{"product_id":"kit-pi-5-air-traffic-noise-predictor","title":"Pi 5 Air Traffic Noise Predictor","description":"\u003ch1\u003ePi 5 Air Traffic Noise Predictor — Build a Real-Time Airport Noise Forecasting System with LSTM AI\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 LSTM-based sound forecasting and IoT data pipeline\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eYou’ll deploy a dual-microphone array at the edge, feed live sound events into an LSTM neural network running on a Raspberry Pi 5, and see how it predicts upcoming noise spikes from incoming flight schedules—minutes before they happen. This kit turns raw airport soundscapes into actionable predictions, perfect for smart city projects, environmental research, or flight-path analysis assignments.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eA weatherproofed outdoor station that captures high-fidelity audio using I2S microphones, processes it in real time with a machine learning model, and outputs a rolling 10-minute noise forecast that can alert residents or airport authorities via a dashboard. You’ll have a fully functional edge AI system that learns from actual flight-noise patterns.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eConfiguring INMP441 I2S microphones and ReSpeaker HAT for synchronous dual-channel audio capture on Pi 5\u003c\/li\u003e\n  \u003cli\u003eTraining and deploying an LSTM model on Raspberry Pi 5 using TensorFlow Lite to forecast sound pressure levels from flight schedule inputs\u003c\/li\u003e\n  \u003cli\u003eBuilding a data pipeline that records and labels sound events, then stores them on NVMe SSD for model retraining\u003c\/li\u003e\n  \u003cli\u003eVisualizing noise predictions on a web dashboard with real-time updates using Flask and MQTT\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\u003eINMP441 I2S Mic\u003c\/td\u003e\n\u003ctd\u003e2\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eReSpeaker 2-Mic HAT\u003c\/td\u003e\n\u003ctd\u003e1\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\u003e10\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\u003eB.Tech ECE\/EEE students designing smart-city noise monitoring for hackathons like Smart India Hackathon, CBSE Class 11–12 learners building AI-driven science fairs, and IIT\/NIT\/VIT engineering teams prototyping edge ML for airport environments. The kit bridges the gap between textbook ML concepts and a real-world, deployable system.\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\u003eOpen the AI companion from the QR code, or message us on WhatsApp for direct troubleshooting. The companion walks through each connection, code snippet, and model-loading step specific to this kit.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDo I need prior machine learning experience to use the LSTM model?\u003c\/summary\u003e\u003cp\u003eNo. The kit includes a pre‑trained model and a Jupyter notebook that explains feature engineering and inference. You can modify the model later as your skills grow.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan this system actually predict noise 10 minutes ahead from flight schedules?\u003c\/summary\u003e\u003cp\u003eYes. The LSTM ingests schedule data (time, aircraft type, runway) together with recent noise patterns and outputs a dB forecast with ~85% accuracy in our airport‑adjacent tests.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eIs the hardware suitable for outdoor deployment near an airport?\u003c\/summary\u003e\u003cp\u003eThe kit components can be housed in a weatherproof enclosure (not included). The ReSpeaker HAT and INMP441 mics are designed for field use; we provide guidelines for protective mounting.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eMicrophone array near airport records sound events — LSTM on Pi 5 predicts noise level 10 minutes ahead from flight schedule.\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\n\u003ca href=\"\/products\/inmp441-i2s-microphone-module-high-snr-mems-mic-for-esp32\"\u003eINMP441 I2S Mic\u003c\/a\u003e x2\u003c\/li\u003e\n    \u003cli\u003eReSpeaker 2-Mic HAT\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 x10\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 Air Traffic Noise Predictor?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Pi 5 Air Traffic Noise Predictor includes all components needed: Raspberry Pi 5 4GB, INMP441 I2S Mic, ReSpeaker 2-Mic HAT, 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 Air Traffic Noise Predictor?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Intermediate level makers, suitable for ages 15-21. Microphone array near airport records sound events — LSTM on Pi 5 predicts noise level 10 minutes ahead from flight schedule. Estimated build time is 5-6 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Pi 5 Air Traffic Noise Predictor online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Pi 5 Air Traffic Noise Predictor 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 Air Traffic Noise Predictor\",\n  \"description\": \"Microphone array near airport records sound events — LSTM on Pi 5 predicts noise level 10 minutes ahead from flight schedule.\",\n  \"sku\": \"CDN-KIT-2343\",\n  \"brand\": {\"@type\": \"Brand\", \"name\": \"Compoden\"},\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"https:\/\/compoden.in\/products\/kit-pi-5-air-traffic-noise-predictor\",\n    \"priceCurrency\": \"INR\",\n    \"price\": \"24460\",\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":53469355835757,"sku":"CDN-KIT-2343","price":28860.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0999\/3997\/5533\/files\/kit-pi-5-air-traffic-noise-predictor.png?v=1781948134","url":"https:\/\/compoden.com\/products\/kit-pi-5-air-traffic-noise-predictor","provider":"Compoden","version":"1.0","type":"link"}