{"product_id":"kit-classroom-air-quality-monitor-kit","title":"Classroom Air Quality Monitor Kit","description":"\u003ch1\u003eESP32 Classroom Air Quality Monitor Kit – Predict AQI with AI and IoT\u003c\/h1\u003e\n\n\u003cp class=\"value-summary\"\u003eEvery part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.\u003c\/p\u003e\n\n\u003cdiv class=\"specs-strip\"\u003e\n  \u003cspan\u003e\u003cstrong\u003eDifficulty:\u003c\/strong\u003e Beginner\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eBuild Time:\u003c\/strong\u003e 3-4 hrs\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 15-18\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e Edge AI and IoT sensor integration\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eWalk 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.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou’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.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eHow to interface analog and digital sensors with ESP32 over I2C and GPIO\u003c\/li\u003e\n  \u003cli\u003eDeploying a TensorFlow Lite regression model on a microcontroller for on-device inference\u003c\/li\u003e\n  \u003cli\u003eStreaming real-time IoT data to Node-RED and building a live monitoring dashboard\u003c\/li\u003e\n  \u003cli\u003eUnderstanding the relationship between TVOC, humidity, temperature, and predicted AQI\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eKit Contents\u003c\/h2\u003e\n\u003ctable\u003e\n  \u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eComponent\u003c\/th\u003e\n\u003cth\u003eQuantity\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n  \u003ctbody\u003e\n    \u003ctr\u003e\n\u003ctd\u003eESP32 Dev Board\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eMQ135 Gas Sensor\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eDHT22\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e0.96in OLED\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eMicroUSB Cable\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eM-M Wires\u003c\/td\u003e\n\u003ctd\u003e15\u003c\/td\u003e\n\u003c\/tr\u003e\n  \u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eWhy Buy This Kit Instead of Sourcing Parts Separately\u003c\/h2\u003e\n\u003ctable\u003e\n  \u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eFactor\u003c\/th\u003e\n\u003cth\u003eSourcing Separately\u003c\/th\u003e\n\u003cth\u003eCompoden Kit\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n  \u003ctbody\u003e\n    \u003ctr\u003e\n\u003ctd\u003eCompatibility checks\u003c\/td\u003e\n\u003ctd\u003eYou verify every part\u003c\/td\u003e\n\u003ctd\u003ePre-tested as a system\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eBuild support\u003c\/td\u003e\n\u003ctd\u003eForums and scattered tutorials\u003c\/td\u003e\n\u003ctd\u003eAI companion trained on this exact project\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eTime to first working build\u003c\/td\u003e\n\u003ctd\u003eDays of debugging\u003c\/td\u003e\n\u003ctd\u003eHours, with step-by-step guidance\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eShipping coordination\u003c\/td\u003e\n\u003ctd\u003eMultiple sellers, multiple delays\u003c\/td\u003e\n\u003ctd\u003eOne shipment from Bengaluru in 3-5 days\u003c\/td\u003e\n\u003c\/tr\u003e\n  \u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eWho This Kit Is For\u003c\/h2\u003e\n\u003cp\u003eCBSE 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.\u003c\/p\u003e\n\n\u003ch2\u003eBuilt and Backed by Compoden\u003c\/h2\u003e\n\u003cp\u003eEvery 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.\u003c\/p\u003e\n\n\u003cdetails\u003e\u003csummary\u003eWhat if I get stuck during the build?\u003c\/summary\u003e\u003cp\u003eScan 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.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDo I need coding experience to build this?\u003c\/summary\u003e\u003cp\u003eThe 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.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I use this for a CBSE science exhibition or ATL project?\u003c\/summary\u003e\u003cp\u003eAbsolutely. 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.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes this kit measure actual AQI or just predict it?\u003c\/summary\u003e\u003cp\u003eThe 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.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eSchool Air — MQ135 and DHT22 data feeds a TFLite regression model on ESP32 predicting AQI — streams predictions to Node-RED.\u003c\/p\u003e\n  \u003ch4\u003eWhat's in this kit\u003c\/h4\u003e\n  \u003cul\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/esp32-30-pin-development-board-cp2102-wifi-bluetooth\"\u003eESP32 Dev Board\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003eMQ135 Gas Sensor\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/dht22-temperature-humidity-sensor-module-accurate-readings\"\u003eDHT22\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/096in-oled-display-128x64-i2cspi-for-arduino-raspberry-pi\"\u003e0.96in OLED\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/microusb-cable-1m-charging-data-cord-for-arduino-android\"\u003eMicroUSB Cable\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003eM-M Wires x15\u003c\/li\u003e\n  \u003c\/ul\u003e\n\u003c\/div\u003e\n\n\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What is included in the Classroom Air Quality Monitor Kit?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Classroom Air Quality Monitor Kit includes all components needed: ESP32 Dev Board, MQ135 Gas Sensor, DHT22, 0.96in OLED, MicroUSB Cable and more. Everything is pre-tested for compatibility and shipped from Bengaluru, India.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What skill level is required for the Classroom Air Quality Monitor Kit?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Beginner level makers, suitable for ages 15-18. School Air — MQ135 and DHT22 data feeds a TFLite regression model on ESP32 predicting AQI — streams predictions to Node-RED. Estimated build time is 3-4 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Classroom Air Quality Monitor Kit online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Classroom Air Quality Monitor Kit is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. 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