{"product_id":"real-time-exercise-form-analyser-kit-with-raspberry-pi-5-ai-camera","title":"Real-Time Exercise Form Analyser Kit with Raspberry Pi 5 AI Camera","description":"\u003ch1\u003eReal-Time Exercise Form Analyser Kit with Raspberry Pi 5 AI Camera\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 hours\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 16-21\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e Real-time AI pose estimation\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eBring education analytics to the gym floor or physics lab with a stand-alone vision system that watches every squat, lunge, or yoga pose in real time. This kit lets students and makers assemble a camera that detects 33 body landmarks at 60 frames per second-without any cloud dependency-then overlay feedback on a crisp 7-inch display, making it ideal for CBSE AI practicals, Smart India Hackathon prototypes, or B.Tech ECE capstone projects.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou will create a compact, on-device pose analyser that uses the Pi Camera Module 3 to capture live video, the Hailo-8L NPU to accelerate MediaPipe BlazePose, and the Raspberry Pi 5 to render landmark overlays onto the included 7-inch HDMI screen. The system can measure squat depth, arm alignment in push-ups, or balance in tree pose-displaying visual cues the moment form deviates from the reference. Everything runs locally, so there is no latency and no privacy concern.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eIntegrating a Raspberry Pi 5 with the Hailo-8L AI HAT and Pi Camera Module 3\u003c\/li\u003e\n  \u003cli\u003eCompiling and running the MediaPipe BlazePose model on the Hailo runtime\u003c\/li\u003e\n  \u003cli\u003eDeveloping a Python application that captures frames, infers 33 body landmarks, and draws real-time overlays\u003c\/li\u003e\n  \u003cli\u003eCalibrating exercise form metrics-angle, symmetry, range of motion-and providing instant feedback on the 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\u003eRaspberry Pi 5 8GB\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eRaspberry Pi AI HAT+\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePi Camera Module 3\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e7in HDMI Display\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eHDMI Cable\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eNVMe SSD 256GB\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\u003eDesigned for B.Tech ECE and CSE students taking on Smart India Hackathon challenges, CBSE Class 12 learners exploring AI practicals under subject code 843, and ATL mentors seeking a ready-to-run pose estimation demo. It picks up where basic GPIO projects leave off, giving you a real computer vision application that runs entirely on-device.\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 on the box to launch an AI companion that walks you through every step; if you still need help, message us on WhatsApp for direct support from our engineers.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes pose estimation require an internet connection?\u003c\/summary\u003e\u003cp\u003eNo - the Hailo-8L accelerator runs BlazePose entirely on-device, so landmark detection and form analysis work offline after the initial software setup.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I use a larger monitor instead of the 7-inch display?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The Raspberry Pi 5 outputs to any HDMI screen; the included 7-inch panel gives you a compact, self-contained demo that is easy to move around a classroom or lab.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eIs the NVMe SSD preloaded with the OS and software?\u003c\/summary\u003e\u003cp\u003eThe SSD arrives unformatted. You will flash Raspberry Pi OS and install the Hailo runtime using the step-by-step instructions provided by the AI companion and our installation guide.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eEducation Analytics - MediaPipe BlazePose accelerated on Hailo-8L detects 33 body landmarks at 60fps - real-time exercise form analysis.\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-8gb-high-performance-single-board-computer\"\u003eRaspberry Pi 5 8GB\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/industrial-ph-sensor-module-for-arduino-esp32-raspberry-pi\"\u003eRaspberry Pi AI HAT+\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\u003e7in HDMI Display\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/elecrow-hdmi-to-hdmi-connector-for-5-inch-raspberry-pi-display\"\u003eHDMI Cable\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 256GB\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 Plus Kit with Raspberry Pi 5 + Camera?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Classroom Engagement Camera Plus Kit with Raspberry Pi 5 + Camera includes all components needed: Raspberry Pi 5 8GB, Raspberry Pi AI HAT+, Pi Camera Module 3, 7in HDMI Display, HDMI Cable 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 Plus Kit with Raspberry Pi 5 + Camera?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Intermediate level makers, suitable for ages 16-21. Education Analytics - MediaPipe BlazePose accelerated on Hailo-8L detects 33 body landmarks at 60fps - real-time exercise form analysis. 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