{"product_id":"kit-tinyml-vibration-fault-classifier","title":"TinyML Vibration Fault Classifier Kit with ESP32 + MPU6050","description":"\u003ch1\u003eTinyML Vibration Fault Classifier Kit: Build an AI-Powered Predictive Maintenance System with ESP32-S3 \u0026amp; 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 Beginner\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eBuild Time:\u003c\/strong\u003e 3-4 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 TinyML model deployment \u0026amp; real-time fault detection\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eEver wondered how factories predict machine breakdowns before they happen? With this kit, you’ll train a tiny machine learning model on an ESP32-S3 that reads vibration data from the MPU6050 accelerometer, classifies patterns as normal or faulty, and lights a green or red LED accordingly — just like a real industrial predictive maintenance system.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou’ll assemble a compact module with the ESP32-S3, MPU6050, and OLED display that continuously monitors vibration. It shows real-time classification on the OLED: ‘Normal Operation’ or ‘Fault Detected’. The LEDs provide instant visual feedback — a green LED blinks when the motor is healthy, and a red LED pulses on a fault.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eHow to collect and label accelerometer data for machine learning\u003c\/li\u003e\n  \u003cli\u003eUploading a pre-trained Edge Impulse model to an ESP32-S3 microcontroller\u003c\/li\u003e\n  \u003cli\u003eReading real-time sensor data from MPU6050 and running on-device inference\u003c\/li\u003e\n  \u003cli\u003eIntegrating an OLED display to show classification results and status LEDs for output\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 SSD1306\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e5mm Red LED\u003c\/td\u003e\n\u003ctd\u003ex2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e5mm Green LED\u003c\/td\u003e\n\u003ctd\u003ex2\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\u003e220Ω 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\u003eIdeal for CBSE Class 11–12 students exploring AI and IoT, B.Tech ECE\/EEE first-years working on mini-projects, and ATL Tinkering Lab participants who want a hands-on introduction to TinyML and predictive maintenance. Also perfect for Smart India Hackathon teams building industrial monitoring prototypes.\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 on the box to chat with the AI companion trained on this exact project, or reach our team via WhatsApp for personalized troubleshooting.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDo I need to write any code, or is the model pre-loaded?\u003c\/summary\u003e\u003cp\u003eThe kit includes a fully pre-trained Edge Impulse model; you just flash it to the ESP32-S3 using Arduino IDE. All necessary code and libraries are provided step-by-step.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I use this kit to detect faults in my own motors or fans?\u003c\/summary\u003e\u003cp\u003eAbsolutely — the MPU6050 can be mounted on any small motor or fan casing. You can even record your own vibration data and retrain the model on Edge Impulse to customize the fault detection.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eWhat will I see on the OLED display if the motor is faulty?\u003c\/summary\u003e\u003cp\u003eThe OLED will show ‘Fault Detected’ along with the classification probability, and the red LED will light up, instantly alerting you to a potential motor issue.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eMPU6050 feeds a pre-trained Edge Impulse model on ESP32-S3 that classifies normal vs faulty motor vibration.\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 SSD1306\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/led-variety-pack-50-pcs-3mm-5mm-mixed-colours\"\u003e5mm Red LED\u003c\/a\u003e x2\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/inductive-proximity-sensor-5mm-npn-no-ceyone-compoden\"\u003e5mm Green LED\u003c\/a\u003e x2\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\/resistor-variety-pack-100-pcs-10-values-14w-carbon-film\"\u003e220Ω 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 TinyML Vibration Fault Classifier Kit with ESP32 + MPU6050?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The TinyML Vibration Fault Classifier Kit with ESP32 + MPU6050 includes all components needed: ESP32-S3 Dev Board, MPU6050, 0.96in OLED SSD1306, 5mm Red LED, 5mm Green LED 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 TinyML Vibration Fault Classifier Kit with ESP32 + MPU6050?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Beginner level makers, suitable for ages 15-18. MPU6050 feeds a pre-trained Edge Impulse model on ESP32-S3 that classifies normal vs faulty motor vibration. Estimated build time is 3-4 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the TinyML Vibration Fault Classifier Kit with ESP32 + MPU6050 online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the TinyML Vibration Fault 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\": \"TinyML Vibration Fault Classifier Kit with ESP32 + MPU6050\",\n  \"description\": \"MPU6050 feeds a pre-trained Edge Impulse model on ESP32-S3 that classifies normal vs faulty motor vibration.\",\n  \"sku\": \"CDN-KIT-1004\",\n  \"brand\": {\"@type\": \"Brand\", \"name\": \"Compoden\"},\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"https:\/\/compoden.in\/products\/kit-tinyml-vibration-fault-classifier\",\n    \"priceCurrency\": \"INR\",\n    \"price\": \"2630\",\n    \"availability\": \"https:\/\/schema.org\/InStock\",\n    \"seller\": {\"@type\": \"Organization\", \"name\": \"Compoden\"}\n  },\n  \"category\": \"AI \u0026 Advanced Boards\"\n}\n\u003c\/script\u003e","brand":"Compoden","offers":[{"title":"Default Title","offer_id":53456310632813,"sku":"CDN-KIT-1004","price":3040.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0999\/3997\/5533\/files\/kit-tinyml-vibration-fault-classifier.png?v=1781946366","url":"https:\/\/compoden.com\/products\/kit-tinyml-vibration-fault-classifier","provider":"Compoden","version":"1.0","type":"link"}