{"product_id":"kit-esp32-offline-ai-sound-classifier","title":"ESP32 Offline AI Sound Classifier Kit with ESP32 + LED","description":"\u003ch1\u003eBuild an ESP32 Offline AI Sound Classifier with Edge Impulse \u0026amp; Visual Alerts\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 15-18\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e Edge AI \u0026amp; Sound Processing\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eImagine a doorbell that recognizes your clap pattern, a security system that alerts on glass breaking, or a pet monitor that detects specific barks—all running offline on a pocket-sized device. This kit turns that vision into a working prototype in an afternoon. You’ll capture real-world audio through a high‑quality INMP441 digital MEMS microphone, process it instantly on an ESP32‑S3, and see results on an OLED display while an LED strip lights up with a unique color for each sound class. No cloud dependency, no latency, and no subscription—just a self‑contained edge AI system you can customize further.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eA self-contained sound classifier that listens through an INMP441 I2S microphone, processes audio in real time on the ESP32‑S3, and displays the detected sound class on a 0.96‑inch OLED screen while illuminating a WS2812B LED strip with a distinct colour per class. You’ll load a pre‑trained Edge Impulse model or train your own on four custom sounds—say, clap, whistle, tap, and speech—directly from the Arduino‑compatible firmware. The entire pipeline, from audio capture to inference, stays on the board, making it a fully offline AI solution you can embed into any project.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eRecord and preprocess audio samples for machine learning using I2S digital microphones.\u003c\/li\u003e\n  \u003cli\u003eDesign an impulse in Edge Impulse, extract MFCC features, and train a neural network classifier.\u003c\/li\u003e\n  \u003cli\u003eExport a TensorFlow Lite model and deploy it onto an ESP32‑S3 with the Arduino framework.\u003c\/li\u003e\n  \u003cli\u003eInterface an OLED display via I2C to show classification results and control addressable LEDs based on the detected sound class.\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\u003eESP32-S3 Dev Board\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\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e0.96in OLED\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eWS2812B 4-LED Strip\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e470Ω Resistors\u003c\/td\u003e\n\u003ctd\u003e5\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e4.7kΩ Resistors\u003c\/td\u003e\n\u003ctd\u003e5\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e400-pt Breadboard\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\u003e20\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eMicro USB Cable\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 is ideal for CBSE Class 11–12 students exploring the new AI curriculum, B.Tech ECE\/EEE undergraduates prototyping embedded ML assignments, and participants in Smart India Hackathon building low‑power IoT solutions. ATL Tinkering Lab mentors will find it a ready‑to‑use edge AI module that aligns with NEP 2020’s emphasis on hands‑on AI literacy, while hobbyists at IIT, NIT, VIT, and BITS can use it as a launchpad for more complex sound‑aware devices.\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\u003eOur AI companion, trained on this exact project, walks you through wiring, firmware upload, and model deployment step-by-step. If you still need human help, drop us a WhatsApp message and we'll guide you.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDo I need prior experience with Edge Impulse?\u003c\/summary\u003e\u003cp\u003eNo. The kit includes a pre‑trained model for four common sounds (clap, whistle, tap, and speech) ready to run. Edge Impulse’s web dashboard is beginner‑friendly, and we provide a guided tutorial to get you started.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I change the sound classes this kit recognizes?\u003c\/summary\u003e\u003cp\u003eAbsolutely. You can record new samples via a web interface, retrain the model in Edge Impulse’s free tier, and re‑deploy it. The ESP32‑S3’s flash storage lets you swap models anytime without buying extra hardware.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes it work without any internet connection after setup?\u003c\/summary\u003e\u003cp\u003eYes. Once the model is flashed, all inference happens on the ESP32‑S3. It requires no internet, no Bluetooth, and no phone app—just power via USB. Perfect for installations where connectivity is unreliable.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003eINMP441 mic + Edge Impulse sound classifier runs on ESP32-S3. Identifies 4 sound classes without cloud.\u003c\/p\u003e\n  \u003ch4\u003eWhat's in this kit\u003c\/h4\u003e\n  \u003cul\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/arduino-uno-r4-wifi-board-with-esp32-s3-module-ra4m1-cortex-m4\"\u003eESP32-S3 Dev Board\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/inmp441-i2s-microphone-module-high-snr-mems-mic-for-esp32\"\u003eINMP441 I2S Mic\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/096in-oled-display-128x64-i2cspi-for-arduino-raspberry-pi\"\u003e0.96in OLED\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/ws2812b-5050-rgb-led-ring-241-leds-9-rings-addressable\"\u003eWS2812B 4-LED Strip\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e470Ω Resistors x5\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/resistor-variety-pack-100-pcs-10-values-14w-carbon-film\"\u003e4.7kΩ Resistors\u003c\/a\u003e x5\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/breadboard-standard-bundle-830400-tie-points-for-prototyping\"\u003e400-pt Breadboard\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003eM-M Wires x20\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/microusb-cable-1m-charging-data-cord-for-arduino-android\"\u003eMicro USB Cable\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 ESP32 Offline AI Sound Classifier Kit with ESP32 + LED?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The ESP32 Offline AI Sound Classifier Kit with ESP32 + LED includes all components needed: ESP32-S3 Dev Board, INMP441 I2S Mic, 0.96in OLED, WS2812B 4-LED Strip, 470Ω Resistors 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 ESP32 Offline AI Sound Classifier Kit with ESP32 + LED?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Intermediate level makers, suitable for ages 15-18. INMP441 mic + Edge Impulse sound classifier runs on ESP32-S3. Identifies 4 sound classes without cloud. Estimated build time is 4-5 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the ESP32 Offline AI Sound Classifier Kit with ESP32 + LED online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the ESP32 Offline AI Sound Classifier Kit with ESP32 + LED is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. 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