to increase food production. Here in this blog, we will be looking at everything you want to know about farming drones and how they are changing the face of the agricultural industry for the good.

Folio3 is Your custom Farming Agriculture Drones and Applications Partner

Folio3 is one of the top tech companies manufacturing high-end farming drones for the agricultural sector. The company has been assisting farmers across various countries with its AI-backed drone technology to improve agricultural practices.

By unlocking the potential of aerial data using AI-powered drones, the company enable farmers to;

- Collect Aerial Data

Farmers can integrate various payloads on the drones including thermal, visual, LiDAR, or other sensors for complete monitoring and assessment of crops

- Data Analytics

The company offers custom-made AI algorithms that can be used to analyze and interpret the data collected from the drones, so farmers are able to get real-time results in form of interactive reports

- Delivering Action

The AI-powered drones by Folio3 can be programmed to performed tasks independently, thereby, significantly reducing the manual interventions required for farm management.

What are some Commercial Applications of Drone Technology in Agriculture and Farming?

There are plenty of drones applications in the agriculture industry. In fact, drones and agriculture are seen as the perfect match of how technology can revolutionize the traditional industries, making them better, more efficient, and productive for the collective benefit of humanity.

Below, we have come up with some widely used drones applications in the agriculture industry.
1) Terrain Mapping
Drones with their inherent capability to survey vast tracts of lands are perfect tools to perform terrain mapping. Today, companies like Folio3 are manufacturing AI drones that are programmable to perform various tasks including terrain mapping for better management of the agricultural industry.

Modern-day drones equipped with LiDAR and other sensors are used by farmers to map the terrain across vast swaths of lands as a reconnaissance tool for land preparations. The advanced computer vision capabilities of drones enable them to accurately map the terrain and offer real-time feedback to farmers for efficient planning and management of fields.
2) Solar Panel Inspection
Farms across the world are switching to renewable energy sources like solar panels to meet their energy needs. By installing large solar farms for agricultural practices, farmers not only ensure a consistent power supply but also significantly reduce the energy expenses.

AI-powered drones can be used to significantly reduce the time and cost required for inspection of solar panels . The farming drones can be used for regular monitoring of the solar panels and assess any potential defects in the grid before it jeopardizes the entire system.

Companies like Folio3 have been designing advanced drones with various imaging payloads including thermal and infrared imaging sensors to help farmers easily supervise solar panel maintenance and identifies any potential defects like diode failure or shattered panels quickly.
3) Livestock Monitoring
The drones in the agriculture industry are also widely used by farmers for effective livestock management. AI-backed programmable drones are perfect tools to automate the monitoring of livestock at the fraction of the cost.

These drones can be used to keep track of the livestock, as well as, to identify any injured or missing livestock. It can also be used to identify pastures across vast swaths of lands and can be pre-programmed to continue tracking the livestock across the pasture.
4) Soil and Field Analysis
Drones are great tools to access insightful data for the quality of the soil at the beginning or end of a crop cycle. AI drones equipped with LiDAR can be used to create 3D maps of the soil to be able to understand any issues with the quality of the soil including the nutrients or any dead zone.

All of this information can be pretty useful to determine the most effective planting patterns, as well as, improved crop management. Drones can also be sued to identify and monitor water resources more effectively across the fields.
5) Seed Planting
Seed planting using drone technology is a relatively new technology as compared to other drones applications in agriculture. However, startup companies have been testing the technology for faster and more effective seed plantations.

Some farming drone manufacturing companies are also testing the payload efficiency of drones in form of tree seeds, fertilizers, water, and herbicide to assess the cost-effectiveness of the technology. Once it gets passed the testing phase, drones would further strengthen the effectiveness and efficiency of the agriculture industry by making it much easier to plant seeds and deliver other required elements to the soil.
6) Crop Spraying
Another area of drones application in the agriculture industry includes crop spraying. Traditionally, farmers are required to spray the entire fields manually with vehicles or at times some farmers also used airplanes for the purpose. However, both of these methods are either too slow or too expensive for the liking of modern-day farming.

Today, smart drones approved by FAA can take huge reservoirs of fertilizers or pesticides as payload for efficient spraying across the field. In fact, AI drones can be programmed for spot spraying as well, making it much safer and cost-effective for farmers to manage the crop yields and stop pest infestation in crops.
7) Crop Mapping and Surveying
Another vital drone application in the agriculture sector is the use of the technology in monitoring of crops across vast swaths of fields. Traditionally this has to be performed by farmers manually which takes forever and is highly inefficient. More recently tech companies have been using satellite or airborne imagery to survey and map the crop fields, which again comes with high costs.

Lately, AI-powered drones have taken over the survey and mapping aspect of farming, making it possible for farmers to keep a close check on the crop efficiently in real-time.
8) Irrigation Monitoring
Another traditionally troublesome area for farmers has been monitoring and management of irrigation. With several miles long irrigation network, there's always a possibility of issues arising.

Today, drones equipped with thermal imaging systems are effectively used to monitor the entire irrigation network efficiently and spot any issues in real-time. With access to real-time information through drones, farmers are in a better position to maximize the drainage and prepare contingency plans to cope with issues.
9) Health assessment:
Lastly, drones are effectively used to monitor crop health. Drones equipped with infrared and thermal sensors are widely used to get real-time imagery for analysis of crop health.

Companies like Folio3 offer customized crop health monitoring software that can be used to instantly assess the chlorophyll content, as well as, estimate soil fertility through crop imagery in the infrared and thermal region of the electromagnetic spectrum.

Drones in Agriculture Market and Trends

Drones in agriculture are known to achieve precision agriculture, which is something that the scientific community is after in order to get prepared for the massive increase in the population in the coming decades.

The precision agriculture takes into account detailed observation and measurement at each and every step of crop farming and livestock data to keep farmers updated with the status of the crop and help them take precautionary measures to save crops from potential damage. The technique also enables farmers to greatly reduce the requirement of manual labor by bringing in a more organized and integrated farming approach, resulting in increased yields through more efficient and effective management of crop farming.

The rapid advancement of drone technology has also resulted in a significant decrease in the cost of drones in agriculture, which again improves the capacity of farmers to integrate the technology into their farming practices for higher yields and better management of crops.

According to stats, the total value of drones application in the agriculture market will increase up to 40% in the coming years, owing to a consistently growing population, unreliable weather patterns, and a massive demand for food in the market.

Some of the various drones application in agriculture industry includes;

- Crop monitoring

- Detecting weeds

- Managing livestock

- Crop health assessment and many more

Modern-day drones are integrated with AI technologies along with strong imagery sensors (Camera and infrared sensors) and GPS navigation systems that enable them to perform various agriculture-related tasks for better and efficient farming practices.

Drones Application in Farming & Agriculture - Advantages and Disadvantages

Just like all technologies, farming drones also comes with its advantages and disadvantages. Below we will be looking at some of the pros and cons of the technology:

- Efficient Agriculture Practice

Drones technology has proven to be the revolutionizing technology for the agricultural sector, automating the various labor-intensive processes and creating more efficient agricultural practices. All of this leads to better crop management, as well as, more yield to meet future needs.

- Prevents Infestation

By automating the crop spraying with real-time monitoring capabilities, drone technology in the application has greatly reduced the infestation rates and improved the yield estimation of crops.

- Moisture Monitoring

Moisture monitoring is important in agriculture to ensure the health of the crops. Drones can help in mapping the entire fields for estimating the moisture content of the soil for better and efficient field management.

- Analyzes Crop Quality

Modern-day drones are powerful to carry various imaging systems including infrared and thermal imaging systems which can be used to evaluate crop quality for nutrient and chlorophyll content.

- Legal Restriction

All drones between 0.55lbs and 55lbs required mandatory registration with the Federal Aviation Administration (FAA). FAA also holds the authority to dictate any use of drones in commercial or private spaces. Thus farmers need to have a complete understanding of the rules and regulations, which can be too complicated for many farmers.

- Flight Route Limitations

Drones also have a limited flight route permitted by the authorities, which has to be followed by all drones. Also, there are various restricted zones where drones can't be used like near airport terminals.

- Knowledge limitations

Most of the farmers aren't well-versed with the technical aspects of drones and struggle to operate drones. Farmers need to get educated about the features and functions of the drones to operate it with complete potential.

- Expensive

While the overall cost of drone technology has considerably reduced over the past decade, it is still much higher for the liking of most farmers. On average farming, drones may cost anywhere from $10,000 to $20,000, which is much expensive for farmers to pay upfront.

FAQs:
How are drones used in agriculture for small farmers?
Drones can be utilized in small farms to map out pre-plating patterns, which enable farmers to maximizer the utilization of the area for plantation of crops. The farmers can also strategize preferred planting pattern for individual crops using drones, which significantly reduce the time to map out the plantation pattern on foot.
How long have drones been around in agriculture and farming?
While the drones have been around for nearly a century (may be not in its current form), the use of drones in agriculture may be traced by to a decade in early 2010s, when the drones were first used to get real-time imagery of farms.
What is the range of cost of drones in agriculture and farming?
The price of agriculture drones may vary greatly depending upon the type, complexity and use of the system. Nonetheless, on average agriculture drones may range between $2000 to over $25000.

Start Gowing with Folio3 AI Today

Connect with us for more information at Contact@folio3.ai

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Drones in Agriculture - Best Drone Applications in Agriculture and Farming

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Unmanned aerial vehicles (UAVs) or Drones have been used extensively in the commercial industry for the past many decades. The earliest commercial use of the ai drone technology may be traced back to the early 1980s, however, it is only in the past two decades that the practical applications of drones have expanded considerably.

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Tree planting drones firing seed missiles

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Tree planting drones firing seed missiles

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Posted by Jo English on 26th April 2019

A company is now producing drones designed to fire seed missiles into fields, aiming to help restore the world's forests. According to National Geographic, between 1990 and 2016, the world lost 502,000 square miles of forest due to a combination of humans cutting them down, and natural factors including wildfires.

With deforestation affecting all life on Earth, it needs addressing urgently, and Biocarbon Engineering believe they can help. The company have designed drones which, in September, planted seeds in a field just south of Yangon, Myanmar. These seeds have now grown into mangrove saplings, about 20 inches tall, and now Biocarbon Engineering are looking to 'replicate this success' elsewhere.

The company's cofounder, Irina Fedorenko told Fast Company "We now have a case confirmed of what species we can plant and in what conditions. We are now ready to scale up our planting and replicate this success".

Biocarbon Engineering also used drones to plant both trees and grasses at abandoned mines in Australia, as well as other locations over the world. Since the project started in 2012, more than six million trees have been planted by non-profit organisation Worldview Impact, which has recently been working with Biocarbon Engineering.

Many of these six million seeds were planted by hand which takes time, so Worldview Impact hopes to use more drones in the future now they've proven to be successful. It's estimated two operators working with 10 drones can plant an amazing 400,000 trees a day.

After flying over the areas, the drones then map it, while collecting data about the soil condition and topography to determine the best locations to plant seeds. They then fire biodegradable pods into the ground, which are filled with a germinated seed and the nutrients it needs.

The project in Myanmar is all about community development and enabling people to care for trees, providing them with jobs, and making environmental restoration in a way that it's profitable for people.

The forest didn't vanish by itself - the forest was cut down by local people. We train local people to be drone pilots, and they want that. They want to be in IT. They want to process data, they want to fly drones, they want to do agroforestry, they want to do regenerative agriculture, they want to create vertical farms, they want to do all this cool stuff. It's not the ambition to be a seedling planter for $1 a day.
So, the drone project isn't just helping the forests themselves, but the local communities too by helping provide new economic opportunities. The project will hopefully have a huge impact with climate change, as researchers recently calculated there's enough room on the planet to plant 1.2 trillion trees, enough to suck up more carbon each year than humans emit. Amazing!

Biodegradable Seedpods
Providing a scalable wetland solution
Wetland restoration has the potential to sequester carbon at rapid rates. The BCE pod is fully biodegradable, designed to ensure seed penetration to minimise tidal impact on germination

Designed to biodegrade in moist soils

Can carry multiple seed types and sizes

Scalable for challenging planting conditions

Suite 3, 112 John St, Singleton, NSW, 2330, Australia
Monday to Friday
+61 0476 896 924
hello@biocarbonengineering.com

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Tree planting drones firing seed missiles - International Forest Industries

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Posted by Jo English on 26th April 2019 A company is now producing drones designed to fire seed missiles into fields, aiming to help restore the world's forests. According to National Geographic, between 1990 and 2016, the world lost 502,000 square miles of forest due to a combination of humans cutting them down, and natural factors including wildfires.

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Differences between Traditional Farming and Smart  Farming

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Differences between Traditional Farming and Smart  Farming

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https://frameworkfilms.net/facts/guide-to-buying-used-drones

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Everytime you look at your smart watch to count calories or ask Alexa or Siri to calculate the value of pie, you are using what is IoT tech. IoT by simplest of definitions is just that - Internet controlling things. IoT devices are 'smart' devices that can transfer data over a network. One of the first network connected devices was a 1982 Coke vending machine at Carnegie Mellon University which was able to report if the drinks were cold or if there were drinks at all.

The term Internet of Things was coined in 1999 by Kevin Ashton, co-founder and executive Director of the MIT Auto ID centre, while he was giving a presentation at Procter and Gamble as their Brand Manager. The presentation that Ashton made for Procter and Gamble was meant to introduce RFID tags to manage the supply chain so that the location and stock at hand of each item coming out of it can be more easily monitored.

Riding the RFID wave LG Electronics then put out a refrigerator known as the Internet Digital DIOS back in the year 2000 which was connected to the Internet. It kept track of the kind of food items that were stored in it as well as their respective quantities by scanning their RFID tags. Though the Internet Digital DIOS refrigerator didn't sell well because most people thought it was too expensive for their needs, it would eventually pave the way for more house appliances to be managed via internet.

According to Cisco Internet Business Solutions Group (IBSG), though the term was coined in 1999, the Internet of Things was born in between 2008 and 2009 at simply the point in time when more "things or objects" were connected to the Internet than people. Citing the growth of smartphones, tablet PCs, etc the number of devices connected to the Internet was brought to 12.5 billion in 2010 while the world's human population increased to 6.8 billion, making the number of connected devices per person more than 1 (1.84 to be exact) for the first time in history.

APPLICATIONS OF IOT IN AGRICULTURE - THE NEED AND IMPLEMENTATION

ROBOTICS

Since the industrial revolution in the 1800s, automation is only getting advanced to efficiently handle more sophisticated tasks and increase production. With increasing demands and shortage of labor across the globe, agriculture robots or commonly known as Agribots are starting to gain attention among farmers. Crop production decreased by an estimated 213 crores approx ($3.1 billion) a year due to labor shortages in the USA alone. Recent advancements in sensors and AI technology that lets machines to train on their surroundings has made agrobots more notable. We are still in the early stages of an ag robotics revolution with most of the products still in early trial phases and R&D mode.

Agriculture is one of the major industries to incorporate drones. Drones equipped with sensors and cameras are used for imaging, mapping and surveying the farms. There are ground based drones and aerial drones. Ground drones are bots that survey the fields on wheels. Aerial drones- formally known as unmanned aerial vehicles (UAVs) or unmanned aircraft systems (UASes) are flying robots. Drones can be remotely controlled remotely or they can fly automatically through software-controlled flight plans in their embedded systems, working in coordination with sensors and GPS. From the drone data, insights can be drawn regarding crop health, irrigation, spraying, planting, soil and field, plant counting and yield prediction and much more. Drones can either be scheduled for farm surveys ( drone as a service ) or can be bought and stored near farms where they can be recharged and maintained. After the surveys the drones need to be taken to nearby labs to analyse the data that has been collected.

REMOTE SENSING

IoT based remote sensing utilizes sensors placed along the farms like weather stations for gathering data which is transmitted to analytical tool for analysis. Sensors are devices sensitive to anomalies. Farmers can monitor the crops from analytical dashboard and take action based on insights.

Crop Monitoring

Sensors placed along the farms monitor the crops for changes in light , humidity, temperature, shape and size. Any anomaly is detected by the sensors is analysed and farmer is notified. Thus remote sensing can help prevent the spread of diseases and keep an eye on the growth of crops.

Weather conditions

The data collected by sensors in terms of humidity, temperature, moisture precipitation and dew detection helps in determining the weather pattern in farms so that cultivation is done for suitable crops.

Soil quality

The analysis of quality of soil helps in determining the nutrient value and drier areas of farms, soil drainage capacity or acidity, which allows to adjust the amount of water needed for irrigation and the opt most beneficial type of cultivation.

COMPUTER IMAGING

Computer imaging involves the use of sensor cameras installed at different corners of the farm or drones equipped with cameras to produce images which undergo digital image processing. Digital image processing is the basic concept of processing an input image using computer algorithms. Image processing views the images in different spectral intensities such as infrared, compares the images obtained over a period of time and detects anomalies thus analysing limiting factors and helps better management of farms.

IOT IN AGRICULTURE- IN SIMPLE WORDS

FAQs

What is IoT?

IoT is abbreviated form of Internet of Things. IoT is a broad terminology given to every object that can relay information when connected to network. The term Internet of Things was coined in 1999 by Kevin Ashton, co founder and executive Director of the MIT Auto ID centre, while he was giving a presentation at Procter and Gamble as their Brand Manager which was meant to introduce RFID tags to manage the supply chain so that the location and stock at hand of each item coming out of it can be more easily monitored.

How is IoT integrated in agriculture?

Agriculture implements IoT through use of robots, drones, sensors and computer imaging integrated with analytical tools for getting insights and monitor the farms. Placement of physical equipment on the farms monitors and records data which is used to get insights.

How is IoT integrated in agriculture?

Agriculture implements IoT through use of robots, drones, sensors and computer imaging integrated with analytical tools for getting insights and monitor the farms. Placement of physical equipment on the farms monitors and records data which is used to get insights.

We are a multinational corporation who is into precision farming and plan to adopt agritech farm management system which lets us manage activities on all farms from head office.
What are the key differences between Saas and IoT agritech that should be considered before investing ?

What are infrastructure requirements for adopting smart farming IoT?

Hardware maintenance costs.

How easy is it to operate IoT agritech ?

IoT in agritech uses technology which integrates sensitive physical hardware with analytical software. Analytical dashboard is mostly a software that is processing the data recorded by equipments. Hence a sound technical knowledge of robotics and computer based intelligence is a prerequisite for operating, maintaining and understanding the insights of these valuable equipments.

I am a food processor who owns several farms throughout the world. How can I integrate IoT for multiple farm management?

Since IoTs require physical devices, each farm will need to install their own set of sensors and bots which will record the data related to that farm only. So every farm will have their own separate dashboard for viewing the insights. Integrating and scaling IoT for several farms in a single platform is not possible unlike SaaS agritech such as CropIn which lets you integrate and manage multinational operations through a single platform.

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IoT Application in Agriculture for Smart Farming | Cropin

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Everytime you look at your smart watch to count calories or ask Alexa or Siri to calculate the value of pie, you are using what is IoT tech. IoT by simplest of definitions is just that - Internet controlling things. IoT devices are 'smart' devices that can transfer data over a network.

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The autonomous robot weeder from Ecorobotix

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After an initial shower of herbicide, it's time for a targeted and precise application by the smart autonomous robot weeder from Ecorobotix.

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AVO · Autonomous weeding robot · Presentation film · Short EN

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Futuristic Farming Has Arrived with Weeding Robots - Modern Farmer

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For sustainable farmers, hand-weeding can be laborious, backbreaking work and can cost upwards of $300 an acre in labor costs. A French startup called

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#Dino - 2019 - Official presentation - Autonomous Mechanical Weeding Robot

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Everytime you look at your smart watch to count calories or ask Alexa or Siri to calculate the value of pie, you are using what is IoT tech. IoT by simplest of definitions is just that - Internet controlling things. IoT devices are 'smart' devices that can transfer data over a network. One of the first network connected devices was a 1982 Coke vending machine at Carnegie Mellon University which was able to report if the drinks were cold or if there were drinks at all.

The term Internet of Things was coined in 1999 by Kevin Ashton, co-founder and executive Director of the MIT Auto ID centre, while he was giving a presentation at Procter and Gamble as their Brand Manager. The presentation that Ashton made for Procter and Gamble was meant to introduce RFID tags to manage the supply chain so that the location and stock at hand of each item coming out of it can be more easily monitored.

Riding the RFID wave LG Electronics then put out a refrigerator known as the Internet Digital DIOS back in the year 2000 which was connected to the Internet. It kept track of the kind of food items that were stored in it as well as their respective quantities by scanning their RFID tags. Though the Internet Digital DIOS refrigerator didn't sell well because most people thought it was too expensive for their needs, it would eventually pave the way for more house appliances to be managed via internet.

According to Cisco Internet Business Solutions Group (IBSG), though the term was coined in 1999, the Internet of Things was born in between 2008 and 2009 at simply the point in time when more "things or objects" were connected to the Internet than people. Citing the growth of smartphones, tablet PCs, etc the number of devices connected to the Internet was brought to 12.5 billion in 2010 while the world's human population increased to 6.8 billion, making the number of connected devices per person more than 1 (1.84 to be exact) for the first time in history.

APPLICATIONS OF IOT IN AGRICULTURE - THE NEED AND IMPLEMENTATION

ROBOTICS

Since the industrial revolution in the 1800s, automation is only getting advanced to efficiently handle more sophisticated tasks and increase production. With increasing demands and shortage of labor across the globe, agriculture robots or commonly known as Agribots are starting to gain attention among farmers. Crop production decreased by an estimated 213 crores approx ($3.1 billion) a year due to labor shortages in the USA alone. Recent advancements in sensors and AI technology that lets machines to train on their surroundings has made agrobots more notable. We are still in the early stages of an ag robotics revolution with most of the products still in early trial phases and R&D mode.

Agriculture is one of the major industries to incorporate drones. Drones equipped with sensors and cameras are used for imaging, mapping and surveying the farms. There are ground based drones and aerial drones. Ground drones are bots that survey the fields on wheels. Aerial drones- formally known as unmanned aerial vehicles (UAVs) or unmanned aircraft systems (UASes) are flying robots. Drones can be remotely controlled remotely or they can fly automatically through software-controlled flight plans in their embedded systems, working in coordination with sensors and GPS. From the drone data, insights can be drawn regarding crop health, irrigation, spraying, planting, soil and field, plant counting and yield prediction and much more. Drones can either be scheduled for farm surveys ( drone as a service ) or can be bought and stored near farms where they can be recharged and maintained. After the surveys the drones need to be taken to nearby labs to analyse the data that has been collected.

REMOTE SENSING

IoT based remote sensing utilizes sensors placed along the farms like weather stations for gathering data which is transmitted to analytical tool for analysis. Sensors are devices sensitive to anomalies. Farmers can monitor the crops from analytical dashboard and take action based on insights.

Crop Monitoring

Sensors placed along the farms monitor the crops for changes in light , humidity, temperature, shape and size. Any anomaly is detected by the sensors is analysed and farmer is notified. Thus remote sensing can help prevent the spread of diseases and keep an eye on the growth of crops.

Weather conditions

The data collected by sensors in terms of humidity, temperature, moisture precipitation and dew detection helps in determining the weather pattern in farms so that cultivation is done for suitable crops.

Soil quality

The analysis of quality of soil helps in determining the nutrient value and drier areas of farms, soil drainage capacity or acidity, which allows to adjust the amount of water needed for irrigation and the opt most beneficial type of cultivation.

COMPUTER IMAGING

Computer imaging involves the use of sensor cameras installed at different corners of the farm or drones equipped with cameras to produce images which undergo digital image processing. Digital image processing is the basic concept of processing an input image using computer algorithms. Image processing views the images in different spectral intensities such as infrared, compares the images obtained over a period of time and detects anomalies thus analysing limiting factors and helps better management of farms.

IOT IN AGRICULTURE- IN SIMPLE WORDS

FAQs

What is IoT?

IoT is abbreviated form of Internet of Things. IoT is a broad terminology given to every object that can relay information when connected to network. The term Internet of Things was coined in 1999 by Kevin Ashton, co founder and executive Director of the MIT Auto ID centre, while he was giving a presentation at Procter and Gamble as their Brand Manager which was meant to introduce RFID tags to manage the supply chain so that the location and stock at hand of each item coming out of it can be more easily monitored.

How is IoT integrated in agriculture?

Agriculture implements IoT through use of robots, drones, sensors and computer imaging integrated with analytical tools for getting insights and monitor the farms. Placement of physical equipment on the farms monitors and records data which is used to get insights.

How is IoT integrated in agriculture?

Agriculture implements IoT through use of robots, drones, sensors and computer imaging integrated with analytical tools for getting insights and monitor the farms. Placement of physical equipment on the farms monitors and records data which is used to get insights.

We are a multinational corporation who is into precision farming and plan to adopt agritech farm management system which lets us manage activities on all farms from head office.
What are the key differences between Saas and IoT agritech that should be considered before investing ?

What are infrastructure requirements for adopting smart farming IoT?

Hardware maintenance costs.

How easy is it to operate IoT agritech ?

IoT in agritech uses technology which integrates sensitive physical hardware with analytical software. Analytical dashboard is mostly a software that is processing the data recorded by equipments. Hence a sound technical knowledge of robotics and computer based intelligence is a prerequisite for operating, maintaining and understanding the insights of these valuable equipments.

I am a food processor who owns several farms throughout the world. How can I integrate IoT for multiple farm management?

Since IoTs require physical devices, each farm will need to install their own set of sensors and bots which will record the data related to that farm only. So every farm will have their own separate dashboard for viewing the insights. Integrating and scaling IoT for several farms in a single platform is not possible unlike SaaS agritech such as CropIn which lets you integrate and manage multinational operations through a single platform.

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IoT Application in Agriculture for Smart Farming | Cropin

# data[].attributes.attachment_link.description
Everytime you look at your smart watch to count calories or ask Alexa or Siri to calculate the value of pie, you are using what is IoT tech. IoT by simplest of definitions is just that - Internet controlling things. IoT devices are 'smart' devices that can transfer data over a network.

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DINO vegetable weeding robot for large-scale vegetable farms

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Dino is an entirely autonomous vegetable weeding robot for large-scale vegetable farms. Its highly precise guidance system guarantees efficient and eco-friendly weeding

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1. Save time on tracking all the field activities with efficient Field activity log tool
2. Keep an eye on your fields regularly with satellite monitoring and crop rotation data
3 .Save time and money by sending scouts directly to problem areas
4. Enhance future farm activities planning with a 14-day weather forecast for your field

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From the Inventor of Roomba®

Tertill is a compact and effective robot that weeds your vegetable garden for you. It's solar-powered, weatherproof, and lives in the garden all season long.

To Tertill, weeds are short and plants are tall. Anything tall enough to touch it's sensors makes the robot turn away, if it passes under the robot, it cuts it.

"... the result is astounding. You are seeing as good weed control with Tertill as with the hand weeding effort."

Dr. Averill at the Cornell University School of Integrative Plant Science.

"This weeding robot will save you time and energy removing weeds automatically."

Ross Trethewey, This Old House

"I love this little thing. It's so adorable! I was intrigued as soon as I came across this listing and, since we expanded our garden this year, I figured I could use all the help I could get with weeding. I love that it's solar powered cause the last thing I need is something else to charge.

Wendy B.

"This robot is for everyone who loves gardening but hates the weeds. It's like a robot vacuum for outside. I think the most important part of using this robot is to watch the videos first. They give you a good introduction to how it works and how best to use it. I think this is an excellent tool. It saves time, effort, sweat, and muscle aches. I HIGHLY recommend it."

Antoinette

Garden Requirements

Tertill should be placed in a weed-free garden that has at least a 4-inch border, a foot between plants or rows, and a relatively flat and smooth surface.

"This is the first time in 32 years that I have come home from vacation to a beautiful garden, rather than a weedy mess. Thanks Tertill!"

Drew W.

"This year has been the most weed free I've experienced since I began gardening about 4 years ago thanks to my Tertill!"

Wanda G.

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Tertill is the solar-powered weeding robot for home vegetable gardens. It eliminates the need for spraying chemicals, struggling with landscaping fabric, or spending hours on your hands and knees weeding - just press the button and let Tertill take care of the rest. Proven as effective as hand-weeding!

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https://itechiteasy.com/satellite-crop-monitoring/

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How does satellite crop monitoring work?

The satellite crop monitoring technology is new technology in Agri-management. It works on the basis of remote sensing technology. Farmers need to take timely decisions to avoid losses. Specifically, in crop management a single failure in assessing problems may lead to a total loss of the crop.

satellite crop monitoring field sensor

Furthermore, the traditional method includes an on-field assessment on a weekly basis. Then, manually analyzing data which may lead to human errors. The on-field study is cumbersome and time-consuming process. So, delay in decision making is a common sight.

In addition, the large landholding needs more human resources to carry out the assessment. Currently, labor issues in the field of agriculture are prevailing. Here comes the satellite crop monitoring technology.

satellite crop monitoring technology

Basically, satellite crop monitoring is nothing but a spectral analysis of crop. This technology helps to monitor crop vegetation index in real-time with spectral analysis.

Furthermore, the high-resolution satellite images of crops help to track positive and negative crop development. The difference in vegetation index informs farmers about deficiencies or diseases. Vegetation index in simple language is nothing but the difference in leaf color.

All the crops undergo periodic vegetative changes. Crops change colour as they mature and grow. As we can see rice fields are ready to harvest when the leaves turn yellowish. So, leaves of the crop give detail insights into plant health. They also tell about ongoing diseases or any upcoming disease. It's just like humans. We feel low when something is not right in our bodies. In exact same way, the plant reacts through leaves.

Furthermore, we can use these changes in color in order to identify deficiencies or diseases in crops. The satellite data and online analytical data can be helpful in decision making. What decision you take during the growth period of the crop directly affects the final yield and quality.

Real-time monitoring

In addition, as of today, you can literally monitor your crop through a browser and mobile app. These solutions are cheaper and you can manage large areas easily. You can simply manage any farm in the world via web-based software. You can analyze the land for a long period of time. Thus, you have all the data to create historical field maps. You can create field productivity maps and make data-driven decisions.

satellite crop monitoring software interface

All these aspects of satellite crop monitoring technology can be a game-changer. You can synchronize and track the tasks all at one place. You can mark the area in question with GPS co-ordinates. The expert then goes to the exact location in the field, takes the picture and uploads it into the system. You can analyze the situation & take the necessary action.

Advantages

The most important advantage is timely decision making. As it has a key role in agriculture. Farmers can forecast crop yields and control vegetation. They can also do smart fertigation by using this technology. An agronomist can predict exact harvesting time. Farmers can track crop development.

Furthermore, business owners can predict the exact capital requirement. The investors can analyze how much to invest. Insurance companies can use this data for risk assessment. They can also analyze historical weather data. These companies can also see the land use and predict yields.

In addition, traders and brokers can predict and plan the sell as per crop yield data. They can also pre-plan logistics requirements. Traders can also forecast the market trend by using this data. The agriculture machinery producers can use this data and integrate it into their product. This data is very useful in commercial forest cultivation and planning.

In conclusion, satellite crop monitoring will bring precision to agriculture. The farmers can make data-driven decisions & thereby further increase yields.

Image courtesy: EOS(Earth Observing System), Planet Labs Inc, Arable

watch satellite crop monitoring in action

Read on: What is a smart home?

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Satellite Crop Monitoring: Everything you need to know

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The satellite crop monitoring technology is new technology in Agri-management. It works on the basis of remote sensing technology. Farmers need to take timely decisions to avoid losses. Specifically, in crop management a single failure in assessing problems may lead to a total loss of the crop.

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In this day and age of self-driving cars, prescription seeding via satellite guidance, and variable-rate nitrogen application based on plant color, it was probably only a matter of time before artificial intelligence took on a role in weed control. If there's any doubt about the future of robotic weeders, consider that John Deere recently saw fit to spend $305 million to acquire Blue River Technology (BRT), a California company that created Lettuce Bot.

Using a built-in camera, the Lettuce Bot scans the field using algorithms and machine vision to identify each sprout as lettuce or a weed image in as little as .02 seconds and sprays the unwanted plant with a targeted jet of herbicide.

Building on that, the company next introduced its See & Spray technology. Relying on a massive library of plant and weed images, the machine has the unique ability to distinguish the slightest differences between the crop and weeds and target the latter with the help of robotic nozzles that are both accurate and precise.

However, Willy Pell, director of new technology at BRT, stops short of calling the technology artificial intelligence. Instead, he says it's closer to "really good memorization."

While it's too early to know how John Deere will incorporate the technology into other machines, it does plan to keep the 60-person company at its present location in Sunnyvale, California. It also plans to continue cotton and soybean field-testing in 2018.

In the meantime, Pell says the existing machine can be taught to make other types of applications, explaining that, "You can flip the technology if you want to apply fungicide or fertilizer on the crop."

Since the See & Spray technology applies a microjet of herbicide to the weeds only (as opposed to a broadcast application across the whole field), the machine is said to reduce chemical use by about 90%.

unmanned machines

Using much the same technology as the See & Spray machine, a company in Switzerland hopes to make the weeding process autonomous. Using a built-in camera, GPS guidance, and a series of sensors, the solar-powered robot from ecoRobotix Ltd. is designed to follow crop rows and to detect the presence of weeds in and between the rows. Two robotic arms then target each individual weed with a microdose of herbicide.

"Because it adapts its speed to the concentration of weeds, it is most suitable for use in fields where the level of concentration is low to moderate, in order to cover the ground at a reasonable speed," explains Claude Juriens, business development manager for ecoRobotix.

Unfortunately, Juriens says it will be at least another year before the company is ready to look at markets outside of Europe. Even within his own country, he doesn't see the robotic weeder being available for sale before the end of 2018.

According to the specifications, the average speed of the machine is close to 78 feet per minute, and it has a working width of around 6½ feet (2 meters).

incorporating mechanical tools

Spot treatment with chemicals isn't the only option in the world of robotic weeders, though. At least two companies are already marketing robotic machines that incorporate mechanical tools. As an example, F. Poulsen Engineering, based in Denmark, offers the Robovator, which is a vision-based hoeing machine for controlling weeds in row crops.

Equipped with a special plant-detection camera above each row, this machine not only tills the soil between the rows but also hoes between each plant in the row using a mechanical tool operated by hydraulic power. The company also offers a thermal weeding model that uses pinpoint flames to eradicate weeds.

"The software for the Robovator was originally designed for transplanted lettuce," says Frank Poulsen, founder of F. Poulsen Engineering. "Now we are working on seeded crops, as well. We see no reason why it cannot be used on closely spaced crops, as the mechanical machine can work on crops spaced 4 inches apart, while the thermal version can go down to 2 inches. Consequently, the Robovator can already be used on a number of crops, and our customers still find new ways to use the machine."

According to Bartley Walker with Pacific Ag Rentals (PAR) in Salinas, California, the Robovator can remove from 95% to 98% of the weeds in transplanted crops and 85% to 90% in seeded crops. As the only dealer for Robovator in the U.S., Walker says PAR not only sells the machine but also offers rentals and custom weeding services in which it provides the tractor, machine, and operator.

"The Robovator can easily be adjusted to any row spacing from 9 to 30 inches and is available in three- to six-row designs for any bed width up to 90 inches," he says. "While most of the machines are still used on vegetables, we're continually finding new applications for them. Most recently, we've used them to weed watermelons and potatoes. In fact, they've already been used on more than 20,000 acres since we brought them to the U.S. The only restriction is the machine won't work on crops with a closed canopy."

Walker notes that while the price obviously depends on bar length, number of rows, accessories, and so on to match the application, the current unit ranges from $125,000 to $160,000, including around $15,000 worth of modifications that PAR makes to the machine to beef it up for the U.S. market.

"Still, some customers have seen a return on investment in as little as six months in labor-intensive crops," he adds. "In essence, one Robovator can replace 10 laborers."

Steketee IC WEEDER

A similar machine from a company based in the Netherlands is the Steketee IC Weeder. Like the Robovator, it, too, uses camera images to calculate the position of plants and then hoes around them.

Joe Sutton, COO of Sutton Ag Enterprises in Salinas, California, says the dealership has already sold around a half-dozen Steketee IC Weeders since becoming the sole U.S. distributor in 2015. However, nearly all of them, to date, have gone to lettuce farms.

"It's mainly used in high-value row-crop vegetables that have previously been very labor-intensive due, in part, to the price and working speed," Sutton relates.

He says a machine that covers an 80-inch bed, or about five rows of lettuce, costs in the range of $100,000. A three-bed version sells at around $230,000.

Meanwhile, the operating speed for both the Robovator and Steketee machine is generally around 3 mph. Although Poulsen says the limiting factor with the Robovator is not how fast the machine can operate, but the type of crop and its sensibility to dirt on the leaves.

"Lettuce growers," he explains, "prefer the leaves to be clean. Other crops are much more tolerant and allow for a speed of 4 mph."

That doesn't mean such machines won't someday be found in North America's row-crop fields, though.

alternatives needed

By some estimates, 255 different weed species have already developed resistance in 92 crops in 70 countries. Yet, no major new herbicide mode of action has been introduced to the marketplace for almost 20 years. This leaves the door wide open for autonomous robotic weeders, as well as manned robotic-weeding implements.

Combined, they represent an emerging industry that's predicted to be worth $400 million by 2025. It's no wonder John Deere has taken notice and invested in the technology.

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In this day and age of self-driving cars, prescription seeding via satellite guidance, and variable-rate nitrogen application based on plant color, it was probably only a matter of time before artificial intelligence took on a role in weed control.

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https://www.cropin.com/iot-internet-of-things-applications-agriculture/?fbclid=IwAR3qAJ4aTJKBXUSrooFCmnPGHyERApsGGlq7kq23Xdw0vf8As1i_XElwQUE

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Everytime you look at your smart watch to count calories or ask Alexa or Siri to calculate the value of pie, you are using what is IoT tech. IoT by simplest of definitions is just that - Internet controlling things. IoT devices are 'smart' devices that can transfer data over a network. One of the first network connected devices was a 1982 Coke vending machine at Carnegie Mellon University which was able to report if the drinks were cold or if there were drinks at all.

The term Internet of Things was coined in 1999 by Kevin Ashton, co-founder and executive Director of the MIT Auto ID centre, while he was giving a presentation at Procter and Gamble as their Brand Manager. The presentation that Ashton made for Procter and Gamble was meant to introduce RFID tags to manage the supply chain so that the location and stock at hand of each item coming out of it can be more easily monitored.

Riding the RFID wave LG Electronics then put out a refrigerator known as the Internet Digital DIOS back in the year 2000 which was connected to the Internet. It kept track of the kind of food items that were stored in it as well as their respective quantities by scanning their RFID tags. Though the Internet Digital DIOS refrigerator didn't sell well because most people thought it was too expensive for their needs, it would eventually pave the way for more house appliances to be managed via internet.

According to Cisco Internet Business Solutions Group (IBSG), though the term was coined in 1999, the Internet of Things was born in between 2008 and 2009 at simply the point in time when more "things or objects" were connected to the Internet than people. Citing the growth of smartphones, tablet PCs, etc the number of devices connected to the Internet was brought to 12.5 billion in 2010 while the world's human population increased to 6.8 billion, making the number of connected devices per person more than 1 (1.84 to be exact) for the first time in history.

APPLICATIONS OF IOT IN AGRICULTURE - THE NEED AND IMPLEMENTATION

ROBOTICS

Since the industrial revolution in the 1800s, automation is only getting advanced to efficiently handle more sophisticated tasks and increase production. With increasing demands and shortage of labor across the globe, agriculture robots or commonly known as Agribots are starting to gain attention among farmers. Crop production decreased by an estimated 213 crores approx ($3.1 billion) a year due to labor shortages in the USA alone. Recent advancements in sensors and AI technology that lets machines to train on their surroundings has made agrobots more notable. We are still in the early stages of an ag robotics revolution with most of the products still in early trial phases and R&D mode.

Agriculture is one of the major industries to incorporate drones. Drones equipped with sensors and cameras are used for imaging, mapping and surveying the farms. There are ground based drones and aerial drones. Ground drones are bots that survey the fields on wheels. Aerial drones- formally known as unmanned aerial vehicles (UAVs) or unmanned aircraft systems (UASes) are flying robots. Drones can be remotely controlled remotely or they can fly automatically through software-controlled flight plans in their embedded systems, working in coordination with sensors and GPS. From the drone data, insights can be drawn regarding crop health, irrigation, spraying, planting, soil and field, plant counting and yield prediction and much more. Drones can either be scheduled for farm surveys ( drone as a service ) or can be bought and stored near farms where they can be recharged and maintained. After the surveys the drones need to be taken to nearby labs to analyse the data that has been collected.

REMOTE SENSING

IoT based remote sensing utilizes sensors placed along the farms like weather stations for gathering data which is transmitted to analytical tool for analysis. Sensors are devices sensitive to anomalies. Farmers can monitor the crops from analytical dashboard and take action based on insights.

Crop Monitoring

Sensors placed along the farms monitor the crops for changes in light , humidity, temperature, shape and size. Any anomaly is detected by the sensors is analysed and farmer is notified. Thus remote sensing can help prevent the spread of diseases and keep an eye on the growth of crops.

Weather conditions

The data collected by sensors in terms of humidity, temperature, moisture precipitation and dew detection helps in determining the weather pattern in farms so that cultivation is done for suitable crops.

Soil quality

The analysis of quality of soil helps in determining the nutrient value and drier areas of farms, soil drainage capacity or acidity, which allows to adjust the amount of water needed for irrigation and the opt most beneficial type of cultivation.

COMPUTER IMAGING

Computer imaging involves the use of sensor cameras installed at different corners of the farm or drones equipped with cameras to produce images which undergo digital image processing. Digital image processing is the basic concept of processing an input image using computer algorithms. Image processing views the images in different spectral intensities such as infrared, compares the images obtained over a period of time and detects anomalies thus analysing limiting factors and helps better management of farms.

IOT IN AGRICULTURE- IN SIMPLE WORDS

FAQs

What is IoT?

IoT is abbreviated form of Internet of Things. IoT is a broad terminology given to every object that can relay information when connected to network. The term Internet of Things was coined in 1999 by Kevin Ashton, co founder and executive Director of the MIT Auto ID centre, while he was giving a presentation at Procter and Gamble as their Brand Manager which was meant to introduce RFID tags to manage the supply chain so that the location and stock at hand of each item coming out of it can be more easily monitored.

How is IoT integrated in agriculture?

Agriculture implements IoT through use of robots, drones, sensors and computer imaging integrated with analytical tools for getting insights and monitor the farms. Placement of physical equipment on the farms monitors and records data which is used to get insights.

How is IoT integrated in agriculture?

Agriculture implements IoT through use of robots, drones, sensors and computer imaging integrated with analytical tools for getting insights and monitor the farms. Placement of physical equipment on the farms monitors and records data which is used to get insights.

We are a multinational corporation who is into precision farming and plan to adopt agritech farm management system which lets us manage activities on all farms from head office.
What are the key differences between Saas and IoT agritech that should be considered before investing ?

What are infrastructure requirements for adopting smart farming IoT?

Hardware maintenance costs.

How easy is it to operate IoT agritech ?

IoT in agritech uses technology which integrates sensitive physical hardware with analytical software. Analytical dashboard is mostly a software that is processing the data recorded by equipments. Hence a sound technical knowledge of robotics and computer based intelligence is a prerequisite for operating, maintaining and understanding the insights of these valuable equipments.

I am a food processor who owns several farms throughout the world. How can I integrate IoT for multiple farm management?

Since IoTs require physical devices, each farm will need to install their own set of sensors and bots which will record the data related to that farm only. So every farm will have their own separate dashboard for viewing the insights. Integrating and scaling IoT for several farms in a single platform is not possible unlike SaaS agritech such as CropIn which lets you integrate and manage multinational operations through a single platform.

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IoT Application in Agriculture for Smart Farming | Cropin

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Everytime you look at your smart watch to count calories or ask Alexa or Siri to calculate the value of pie, you are using what is IoT tech. IoT by simplest of definitions is just that - Internet controlling things. IoT devices are 'smart' devices that can transfer data over a network.

# data[].attributes.attachment_link.title
IoT Application in Agriculture for Smart Farming | Cropin

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The IoT applications in farming target conventional farming operations, and helps to implement smart farming to meet the increasing demands. Know more.

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IoT (Internet of Things)

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The Natural Resources Conservation Service has adopted a holistic approach to help land managers protect soil and related resources. This approach assesses the natural processes and functions of an area, such as a watershed, and determines how these functions affect the quality of the soil, water, air, plant, and animal resources.

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IoT Application in Agriculture for Smart Farming | Cropin

# data[].attributes.attachment_link.description
The IoT applications in farming target conventional farming operations, and helps to implement smart farming to meet the increasing demands. Know more.

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IoT (Internet of Things)

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Agriculture Technology from Location

Today's farmers use sophisticated agriculture technology because they can save time and money.

Because crops are location-based, this makes Geographic Information Systems (GIS) an EXTREMELY relevant tool for farmers.

For example, farmers use precision GPS on the field to save fertilizer. Also, satellites and drones collect vegetation, topography, and weather information from the sky.

All this data can go into agriculture maps for better decision-making. Let's look at some other agriculture technology examples.

Data from the Machine - Precision Farming

Farmers use precision agriculture because they can reduce the amount of fertilizer applied to the field.

Not only do farmers save money on fertilizer, but they save the environment from over-application. This is because a lot of the excess fertilizer tends to end up in streams and rivers by runoff.

Precision farming applies fertilizer only where it's needed. It's site-specific.

Sensors on a machine gather information about the crops. Also, the GPS gives you the exact position on the field. Precision farming then applies a variable rate of fertilizer to nutrient-deficient sites.

The farmer who uses precision farming can save anywhere in the ballpark of 2-15$ per acre. Over time, this makes an incredible investment.

Data from the Sky - Satellites and Drones

What do crops need to grow? Other than sunlight and nutrients, plants need the right amount of water. Too much (flooding) or little (drought) water impacts crop growth.

Satellite technology like Soil Moisture Ocean Salinity (SMOS) collect real-time microwave energy from the Earth's surface. This can better forecast crop production and monitor drought and flooding.

Landsat satellites analyze the greenness of vegetation using indices like Normalized Difference Vegetation Index (NDVI). We have a local and global estimate of crop productivity for the entire planet from a long list of satellites orbiting the Earth.

What can drones collect on a field?

Instead of workers scouting fields, drones can cover more ground. Drones can inspect crop health from the sky and where plant stress is occurring. Farmers can make actionable decisions on applying nitrogen and monitoring yields. Farmers can use precision watering sensors because they know where it's needed most. They can combat the spread of pests by identifying critical intervention areas.

One small drone can help make some VERY powerful decisions for farmers.

The United States Department of Agriculture (USDA) National Agricultural Statistics Services (NASS) developed the mapping application CropScape where farmers can obtain acreage estimates of crop types.

In the application, farmers can see what crops are growing where and how much. In addition, government have also used CropScape on issues like food security, land-cover change and pesticide control.

On a global scale, the Food and Agriculture Organization of the United Nations AgroMap breaks down primary food crops with its global spatial database of agricultural land-use statistics.

For large-scale planning, online tools like plant hardiness defines suitable climatic growing areas for different types of crops. Likewise, the Canadian Land Inventory was the first GIS data set produced. Its purpose was to classify the varying potential for agricultural production in Canada.

Modelling - Mashing data sets

Researchers are mashing together with various inputs to better model and understand crop production.

The Crop Assimilation Model (CAM) and Soil-Water-Air-Plant (SWAP) in GRASS GIS serve as crop productivity monitoring tools by simulating soil, water, and crop processes.

The Length of the Growing Period (LGP) is when crops meet the full evapotranspiration demands of precipitation and soil moisture-holding capacity. Each crop type has specific moisture requirements making LGP difficult to calculate.

The Erosion-Productivity Impact Calculator (EPIC) models crop yields and irrigation requirements for climate change. While the Agricultural Non-Point Source (AGNPS) Model predicts the effects of agriculture on water quality.

...And the Versatile Soil Moisture Budget (VSMB) simulates soil moisture conditions of cropland areas taking into account evapotranspiration, rainfall, runoff, and other factors.

Geographic Information Systems assist decision-support. Reducing Emissions from Deforestation and forest Degradation (REDD) by IDRISI determines the opportunity cost of potential agricultural revenue versus deforestation.

Aspect and microclimate can locate potential areas that can be harvested like the south-facing slopes of the Swiss Alps. The south-facing slopes shelter from cold and dry winds which is critical to successful crop growth.

Meeting Future Food Demand

How can we fulfill the needs of a growing and increasingly affluent population? Agriculture technology is helping diagnose food security like in this Feeding the World Story Map.

Can we learn from historical imagery and data? Landsat satellite data provides a unique view of historical agricultural land. When you plot historical trends of land use over time, is there enough arable land to serve a growing population?

Maps serve the purpose of raising awareness about global hunger and places that are in need like the FAO Hunger Map and World Food Programme Food Security Analysis.

Overall, satellite, mobile collection, and GIS data are safeguarding food-insecure populations by establishing underlying causes.

Conclusion - Agriculture Technology

Precision farming, satellites, drones, web maps, and sophisticated models - this list represents some of the agriculture technology that farmers and researchers use today.

The modern-day farmer needs to understand a lot more than just what to seed - soils, weeds, nutrients, weather, insects, disease, machinery, and climate.

These emerging trends provide the location intelligence farmers need to get the job done faster and with more knowledge.

What are some of the other growing trends for agriculture technology that you know of?

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Agriculture Technology: How GIS Can Help You Win the Farm - GIS Geography

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Today's farmers use sophisticated agriculture technology because they can save time and money. Because crops are location-based, this makes Geographic Information Systems (GIS) an EXTREMELY relevant tool for farmers. For example, farmers use precision GPS on the field to save fertilizer. Also, satellites and drones collect vegetation, topography, and weather information from the sky.

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IoT Application in Agriculture for Smart Farming | Cropin

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The IoT applications in farming target conventional farming operations, and helps to implement smart farming to meet the increasing demands. Know more.

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IoT (Internet of Things)

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Farmers spend more than $34 billion a year on labor in the U.S., according to the USDA. And many would like to hire more help. But the agriculture industry here faces labor shortages, thanks in part to the scarcity of H2B visas, and an aging worker population. Older workers can't necessarily handle the hours or repetitive physical tasks they once might have.

That's where Root AI, a start-up in Somerville, Massachusetts, comes in. The company's first agricultural robot, dubbed the Virgo 1, can pick tomatoes without bruising them, and detect ripeness better than humans.

The Virgo is a self-driving robot with sensors and cameras that serve as its eyes. Because it also has lights on board, it can navigate large commercial greenhouses any hour of the day or night, detecting which tomatoes are ripe enough to harvest. A "system-on-module" runs the Virgo's AI-software brain. A robotic arm, with a dexterous hand attached, moves gently enough to work alongside people, and can independently pick tomatoes without tearing down vines.

The robot's "fingers" are made of a food-safe plastic that's about as flexible as a credit card, and easily cleaned. Josh Lessing, founder and CEO of Root AI, says that easy-to-clean trait is important.

"People don't think about this -- you have to manage disease on a farm. Just as if I picked with my own hands, there's a risk of spreading around mold, viruses or insects with a robot. That's why you want these to be washable. It is part of the work you do to keep the plants safe."

One of the most unique things about the Virgo, he notes, is that the company can write new AI software and add additional sensors or grippers to handle different crops. "It's a complete mobile platform enabled to harvest whatever you need," says Lessing.

In this way, the Virgo is a departure from other crop-specific harvesting machines on the market and in development, like Abundant Robotics' apple picker, Agrobot's strawberry picker, and Sweeper's pepper-picker.

The Virgo has been tested at commercial greenhouses, including in the U.S. and Canada already. And Root AI has raised funding from noteworthy venture firms, including Accomplice, First Round, Half Court, Liquid2 and Schematic.

Lessing expects to see the Virgo in broad commercial use next year, and to develop new software that enables it to pick other high-value crops like cucumbers, strawberries and peppers after that.

For more on tech, transformation and the future of work, join CNBC at @ Work: Human Capital + Finance Summit in Chicago on July 19.

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This robot can pick tomatoes without bruising them and detect ripeness better than humans

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Farmers spend more than $34 billion a year on labor in the U.S., according to the USDA. And many would like to hire more help. But the agriculture industry here faces labor shortages, thanks in part to the scarcity of H2B visas, and an aging worker population.

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Indoor Farming Company AppHarvest Acquires Root AI - DailyAlts -

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Indoor Farming Company AppHarvest Acquires Root AI. Root AI makes intelligent robots for high-tech indoor farming.

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Artificial Intelligence: Indoor Farming Company AppHarvest Acquires Root AI

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Introducing AI-equipped Tomato Harvesting Robots to Farms May Help to Create Jobs | Solutions Wherever You Go | Panasonic Newsroom Global

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The number of people engaged in agriculture in Japan is decreasing, and the country’s elderly popul...

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Harvesting fruit and vegetables is repetitive and arduous. The human workforce is dwindling due to lack of interest, and now, the unprecedented disruption of the COVID-19 pandemic. Harvesting crops can be a prime task for agro robots to help us with - so what's out there?

The term 'robot' comes from the Czech word 'roboti', meaning 'drudge worker'. Since it was coined in 1920, robots have taken over more and more of the 'drudge work' in our lives, including harvesting robots that can help us gather our fruit and veg.

Using Robots To Harvest Crops

Mechanical harvesters were the first step towards robot agriculture - machinery that uses simple, forceful methods (like physically shaking fruit from trees or cutting wheat from the ground) to gather in the harvest. The first mechanical tomato harvester was patented in 1960 - a machine that cut the plants at soil level and then shook them to separate the tomatoes. By 1970, 95% of all California-grown tomatoes destined for tins and sauces were harvested by machine.

But robots can't harvest all crops. Mechanical harvesting is best suited for crops that won't be damaged easily (like almonds) or where bruising might not matter, like tomatoes for sauce. But supermarkets have extremely high standards for fresh produce, so more sophisticated agro robots are needed to harvest crops that require a gentle touch.

Read why agro robots still need humans to function.

Machine Vision: Agro Robots Need To "See"

Automated harvesters use a combination of machine vision with a grasping tool to pick fruit and vegetables with precision. For some crops this is relatively straightforward-for example, a robot harvesting wheat only needs to recognise the shape of rows planted in a field, which can be done by emitting lasers at the crop and measuring the reflection. But other agro robots need to detect the colour of ripeness, amongst other characteristics.

To distinguish colours, robots can use machine vision to detect the different wavelengths (and so different colours) of light reflected off leaves and fruit. Some robots could also detect the thermal radiation (heat) given off by fruit, compared to leaves. And while it's easier to see contrasting colours, it's not impossible to harvest crops that are largely the same colour: in 2019 Cambridge University, UK, unveiled the Vegebot, which can recognise the shape of a single lettuce in a field of green.

Asparagus is even more challenging to harvest: multiple stems grow at different times, and white asparagus needs to be picked while still underground or it turns green when it sprouts through the soil. So Dutch inventor Ad van Vinken built a robot that can 'see' underground: it emits an electrical signal into the ground, and the water in the asparagus conducts that electricity. Sensors detect the difference between that and the surrounding soil, signalling the robot to dig and harvest.

Copying The Human Hand

The collecting arm of a harvesting robot needs to be mobile enough to reach into foliage, and delicate enough to handle fruit without damaging it. Most robots do this with pincers or claws, and researchers are working to build robots that can mimic the soft dexterity of the human hand.

Some agro robots go for a different advantage: extra limbs. Although it costs around 777,500 EUR to build, a 1.8m tall raspberry harvesting robot could pick 25,000 berries in a day using its four pincer-like picking hands. But why use hands at all? In 2019, a robot that uses suction to pick apples was successfully trialled in New Zealand.

So far, though, most of these robots are still in development, and are not faster at identifying or harvesting produce than a human. The best strawberry harvesting robot currently picks about 50% of strawberries, and moves at 3 inches per second. And the Vegebot damages 38% of the lettuce it picks, which is too high for supermarket standards.

But if these design problems can be solved, the cost benefits will be huge. And harvesting robots could be sent out repeatedly to harvest a field, whereas currently many farmers only harvest a field once to save costs, generating food waste.

The First Fully Autonomous Farms

Agro robots are not just limited to harvesting one type of crop, though: they could take over entire farming systems. The world's first fully autonomous outdoor farm, the UK's 'Hands Free Hectare', managed to plant, tend and harvest 4.5 tonnes of barley and 6.5 tonnes of wheat from a hectare of land in 2017 and 2018, without a single person entering the field. The robots are all classic agricultural machines retrofitted with new technology - like a tractor with a drone autopilot system.

Now scaled up to a full farm of 35 hectares, it's already paying dividends: researchers have been able to run the farm from home during COVID-19 pandemic!
With agro robots taking over the drudge work, how will agriculture change? Let us know in the comments below!

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Agro Robots | Which Robots Actually Work On Farms?

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Harvesting fruit and vegetables is repetitive and arduous. The human workforce is dwindling due to lack of interest, and now, the unprecedented disruption of the COVID-19 pandemic. Harvesting crops can be a prime task for agro robots to help us with - so what's out there?

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Everytime you look at your smart watch to count calories or ask Alexa or Siri to calculate the value of pie, you are using what is IoT tech. IoT by simplest of definitions is just that - Internet controlling things. IoT devices are 'smart' devices that can transfer data over a network. One of the first network connected devices was a 1982 Coke vending machine at Carnegie Mellon University which was able to report if the drinks were cold or if there were drinks at all.

The term Internet of Things was coined in 1999 by Kevin Ashton, co-founder and executive Director of the MIT Auto ID centre, while he was giving a presentation at Procter and Gamble as their Brand Manager. The presentation that Ashton made for Procter and Gamble was meant to introduce RFID tags to manage the supply chain so that the location and stock at hand of each item coming out of it can be more easily monitored.

Riding the RFID wave LG Electronics then put out a refrigerator known as the Internet Digital DIOS back in the year 2000 which was connected to the Internet. It kept track of the kind of food items that were stored in it as well as their respective quantities by scanning their RFID tags. Though the Internet Digital DIOS refrigerator didn't sell well because most people thought it was too expensive for their needs, it would eventually pave the way for more house appliances to be managed via internet.

According to Cisco Internet Business Solutions Group (IBSG), though the term was coined in 1999, the Internet of Things was born in between 2008 and 2009 at simply the point in time when more "things or objects" were connected to the Internet than people. Citing the growth of smartphones, tablet PCs, etc the number of devices connected to the Internet was brought to 12.5 billion in 2010 while the world's human population increased to 6.8 billion, making the number of connected devices per person more than 1 (1.84 to be exact) for the first time in history.

APPLICATIONS OF IOT IN AGRICULTURE - THE NEED AND IMPLEMENTATION

ROBOTICS

Since the industrial revolution in the 1800s, automation is only getting advanced to efficiently handle more sophisticated tasks and increase production. With increasing demands and shortage of labor across the globe, agriculture robots or commonly known as Agribots are starting to gain attention among farmers. Crop production decreased by an estimated 213 crores approx ($3.1 billion) a year due to labor shortages in the USA alone. Recent advancements in sensors and AI technology that lets machines to train on their surroundings has made agrobots more notable. We are still in the early stages of an ag robotics revolution with most of the products still in early trial phases and R&D mode.

Agriculture is one of the major industries to incorporate drones. Drones equipped with sensors and cameras are used for imaging, mapping and surveying the farms. There are ground based drones and aerial drones. Ground drones are bots that survey the fields on wheels. Aerial drones- formally known as unmanned aerial vehicles (UAVs) or unmanned aircraft systems (UASes) are flying robots. Drones can be remotely controlled remotely or they can fly automatically through software-controlled flight plans in their embedded systems, working in coordination with sensors and GPS. From the drone data, insights can be drawn regarding crop health, irrigation, spraying, planting, soil and field, plant counting and yield prediction and much more. Drones can either be scheduled for farm surveys ( drone as a service ) or can be bought and stored near farms where they can be recharged and maintained. After the surveys the drones need to be taken to nearby labs to analyse the data that has been collected.

REMOTE SENSING

IoT based remote sensing utilizes sensors placed along the farms like weather stations for gathering data which is transmitted to analytical tool for analysis. Sensors are devices sensitive to anomalies. Farmers can monitor the crops from analytical dashboard and take action based on insights.

Crop Monitoring

Sensors placed along the farms monitor the crops for changes in light , humidity, temperature, shape and size. Any anomaly is detected by the sensors is analysed and farmer is notified. Thus remote sensing can help prevent the spread of diseases and keep an eye on the growth of crops.

Weather conditions

The data collected by sensors in terms of humidity, temperature, moisture precipitation and dew detection helps in determining the weather pattern in farms so that cultivation is done for suitable crops.

Soil quality

The analysis of quality of soil helps in determining the nutrient value and drier areas of farms, soil drainage capacity or acidity, which allows to adjust the amount of water needed for irrigation and the opt most beneficial type of cultivation.

COMPUTER IMAGING

Computer imaging involves the use of sensor cameras installed at different corners of the farm or drones equipped with cameras to produce images which undergo digital image processing. Digital image processing is the basic concept of processing an input image using computer algorithms. Image processing views the images in different spectral intensities such as infrared, compares the images obtained over a period of time and detects anomalies thus analysing limiting factors and helps better management of farms.

IOT IN AGRICULTURE- IN SIMPLE WORDS

FAQs

What is IoT?

IoT is abbreviated form of Internet of Things. IoT is a broad terminology given to every object that can relay information when connected to network. The term Internet of Things was coined in 1999 by Kevin Ashton, co founder and executive Director of the MIT Auto ID centre, while he was giving a presentation at Procter and Gamble as their Brand Manager which was meant to introduce RFID tags to manage the supply chain so that the location and stock at hand of each item coming out of it can be more easily monitored.

How is IoT integrated in agriculture?

Agriculture implements IoT through use of robots, drones, sensors and computer imaging integrated with analytical tools for getting insights and monitor the farms. Placement of physical equipment on the farms monitors and records data which is used to get insights.

How is IoT integrated in agriculture?

Agriculture implements IoT through use of robots, drones, sensors and computer imaging integrated with analytical tools for getting insights and monitor the farms. Placement of physical equipment on the farms monitors and records data which is used to get insights.

We are a multinational corporation who is into precision farming and plan to adopt agritech farm management system which lets us manage activities on all farms from head office.
What are the key differences between Saas and IoT agritech that should be considered before investing ?

What are infrastructure requirements for adopting smart farming IoT?

Hardware maintenance costs.

How easy is it to operate IoT agritech ?

IoT in agritech uses technology which integrates sensitive physical hardware with analytical software. Analytical dashboard is mostly a software that is processing the data recorded by equipments. Hence a sound technical knowledge of robotics and computer based intelligence is a prerequisite for operating, maintaining and understanding the insights of these valuable equipments.

I am a food processor who owns several farms throughout the world. How can I integrate IoT for multiple farm management?

Since IoTs require physical devices, each farm will need to install their own set of sensors and bots which will record the data related to that farm only. So every farm will have their own separate dashboard for viewing the insights. Integrating and scaling IoT for several farms in a single platform is not possible unlike SaaS agritech such as CropIn which lets you integrate and manage multinational operations through a single platform.

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IoT Application in Agriculture for Smart Farming | Cropin

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Everytime you look at your smart watch to count calories or ask Alexa or Siri to calculate the value of pie, you are using what is IoT tech. IoT by simplest of definitions is just that - Internet controlling things. IoT devices are 'smart' devices that can transfer data over a network.

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Fields plowing is performed by a robot having the shape of driverless tractor.

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Fields plowing is performed by a robot having the shape of driverless tractor.

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Robots using Machine Vision Algorithms in Agriculture

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Find out how robots are already extensively used in agriculture tasks and how RSIP Vision will help you operate them via cutting-edge machine vision algorithms.

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MOBILE ROBOTS FOR

INDUSTRIAL PRODUCTIVITY

Scalable and flexible systems for material handling and data management in a range of industrial environments

SMART

Mobile and Autonomous teams of flexible robots

PRACTICAL

Designed to work with

and alongside people

SUSTAINABLE

HV-100

Harvest Automation's flagship product is designed to perform material handling tasks in unstructured, outdoor environments such as those typically found in commercial growing operations. The robots work safely alongside people and require minimal training to operate, while vastly reducing production costs and improving productivity. The HV-100 robots reduce direct labor headcount and costs while enabling efficiency initiatives such as resource management, just in time production, and inventory control.

HV-100 Features

Effective in greenhouse, hoop house and nursery environments

High placement accuracy

Handles most common container sizes

Quick swap rechargeable battery

Minimal training and setup

No programming required

Fully autonomous both indoor and outdoor

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Harvest Automation | Mobile Autonomous Robots for Agriculture

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Scalable and flexible systems for material handling and data management in a range of industrial environments SMART Mobile and Autonomous teams of flexible robots PRACTICAL Designed to work with and alongside people SUSTAINABLE HV-100 Harvest Automation's flagship product is designed to perform material handling tasks in unstructured, outdoor environments such as those typically found in commercial growing operations.

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"What is Greenhouse Farming?": Greenhouse Farming is the process of cultivating crops and vegetable in a greenhouse ecosystems environment. Cultivation in greenhouses is a practice that has allowed farmers to increase their performance, while improving the quality of products, isolating them in micro-ecosystems that have the ideal conditions for plants to grow healthy, strong and beautiful.

To create these ideal micro-ecosystems, farmers study what exactly their plants need, and then, as basic as it sounds, give it to them.

Technology makes great things possible, and that's why today we can enjoy all kinds of fruits and vegetables, no matter what season we are in. We owe this achievement, among other things, to greenhouse cultivation.

Why cultivate in a greenhouse?

As we mentioned earlier, greenhouses must be a kind of oasis for your plants, providing them with enough light, ventilation, humidity and an adequate temperature.

Well implemented greenhouses can be a low-cost solution for increasing a farmer's productivity in countries with more harsh climates, climatic restrictions or other external risks such as hail or insect pests.

Whether you're a commercial farmer or just a gardener, greenhouse growing will expand your boundaries: it will help you grow more dainty plants and improve fruit quality.

What should a greenhouse have?

Plants are like people: not everyone likes the same things. Just as there are people who prefer the beach over the mountain and the sweet over the spicy, each plant species has its own particular preferences.

Although each farmer must take these preferences into account when setting up his greenhouse, there are certain considerations that are general and that every greenhouse should cover:

The first of these is Sunlights. To grow strong and beautiful, plants need food. No, a sandwich or hamburger does not work for them. They need ATP, a nutrient that is only obtained through a process called photosynthesis.

That means that, in any case, our plants need sufficient light and moisture. More experienced farmers recommend six to eight hours of light a day and at least 45% to 60% humidity in the air.

To grow in a greenhouse, it is also recommended that the average temperature should not exceed 20ºC during the day and should not fall below 7ºC at night.

Plants in a safe place

We were talking about how people and plants are so much alike. Well, once again, we can make the comparison. Just as there are tough people, there are others who are more delicate.

There is always in your group of friends or family that person who is, to be honest, too delicate. He or she does not like to get dirty, hot or too cold. Well, if your friend or a family member were a fruit, he would be a tomato.

A tomato? Well, yes. This delicious fruit, the main star of a rich Napoli sauce or a delicious Capressa salad, is usually very delicate... and is therefore almost always grown in a greenhouse.

Without a large enough soil and moist soil, young roots are not able to grow strong enough to support the fruits. On the other hand, if temperatures are above 25° or 27° degrees, the development of the tomato is altered and it does not bear fruit correctly.

These very specific conditions can only be achieved in a sufficiently controlled environment, and in most cases require the use of greenhouses for their cultivation.

But it is not only a matter of delicacy. If you live in a country with four well-marked seasons, you know the sudden changes in temperature that can occur from one moment to the next.

In these cases, there is always the possibility that the crops will not be able to adapt to these abrupt changes, and that is why greenhouses are used to protect the plants and to produce fruit all year round.

That does not mean that thanks to a greenhouse you can grow mangoes in the Himalayas, but at least you can be sure that you can eat Neapolitan pasta all year round.

In January last year, the MSC Group, an agricultural manufacturing company specializing in the development of high-quality greenhouses, listed the main benefits and advantages of growing using greenhouses. Several of them have already been mentioned, but we would like to explain them a little better.

The first of these advantages has, of course, a business reason. Cultivation in greenhouses, by allowing the farmer to plant under optimal conditions, ensures the good development of the crop. And as you can all imagine, a plant that grows well is a plant that bears good fruit.... fruits that can be sold on the market at a good price.

It feels good to know that a profit is safe, doesn't it? When a farmer chooses to grow in greenhouses, the risk is reduced in the face of possible random setbacks, such as some kind of extreme rise in temperature or a period of drought.

After all, nature is extremely unpredictable!

When growing using greenhouses it is much easier to keep track of how resources are used and to manage them correctly. Farmers can monitor the growth of their plants more carefully, and use the necessary fertilizers at each stage of development, for example.

The same goes for water. Many of the most advanced greenhouses have irrigation systems - which can work automatically or manually - that not only preserve the planet's most valuable resource, but also save us time and money.

We have always been taught that fire is fought with fire, but in the case of pests, we must be very careful. To deal with them, the farmer must use pesticides. While these are designed to affect plants as little as possible, nothing changes the fact that pesticides are, in fact, poison.

For this reason, they must be applied with great care and in specific places, to avoid any possible damage to the crop.

This is where our beloved micro-ecosystems make their triumphal entrance. A good properly designed and built greenhous e makes it much easier to control pests and diseases.

For what reason? By keeping plants isolated from the environment, it becomes easier to identify where the problem is (focus of infection) and how to control the situation.

However, when growing with greenhouses, since the farmer works with controlled micro-ecosystems that can be changed at will, it is much easier to deal with - or ignore - external agents.

No matter how heavy the rain is or how low the temperatures have fallen, the plants remain protected in your oasis. No matter how strong the sun or how dry the environment, the crops remain moist. So there is no need to worry about seasonal changes, as the crops can continue to be grown all year round.

Technology at the service of agriculture

Is technology limited to industrialization? Nothing could be more false than that. Today, many of the most advanced systems are being incorporated into agriculture to make processes more efficient, faster and environmentally friendly.

Solar and wind energy are still being studied, but they promise to bring incredible results to greenhouse farming.

All you have to do is sit back and wait, for the 21st century is not even in its first half yet, and the world is no longer even remotely like it used to be in the 20th century.

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Are you interested in this topic?

We are sure now you have a better idea of " What is Greenhouse Farming? ". We want to know how passionate you are about agriculture, leave us a comment and share with us what you know about greenhouses and their many advantages! Ask questions, let's debate! This is how we will continue enriching this article every day. See you in the next article!

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WHAT IS GREENHOUSE FARMING? - GreenHouse Planter

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"What is Greenhouse Farming?": Greenhouse Farming is the process of cultivating crops and vegetable in a greenhouse ecosystems environment. Cultivation in greenhouses is a practice that has allowed farmers to increase their performance, while improving the quality of products, isolating them in micro-ecosystems that have the ideal conditions for plants to grow healthy, strong and beautiful.

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Smart Farming
Agiculture
IOT in

Smart Agriculture And Modern Technology

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Now we need to discuss the  impacts, challenges and potential of ICT in farming in the future

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Now we need to discuss the  impacts, challenges and potential of ICT in farming in the future

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Here is my exploration of some of the benefits arising from the application of IoT in agriculture. IoT application leads to Increase the production of crops and livestock through creating the right environment, monitoring and controlling various aspects. Secondly, IoT helps in reducing the cost of production, especially in largescale farming. The IoT devices reduce the need for human interventions, thus reducing the number of employees on a farm.  Do you have anything to add?

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IoT is bringing revolution to almost every aspect of our lives by changing how we do things. The use of Smart IoT devices is on the rise with all the industries heavily investing in IoT. The main aims of investing in IoT are to improve operations efficiency, improve product quality, and reduce the costs of production. The Agricultural industry is among the industries seeking to reap the benefits of IoT. The use of IoT in agriculture is commonly referred to as Smart Farming or Smart Agriculture. It uses various IoT sensors to send the farm's data, like humidity, temperature, soil moisture, etc. to the cloud which can be monitored and controlled from anywhere in the world.

According to the Food and Agricultural Organization (FAO), there will be eight billion people globally by the year 2025 and 9.6 billion by 2050. This means that food production must go up by 70 percent to feed that population. IoT is one of the technologies expected to assist in reaching that goal.

How IoT is implemented in Agriculture

There are several ways of implementing Smart Agriculture using IoT

1. Precision Farming

2. Agricultural Drones

3. Livestock Monitoring

4. Smart Greenhouses

1. Precision Farming

Precision farming is the most famous application of smart farming using IoT. Precision farming is the practice of making agricultural processes more accurate and controlled for rearing livestock and crop growing. The main components of precision farming are the IT systems, sensors, control systems, automated hardware, and autonomous vehicles, among others. IoT introduces the idea of connecting these systems and devices using the internet for better data storage and analytics. IoT improves services such as livestock monitoring, soil moisture probes, inventory monitoring, and tracking of vehicles, among others. Precision farming involves the collection of data through sensors and analyzing it for use by farmers to make informed and quick decisions.

2. Agricultural Drones

Drones are being used to improve several agricultural practices in Smart Farming Using IoT. There are two types of agricultural drones, the surface-based and aerial-based. The drones are used for activities such as assessment of crop health, spraying of crops, planting, soil and field analysis, crop monitoring, and irrigation.

Drones can collect multispectral, thermal and visual imagery data that provide the farmers with a wide array of metrics such as plant health, plant count and expected yield, soil nitrogen and moisture content, drainage mapping, and canopy cover mapping. The data helps the farmer make the right decisions and use only the required resources to avoid wastage.

Aerial drones cover more land than a ground-based human observer in the same amount of time as it has the ability to avoid barriers. Automating drones to carry out routine assessments eliminates the need for human operation. The drones are deployed to cover large tracts of land where regular monitoring is required. Also, drones are very useful in situations where bacteria, fungus, or pests are difficult to control and require regular spraying and monitoring.

3. Livestock Monitoring

Livestock monitoring is also become 'Smart' in smart agriculture using IoT. It enables farmers to monitor the condition of their animals. The farmer can monitor the animals' activities such as movements, eating habits, weight, and reproductive cycle, among others.

The IoT solutions for livestock monitoring involves animal wearables that connect to a gateway using a low-cost and low bandwidth technology (LoRaWAN) to transmit data to the cloud. The wearables contain sensors that monitor aspects such as blood pressure, respiration, heart rate, body temperature, and digestion, among others. The data is used in decision making and keeping the health in check. The farmers are able to take corrective measures well in time. For instance, they are able to identify a sick animal and call a veterinary doctor well in time to prevent death or spread the disease to other animals. Reproductive cycles and calving are monitored by collecting data relating to time on heat, and the time to give birth.

An example of an IoT livestock monitoring device is the Cattle Traxx. This device contains battery-and-solar-charged sensors which transmit data using LoRaWAN (Low Power Wide Area Network). The sensors on the cow form a mesh network to enable efficient data collection. Cattle Traxx collects data regarding animal health using the sensors, and location details using Geofencing.

4. Smart Greenhouses

Traditional greenhouses relied on manual interventions to control environmental parameters for the growth of crops. However, manual interventions have disadvantages such as energy loss and production loss. Smart greenhouse solves these issues by use of IoT systems by monitoring and controlling aspects such as temperatures, luminosity, soil and mineral content, and humidity. Using the collected data, optimal plant growth conditions can be maintained to ensure maximum production. The actuators are controlled automatically to control the conditions by performing actions like opening a window, turning on the lights, and controlling the heater and fan, among others.

Smart greenhouses also help in reducing wastage smart agriculture using IOT. By monitoring moisture content, the right amount of water can be used for irrigation and this prevents wastage, the same case applies to soil mineral content as the right minerals in the right amounts are used. This reduces wastage and maintains a balance that is best for crop growth.

Benefits of IoT Applications in Agriculture

Several benefits arise from the application of IoT in Agriculture. IoT application leads to Increase production in crops and livestock through creating the right environment, monitoring and controlling different aspects. Secondly, IoT helps in reducing the cost of production, especially in largescale farming. The IoT devices reduce the need for human interventions, thus reducing the number of employees on a farm. Additionally, the IoT application reduces the wastage of resources such as water, fertilizers, and machine spare parts. They ensure only the right amounts of water and minerals are added to the soil. Sensors on vehicles and agricultural machines aid in predictive maintenance to ensure timely repairs and only the faulty parts are replaced. Lastly, the application of IoT improves overall farm operational efficiencies by providing data that allows every process to run optimally.

Conclusion - Smart Farming using IoT

So after knowing about some IoT applications in agriculture, we can say that it is definitely revolutionize the agriculture industry in a few years. IoT has been applied in several areas of agriculture. A lot of research is underway to ensure more IoT devices are used to make the managing of farms easier and increase productivity. IoT is allowing farmers to easily obtain data that is useful in many ways such as decision making. With the increasing demand for food due to the rapid population increase, we expect more IoT applications in the next few years.

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Smart Farming- IoT Applications in Agriculture

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The use of IoT in agriculture is commonly referred to as Smart Farming or Smart Agriculture. It uses various IoT sensors to send the farm's data, like humidity, temperature, soil moisture, etc. to the cloud which can be monitored and controlled from anywhere in the world.

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There are certain challenges you need to be aware of if you are considering investing into smart farming.
1. The hardware
In any case, the quality of your sensors is crucial to the success of your product.
2. The brain
You need to have powerful data analytics capabilities and apply predictive algorithms and machine learning in order to obtain actionable insights based on the collected data.

4. The mobility
Each connected device should be autonomous and have enough wireless range to communicate with the other devices and send data to the central server.

If you have any more useful information, let 's commet here.

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Eastern Peak - Technology Consulting & Development Company

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Thus, it is only logical that IoT, connected devices, and automation would find its application in agriculture, and as such, tremendously improve nearly every facet of it. How could one still rely on horses and plows when self-driving cars and virtual reality are no longer a sci-fi fantasy but an everyday occurrence?

Farming has seen a number of technological transformations in the last decades, becoming more industrialized and technology-driven. By using various smart agriculture gadgets, farmers have gained better control over the process of raising livestock and growing crops, making it more predictable and improving its efficiency.

This, along with the growing consumer demand for agriculture products, has contributed to the increased proliferation of smart farming technologies worldwide. In 2022, the market share for IoT in agriculture reached $13.76 billion.

In this article, we will explore the IoT use cases in agriculture and examine their benefits. So, if you are considering investing into smart farming, or are planning to build an IoT solution for agriculture, dive right in.
What is smart agriculture? The definition and market size

There are many ways to refer to modern agriculture. For example, AgriTech refers to the application of technology in agriculture in general.

Smart agriculture, on the other hand, is mostly used to denote the application of IoT solutions in agriculture. So what is smart agriculture using IoT? By using IoT sensors to collect environmental and machine metrics, farmers can make informed decisions, and improve just about every aspect of their work - from livestock to crop farming.

For example, by using smart agriculture sensors to monitor the state of crops, farmers can define exactly how many pesticides and fertilizers they have to use to reach optimal efficiency. The same applies to the smart farming definition.

Although smart agriculture IoT, as well as industrial IoT in general, aren't as popular as consumer connected devices; yet the market is still very dynamic. The adoption of IoT solutions for agriculture is constantly growing.

Namely, COVID-19 has had a positive impact on IoT in the agriculture market share. Disruptions in the supply chain, and the shortage of qualified workers, has propelled its CAGR to 9,9%. In fact, as per recent reports, the smart framing market share is set to reach $28.56 billion by 2030.

At the same time, the global smart agriculture market size is to triple by 2025, reaching $15.3 billion (compared to being slightly over $5 billion back in 2016).

Because the market is still developing, there is still ample opportunity for businesses willing to join in. Building IoT products for agriculture within the coming years can set you apart as an early adopter, and as such, help you pave the way to success.

But why should you consider building an IoT application for agriculture in the first place?

The Benefits of smart farming: How's IoT shaping agriculture

Technologies and IoT have the potential to transform agriculture in many aspects. Namely, there are 6 ways IoT can improve agriculture:

Data, tons of data, collected by smart agriculture sensors, e.g. weather conditions, soil quality, crop's growth progress or cattle's health. This data can be used to track the state of your business in general as well as staff performance, equipment efficiency, etc.

Better control over the internal processes and, as a result, lower production risks. The ability to foresee the output of your production allows you to plan for better product distribution. If you know exactly how much crops you are going to harvest, you can make sure your product won't lie around unsold.

Cost management and waste reduction thanks to the increased control over the production. Being able to see any anomalies in the crop growth or livestock health, you will be able to mitigate the risks of losing your yield.

Increased business efficiency through process automation. By using smart devices, you can automate multiple processes across your production cycle, e.g. irrigation, fertilizing, or pest control.

Enhanced product quality and volumes. Achieve better control over the production process and maintain higher standards of crop quality and growth capacity through automation.

Reduced environmental footprint. Automation also carries environmental benefits. Smart farming technologies can cut down on the use of pesticides and fertilizer by offering more precise coverage, and thus, reduce greenhouse gas emissions.

As a result, all of these factors can eventually lead to higher revenue.

Now that we have outlined how IoT can be advantageously applied in the sphere of agriculture, let's take a look at how the listed benefits can find their application in real life.

IoT use cases in agriculture (with examples)

There are many types of IoT sensors for agriculture as well as IoT applications in agriculture in general:

1. Monitoring of climate conditions

Probably the most popular smart agriculture gadgets are weather stations, combining various smart farming sensors. Located across the field, they collect various data from the environment and send it to the cloud. The provided measurements can be used to map the climate conditions, choose the appropriate crops, and take the required measures to improve their capacity (i.e. precision farming).

2. Greenhouse automation

Typically, farmers use manual intervention to control the greenhouse environment. The use of IoT sensors enables them to get accurate real-time information on greenhouse conditions such as lighting, temperature, soil condition, and humidity.

In addition to sourcing environmental data, weather stations can automatically adjust the conditions to match the given parameters. Specifically, greenhouse automation systems use a similar principle.

3. Crop management

One more type of IoT product in agriculture and another element of precision farming are crop management devices. Just like weather stations, they should be placed in the field to collect data specific to crop farming; from temperature and precipitation to leaf water potential and overall crop health.

4. Cattle monitoring and management

Just like crop monitoring, there are IoT agriculture sensors that can be attached to the animals on a farm to monitor their health and log performance. Livestock tracking and monitoring help collect data on stock health, well-being, and physical location.

For example, such sensors can identify sick animals so that farmers can separate them from the herd and avoid contamination. Using drones for real-time cattle tracking also helps farmers reduce staffing expenses. This works similarly to IoT devices for petcare .

5. Precision farming

Also known as precision agriculture, precision farming is all about efficiency and making accurate data-driven decisions. It's also one of the most widespread and effective applications of IoT in agriculture.

By using IoT sensors, farmers can collect a vast array of metrics on every facet of the field microclimate and ecosystem: lighting, temperature, soil condition, humidity, CO2 levels, and pest infections. This data enables farmers to estimate optimal amounts of water, fertilizers, and pesticides that their crops need, reduce expenses, and raise better and healthier crops.

For example, CropX builds IoT soil sensors that measure soil moisture, temperature, and electric conductivity enabling farmers to approach each crop's unique needs individually. Combined with geospatial data, this technology helps create precise soil maps for each field. Mothive offers similar services, helping farmers reduce waste, improve yields, and increase farm sustainability.

6. Agricultural drones

Perhaps one of the most promising agritech advancements is the use of agricultural drones in smart farming. Also known as UAVs (unmanned aerial vehicles), drones are better equipped than airplanes and satellites to collect agricultural data. Apart from surveillance capabilities, drones can also perform a vast number of tasks that previously required human labor: planting crops, fighting pests and infections, agriculture spraying, crop monitoring, etc.

Read more: Why Use Agriculture Drones? Main Benefits and Best Practices

DroneSeed, for example, builds drones for planting trees in deforested areas. The use of such drones is 6 times more effective than human labor. A Sense Fly agriculture drone eBee SQ uses multispectral image analyses to estimate the health of crops and comes at an affordable price.

7. Predictive analytics for smart farming

Precision agriculture and predictive data analytics go hand in hand. While IoT and smart sensor technology are a goldmine for highly relevant real-time data, the use of data analytics helps farmers make sense of it and come up with important predictions: crop harvesting time, the risks of diseases and infestations, yield volume, etc. Data analytics tools help make farming, which is inherently highly dependent on weather conditions, more manageable, and predictable.

For example, the Crop Performance platform helps farmers access the volume and quality of yields in advance, as well as their vulnerability to unfavorable weather conditions, such as floods and drought. It also enables farmers to optimize the supply of water and nutrients for each crop and even select yield traits to improve quality.

Applied in agriculture, solutions like SoilScout enable farmers to save up to 50% irrigation water, reduce the loss of fertilizers caused by overwatering, and deliver actionable insights regardless of season or weather conditions.

8. End-to-end farm management systems

A more complex approach to IoT products in agriculture can be represented by the so-called farm productivity management systems. They usually include a number of agriculture IoT devices and sensors, installed on the premises as well as a powerful dashboard with analytical capabilities and in-built accounting/reporting features.

In addition to the listed IoT agriculture use cases, some prominent opportunities include vehicle tracking (or even automation), storage management, logistics, etc.

9. Robots and autonomous machines

Robotic innovations also offer a promising future in the field of autonomous machines for agricultural purposes. Some farmers already use automated harvesters, tractors, and other machines and vehicles that can operate without a human controlling it. Such robots can complete repetitive, challenging, and labor-intensive tasks.

For instance, modern agrobots include automated tractors that can work on assigned routes, send notifications, start work at planned hours, etc. Such tractors are driverless and cut farmers' labor costs. Bear Flag Robotics is one company that works on such technology at the moment.

In addition, smart farming also uses robots for planting seeds, weeding, and watering. The given jobs are very demanding and labor-intensive. Yet, robots, such as ones from Eco Robotics, can detect weeds or plant seeds using computer vision and AI technology. These agricultural robots work delicately, drastically reducing harm to the plants and the environment.

Things to consider before developing your smart farming solution

As we can see, the use cases for IoT in agriculture are endless. There are many ways smart devices can help you increase your farm's performance and revenue. However, agriculture IoT apps development is no easy task.

There are certain challenges you need to be aware of if you are considering investing into smart farming.

1. The hardware

To build an IoT solution for agriculture, you need to choose the sensors for your device (or create a custom one). Your choice will depend on the types of information you want to collect and the purpose of your solution in general.

In any case, the quality of your sensors is crucial to the success of your product: it will depend on the accuracy of the collected data and its reliability.

2. The brain

Data analytics should be at the core of every smart agriculture solution. The collected data itself will be of little help if you cannot make sense of it.

Thus, you need to have powerful data analytics capabilities and apply predictive algorithms and machine learning in order to obtain actionable insights based on the collected data.

3. The maintenance

Maintenance of your hardware is a challenge that is of primary importance for IoT products in agriculture, as the sensors are typically used in the field and can be easily damaged.

Thus, you need to make sure your hardware is durable and easy to maintain. Otherwise you will need to replace your sensors more often than you would like.

4. The mobility

Smart farming applications should be tailored for use in the field. A business owner or farm manager should be able to access the information on site or remotely via a smartphone or desktop computer.

Plus, each connected device should be autonomous and have enough wireless range to communicate with the other devices and send data to the central server.

5. The infrastructure

To ensure that your smart farming application performs well (and to make sure it can handle the data load), you need a solid internal infrastructure.

Furthermore, your internal systems have to be secure. Failing to properly secure your system only increases the likeliness of someone breaking into it, stealing your data or even taking control of your autonomous tractors.

The need to transmit data between many agricultural facilities still poses a challenge for the adoption of smart farming. Needless to say, the connection between these facilities should be reliable enough to withstand bad weather conditions and to ensure non-disruptive operations.

Today, IoT devices still use varying connection protocols, although the efforts to develop unified standards in this area are currently underway. The advent of 5G and technologies like space-based Internet will, hopefully, help find a solution to this problem.

7. Data collection frequency

Because of the high variety of data types in the agricultural industry, ensuring the optimal data collection frequency can be problematic. The data from field-based, aerial and environmental sensors, apps, machinery, and equipment, as well as processed analytical data, can be a subject of restriction and regulations.

Today, the safe and timely delivery, and sharing of this data is one of the current smart farming challenges.

8. Data security in the agriculture industry

Precision agriculture and IoT technology imply working with large sets of data, which increases the number of potential security loopholes that perpetrators can use for data theft and hacking attacks. Unfortunately, data security in agriculture is still, to a large extent, an unfamiliar concept.

Many farms, for example, use drones that transmit data to farm machinery. This machinery connects to the Internet but has little to zero security protection, such as user passwords or remote access authentications.

Some of the basic IoT security recommendations include monitoring data traffic, using encryption methods to protect sensitive data, leveraging AI-based security tools to detect traces of suspicious activity in real-time, and storing data in the blockchain to ensure its integrity.

To fully benefit from IoT, farmers will have to get familiar with the data security concept, set up internal security policies, and adhere to them.

Our work case of IoT solutions for agriculture

Our team at Eastern Peak has also contributed to the progress of IoT applications in agriculture. The IoT-powered irrigation application, GreenIQ, helps gardeners reduce water usage by 50%, monitor humidity levels, and predict the best timing for irrigation. GreenIQ uses smart sensors to analyze meteorological conditions and soil types, creating the perfect irrigation strategy and adapting to new environments.

The GreenIQ application also integrates with the most well-known home automation platforms. This app is another valuable contribution to eco-friendly gardening and one of many examples of how smart farming products can change the future of agriculture.

Grow your agriculture business with smart IoT solutions from Eastern Peak

According to the UN Food and Agriculture Organization (FAO) , the global population is expected to surpass 9 billion people by 2050. To produce enough food for the given population, agriculture production volumes have to increase by 50%.

As the resources for agricultural operations are limited (most of the lands suitable for farming are already in use), the only way to increase volume is to improve production efficiency. There is no doubt as to the extent with which smart farming can help tackle this challenge; in fact, it seems that it is not possible without it. Here at Eastern Peak we develop custom IoT solutions for agriculture, tailored to your particular needs.

How to get started?

From cattle tracking to advanced field mapping, IoT applications in smart agriculture vary from farm to farm depending on your market segment, climate, and region. In many instances, out-of-the-box tools won't be relevant, and you may need a tailored smart farming IoT solution. At Eastern Peak we approach each customer individually to meet their unique needs.

The product discovery phase is the best first step you can take to lay a solid foundation for the development of your app. It includes a functional specification, UX/UI design, and a visual prototype that will give you a clear vision of the end product. On average, this phase takes 4-6 weeks.
The product discovery phase can help you:

define a full scope of work and develop a roadmap for the project

set a realistic budget for your MVP and plan your resources

test the waters with your audience using a visual prototype

craft a convincing investment pitch

get to know your team

We at Eastern Peak have already helped many startups and Fortune 500 companies digitize and streamline their operations with the help of technologies. We provide end-to-end services building IoT solutions across a number of business domains, from hardware design to software development, testing, and integration. To receive professional consultation from our experts, get in touch with us using our contact form. Read also:
About the author:

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IoT in Agriculture: 9 Technology Use Cases for Smart Farming (and Challenges to Consider)

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Farming has seen a number of technological transformations in the last years,and IoT in agriculture is one of them. Here you can find the best IoT use cases

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As far as I think the potential of ICT in farming in the future is as follows
- The future of smart agriculture will apply to many countries instead of some developed countries like now.
- Everything will be done automatically, humans only need to stand in the position of the operator to dare to monitor the operation of the machine.

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Benefit:
1. Minimizing Production Risks
2. Increased Production
3. Maximizing Profits
4. Disease & Pest Prevention
5. Year-Round Growing
6. Increased Stability and Security