{"product_id":"ai-solar-fault-detector-with-pi-5-10w-kit","title":"AI Solar Fault Detector with Pi 5 - 10W Kit","description":"\u003ch1\u003eBuild an AI Solar Fault Detection System with Raspberry Pi 5 - Identify Shading, Soiling, and Cell Degradation Instantly\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 15-21\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e AI model deployment for solar panel fault classification\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eSolar installations are booming across India, but invisible faults like partial shading, soiling, and early cell degradation silently slash energy output. This kit lets you build an edge-AI system that spots those faults in seconds, using a Raspberry Pi 5, INA226 power monitors, and a TensorFlow Lite classifier you train yourself. By tracing IV curves on two real 10W panels, the system learns to distinguish three common failure modes, giving you the same kind of insight used by professional solar diagnostics - without needing a lab full of expensive equipment.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou will assemble a portable fault detection station that connects to two solar panels via four INA226 modules, captures high-resolution current-voltage sweeps, and streams them to a Pi 5. A TFLite model running on the Pi's CPU then classifies each IV curve as normal, shading-affected, soiled, or suffering from cell degradation. The result is displayed on an attached screen or logged for further analysis - a complete, ready-to-demonstrate project for your engineering portfolio.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eTracing IV curves by sweeping load conditions and sampling current\/voltage synchronously\u003c\/li\u003e\n  \u003cli\u003eInterfacing INA226 power monitors with a Pi 5 over I2C and reading electrical parameters programmatically\u003c\/li\u003e\n  \u003cli\u003eTraining a TensorFlow Lite model to classify solar panel faults from real-world data\u003c\/li\u003e\n  \u003cli\u003eDeploying a TFLite model on a Raspberry Pi 5 and integrating it with live sensor input for on-device inference\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\u003eINA226 Power Monitor\u003c\/td\u003e\n\u003ctd\u003e4\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eSolar Panel 10W\u003c\/td\u003e\n\u003ctd\u003e2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eNVMe SSD 128GB\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    \u003ctr\u003e\n\u003ctd\u003eM-M Wires\u003c\/td\u003e\n\u003ctd\u003e25\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 is designed for CBSE Class 11-12 students pursuing AI or renewable energy modules, B.Tech ECE\/EEE learners working on mini-projects or Smart India Hackathon entries, and researchers at NITs, IITs, and VIT who need a reproducible edge-AI testbed. It also fits perfectly into ATL Tinkering Lab curricula, offering a real-world application of sensors, embedded systems, and machine learning in a single project.\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 our AI companion, which walks you through troubleshooting, wiring checks, and code fixes - and if you prefer, reach out directly on WhatsApp for human guidance.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I use different wattage solar panels?\u003c\/summary\u003e\u003cp\u003eThe INA226 modules and the TFLite model are calibrated for 10W panels from the kit. Using panels with different electrical characteristics will require retraining the model, but the same hardware and codebase will work once you collect new training data.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eHow is the TFLite model trained?\u003c\/summary\u003e\u003cp\u003eThe kit includes a companion dataset of IV curves from typical shading, soiling, and degradation scenarios. You will run a provided Python script on the Pi 5 to train a simple neural network and convert it to TensorFlow Lite format, step by step.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes this kit come with an enclosure or mounting hardware?\u003c\/summary\u003e\u003cp\u003eThe kit focuses on electronic components and the core build. You can easily 3D-print or laser-cut a housing; the AI companion includes design files and guidance for a portable test rig.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eIV curve tracing on multiple panels detected by Pi 5 - TFLite classifier identifies shading, soiling and cell degradation.\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\u003eINA226 Power Monitor x4\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/6v-2w-solar-panel-for-diy-electronics-iot-projects\"\u003eSolar Panel 10W\u003c\/a\u003e x2\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/official-raspberry-pi-m2-hat-nvme-ssd-add-on-board-for-pi-5\"\u003eNVMe SSD 128GB\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 x25\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 Pi 5 Solar Panel Fault Detection System?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Pi 5 Solar Panel Fault Detection System includes all components needed: Raspberry Pi 5 4GB, INA226 Power Monitor, Solar Panel 10W, NVMe SSD 128GB, Pi 5 M.2 HAT+ 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 Pi 5 Solar Panel Fault Detection System?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Intermediate level makers, suitable for ages 15-21. IV curve tracing on multiple panels detected by Pi 5 - TFLite classifier identifies shading, soiling and cell degradation. Estimated build time is 5-6 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Pi 5 Solar Panel Fault Detection System online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Pi 5 Solar Panel Fault Detection System 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\": \"Pi 5 Solar Panel Fault Detection System\",\n  \"description\": \"IV curve tracing on multiple panels detected by Pi 5 - TFLite classifier identifies shading, soiling and cell degradation.\",\n  \"sku\": \"CDN-KIT-2337\",\n  \"brand\": {\"@type\": \"Brand\", \"name\": \"Compoden\"},\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"https:\/\/compoden.in\/products\/kit-pi-5-solar-panel-fault-detection-system\",\n    \"priceCurrency\": \"INR\",\n    \"price\": \"24655\",\n    \"availability\": \"https:\/\/schema.org\/InStock\",\n    \"seller\": {\"@type\": \"Organization\", \"name\": \"Compoden\"}\n  },\n  \"category\": \"AI IoT\"\n}\n\u003c\/script\u003e","brand":"Compoden","offers":[{"title":"Default Title","offer_id":53469355573613,"sku":"CDN-KIT-2337","price":29090.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0999\/3997\/5533\/files\/kit-pi-5-solar-panel-fault-detection-system.png?v=1781948124","url":"https:\/\/compoden.com\/products\/ai-solar-fault-detector-with-pi-5-10w-kit","provider":"Compoden","version":"1.0","type":"link"}