{"product_id":"kit-esp32-s3-anomaly-detection-kit","title":"ESP32-S3 Anomaly Detection Kit","description":"\u003ch1\u003eESP32-S3 Anomaly Detection Kit – Build an Edge AI Machine Health Alert System\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 5-6 hours\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 16-21\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e Edge AI anomaly detection\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eImagine a motor on a factory floor, a pump in a lab, or a drone motor – you can build a device that learns its normal vibration signature and screams with a buzzer when something changes. This ESP32-S3 anomaly detection kit enables you to deploy a trained Edge Impulse model on real hardware, turning a tiny IMU into a predictive maintenance tool. Perfect for Smart India Hackathon projects, B.Tech final years, or CBSE AI curriculum, you'll create an intelligent monitor that could save machines and money.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou’ll assemble a standalone device that continuously reads 3-axis vibration from an MPU6050, processes the data on the ESP32-S3, and triggers a piezo buzzer plus red\/green LEDs if the pattern deviates from normal. The kit teaches how to train a model in Edge Impulse, deploy it, and integrate sensor feedback – all without cloud dependency, keeping inference local and fast.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eTrain an anomaly detection model in Edge Impulse using vibration data\u003c\/li\u003e\n  \u003cli\u003eDeploy a TensorFlow Lite model to ESP32-S3 for real-time inference\u003c\/li\u003e\n  \u003cli\u003eInterface MPU6050 over I2C to capture accelerometer and gyroscope signals\u003c\/li\u003e\n  \u003cli\u003eBuild a physical alert system with buzzer and LEDs that reacts to ML 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\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\u003ePiezo Buzzer\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eLED Red\u003c\/td\u003e\n\u003ctd\u003e2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eLED Green\u003c\/td\u003e\n\u003ctd\u003e2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e220Ω Resistors\u003c\/td\u003e\n\u003ctd\u003e5\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\u003eThis kit is designed for intermediate learners who already have some experience with Arduino or ESP32. It's ideal for B.Tech ECE\/EEE students building AIoT projects, CBSE Class 11–12 students exploring the AI syllabus, and teams competing in Smart India Hackathon. ATL Tinkering Labs and IIT\/NIT\/VIT\/BITS Pilani makers will find the edge AI focus especially relevant for industry-readiness.\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 (accessed via QR) walks you through every connection and code block; if you still hit a snag, WhatsApp support from the Compoden team responds within hours.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eHow do I train the anomaly detection model?\u003c\/summary\u003e\u003cp\u003eYou'll capture normal vibration data from your machine, label it in Edge Impulse, and let the platform generate an autoencoder model. No deep ML expertise needed – the companion video shows every step.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I use this for a specific machine like a water pump or drone?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The model learns the normal pattern of whatever you monitor. Mount the MPU6050 on the machine housing, capture baseline data, and retrain the model to catch deviations.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eWhat if my model doesn't detect anomalies accurately?\u003c\/summary\u003e\u003cp\u003eThe companion provides tuning tips – you can adjust the threshold and collect more diverse training data. You can also connect over WhatsApp for model debugging advice.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eEdge Impulse anomaly detection model on ESP32-S3 monitors vibration from MPU6050 — alerts when machine pattern changes.\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\/mpu6050-3-axis-gyroaccel-sensor-module-compoden\"\u003eMPU6050 IMU\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/piezoelectric-buzzer-26mm-sensor-transducer-compoden\"\u003ePiezo Buzzer\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/heltec-lora-esp32-oled-development-board-with-wifi-ble\"\u003eLED Red\u003c\/a\u003e x2\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/heltec-lora-esp32-oled-development-board-with-wifi-ble\"\u003eLED Green\u003c\/a\u003e x2\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\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-S3 Anomaly Detection Kit?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The ESP32-S3 Anomaly Detection Kit includes all components needed: ESP32-S3 Dev Board, MPU6050 IMU, Piezo Buzzer, LED Red, LED Green 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 Anomaly Detection Kit?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Intermediate level makers, suitable for ages 16-21. Edge Impulse anomaly detection model on ESP32-S3 monitors vibration from MPU6050 — alerts when machine pattern changes. Estimated build time is 5-6 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the ESP32-S3 Anomaly Detection Kit online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the ESP32-S3 Anomaly Detection Kit is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. 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