{"product_id":"kit-wildlife-camera-trap-kit-v28","title":"Wildlife Camera Trap Kit v28","description":"\u003ch1\u003eRaspberry Pi 5 Wildlife Camera Trap Kit – AI Trail Camera with On-Device Classification\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 \u0026amp; ethical considerations\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eTurn a Raspberry Pi 5 into a battery-conscious camera trap that identifies wildlife in real time, then dive into the ethics of AI-assisted conservation. You’ll deploy a TensorFlow Lite animal classifier that runs offline, dramatically cutting down false triggers and storing only meaningful encounters on the high-speed NVMe SSD. The build guide includes a dedicated module on academic ethics and the real-world limitations of AI in natural habitats, making it a powerful project for senior secondary computer science, B.Tech ECE\/EEE workshops, or a Smart India Hackathon wildlife challenge.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eA fully functional motion-activated camera trap. When the PIR sensor (software-defined alongside the camera) detects movement, the Pi Camera Module 3 captures a frame, runs a TensorFlow Lite classification model on the Raspberry Pi 5’s onboard AI inference, and decides whether to store the image. Logs of species and timestamps are written to the NVMe SSD, ready for later analysis. The result is a self-contained, low-power tool that can distinguish a langur from a deer and ignore wind-blown vegetation — all without cloud connectivity.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eDeploy a custom TensorFlow Lite animal classifier on Raspberry Pi 5\u003c\/li\u003e\n  \u003cli\u003eCapture images with Pi Camera Module 3 and optimize for low-light conditions\u003c\/li\u003e\n  \u003cli\u003eIntegrate an NVMe SSD using the Pi 5 M.2 HAT for high-speed data logging\u003c\/li\u003e\n  \u003cli\u003eEvaluate ethical considerations in wildlife AI — data bias, disturbance, and responsible deployment\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\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\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\u003eStudents aged 16–21 tackling practical AI ethics in wildlife monitoring will find this kit directly relevant. CBSE Class 11–12 learners can use the project for CS investigatory work, while B.Tech ECE and EEE students will get hands-on experience with embedded computer vision. Smart India Hackathon teams focusing on wildlife conservation and ATL Tinkering Labs pursuing advanced edge AI explorations will also benefit from the ready-to-assemble hardware and the ethics-centric build guide.\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 access the AI companion, trained on this exact kit’s assembly and coding steps. For extra help, reach us on WhatsApp — our engineers respond within hours.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I use this camera trap for my CBSE AI project?\u003c\/summary\u003e\u003cp\u003eYes, the project guide includes a complete ethics and limitations discussion module, aligning perfectly with CBSE AI curriculum requirements for responsible technology use.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes the kit work for night-time wildlife monitoring?\u003c\/summary\u003e\u003cp\u003eThe Pi Camera Module 3 performs well in low light; you can pair it with an external IR illuminator (not included) for full nocturnal capture, and the kit’s software supports IR-cut switching.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eHow do I power the trap in the field?\u003c\/summary\u003e\u003cp\u003eThe included USB-C PSU is designed for indoor setup. For field deployment, a standard 5V power bank with USB-C output (not included) can run the system for several hours, and the guide explains how to optimize power consumption.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eWildlife — TFLite skin lesion classifier on Pi 5 demonstrates AI-assisted preliminary triage — academic ethics and limitations discussion included.\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\/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-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 Wildlife Camera Trap Kit v28?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Wildlife Camera Trap Kit v28 includes all components needed: Raspberry Pi 5 4GB, Pi Camera Module 3, NVMe SSD 256GB, 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 Wildlife Camera Trap Kit v28?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Intermediate level makers, suitable for ages 16-21. Wildlife — TFLite skin lesion classifier on Pi 5 demonstrates AI-assisted preliminary triage — academic ethics and limitations discussion included. Estimated build time is 5-6 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Wildlife Camera Trap Kit v28 online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Wildlife Camera Trap Kit v28 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\": \"Wildlife Camera Trap Kit v28\",\n  \"description\": \"Wildlife — TFLite skin lesion classifier on Pi 5 demonstrates AI-assisted preliminary triage — academic ethics and limitations discussion included.\",\n  \"sku\": \"CDN-KIT-4237\",\n  \"brand\": {\"@type\": \"Brand\", \"name\": \"Compoden\"},\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"https:\/\/compoden.in\/products\/kit-wildlife-camera-trap-kit-v28\",\n    \"priceCurrency\": \"INR\",\n    \"price\": \"26860\",\n    \"availability\": \"https:\/\/schema.org\/InStock\",\n    \"seller\": {\"@type\": \"Organization\", \"name\": \"Compoden\"}\n  },\n  \"category\": \"Edge AI \u0026 Computer Vision\"\n}\n\u003c\/script\u003e","brand":"Compoden","offers":[{"title":"Default Title","offer_id":53463950852461,"sku":"CDN-KIT-4237","price":31690.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0999\/3997\/5533\/files\/kit-wildlife-camera-trap-kit-v28.png?v=1781949867","url":"https:\/\/compoden.com\/products\/kit-wildlife-camera-trap-kit-v28","provider":"Compoden","version":"1.0","type":"link"}