{"product_id":"kit-classroom-engagement-camera-kit-v29","title":"Classroom Engagement Camera Kit v29","description":"\u003ch1\u003eClassroom Engagement Camera Kit v29 — Build a Distracted Driving Detector with Raspberry Pi 5\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 hrs\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 16-21\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e Computer Vision \u0026amp; AI for Driver Monitoring\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eThis kit lets you build a distracted driving detection system that uses MediaPipe Face Mesh to track driver gaze direction and detect phone usage — all on a Raspberry Pi 5 camera setup. Originally designed for education analytics, it also doubles as a classroom attention monitor, giving you a flexible project that fits hackathons, final‑year submissions, or hands‑on AI exploration.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eA compact edge AI camera that monitors a driver's face in real time and alerts through a piezo buzzer whenever it spots prolonged gaze away from the road or phone handling. Reposition the camera and the same codebase tracks student engagement — logging who looks at the board and who’s scrolling on a phone. You’ll walk away with a fully functional prototype, solid Python scripts, and a demonstrable understanding of computer vision on embedded hardware.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eConfigure a Raspberry Pi 5 with a Pi Camera Module 3 and boot from a fast NVMe SSD via the M.2 HAT+\u003c\/li\u003e\n  \u003cli\u003eImplement MediaPipe Face Mesh to extract 468 facial landmarks and estimate head‑pose in real time\u003c\/li\u003e\n  \u003cli\u003eWrite Python logic that classifies distracted driving events (gaze‑off‑road, phone‑in‑hand) from live video\u003c\/li\u003e\n  \u003cli\u003eInterface a piezo buzzer for instant audio alerts and record incident timestamps to an SSD‑backed database\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\u003eRaspberry Pi 5 4GB\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePi Camera Module 3\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePiezo Buzzer\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eNVMe SSD 128GB\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePi 5 M.2 HAT+\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eUSB-C PSU\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\u003ex10\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\u003eCBSE Class 11‑12 students and B.Tech ECE\/EEE candidates building AI projects for board practicals or placements. Smart India Hackathon teams tackling automotive safety, ATL Tinkering Labs introducing edge AI, and IIT\/NIT\/VIT\/BITS researchers needing a ready‑to‑deploy gaze‑tracking testbed. The flexible use‑case also makes it a strong pick for educators demonstrating computer vision in the classroom.\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 an AI companion that knows every step of this exact kit, or message us on WhatsApp for direct support from our engineers.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I use this kit for a classroom attention monitor instead of a distracted driving detector?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The same hardware and MediaPipe‑based gaze logic work perfectly for education analytics — just place the camera facing the class and adjust the detection thresholds in the provided Python scripts.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDo I need to solder anything?\u003c\/summary\u003e\u003cp\u003eNo soldering at all. The kit uses pre‑assembled modules and M‑M jumper wires that plug straight into the Raspberry Pi 5 GPIO header.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eIs the NVMe SSD pre‑loaded with software?\u003c\/summary\u003e\u003cp\u003eYes, the 128GB SSD arrives with Raspberry Pi OS, MediaPipe, OpenCV, and working example scripts for both distracted driving and classroom engagement detection.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eEducation Analytics — Mediapipe Face Mesh monitors gaze direction and phone use on Pi 5 camera — distracted driving detection system.\u003c\/p\u003e\n  \u003ch4\u003eWhat's in this kit\u003c\/h4\u003e\n  \u003cul\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/raspberry-pi-5-model-b-4gb-technical-specs-projects\"\u003eRaspberry Pi 5 4GB\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/4-channel-relay-board-for-esp32-30-pin-5v-control\"\u003ePi Camera Module 3\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\u003ca href=\"\/products\/official-raspberry-pi-m2-hat-nvme-ssd-add-on-board-for-pi-5\"\u003eNVMe SSD 128GB\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/raspberry-pi-5-pcie-to-m2-nvme-ssd-expansion-board-by-elecrow\"\u003ePi 5 M.2 HAT+\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/raspberry-pi-4-official-power-supply-5v-3a-usb-c-compoden\"\u003eUSB-C PSU\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003eM-M Wires x10\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 Classroom Engagement Camera Kit v29?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Classroom Engagement Camera Kit v29 includes all components needed: Raspberry Pi 5 4GB, Pi Camera Module 3, Piezo Buzzer, NVMe SSD 128GB, Pi 5 M.2 HAT+ 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 Classroom Engagement Camera Kit v29?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Intermediate level makers, suitable for ages 16-21. Education Analytics — Mediapipe Face Mesh monitors gaze direction and phone use on Pi 5 camera — distracted driving detection system. Estimated build time is 5-6 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Classroom Engagement Camera Kit v29 online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Classroom Engagement Camera Kit v29 is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. 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