{"product_id":"kit-manufacturing-qc-vision-kit-with-raspberry-pi-5-plus-camera","title":"Manufacturing QC Vision Kit with Raspberry Pi 5 + Camera","description":"\u003ch1\u003eRaspberry Pi 5 Manufacturing QC Vision Kit: Build an AI-Powered Object Counter That Works on Your Factory Floor\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 5-6 hrs\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 18-21\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e TensorFlow Object Detection on Edge Devices\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eImagine a production line where every product passing a checkpoint is automatically counted and flagged if it crosses a boundary incorrectly. With this kit, you’ll build exactly that — a Raspberry Pi 5 camera system running a TensorFlow object detection model to count people or items crossing a virtual line in the video feed. Whether you’re prototyping for a factory floor or learning industrial computer vision, you’ll have a working QC tool in under 6 hours.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou’ll assemble a self-contained vision system that monitors a camera feed in real time, detects objects of interest, and tracks them as they cross a predefined line. The Raspberry Pi 5 with AI HAT+ accelerates the model, so inference runs smoothly at the edge without cloud dependency. At the end, you’ll have a functional object counter ready for warehouse or assembly line prototyping, complete with LED indicators for status alerts.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eDeploy and accelerate a TensorFlow object detection model on the Raspberry Pi AI HAT+\u003c\/li\u003e\n  \u003cli\u003eConfigure a camera pipeline with Pi Camera Module 3 for real-time video processing\u003c\/li\u003e\n  \u003cli\u003eImplement line-crossing counting logic using bounding box coordinates\u003c\/li\u003e\n  \u003cli\u003eWire GPIO LEDs to signal count thresholds or system states\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\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\u003e5mm LED\u003c\/td\u003e\n\u003ctd\u003e3\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e220Ω Resistors\u003c\/td\u003e\n\u003ctd\u003e5\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eM-F Wires\u003c\/td\u003e\n\u003ctd\u003e10\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eMicroSD Card 32GB\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\u003eThis kit targets B.Tech students in ECE\/EEE and computer science who need a real-world AI project for their major or capstone. It’s also perfect for Smart India Hackathon participants focused on manufacturing or Industry 4.0 themes, and for trainees at IIT, NIT, VIT, or BITS campuses exploring edge AI. Hobbyists with intermediate Raspberry Pi experience who want to move into industrial computer vision will find the guided build invaluable.\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 access the AI build companion, which provides step-by-step troubleshooting. You can also message us on WhatsApp for human support in under an hour.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes this kit work without an internet connection?\u003c\/summary\u003e\u003cp\u003eYes, the TensorFlow model runs entirely on the Raspberry Pi AI HAT+ once loaded; an internet connection is only needed for initial model download and the AI companion.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I modify the object detection model to count different objects?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The pre-trained model can be fine-tuned with your own dataset. The build guide explains how to swap the model for custom object classes like components or workers.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eIs this kit suitable for a college engineering project?\u003c\/summary\u003e\u003cp\u003eDefinitely. It covers embedded vision, edge AI, and IoT integration — ideal for B.Tech final year projects or Smart India Hackathon submissions. The kit includes everything needed for a working prototype.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eManufacturing QC — Pi 5 AI HAT+ runs TensorFlow object detection model counting people or objects crossing a line in camera feed.\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\/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\u003e\n\u003ca href=\"\/products\/inductive-proximity-sensor-5mm-npn-no-ceyone-compoden\"\u003e5mm LED\u003c\/a\u003e x3\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/resistor-variety-pack-100-pcs-10-values-14w-carbon-film\"\u003e220Ω Resistors\u003c\/a\u003e x5\u003c\/li\u003e\n    \u003cli\u003eM-F Wires x10\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/microsd-card-reader-spi-module-for-arduino\"\u003eMicroSD Card 32GB\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 Manufacturing QC Vision Kit with Raspberry Pi 5 + Camera?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Manufacturing QC Vision Kit with Raspberry Pi 5 + Camera includes all components needed: Raspberry Pi 5 4GB, Raspberry Pi AI HAT+, Pi Camera Module 3, 5mm LED, 220Ω Resistors 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 Manufacturing QC Vision Kit with Raspberry Pi 5 + Camera?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Advanced level makers, suitable for ages 18-21. Manufacturing QC — Pi 5 AI HAT+ runs TensorFlow object detection model counting people or objects crossing a line in camera feed. Estimated build time is 5-6 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Manufacturing QC Vision Kit with Raspberry Pi 5 + Camera online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Manufacturing QC Vision Kit with Raspberry Pi 5 + Camera is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. 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