{"product_id":"kit-multi-sensor-fusion-fall-detection-wearable","title":"Multi-Sensor Fusion Fall Detection Wearable Kit with ESP32 + MPU6050","description":"\u003ch1\u003eESP32-S3 Multi-Sensor Fall Detection Wearable Kit – AI-Powered Safety on Your Wrist\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 Advanced\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eBuild Time:\u003c\/strong\u003e 6-8 hrs\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 21-24\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e Embedded Machine Learning \u0026amp; Sensor Fusion\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eWhat if a wearable could distinguish between bending down and a dangerous fall—and automatically call for help? This kit lets you build exactly that. Using the ESP32-S3’s neural network accelerator, a TensorFlow Lite model classifies motion data from the MPU6050 fused with SpO2 pulse signals from the MAX30102. When a fall is detected, the SIM800L GSM module sends an SMS with GPS coordinates, creating a vital safety net for elderly care, lone-worker monitoring, or remote patient observation.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eA wrist-worn device that continuously monitors motion and vitals. An AI model running on the ESP32-S3 distinguishes falls from everyday activities like sitting or walking. On detection, the firmware triggers an SMS alert with the wearer's real-time GPS location to a pre-programmed number—providing autonomy and peace of mind without requiring a smartphone or constant cloud connectivity.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eDeploy a TensorFlow Lite model on ESP32-S3 for real-time motion classification\u003c\/li\u003e\n  \u003cli\u003eFuse MPU6050 inertial data with MAX30102 SpO2 readings to improve fall recognition accuracy\u003c\/li\u003e\n  \u003cli\u003eIntegrate NEO-6M GPS and SIM800L GSM for location-aware emergency alerts\u003c\/li\u003e\n  \u003cli\u003eDesign wearable‑grade power management with LiPo battery, buck converter, and OLED status display\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\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eMAX30102\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eNEO-6M GPS\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eSIM800L GSM\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eLM2596 Buck Converter\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e3.7V LiPo 1000mAh\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eTP4056 Module\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\u003e1000µF 25V Caps\u003c\/td\u003e\n\u003ctd\u003e2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e100nF Caps\u003c\/td\u003e\n\u003ctd\u003e10\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePCB Prototype Board\u003c\/td\u003e\n\u003ctd\u003e2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eVelcro Wristband\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eSoldering Iron\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eSolder Wire\u003c\/td\u003e\n\u003ctd\u003e1\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\u003eB.Tech ECE\/EEE students developing IoT‑healthcare final‑year projects, Smart India Hackathon teams tackling wearable safety solutions, and embedded AI enthusiasts who want to run TensorFlow Lite Micro on a real, low‑power wearable. M.Tech researchers and NIT\/VIT project groups will find the sensor‑fusion dataset and pre‑trained model equally valuable as a starting point for further innovation.\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\u003eThe AI companion provides instant, step‑by‑step debugging specific to this circuit. You can also reach us on WhatsApp for a human review of your setup.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes the kit include the AI model?\u003c\/summary\u003e\u003cp\u003eYes, you receive a pre‑trained TensorFlow Lite fall‑detection model optimized for the ESP32‑S3, along with the training pipeline code so you can retrain with your own motion data.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I change the SOS message or fall sensitivity?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The Arduino‑compatible firmware is fully open and commented; you can edit the SMS template, add multiple emergency contacts, and fine‑tune the classification threshold to balance false positives and latency.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eWhat programming background is required?\u003c\/summary\u003e\u003cp\u003eFamiliarity with C\/C++ and the Arduino IDE or PlatformIO is recommended. The guide walks you through every upload and calibration step, and the AI companion answers code‑level questions specific to this board and sensor stack.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eMPU6050 + MAX30102 SpO2 + GPS fused by ESP32-S3 TFLite model. Classifies fall vs normal activity. GSM SOS.\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\/max30102-heart-rate-pulse-oximeter-sensor-module\"\u003eMAX30102\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/neo-6m-gps-module-with-built-in-antenna\"\u003eNEO-6M GPS\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/ttgo-t-call-esp32-sim800l-module-for-iot-gsm-projects\"\u003eSIM800L GSM\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/lm2596-buck-converter-step-down-voltage-regulator-module\"\u003eLM2596 Buck Converter\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/37v-30c-1000mah-lipo-battery-yy802542-for-drones\"\u003e3.7V LiPo 1000mAh\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/tp4056-1a-li-ion-charger-module-with-protection-micro-usb\"\u003eTP4056 Module\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\u003e1000µF 25V Caps x2\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 x10\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/esp-wroom-32-breakout-board-pcb-55x52mm\"\u003ePCB Prototype Board\u003c\/a\u003e x2\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/velcro-anti-static-wristband-esd-safe-compoden\"\u003eVelcro Wristband\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/soldering-kit-25w-with-solder-wire-flux-paste-compoden\"\u003eSoldering Iron\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/soldering-kit-25w-with-solder-wire-flux-paste-compoden\"\u003eSolder Wire\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 Multi-Sensor Fusion Fall Detection Wearable Kit with ESP32 + MPU6050?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Multi-Sensor Fusion Fall Detection Wearable Kit with ESP32 + MPU6050 includes all components needed: ESP32-S3 Dev Board, MPU6050, MAX30102, NEO-6M GPS, SIM800L GSM 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 Multi-Sensor Fusion Fall Detection Wearable Kit with ESP32 + MPU6050?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Advanced level makers, suitable for ages 21-24. MPU6050 + MAX30102 SpO2 + GPS fused by ESP32-S3 TFLite model. Classifies fall vs normal activity. GSM SOS. Estimated build time is 6-8 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Multi-Sensor Fusion Fall Detection Wearable Kit with ESP32 + MPU6050 online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Multi-Sensor Fusion Fall Detection Wearable 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\": \"Multi-Sensor Fusion Fall Detection Wearable Kit with ESP32 + MPU6050\",\n  \"description\": \"MPU6050 + MAX30102 SpO2 + GPS fused by ESP32-S3 TFLite model. Classifies fall vs normal activity. GSM SOS.\",\n  \"sku\": \"CDN-KIT-1028\",\n  \"brand\": {\"@type\": \"Brand\", \"name\": \"Compoden\"},\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"https:\/\/compoden.in\/products\/kit-multi-sensor-fusion-fall-detection-wearable\",\n    \"priceCurrency\": \"INR\",\n    \"price\": \"8230\",\n    \"availability\": \"https:\/\/schema.org\/InStock\",\n    \"seller\": {\"@type\": \"Organization\", \"name\": \"Compoden\"}\n  },\n  \"category\": \"AI \u0026 Advanced Boards\"\n}\n\u003c\/script\u003e\u003cp\u003e\u003cstrong\u003eChoose your assembly option:\u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eSoldering Kit\u003c\/strong\u003e — 25W soldering iron, 60\/40 solder wire, flux, and small perfboard for permanent assembly.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eBreadboard Combo\u003c\/strong\u003e — 800-point full-size breadboard with 65-piece jumper wire pack for solderless prototyping.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Compoden","offers":[{"title":"Soldering Kit","offer_id":53459823591789,"sku":"CDN-KIT-1028-SLD","price":8330.0,"currency_code":"INR","in_stock":true},{"title":"Breadboard Combo","offer_id":53459823624557,"sku":"CDN-KIT-1028-BB","price":7800.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0999\/3997\/5533\/files\/kit-multi-sensor-fusion-fall-detection-wearable.png?v=1781946379","url":"https:\/\/compoden.com\/products\/kit-multi-sensor-fusion-fall-detection-wearable","provider":"Compoden","version":"1.0","type":"link"}