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Name_Matrice Number_Programme_Title_5 Keywords

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Improve Greenhouse System Through IoT Technology

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Improve Greenhouse System Through IoT Technology

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Mukhlis Radzai_834994

STIQ6014_A

Keywords : Internet Of Things, Automation, Smart Agriculture, Environmental Optimization, Smart Greenhouse

Problem Statement:

1. Traditional farm/existing greenhouse or farm requires a significant amount of human labor and energy

2. Existing greenhouse/farm cannot provide the optimal environment conditions needed for maximum crop yield and quality

3. Managing plant health and optimizing growth in greenhouses is a challenge, especially in Malaysia's humid climate.

5 Articles:

1. A Revisit of Internet of Things Technologies for Monitoring and Control Strategies in Smart Agriculture (MDPI-2022)

Rehman, A., Saba, T., Kashif, M., Fati, S. M., Bahaj, S. A., & Chaudhry, H. (2022). A Revisit of Internet of Things Technologies for Monitoring and Control Strategies in Smart Agriculture. In Agronomy (Vol. 12, Issue 1). MDPI. https://doi.org/10.3390/agronomy12010127

2. Design, technology, and management of greenhouse: A review (Elsevier-2022)

Badji, A., Benseddik, A., Bensaha, H., Boukhelifa, A., & Hasrane, I. (2022). Design, technology, and management of greenhouse: A review. In Journal of Cleaner Production (Vol. 373). Elsevier Ltd. https://doi.org/10.1016/j.jclepro.2022.133753

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3. Internet of Things in Greenhouse Agriculture A Survey on Enabling Technologies Applications and Protocols (IEEE Access-2022)

Farooq, M. S., Riaz, S., Helou, M. A., Khan, F. S., & Abid, A. (2022). A Survey on IoT in Agriculture for the Implementation of Greenhouse Farming. IEEE Access, 1–1. https://doi.org/10.1109/access.2022.3166634

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4. Climate-smart agro-hydrological model for a large scale rice irrigation scheme in Malaysia (MDPI-2020)

Ismail, H., Kamal, M. R., bin Abdullah, A. F., & bin Mohd, M. S. F. (2020). Climate-smart agro-hydrological model for a large scale rice irrigation scheme in Malaysia. Applied Sciences (Switzerland), 10(11). https://doi.org/10.3390/app10113906

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5. IoT-based sensor data fusion for determining optimality degrees of microclimate parameters in commercial greenhouse production of tomato (MDPI-2020)

Rezvani, S. M. E., Abyaneh, H. Z., Shamshiri, R. R., Balasundram, S. K., Dworak, V., Goodarzi, M., Sultan, M., & Mahns, B. (2020). IoT-based sensor data fusion for determining optimality degrees of microclimate parameters in commercial greenhouse production of tomato. Sensors (Switzerland), 20(22), 1–32. https://doi.org/10.3390/s20226474

Research Question:

1. What are the current conditions and limitations of the existing greenhouse infrastructure in terms of temperature regulation, humidity levels, soil moisture management, and light exposure?

2. How can an IoT-based greenhouse monitoring system be designed and implemented to effectively monitor and manage temperature, humidity, and light exposure in real-time?

3. How effective and practical is the IoT-based greenhouse monitoring system in providing real-time data collection and visualization, and what improvements can be made to enhance its utility for greenhouse management?

Research Objective:

1. To identify the current greenhouse infrastructure, focusing on its current temperature regulation, humidity levels, soil moisture management and light exposure

2. To design and develop an IoT-based greenhouse monitoring system that can monitoring on temperature, humidity and light

3. To evaluate the current performance in real-time and practicality of the IoT-based greenhouse monitoring system, with a particular emphasis on its real-time data collection and the utility of the visualization dashboard

Output Tangible:

1. Improved Greenhouse System

New sensors for soil moisture, temperature, and light.

A solar panel to power everything without needing external electricity.

2. Automatic Controls

The system automatically controls the greenhouse environment

3. Dashboard Monitoring

A screen or app which can see all the data moisture, temperature and humidity in real time.

4. Solar-Powered System

A solar panel that powers the whole system with sensors, fan, pump and light making the greenhouse self-sustaining without needing extra electricity.

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Siti Nurhaninah 835002 Master ICT Coursework 

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Title:

Enhancing College Students' Financial Literacy And Interest In Financial Tools Through A Machine Learning-Based Model

Problem statement:

Financial Struggles: Students lack financial literacy, leading to overspending, debt, and instability

Ineffective Education: Traditional programs fail to provide personalized, practical training

Limited Use of Financial Tools: Students struggle with budgeting, credit management, and investments.

Keywords:

Financial Literacy

College Students

Machine Learning

Financial Tools

Interest

Journals:

1. Alshebami, A. S., & Aldhyani, T. H. H. (2022). The Interplay of Social Influence, Financial Literacy, and Saving Behaviour among Saudi Youth and the Moderating Effect of Self-Control. Sustainability (Switzerland), 14(14). https://doi.org/10.3390/su14148780

2. Johan, I., Rowlingson, K., & Appleyard, L. (2021). The Effect of Personal Finance Education on The Financial Knowledge, Attitudes and Behaviour of University Students in Indonesia. Journal of Family and Economic Issues, 42(2). https://doi.org/10.1007/s10834-020-09721-9

3. Levantesi, S., & Zacchia, G. (2021). Machine Learning and Financial Literacy: An Exploration of Factors Influencing Financial Knowledge in Italy. Journal of Risk and Financial Management, 14(3). https://doi.org/10.3390/jrfm14030120

4. Zhao, Z., Tian, Y., & Bai, T. (2022). A Study for Precise Financial Support Model for Undergraduates with Financial Difficulties Using Machine Learning. ACM International Conference Proceeding Series, 162–167. https://doi.org/10.1145/3561877.3561903

5. Zhu, A. Y. F. (2025). Unlocking financial literacy with machine learning: A critical step to advance personal finance research and practice. Technology in Society, 81. https://doi.org/10.1016/j.techsoc.2024.102797

Research Objective:

1. To identify college students' financial literacy and interest in using financial tools.

2. To design and develop a machine learning-based model for classifying financial literacy among college students.

3. To evaluate the accuracy of the machine learning-based model in classifying financial literacy levels and to analyse students' interest in financial tools.

Tangible output:

Financial Literacy Report – Analysis of students' financial literacy levels and interests.

ML-Based Classification Model – A functional machine learning model for financial literacy assessment.

Dataset & Results – Structured dataset with classification outcomes.

Model Evaluation Report – Accuracy and performance analysis of the ML model.

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Vehicle Rental Management System with Data Visualization

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Vehicle Rental Management System with Data Visualization

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AdamIrmanAsmadi_834991

MScIT

1) Problem statement:

a) The owner finds it difficult to search, sort, and filter the vehicle renters and rental vehicle data, often dealing with redundant information in the vehicle renters’ data.

b) Tedious process for vehicle renters to book a vehicle.

c) Owner does not have platform to view business performance.

2) Keyword: Data Visualization, Web-based, Information system development, SDLC process

3) Article:

a) Refactoring a Full Stack Web Application to Remove Barriers for Student Developers and to Add Customization

for Instructors. (Google Scholar, 2020)

Cook, J., Weiss, R., & Mache, J. (n.d.). Refactoring a Full Stack Web Application to Remove Barriers for Student Developers and to Add Customization for Instructors.

b) Visualization Research of WEB front-end development technology in Shandong Yellow River Union Cloud Exhibition Hall. (ACM Library, 2022)

Shan, T.-C., Zhang, A.-N., Jiang, H., & Xu, Z.-X. (2022). Visualization Research of WEB front-end development technology in Shandong Yellow River Union Cloud Exhibition Hall.

c) Design and Development of Website Dr.Changkitchen Diet Catering Using SDLC Waterfall Model. (ACM Library, 2021)

Maulana, F. I., Susanto, V., Shilo, P., Gunawan, J., Pangestu, G., & Raharja, D. R. B. (2021). Design and Development of Website Dr.Changkitchen Diet Catering Using SDLC Waterfall Model. ACM International Conference Proceeding Series.

d) Agile versus Waterfall Project Management:

Decision Model for Selecting the Appropriate Approach

to a Project. (ScienceDirect, 2021)

Thesing, T., Feldmann, C., & Burchardt, M. (2021). Agile versus Waterfall Project Management: Decision model for selecting the appropriate approach to a project.

e) Variability in Data Visualization: a Software Product Line Approach. (ACM Library, 2022)

Horcas, J. M., Galindo, J. A., & Benavides, D. (2022). Variability in Data Visualization: a Software Product Line Approach. 26th ACM International Systems and Software Product Line Conference, SPLC 2022.

4) Research objective:

a) To identify all the requirement needed to develop Vehicle Rental Management System with Data Visualization.

b)  To design and develop the Vehicle Rental Management System with Data Visualization based on the requirements.

c) To evaluate Vehicle Rental Management System with Data Visualization based on standard metric.

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Student-Centred Interface for an Islamic Digital Library: AI Summarization for Enhanced Free eBook Access

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Student-Centred Interface for an Islamic Digital Library: AI Summarization for Enhanced Free eBook Access

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Domain: Education

Keywords: AI Summarization, Digital Library, User Experience, User Friendly, Scalability.

Main Issues:

Research Objectives:

1. To design and develop an inclusive academic Islamic digital library that provides free access to Islamic eBooks, catering especially to Tahfiz students in Malaysia.

2. To integrate advanced information technology and AI-driven solutions to optimise searchability, usability and compatibility with various devices.

3. To assess user engagement and satisfaction through user experience testing and feedback analysis from Tahfiz students and educators.

Problem Statement: The research addresses the lack of inclusivity, accessibility, user friendly, and scalability in existing Islamic digital libraries while exploring sustainable solutions for long-term viability.

1. Lack of a dedicated Islamic Digital Library in Malaysia where there is no specialized academic Islamic Library that provides free access to ebooks for Tahfiz students, limiting their access to structured and comprehensive Islamic educational resources.

2. The absence of advances in IT and AI integration where current digital libraries lack intelligent searchability, adaptive learning features, and user-friendly designs, results in inefficient access to relevant Islamic educational content.

Output Tangible For IDLP

1. Functional Islamic Digital Library Platform

-A fully developed digital platform providing free access to 3,000+ Islamic eBooks with AI-powered search, recommendation features and accessibility tools.

2. AI-Enhanced Search System

-An advanced search engine that uses AI technologies. For example (Elasticsearch, OpenAI Embeddings, and NLP) enable efficient and context-aware book retrieval.

3. Accessibility & User Friendly Features

-A platform equipped with text-to-speech, voice search, and multilingual support to ensure inclusivity for students with disabilities.

4. Data & System Documentation

-Detailed system architecture, user guides and recommendations for future improvements to ensure the platform's scalability and sustainability.

5 Journals / Articles:

1. Barifah, M., Landoni, M., & Eddakrouri, A. (2020). Evaluating the user experience in a digital library. Proceedings of the Association for Information Science and Technology, 57(1), e280. (Wiley Access)

2. Jahani, H., Azzopardi, L., & Sanderson, M. (2024). Measuring the retrievability of digital library content using analytics data. Journal of the Association for Information Science and Technology, 75(11), 1233-1248. https://doi.org/10.1002/asi.24886

(Wiley Access)

3. Kato, A., Kisangiri, M., & Kaijage, S. (2021). A review Development of digital library resources at university level. Education Research International, 2021, 1–13. https://doi.org/10.1155/2021/8883483

(Wiley Access)

4. Shukor, N. L. S. A., Fuad, N., & Tukiran, Z. (2023). Development of Islamic Digital Library. Evolution in Electrical and Electronic Engineering, 4(2), 791-798. (IEEE Access).

5. Zhou, L., Yang, Y., Ji, Z., Du, Y., Zhou, M., & Huang, G. (2024). Research on the Design and Educational Application of Library Management System Based on SSM and MySQL Technology. Research on the Design and Educational Application of Library Management System Based on SSM and MySQL Technology, 4, 139–146. https://doi.org/10.1145/3670013.3670029

(ACM Digital Library)

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Development of Centralized Database Management System to Enhance Service Records and Operational Efficiency in Car Service Center

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Development of Centralized Database Management System to Enhance Service Records and Operational Efficiency in Car Service Center

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Siti Ainul Nurizzati (834896) (IT)

Keywords:

1. Automotive

2. After sale - service

3. Database Record Management System (DBMS)

4. Digitization

5. Document

Problem Statement:

Misplaced or lost of physical document

Inefficient record-keeping and retrieval of document in car service centers.

Dependency on manual documentation leading to operational delay

5 Journal Article:

1. Digital Twins in The Automotive Industry: The Road Toward Physical-Digital Convergence (MDPI, 2022)

2. Impact of Dynamic Capabilities on Customer Satisfaction Through Digital Transformation in The Automotive Sector (MDPI, 2022)

3. Research on The Influence of After sale-service Quality Factors on Customer Satisfaction (Elsevier, 2020)

4. The Effect of Service Quality on Customer Satisfaction in an Automotive After sale-service (MDPI, 2021)

5. Analysis of Challenges for Automobile Service Garages in India : A Structural Modelling Approach (Emerald Insight, 2020)

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HCI for Mental Health: Design An Interface to Reduce Digital Fatigue

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HCI for Mental Health: Design An Interface to Reduce Digital Fatigue

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1) To design a minimalist HCI interface design to lessen users digital fatigue.

2) To identify the HCI strategies that best improve user experience and reduce digital fatigue.

3) To investigate how interdisciplinary approaches inform HCI design for digital mental wellbeing.Jagvinderjit Singh_835000

STIQ6014_B

Problem statement:

Continuous interaction with digital environments can lead to information overload, emotional exhaustion, stress, and mental health issues like anxiety and depression. This digital fatigue, particularly from social media and excessive smartphone use, is exacerbated by poorly designed interfaces. To address this, Human Computer Interaction (HCI) principles should focus on designing interfaces that reduce stress by minimizing notifications, optimizing information architecture, and enhancing accessibility. The goal is to create user-friendly interfaces that mitigate digital technology fatigue and improve user experiences.

keywords:

1. Human Computer Interaction (HCI)

2. Mental Health

3. Digital Fatigue

4. User Interface (UI)

5. User Experience

Articals

1. Yoo, D. W., Woo, H., Pendse, S. R., Lu, N. Y., Birnbaum, M. L., Abowd, G. D., & De Choudhury, M. (2024). Missed Opportunities for Human-Centered AI Research: Understanding Stakeholder collaboration in Mental Health AI research. Proceedings of the ACM on Human-Computer Interaction, 8(CSCW1), 1–24. https://doi.org/10.1145/3637372(ACM)(2024)

2. Ahmed, N., Al-Hazwani, I., Fedosov, A., Schluchter, T., & Huang, E. M. (2024b). Design Cards for Culturally Sensitive Mental Health Technologies: Integrating Hofstede’s Cultural Dimension Theory into Human-Centered Design Processes. NordiCHI ’24 Adjunct: Adjunct Proceedings of the 2024 Nordic Conference on Human-Computer Interaction, 1–23. https://doi.org/10.1145/3677045.3685446(ACM)(2024)

3. Lorenz, M., Amorim, T., Dey, D., Sadeghi, M., & Ebel, P. (2024b). Computational Models for In-Vehicle User Interface Design: A Systematic Literature Review. AutomotiveUI ’24: Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 204–215. https://doi.org/10.1145/3640792.3675735(ACM)(2024)

4. Nourriz, S., Bezabih, A., & Smith, C. E. (2024b). On the Design Risks of Empathy Fatigue. EmpathiCH ’24: Proceedings of the 3rd Empathy-Centric Design Workshop: Scrutinizing Empathy Beyond the Individual, 34–39. https://doi.org/10.1145/3661790.3661798(ACM)(2024)

5.Dogan, H., Giff, S., & Barsoum, R. (2024b). User Experience Research: Point of View Playbook. CHI EA ’24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 1–7. https://doi.org/10.1145/3613905.3637136(ACM)(2024)

Research Objective

1) To design a minimalist HCI interface design to lessen users digital fatigue.

2) To identify the HCI strategies that best improve user experience and reduce digital fatigue.

3) To investigate how interdisciplinary approaches inform HCI design for digital mental wellbeing.

Output tangible

1) User Centered Design: Focus on creating interfaces that prioritize user comfort and engagement, reducing the likelihood of digital fatigue.

2)Accessibility and Inclusivity: Ensure that the interface is accessible to all users, including those with disabilities, to promote equity in mental health support.

3)Simplicity and Clarity: Design intuitive and clutter-free interfaces that facilitate easy navigation and reduce cognitive load.

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Using Data Analytics to Enhance Decision-Making in IT Project Management

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Using Data Analytics to Enhance Decision-Making in IT Project Management

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Muhammad Izwan Haikal bin Zaidi

835110

Problem statement : IT project coordinator often choose methodologies like Agile or Waterfall without using data, leading to poor decisions and project issues. Data analytics can help improve these choices by providing clear insights.

Keyword :

Data Analytics

IT Projects

Decision-Making

Agile

Waterfall

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Develop a Trust-Centric AI Framework for E-Commerce: Enhancing Customer Experience and Loyalty

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Develop a Trust-Centric AI Framework for E-Commerce: Enhancing Customer Experience and Loyalty

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Keywords :

1; Artificial Intelligence (AI),

2; E-commerce,

3; Customer Experience,

4; Personalized Engagement,

5; AI-driven Personalization,

6; Customer Behavior & Customer Satisfaction

Problem statement:

AI is transforming e-commerce by enabling personalized customer experiences, improving engagement and satisfaction (Anderson & Johnson, 2024). AI-driven tools like predictive analytics, chatbots, and recommendation systems enhance customer interactions, boosting conversion rates and retention (Balasubramanian, 2024). However, trust and loyalty remain challenges, as customers are wary of data handling, algorithmic decisions, and transparency in AI recommendations (Davoodi & Mezei, 2024). Trust significantly influences consumer behavior, and a lack of transparency in AI-driven personalization can undermine loyalty (Anderson & Johnson, 2024; Davoodi & Mezei, 2024). As AI adoption grows, a trust-centric framework is needed to strengthen user confidence and ensure long-term loyalty in AI-powered e-commerce (Davoodi & Mezei, 2024).

Research objective :

a. To examine the critical determinants of customer trust in AI-driven e-commerce platforms.

b. To investigate the relationship between AI-driven personalization, customer trust, and long-term loyalty.

C. To propose a framework for AI implementation in e-commerce that enhances trust and customer loyalty.

Research Question:

The question this research seeks to answer is as follows:

1.      What factors influence customer trust in AI-driven e-commerce platforms?

2.      How does AI-driven personalization affect customer trust and long-term loyalty in e-commerce?

3. How can AI-based e-commerce frameworks be designed to enhance customer trust and foster loyalty?

Journals:

1. Anderson, J., & Johnson, D. (2024). The role of artificial intelligence in enhancing e-commerce customer experience (No. 13355). EasyChair.

2. Gkikas, D. C., & Theodoridis, P. K. (2024). Predicting online shopping behavior: Using machine learning and Google Analytics to classify user engagement. Applied Sciences, 14(23), 11403. https://doi.org/10.3390/app142311403

3. Macumber, R., & Eswar Pagadala, V. D. (2024). Google, SEO and helpful content: How artificial intelligence can be helpful for e-commerce websites. Journal of Digital & Social Media Marketing, 12(3), 206-226.

4. Davoodi, L., & Mezei, J. (2024). A Large Language Model and Qualitative Comparative Analysis-Based Study of Trust in E-Commerce. Applied Sciences, 14(21), 10069. (MPDI) https://doi.org/10.3390/app142110069

5. ran, M. T. (2024). Unlocking the AI-Powered Customer Experience: Personalized Service, Enhanced Engagement, and Data-Driven Strategies for E-Commerce Applications. In Enhancing and Predicting Digital Consumer Behavior with AI (pp. 375-382). IGI Global.

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Osama Al-Rifai Assignment 1