{"product_id":"kit-sport-form-coach-kit-v3","title":"Sport Form Coach Kit v3","description":"\u003ch1\u003eSport Form Coach Kit v3: Your Wearable AI Coach for Perfect Sports Gestures\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 Embedded Machine Learning\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eIn sports like cricket, tennis, or badminton, a single flawed movement can be the difference between a win and a loss. Coaches spend years spotting those micro-errors by eye. This kit lets you bring that same scrutiny to your own practice—using a tiny, wrist-worn device that watches your every motion and tells you exactly which gesture you just performed.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou'll assemble a wearable module powered by an ESP32 and an MPU6050 accelerometer. An on-device TensorFlow Lite Micro model classifies the accelerometer patterns into specific gestures (like a cover drive, a smash, or a topspin shot) and publishes the label over MQTT. A small OLED screen displays live IMU data and the current classified gesture. The device is fully self-contained—no phone or laptop needed during practice—and the MQTT broker lets you log hundreds of reps for later analysis.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eCapture and stream 6-axis motion data from an MPU6050 IMU\u003c\/li\u003e\n  \u003cli\u003eTrain a TensorFlow Lite Micro model for gesture classification\u003c\/li\u003e\n  \u003cli\u003eDeploy the model on an ESP32 microcontroller for real-time inference\u003c\/li\u003e\n  \u003cli\u003ePublish classified gesture labels to an MQTT broker for logging and review\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\u003eIdeal for students preparing for CBSE Class 11-12 CS projects, B.Tech ECE or CSE early-year labs, and participants of Tinkering Labs and Smart India Hackathon. Sports enthusiasts who want to add data-driven feedback to their training will find an immediate hands-on project here. No prior machine learning experience is needed—the build starts from first principles.\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 talk to the AI companion trained on this kit; it can debug wiring, code, and model errors. For tricky situations, our WhatsApp support team typically responds within a few hours.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDo I need any prior machine learning knowledge?\u003c\/summary\u003e\u003cp\u003eNo. The guided build includes a ready-to-modify TFLite Micro model and explains every step from data capture to deployment on the ESP32.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I train the device for my own sports gestures?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The included Python script lets you record your own motion datasets, retrain the model, and flash it onto the ESP32. Common customisations are for cricket shots, tennis serves, and badminton smashes.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eHow do I see the gesture labels after a training session?\u003c\/summary\u003e\u003cp\u003eLabels are published to an MQTT broker that you can monitor from any device on the same Wi‑Fi network. A simple subscriber script (provided) logs all gestures with timestamps for review.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eSports — TFLite 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 Sport Form Coach Kit v3?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Sport Form Coach Kit v3 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 Sport Form Coach Kit v3?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Beginner level makers, suitable for ages 15-18. Sports — 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 Sport Form Coach Kit v3 online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Sport Form Coach Kit v3 is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. 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