{"product_id":"kit-ai-assisted-presence-and-behaviour-detector","title":"AI-Assisted Presence and Behaviour Detector Kit with ESP32","description":"\u003ch1\u003eBuild a Room Occupancy Classifier with On-Device AI – ESP32 TensorFlow Lite Kit\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 12-15 hours\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 25+\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e On-device machine learning deployment with TensorFlow Lite\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eTransform a simple ESP32-CAM into a silent, always‑on AI brain that knows exactly how a room is being used—without ever sending data to the cloud. By combining camera snapshots, passive infrared motion, and door usage patterns, you’ll train a compact TensorFlow Lite model that classifies occupancy in real time: vacant, single occupant, multiple occupants, or transition. Perfect for energy‑saving home automation, elder‑care monitoring, or a privacy‑respecting smart security layer.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou’ll assemble and program a wall‑mountable sensor module that fuses three sensor streams into a single occupancy inference. Every few seconds the ESP32‑CAM captures a low‑resolution image, reads two PIR sensors for motion direction, and monitors reed switches on doors. The on‑device TensorFlow Lite model processes the combined feature vector and outputs a high‑confidence occupancy state. That state can trigger lights, HVAC, or alerts through MQTT—fully local, no internet required.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eFusing multi‑sensor data (PIR, magnetic reed switch, ESP32‑CAM) into a unified feature vector for an AI model\u003c\/li\u003e\n  \u003cli\u003eCapturing and preprocessing images from the ESP32‑CAM for on‑device inference at multiple frames per second\u003c\/li\u003e\n  \u003cli\u003eTraining a compact TensorFlow Lite model for 4‑class occupancy classification and converting it to run within the ESP32’s memory limits\u003c\/li\u003e\n  \u003cli\u003eDeploying the model to the ESP32 and accelerating inference using hardware‑specific operators and careful buffer management\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-CAM\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eHC-SR501 PIR\u003c\/td\u003e\n\u003ctd\u003e2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eReed Switch\u003c\/td\u003e\n\u003ctd\u003e3\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eActive Buzzer\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\u003eLM1117 3.3V Reg\u003c\/td\u003e\n\u003ctd\u003e2\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\u003e10kΩ Resistors\u003c\/td\u003e\n\u003ctd\u003e5\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\u003eEnclosure Box\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e5V 2A Power Supply\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\u003eEngineers and data scientists exploring TinyML for real‑world environments, B.Tech ECE\/CS final‑year students prototyping AI‑powered assistive tech for Smart India Hackathon, and experienced hobbyists ready to move beyond Arduino into embedded machine learning. If you’ve wanted to run a neural network on a microcontroller without a cloud dependency, this kit gives you a polished, end‑to‑end project that plugs straight into Home Assistant or any MQTT‑based automation.\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 inside the box to chat with the AI companion, which knows every wiring connection and code snippet for this kit. If you need a human, WhatsApp our support team—we typically respond within a few hours.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I modify the model to detect other states like sleeping or cooking?\u003c\/summary\u003e\u003cp\u003eYes. The companion walks you through collecting new labeled data in your room and retraining the TensorFlow Lite model, so you can define any custom occupancy categories you need.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eWill this work with Home Assistant or Node‑RED?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The ESP32 publishes the occupancy state via MQTT, which natively integrates with Home Assistant, Node‑RED, and other platforms for fully local automation.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eHow accurate is the occupancy detection in a real home?\u003c\/summary\u003e\u003cp\u003eAfter you calibrate the sensors to your room layout, the model typically exceeds 92% accuracy in distinguishing vacant, single‑person, and crowd conditions. It runs entirely on the ESP32, so there’s no internet latency or privacy concern.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eESP32-CAM + PIR + door sensors feed an on-device TensorFlow Lite model that classifies room occupancy state.\u003c\/p\u003e\n  \u003ch4\u003eWhat's in this kit\u003c\/h4\u003e\n  \u003cul\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/esp32-cam-mb-programmer-module-with-micro-usb-ch340g-plug-play\"\u003eESP32-CAM\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/hc-sr501-pir-motion-sensor-ir-module-combo-for-arduino\"\u003eHC-SR501 PIR\u003c\/a\u003e x2\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/reed-switch-sensor-normally-open-magnetic-switch-for-arduino\"\u003eReed Switch\u003c\/a\u003e x3\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/active-buzzer-dc-3-5v-85db-sounder-module-for-arduino-raspberry-pi\"\u003eActive Buzzer\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\u003eLM1117 3.3V Reg x2\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\/resistor-variety-pack-100-pcs-10-values-14w-carbon-film\"\u003e10kΩ Resistors\u003c\/a\u003e x5\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\/enclosure-box-for-diy-electronics-projects-compoden\"\u003eEnclosure Box\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/4-channel-relay-board-for-esp32-30-pin-5v-control\"\u003e5V 2A Power Supply\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 AI-Assisted Presence and Behaviour Detector Kit with ESP32?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The AI-Assisted Presence and Behaviour Detector Kit with ESP32 includes all components needed: ESP32-CAM, HC-SR501 PIR, Reed Switch, Active Buzzer, LM2596 Buck Converter 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 AI-Assisted Presence and Behaviour Detector Kit with ESP32?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Expert level makers, suitable for ages 25+. ESP32-CAM + PIR + door sensors feed an on-device TensorFlow Lite model that classifies room occupancy state. Estimated build time is 12-15 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the AI-Assisted Presence and Behaviour Detector Kit with ESP32 online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the AI-Assisted Presence and Behaviour Detector Kit with ESP32 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\": \"AI-Assisted Presence and Behaviour Detector Kit with ESP32\",\n  \"description\": \"ESP32-CAM + PIR + door sensors feed an on-device TensorFlow Lite model that classifies room occupancy state.\",\n  \"sku\": \"CDN-KIT-0234\",\n  \"brand\": {\"@type\": \"Brand\", \"name\": \"Compoden\"},\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"https:\/\/compoden.in\/products\/kit-ai-assisted-presence-and-behaviour-detector\",\n    \"priceCurrency\": \"INR\",\n    \"price\": \"4580\",\n    \"availability\": \"https:\/\/schema.org\/InStock\",\n    \"seller\": {\"@type\": \"Organization\", \"name\": \"Compoden\"}\n  },\n  \"category\": \"Home Automation\"\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":53459774996845,"sku":"CDN-KIT-0234-SLD","price":3840.0,"currency_code":"INR","in_stock":true},{"title":"Breadboard Combo","offer_id":53459775029613,"sku":"CDN-KIT-0234-BB","price":3240.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0999\/3997\/5533\/files\/kit-ai-assisted-presence-and-behaviour-detector.png?v=1781944323","url":"https:\/\/compoden.com\/products\/kit-ai-assisted-presence-and-behaviour-detector","provider":"Compoden","version":"1.0","type":"link"}