Classroom Air Quality Monitor Kit
ESP32 Classroom Air Quality Monitor Kit – Predict AQI with AI and IoT
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Walk into your classroom, power up this device, and watch it not just measure air quality but predict what comes next — all on a tiny microcontroller running a machine learning model. This kit turns a standard ESP32 into an intelligent air quality monitor that learns from sensor patterns and streams predictions to a live dashboard, making it ideal for science exhibitions, CBSE AI practicals, or a first step into embedded ML.
What You'll Build
You’ll assemble a complete monitor that reads real-time gas concentrations (MQ135) and environmental conditions (DHT22). The ESP32 runs a TensorFlow Lite regression model trained to predict AQI values from these sensor feeds. Readings and predictions appear on the 0.96-inch OLED, while the exact AQI forecast flows wirelessly to a Node-RED dashboard — a working AIoT system from one box.
What You'll Learn
- How to interface analog and digital sensors with ESP32 over I2C and GPIO
- Deploying a TensorFlow Lite regression model on a microcontroller for on-device inference
- Streaming real-time IoT data to Node-RED and building a live monitoring dashboard
- Understanding the relationship between TVOC, humidity, temperature, and predicted AQI
Kit Contents
| Component | Quantity |
|---|---|
| ESP32 Dev Board | 1 |
| MQ135 Gas Sensor | 1 |
| DHT22 | 1 |
| 0.96in OLED | 1 |
| MicroUSB Cable | 1 |
| M-M Wires | 15 |
Why Buy This Kit Instead of Sourcing Parts Separately
| Factor | Sourcing Separately | Compoden Kit |
|---|---|---|
| Compatibility checks | You verify every part | Pre-tested as a system |
| Build support | Forums and scattered tutorials | AI companion trained on this exact project |
| Time to first working build | Days of debugging | Hours, with step-by-step guidance |
| Shipping coordination | Multiple sellers, multiple delays | One shipment from Bengaluru in 3-5 days |
Who This Kit Is For
CBSE Class 11–12 students tackling AI or IT practicals will find the TFLite-on-ESP32 flow matches syllabus goals. B.Tech ECE and EEE students can use it for IoT lab submissions or Smart India Hackathon prototypes. ATL Tinkering Labs get a ready-made activity that covers sensors, ML, and dashboard building — all with components trusted in Indian institutions.
Built and Backed by Compoden
Every Compoden kit ships with an AI build companion trained on this exact project — accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.
What if I get stuck during the build?
Scan the QR code to chat with the AI companion, or drop a message on WhatsApp — we’ll help you debug the exact step you’re on.
Do I need coding experience to build this?
The kit comes with pre-written firmware and a drag-and-drop Node-RED dashboard template. You’ll upload code to the ESP32 and arrange dashboard widgets — no coding from scratch required.
Can I use this for a CBSE science exhibition or ATL project?
Absolutely. The real-time AQI prediction with ML and IoT streaming matches many project requirements. The OLED display and Node-RED dashboard make it demonstration-ready.
Does this kit measure actual AQI or just predict it?
The MQ135 detects TVOC and equivalent CO2, which the TFLite model uses along with temperature and humidity to predict a composite AQI value. It is a learned approximation, not a calibrated reference instrument.
School Air — MQ135 and DHT22 data feeds a TFLite regression model on ESP32 predicting AQI — streams predictions to Node-RED.
What's in this kit
- ESP32 Dev Board
- MQ135 Gas Sensor
- DHT22
- 0.96in OLED
- MicroUSB Cable
- M-M Wires x15
Shipping Information
- Prepaid Orders: ₹75 for orders up to ₹999, FREE shipping above ₹999
- COD Orders: ₹125 shipping + ₹50 COD fee = ₹175 total
- Delivery Timeline: Dispatch in 1-2 days, delivery in 2-7 days depending on location
Returns & Warranty
- 7-Day Return: Manufacturing defects only (approval required)
- Warranty: 7 days from delivery
- Non-Returnable: Batteries, consumables, cut wires, clearance items