{"product_id":"kit-esp32-s3-edge-impulse-motion-classifier","title":"ESP32-S3 Edge Impulse Motion Classifier Kit with ESP32 + MPU6050","description":"\u003ch1\u003eBuild a Real-Time Motion Classifier on ESP32-S3 with Edge Impulse and MPU6050\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 Intermediate\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eBuild Time:\u003c\/strong\u003e 4-5 hours\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 15-18\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e Embedded Machine Learning\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eWith this kit, you'll train a machine learning model on your PC using Edge Impulse, deploy it to the ESP32-S3, and strap the MPU6050 to your ankle to see real-time activity classification on the OLED. It's a complete end-to-end embedded ML project that mirrors industrial human activity recognition systems, scaled for learning.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou'll wire the MPU6050 accelerometer to the ESP32-S3, collect motion data for three activities, train a neural network in Edge Impulse, and deploy the TFLite model to classify walking, running, and idle states. The OLED displays predicted activity and confidence scores instantly, turning raw sensor data into actionable insight.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eCollecting and labeling accelerometer data for machine learning\u003c\/li\u003e\n  \u003cli\u003eDesigning and training a neural network using Edge Impulse's web interface\u003c\/li\u003e\n  \u003cli\u003eDeploying a TensorFlow Lite model on the ESP32-S3 for real-time inference\u003c\/li\u003e\n  \u003cli\u003eDisplaying sensor outputs and ML predictions on an OLED screen\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-S3 Dev Board\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eMPU6050\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e0.96in OLED\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e4.7kΩ Resistors\u003c\/td\u003e\n\u003ctd\u003ex5\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e100nF Caps\u003c\/td\u003e\n\u003ctd\u003ex5\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e400-pt Breadboard\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eM-M Wires\u003c\/td\u003e\n\u003ctd\u003ex20\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eMicro USB Cable\u003c\/td\u003e\n\u003ctd\u003ex1\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\u003eThis kit is ideal for CBSE Class 11-12 students exploring AI and IoT for their practical exams, B.Tech ECE\/EEE undergraduates building mini-projects, and teams preparing for Smart India Hackathon or ATL Tinkering Lab innovation challenges. If you've tinkered with Arduino and want to step into embedded machine learning, this kit provides the perfect guided pathway.\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\u003eOur AI companion provides live troubleshooting for every step. You can also send a photo via WhatsApp and our team in Bengaluru will help within 24 hours.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDo I need prior machine learning experience?\u003c\/summary\u003e\u003cp\u003eNo. Edge Impulse handles the heavy lifting; you'll label data and click 'Train'. The kit includes example datasets and a pre-trained model to get immediate results.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I extend this project to classify more than three activities?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The pipeline is fully adaptable. Once you understand data collection and training, you can add gestures like jumping or sitting — the ESP32-S3 has plenty of processing headroom.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes the classifier work offline after setup?\u003c\/summary\u003e\u003cp\u003eYes. The TFLite model runs locally on the ESP32-S3; no internet connection is needed for inference. Edge Impulse is only required during the training phase on your computer.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eMPU6050 feeds Edge Impulse TFLite model on ESP32-S3 classifying walking, running and idle states.\u003c\/p\u003e\n  \u003ch4\u003eWhat's in this kit\u003c\/h4\u003e\n  \u003cul\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/arduino-uno-r4-wifi-board-with-esp32-s3-module-ra4m1-cortex-m4\"\u003eESP32-S3 Dev Board\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/mpu6050-imu-module-6-axis-gyro-accelerometer-for-arduino\"\u003eMPU6050\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\n\u003ca href=\"\/products\/resistor-variety-pack-100-pcs-10-values-14w-carbon-film\"\u003e4.7kΩ Resistors\u003c\/a\u003e x5\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/capacitor-variety-pack-6-values-100nf-to-470uf-30-pieces\"\u003e100nF Caps\u003c\/a\u003e x5\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/breadboard-standard-bundle-830400-tie-points-for-prototyping\"\u003e400-pt Breadboard\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003eM-M Wires x20\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/microusb-cable-1m-charging-data-cord-for-arduino-android\"\u003eMicro USB Cable\u003c\/a\u003e\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-S3 Edge Impulse Motion Classifier Kit with ESP32 + MPU6050?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The ESP32-S3 Edge Impulse Motion Classifier Kit with ESP32 + MPU6050 includes all components needed: ESP32-S3 Dev Board, MPU6050, 0.96in OLED, 4.7kΩ Resistors, 100nF Caps 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-S3 Edge Impulse Motion Classifier Kit with ESP32 + MPU6050?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Intermediate level makers, suitable for ages 15-18. MPU6050 feeds Edge Impulse TFLite model on ESP32-S3 classifying walking, running and idle states. Estimated build time is 4-5 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the ESP32-S3 Edge Impulse Motion Classifier Kit with ESP32 + MPU6050 online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the ESP32-S3 Edge Impulse Motion Classifier Kit with ESP32 + MPU6050 is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. Ships from Bengaluru in 1-5 business days across India.\"\n      }\n    }\n  ]\n}\n\u003c\/script\u003e\n\n\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"Product\",\n  \"name\": \"ESP32-S3 Edge Impulse Motion Classifier Kit with ESP32 + MPU6050\",\n  \"description\": \"MPU6050 feeds Edge Impulse TFLite model on ESP32-S3 classifying walking, running and idle states.\",\n  \"sku\": \"CDN-KIT-1327\",\n  \"brand\": {\"@type\": \"Brand\", \"name\": \"Compoden\"},\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"https:\/\/compoden.in\/products\/kit-esp32-s3-edge-impulse-motion-classifier\",\n    \"priceCurrency\": \"INR\",\n    \"price\": \"2400\",\n    \"availability\": \"https:\/\/schema.org\/InStock\",\n    \"seller\": {\"@type\": \"Organization\", \"name\": \"Compoden\"}\n  },\n  \"category\": \"ESP32 Fundamentals\"\n}\n\u003c\/script\u003e","brand":"Compoden","offers":[{"title":"Default Title","offer_id":53456640049517,"sku":"CDN-KIT-1327","price":2770.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0999\/3997\/5533\/files\/kit-esp32-s3-edge-impulse-motion-classifier.png?v=1781946584","url":"https:\/\/compoden.com\/products\/kit-esp32-s3-edge-impulse-motion-classifier","provider":"Compoden","version":"1.0","type":"link"}