A campus-grade IoT air quality monitoring system built to detect vape aerosols in real time — keeping shared spaces safer for everyone.
Vaping inside campus buildings is a growing concern. Traditional enforcement relies on manual patrols — slow, inconsistent, and easy to evade. FreshZone replaces guesswork with data: low-cost ESP32-based sensors continuously sample the air for PM1.0 particulate matter — the ultra-fine particles produced by vape aerosol — then stream readings to a live web dashboard accessible to all authorized staff.
When aerosol concentrations exceed safe thresholds, the system automatically flags the location, sends push notifications to registered staff, and logs the incident for review. The goal is faster response, better documentation, and measurable improvement in campus air quality.
Particles under 1 µm are the primary output of vape devices. FreshZone focuses on PM1.0 exclusively because it is highly specific to fresh fine aerosol and produces far fewer false positives than broader particle metrics.
The PMS7003 fires a precision laser through a sampling chamber. Airborne particles scatter the beam, and the scatter intensity maps directly to a PM1.0 concentration value in µg/m³, sampled once every second.
The ESP32 reads the sensor output and transmits readings to the FreshZone server every 3–5 seconds over Wi-Fi. When PM1.0 exceeds the threshold, the server immediately pushes a Web Push alert to all registered staff devices.
No cameras, no microphones. We detect aerosols — not people. All data is anonymized at the sensor level.
Sensor data updates every 3 seconds. Staff sees live PM1.0 data before manual inspection would even begin.
PWA-ready on any device. Works on low-end phones with offline fallback through a service worker.
Every detection event is logged with timestamp, location, and PM1.0 peak reading. Full history is exportable as CSV.
Identified vaping as a campus enforcement gap. Selected the ESP32 + PMS7003 sensor stack after evaluating cost vs. accuracy trade-offs.
Built the first physical sensor enclosure and the Node.js REST API. Validated PM readings against a reference monitor in a controlled room test.
Launched the live dashboard with role-based access, OTP email auth, real-time PM1.0 detection cards, and Web Push alerts for staff and admins.
Three sensor nodes active across campus. History export, CSV reporting, incident ticketing, and continuous UI improvements now in production.
FreshZone is a research project developed by a team of Information Technology Mobile App and Web Development students — combining hardware engineering, full-stack web development, and UX design.
Node.js API, database design, sensor integration & deployment
Dashboard interface, design system, PWA implementation
ESP32 firmware, sensor calibration & enclosure design
Server-side logic, API integration & database management
We thank our thesis adviser, the campus administration, and all faculty who supported this project — and every staff member who gave feedback during testing.
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