# data[].attributes.body
• Audience: school nurse, athletic trainer
• Value: baseline tracking + post-exercise checks
• Edge: includes refractometer reference workflow

# data[].attributes.body
• Audience: athletes during practice
• Value: rapid check between drills
• Edge: consistent electrode placement

# data[].attributes.body
• Smart bottle cap that estimates intake + prompts
• Locker-room kiosk that logs hydration via touch
• App-only coach dashboard fed by our prototype

# data[].attributes.body
• Impedance front-end principles
• RH/Temp sensors; optional flow/CO₂ gating
• Signal conditioning, ADC sampling, BLE data push
• Power: LiPo + charging, battery life estimation

# data[].attributes.body
• Audience: student athletes, hikers, workers in heat
• Value: quick hydration index + water/electrolyte advice
• Edge: multi-sensor (bioimpedance + breath RH/T)

# data[].attributes.body
• AC injection, complex impedance (magnitude, phase)
• Two-frequency approach (e.g., 50 kHz & 200 kHz)
• Safety: microamp currents; contraindications (implants)
• Skin-electrode contact, temperature compensation

# data[].attributes.body
• Feature extraction (|Z|, phase, deltas)
• Calibration vs. references (USG, % body-mass change)
• Simple models: linear/logistic regression
• Evaluation: ROC, AUC, Bland–Altman, repeatability

# data[].attributes.body
• Instructions-for-use, hygiene for mouthpieces
• Informed assent/consent for volunteer testing
• Disclaimers: educational, not diagnostic

# data[].attributes.body
Smart bottles (track intake, reminders)
• Consumer BIA scales/wearables (fluid status proxies)
• Athletic trainer tools (USG strips/refractometers)
• Industrial heat-stress monitors (WBGT, sweat-loss calculators)

# data[].attributes.body
• Few quick checks combining multiple signals
• Limited guidance that adapts to context (heat, effort)
• School-friendly, low-cost, open prototype data

# data[].attributes.body
• Fuse BIA + breath RH/T + temp
• Personalized baselines; simple traffic-light results
• Validated vs. % body-mass change + USG

# data[].attributes.body
• ESP32: $8
• Impedance AFE eval: $30–$60
• Sensors (RH/T, optional flow/CO₂): $12–$40
• Electrodes & wiring: $10
• Battery + charger: $12
• Enclosure/3D print: $15
• Validation refractometer: $25–$40
• Est. total: $150–$250

# data[].attributes.body
• W1–2: parts ordering, safety review
• W3–4: electronics bring-up, basic readings
• W5–6: firmware + phone/laptop app
• W7–8: pilot tests, calibration plan
• W9–10: validation sessions (pre/post exercise)
• W11: analysis & model tuning
• W12: final report, poster, demo video

# data[].attributes.body
• Noisy signals → repeated measures, consistent grip
• Electrode inconsistency → jig/handle design
• Low participation → recruit teammates early, consent forms
• Schedule slips → lock milestones, weekly stand-ups

# data[].attributes.body
• EE mentor: circuit/safety review
• Data mentor: stats/model validation
• Coach/trainer: protocol design, volunteer access
• Maker mentor: enclosure/ergonomics

# data[].attributes.body
• Safe current limits and frequencies for BIA
• Best electrode materials/placement
• Minimum sample size for ROC/AUC ~0.75 target
• Consent language for school setting

# data[].attributes.body
• Texts on bioimpedance & hydration
• Human-subjects guidelines for schools
• Sports medicine hydration guidance
• Sensor datasheets (impedance AFE, RH/T)
• Prior student projects; open-source code
We NEED: Add citation on each card: [Author, Title, Year, URL].

# data[].attributes.body
Students and workers in heat lack a fast, low-cost way to check hydration on-site. Lab tools (osmolality), bathroom tests (USG), or single-signal devices have limits. Build a handheld multi-sensor device that outputs a Hydration Index and intake guidance, validated against % body-mass change and USG.

# data[].attributes.body
• Repeatable readings
• Correlation ≥0.6 with % mass change; AUC ≥0.75
• Under $250 BOM; <90s per test; safe and documented
• User guide + validation report + demo video

# data[].attributes.body
• Understand real user needs using human-centered design
• Identify unmet problems around UV exposure
• Define markets that benefit most
• Use surveys + mentor feedback to guide design
• Prepare for interviews and design iteration

# data[].attributes.body
• Health matters, but convenience comes first
• Long-term UV harm is underestimated
• Automatic tools are preferred
• Cost and ease of use > advanced features
• Minimal effort solutions are most attractive

# data[].attributes.body
• Real-time UV exposure awareness
• Reminders to apply sunscreen or seek shade
• Personalized data (not general weather info)
• Alerts without constant checking
• Easy integration into daily life

# data[].attributes.body
• Students and teenagers
• Athletes (soccer, runners, outdoor sports)
• Spend long hours outdoors
• Familiar with wearable tech
• Active during peak UV hours

# data[].attributes.body
• Outdoor workers
• Parents monitoring children
• Individuals with sensitive skin
• People with medical risk factors
• Recreational outdoor users

# data[].attributes.body
• Sunscreen often forgotten during activities
• Temperature used instead of UV Index
• Wearables are common and accepted
• UV exposure is easily overlooked

# data[].attributes.body
• Consumer surveys conducted
• Peer interviews and discussions
• Mentor feedback sessions
• Design ideas tested informally

# data[].attributes.body
• Team experiences outdoor UV exposure
• Manual UV checking is inconvenient
• Cumulative exposure is easy to miss
• Firsthand validation of problem

# data[].attributes.body
• Most users don’t check UV Index
• Many have experienced sunburn
• Real-time tracking is appealing
• Alerts/reminders strongly preferred
• Comfort and size are critical

# data[].attributes.body
• Explain product in simple language
• Focus on why it matters
• Physical prototypes are essential
• User-facing features matter most

# data[].attributes.body
• “Fitbit for sun safety” messaging
• Built large-scale cardboard prototype
• Prioritized alerts and guidance
• Improved communication for non-engineers

# data[].attributes.body
• Project is feasible and meaningful
• Marketing needs improvement
• Move toward real components
• Transition from concept to prototype

# data[].attributes.body
• Low awareness of UV exposure
• Desire to protect skin health
• Preference for convenience
• Interest in wearable solutions

# data[].attributes.body
• Varying skin sensitivity
• Different outdoor exposure levels
• Different willingness to wear devices
• Different alert preferences

# data[].attributes.body
• UV risk underestimated on cool/cloudy days
• Cumulative exposure misunderstood
• Alerts valued more than raw data
• Few accurate UV wearables exist

# data[].attributes.body
• No personal UV awareness
• Forgotten sunscreen application
• No cumulative UV tracking
• Reliance on inaccurate weather cues
• Poor communication of UV risk

# data[].attributes.body
People lack an easy, personal way to track real-time and cumulative UV exposure, leading to preventable skin damage and long-term health risks.

# data[].attributes.body
• Comfortable wrist-worn device
• Automated alerts and reminders
• Simple, clear app interface
• Personalized UV insights
• Minimal user effort

# data[].attributes.body
• Conduct formal customer interviews
• Refine feature wishlist
• Begin electronics prototyping
• Test usability with real users
• Iterate based on feedback