{"product_id":"kit-esp32-tflite-gesture-sensor-hub","title":"ESP32 TFLite Gesture Sensor Hub","description":"\u003ch1\u003eBuild a Gesture-Controlled AI IoT Hub with ESP32 TFLite Kit\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 \u0026amp; MQTT Communication\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eWave your hand to dim lights, flick right to skip a song — this kit turns an ESP32 into an intelligent gesture sensor that classifies movements in real-time using TensorFlow Lite Micro and sends commands over Wi-Fi via MQTT. It's a complete foundation for touchless interfaces, assistive tech prototypes, and smart home experiments that react to motion naturally without cloud dependency.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou'll assemble a compact hub that reads accelerometer data from the MPU6050, runs a pre-trained TFLite model to recognize gestures like wave, circle, swipe, and tilt, displays the detected label on the OLED, and publishes it to an MQTT broker — ready to trigger any connected device. The final device fits on your palm and can be powered by a USB power bank for wearable or standalone use.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eDeploy a TensorFlow Lite Micro model on an ESP32 microcontroller\u003c\/li\u003e\n  \u003cli\u003eInterface an MPU6050 accelerometer\/gyroscope for real-time motion data capture\u003c\/li\u003e\n  \u003cli\u003eStream sensor data over Wi-Fi using the MQTT protocol\u003c\/li\u003e\n  \u003cli\u003eInterpret model output and display results on a 0.96-inch OLED\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\u003eMPU6050 IMU\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 building AI or IoT capstone projects will find a ready-to-run TinyML companion. B.Tech ECE\/EEE undergraduates prototyping for Smart India Hackathon or college competitions get a head start on gesture-controlled automation. ATL Tinkering Lab mentors and IIT\/NIT\/VIT\/BITS hobbyists exploring edge AI gain a hands-on introduction to embedded machine learning.\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 trained on this kit; it can diagnose wiring errors, suggest code fixes, and explain model output. If you still need help, reach our support team on WhatsApp for a quick reply.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I add more gestures to the model?\u003c\/summary\u003e\u003cp\u003eYes, the AI companion includes a guided workflow to collect your own accelerometer data, retrain the TFLite model using Google Colab, and deploy the updated firmware. No advanced ML experience required.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes this work with home automation platforms like Home Assistant?\u003c\/summary\u003e\u003cp\u003eAbsolutely. Once the MQTT messages are published, you can integrate them with Home Assistant or Node-RED using the provided sample configuration. Automate lights, fans, or curtains based on specific gestures.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eWhat power source can I use for portable operation?\u003c\/summary\u003e\u003cp\u003eThe ESP32 can run from a standard USB power bank via the included microUSB cable. For wearable projects, you can connect a 3.7V LiPo battery to the 5V and GND pins (battery not included). The AI companion shows the safe wiring.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eTFLite Micro gesture classifier on ESP32 reads MPU6050 accelerometer data and publishes gesture labels to MQTT broker.\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\u003e\u003ca href=\"\/products\/mpu6050-3-axis-gyroaccel-sensor-module-compoden\"\u003eMPU6050 IMU\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 ESP32 TFLite Gesture Sensor Hub?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The ESP32 TFLite Gesture Sensor Hub includes all components needed: ESP32 Dev Board, MPU6050 IMU, 0.96in OLED, MicroUSB Cable, M-M Wires 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 ESP32 TFLite Gesture Sensor Hub?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Beginner level makers, suitable for ages 15-18. TFLite Micro gesture classifier on ESP32 reads MPU6050 accelerometer data and publishes gesture labels to MQTT broker. Estimated build time is 3-4 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the ESP32 TFLite Gesture Sensor Hub online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the ESP32 TFLite Gesture Sensor Hub is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. 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