{"product_id":"kit-wildlife-camera-trap-plus-kit-with-raspberry-pi-5-plus-camera","title":"Wildlife Camera Trap Plus Kit with Raspberry Pi 5 + Camera","description":"\u003ch1\u003eWildlife Camera Trap Kit with Raspberry Pi 5 \u0026amp; AI HAT+ – Edge Object Detection\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 4-5 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\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eThis kit transforms a Raspberry Pi 5 into a wildlife camera trap that runs YOLOv8s object detection on a Hailo-8L neural processor via the AI HAT+. You’ll capture 1080p video, detect animals in real time, and benchmark the latency and power draw of hardware-accelerated inference against software-only YOLO on the Pi’s CPU. Perfect for field biologists, engineering students, and anyone exploring edge AI for conservation.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou’ll assemble a complete wildlife monitoring station that triggers video recording upon detecting motion or specific animal classes, stores footage on a fast NVMe SSD, and can be deployed in the field with battery power. The system uses the Pi AI HAT+ to offload neural network inference, freeing the CPU for other tasks and reducing energy consumption – a critical comparison for remote applications. By the end, you’ll have a portable, intelligent camera trap and a deep understanding of how hardware acceleration changes the edge AI landscape.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eDeploy YOLOv8s object detection model to Hailo-8L neural processor via Raspberry Pi AI HAT+ with OpenCV integration.\u003c\/li\u003e\n  \u003cli\u003eIntegrate Pi Camera Module 3 to capture 1080p video, trigger recordings on detection, and configure region-of-interest filtering.\u003c\/li\u003e\n  \u003cli\u003eBenchmark inference latency and power consumption between Hailo-8L acceleration and CPU-only software inference, then analyze the trade-offs for battery-operated field devices.\u003c\/li\u003e\n  \u003cli\u003eSet up NVMe SSD storage for reliable, high-speed field recording and learn file management strategies for long-term wildlife monitoring.\u003c\/li\u003e\n  \u003cli\u003eFine-tune detection thresholds for specific wildlife classes (e.g., elephant, deer, tiger) and implement motion‑triggered capture logic.\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\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\u003eThis kit fits B.Tech ECE\/EEE students from IITs, NITs, VIT, and BITS Pilani who are building embedded AI or IoT projects for wildlife conservation. It also works for CBSE Class 11‑12 students with strong coding interests and ATL Tinkering Labs exploring AI‑enabled camera systems. Participants in Smart India Hackathon focusing on IoT‑based wildlife monitoring will find the kit ready to prototype and iterate quickly.\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\u003eThe AI companion walks you through wiring, code, and model deployment step by step. You can also send a WhatsApp message for human assistance on the day of the build.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes the kit include pre‑trained model files and detection scripts?\u003c\/summary\u003e\u003cp\u003eYes, the companion provides all code, the compiled YOLOv8s model for Hailo-8L, and a benchmarking script that records latency and power data for both hardware‑accelerated and CPU‑only inference runs.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I use this kit in the field with a battery?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The AI HAT+ is power‑efficient and the guide includes tips for using portable USB‑C power banks (not included). You’ll learn how the lower power draw of Hailo inference compares to running YOLO entirely on the CPU.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eWhat wildlife classes are supported out of the box?\u003c\/summary\u003e\u003cp\u003eThe default model covers 80 COCO classes; the companion shows you how to restrict detections to a custom list (e.g., elephant, bear, deer) so false triggers from birds or humans are filtered out.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eWildlife — YOLOv8s on Hailo-8L via Pi AI HAT+ detects objects at full 1080p — compare latency and power vs software inference.\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\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 Wildlife Camera Trap Plus Kit with Raspberry Pi 5 + Camera?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Wildlife Camera Trap Plus Kit with Raspberry Pi 5 + Camera includes all components needed: Raspberry Pi 5 8GB, Raspberry Pi AI HAT+, Pi Camera Module 3, NVMe SSD 256GB, USB-C PSU and more. 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