{"product_id":"smart-doorbell-camera-kit-v13-bayesian-ai-security-robot-on-pi-5","title":"Smart Doorbell Camera Kit v13 - Bayesian AI Security Robot on Pi 5","description":"\u003ch1\u003eSmart Doorbell Camera Kit v13 – Build a Bayesian AI Security Robot on Raspberry Pi 5\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 10-12 hrs\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 18-25\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e Bayesian neural network programming and path planning\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eThis isn’t a stationary doorbell camera; it’s a mobile security robot that patrols and reasons about uncertainty. Where typical robots rush past ambiguous sensor readings, this one employs a Bayesian neural network to gauge how confident it is about every detected obstacle. If confidence dips, the robot reroutes conservatively, avoiding blind lunges that could damage hardware or miss an intruder. For engineering students and AI enthusiasts, it’s a real-world lesson in deploying probabilistic models on edge hardware—exactly the kind of project that stands out in your portfolio or during a Smart India Hackathon submission.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou’ll assemble a four-wheeled robot chassis that hosts a Raspberry Pi 5, RPLidar A1 360° scanner, Pi Camera Module 3, and an NVMe SSD over the M.2 HAT. The core software runs a Bayesian neural network that processes LIDAR point clouds to detect obstacles and quantify prediction uncertainty. When a doorway or hallway corner appears with low confidence scores, the robot defaults to a cautious path—slowing down, widening its turn radius, and relying more on visual camera data. The result is a doorbell security robot that doesn’t just say “something is here,” but also “here’s how sure I am, and here’s the plan accordingly.”\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eImplement a Bayesian neural network on Raspberry Pi 5 with uncertainty quantification\u003c\/li\u003e\n  \u003cli\u003eProcess LIDAR point clouds in real time and fuse sensor data with camera feeds\u003c\/li\u003e\n  \u003cli\u003eDesign path planning algorithms that adapt motor commands based on confidence levels\u003c\/li\u003e\n  \u003cli\u003eIntegrate NVMe storage for high-speed data logging and model training\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\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eRPLidar A1\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePi Camera Module 3\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eCytron Motor Driver\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eDC Motor\u003c\/td\u003e\n\u003ctd\u003ex2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eRobot Chassis\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eNVMe SSD 512GB\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePi 5 M.2 HAT+\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eUSB-C PSU\u003c\/td\u003e\n\u003ctd\u003ex1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eM-M Wires\u003c\/td\u003e\n\u003ctd\u003ex20\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\/EEE students, final-year project teams, and robotics club members at IITs, NITs, VIT, or BITS Pilani who want to move beyond line-following robots. It’s ideal for Smart India Hackathon participants building security solutions, or anyone who has worked with Raspberry Pi and Python and is ready to tackle advanced sensor fusion and probabilistic models. The 10-12 hour build assumes you’re comfortable with Linux, motor wiring, and Python libraries like PyTorch or TensorFlow Probability.\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 companion; it provides context-aware steps for this exact kit, from wiring the Cytron driver to deploying the Bayesian neural network. WhatsApp and email support are available as a backup.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes the kit include pre-trained Bayesian neural network models?\u003c\/summary\u003e\u003cp\u003eYes, the AI companion delivers a pre-trained model optimized for the RPLidar A1 and Pi Camera 3, along with scripts to fine-tune it on your own environment using the NVMe SSD for rapid I\/O.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eWhat software libraries are required to implement uncertainty quantification?\u003c\/summary\u003e\u003cp\u003eThe companion guides you through installing Python 3.11, PyTorch (or TensorFlow Probability), and RPLidar’s SDK on Raspberry Pi OS. All dependencies are pinned to versions verified for this kit.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I repurpose the robot for a different security scenario, like intruder classification?\u003c\/summary\u003e\u003cp\u003eAbsolutely. The chassis, LIDAR, and camera are modular, and the codebase is open. You can swap the neural network head to perform facial recognition, anomaly detection, or multi-object tracking—the AI companion includes adaptation tips.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eDoorbell Security — Bayesian neural network on Pi 5 quantifies uncertainty in obstacle detection — robot plans conservative paths when uncertain.\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\/rplidar-a1-360-laser-scanner-for-robotics-slam-compoden\"\u003eRPLidar A1\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\u003eCytron Motor Driver\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/l293d-motor-driver-shield-for-arduino-drive-dc-stepper-motors\"\u003eDC Motor\u003c\/a\u003e x2\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/2-wheel-smart-car-robot-chassis-kit-diy-for-arduino-raspberry-pi\"\u003eRobot Chassis\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 512GB\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    \u003cli\u003eM-M Wires x20\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 Smart Doorbell Camera Kit v13?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Smart Doorbell Camera Kit v13 includes all components needed: Raspberry Pi 5 8GB, RPLidar A1, Pi Camera Module 3, Cytron Motor Driver, DC Motor 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 Smart Doorbell Camera Kit v13?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Advanced level makers, suitable for ages 18-25. Doorbell Security — Bayesian neural network on Pi 5 quantifies uncertainty in obstacle detection — robot plans conservative paths when uncertain. Estimated build time is 10-12 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Smart Doorbell Camera Kit v13 online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Smart Doorbell Camera Kit v13 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\": \"Smart Doorbell Camera Kit v13\",\n  \"description\": \"Doorbell Security — Bayesian neural network on Pi 5 quantifies uncertainty in obstacle detection — robot plans conservative paths when uncertain.\",\n  \"sku\": \"CDN-KIT-4154\",\n  \"brand\": {\"@type\": \"Brand\", \"name\": \"Compoden\"},\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"https:\/\/compoden.in\/products\/kit-smart-doorbell-camera-kit-v13\",\n    \"priceCurrency\": \"INR\",\n    \"price\": \"64550\",\n    \"availability\": \"https:\/\/schema.org\/InStock\",\n    \"seller\": {\"@type\": \"Organization\", \"name\": \"Compoden\"}\n  },\n  \"category\": \"AI Robotics\"\n}\n\u003c\/script\u003e","brand":"Compoden","offers":[{"title":"Default Title","offer_id":53463947772269,"sku":"CDN-KIT-4154","price":74740.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0999\/3997\/5533\/files\/kit-smart-doorbell-camera-kit-v13.png?v=1781949817","url":"https:\/\/compoden.com\/products\/smart-doorbell-camera-kit-v13-bayesian-ai-security-robot-on-pi-5","provider":"Compoden","version":"1.0","type":"link"}