{"product_id":"kit-classroom-engagement-camera-kit-v26","title":"Classroom Engagement Camera Kit v26","description":"\u003ch1\u003eClassroom Engagement Camera Kit v26 — YOLOv8 Empty Shelf Detector for Retail Analytics Education\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 Edge AI deployment with YOLOv8\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eTransform a Raspberry Pi 5 into a practical retail AI camera that watches store shelves, detects empty spots using YOLOv8, and logs restocking alerts. Designed for students and educators who want to move beyond toy datasets and build a project that mirrors real-world inventory monitoring systems. Everything runs locally on the Pi with NVMe SSD acceleration — no cloud dependency.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou'll assemble a self-contained vision sensor that streams live shelf images, runs YOLOv8n inference at the edge, and flags positions where product facing is missing. The system writes timestamped alerts to a log file and can trigger a local dashboard. It's the same pipeline retail chains deploy to minimise out-of-stock losses, condensed into a portable classroom-friendly format.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eTrain a custom YOLOv8 object detector on empty-shelf vs. stocked-shelf imagery\u003c\/li\u003e\n  \u003cli\u003eDeploy ONNX-optimised models on Raspberry Pi 5 with Pi Camera Module 3 Wide\u003c\/li\u003e\n  \u003cli\u003eAccelerate model inference and logging with an NVMe SSD over the M.2 HAT+\u003c\/li\u003e\n  \u003cli\u003eStructure an end-to-end edge AI application from capture to actionable alert\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\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePi Camera Module 3 Wide\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eNVMe SSD 128GB\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePi 5 M.2 HAT+\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eUSB-C PSU\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\u003eCBSE Class 11-12 students exploring AI electives, B.Tech ECE\/EEE undergraduates working on Smart India Hackathon retail or smart city themes, and ATL Tinkering Lab mentors who need a compact yet powerful edge vision module. It also fits capstone projects at IIT, NIT, VIT or BITS where the brief demands working prototypes with measurable business impact.\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 launch the AI companion; it knows the exact wiring, YOLOv8 configuration, and common mistakes. WhatsApp support is also available if you need a human debugging partner.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes this kit include pre-trained YOLOv8 models?\u003c\/summary\u003e\u003cp\u003eThe AI companion guides you through training a custom model using included sample shelf images, or you can bring your own dataset. A lightweight ONNX model runs on the Pi for real-time inference.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I use a different camera or SD card instead of the NVMe SSD?\u003c\/summary\u003e\u003cp\u003eAn SD card will throttle performance during inference logging. The kit’s Pi Camera Module 3 Wide and NVMe SSD are selected to deliver consistent 5-8 FPS without thermal throttling.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eWill this project work for a retail-related hackathon like SIH?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The edge inference pipeline, alert logging, and Pi-based standalone design directly map to problem statements on smart inventory management, unattended retail, and supply-chain visibility.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eEducation Analytics — YOLOv8 detects empty shelf positions from camera and logs restocking alerts — practical retail AI application.\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 Wide\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  \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 v26?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Classroom Engagement Camera Kit v26 includes all components needed: Raspberry Pi 5 4GB, Pi Camera Module 3 Wide, NVMe SSD 128GB, Pi 5 M.2 HAT+, USB-C PSU 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 v26?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Intermediate level makers, suitable for ages 16-21. Education Analytics — YOLOv8 detects empty shelf positions from camera and logs restocking alerts — practical retail AI application. Estimated build time is 5-6 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Classroom Engagement Camera Kit v26 online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Classroom Engagement Camera Kit v26 is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. 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