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ESP32 Sound Classification IoT Alert
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ESP32 Sound Classification IoT Alert

SKU: CDN-KIT-2310 Brand: Compoden Category: Electronics > AI IoT > Project Kits
Rs. 2,470.00
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ESP32 Sound Classification IoT Alert Kit: Detect Glass Break, Alarm & Baby Cry with AI

Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.

Difficulty: Beginner Build Time: 3-4 hours Age: 15-18 Skill: Edge Impulse Audio ML & MQTT

This kit transforms an ESP32-S3 into a smart sound monitor that recognises critical audio events — a window shattering, a smoke alarm, or a baby crying — and sends an instant alert to your phone via MQTT. Powered by Edge Impulse's on-device machine learning, it runs inference locally without cloud delay. In three to four hours, you'll have a working prototype ready for home safety, a hackathon demo, or a school project.

What You'll Build

You'll assemble a compact IoT device that listens for three distinct sound classes. When glass break, alarm, or baby cry is detected, the onboard red LEDs flash and the piezo buzzer sounds locally, while the class is published to an MQTT topic of your choice. Connect it to Node-RED, Home Assistant, or any MQTT dashboard to create push notifications, log events, or trigger other smart devices. The kit includes a pre-trained Edge Impulse model, so you'll see results immediately, then retrain with your own audio samples later.

What You'll Learn

  • How to wire an I2S MEMS microphone (INMP441) to an ESP32-S3 for high-quality audio capture.
  • Training a sound classification model in Edge Impulse Studio using spectrogram features.
  • Deploying an Edge Impulse model to an ESP32-S3 and running continuous inference in Arduino IDE.
  • Publishing detection results to an MQTT broker and reading them on a phone or web dashboard.

Kit Contents

Component Quantity
ESP32-S3 Dev Board 1
INMP441 I2S Mic 1
LED Red 2
Piezo Buzzer 1
220Ω Resistors 3
MicroUSB Cable 1
M-M Wires 10

Why Buy This Kit Instead of Sourcing Parts Separately

Factor Sourcing Separately Compoden Kit
Compatibility checks You verify every part Pre-tested as a system
Build support Forums and scattered tutorials AI companion trained on this exact project
Time to first working build Days of debugging Hours, with step-by-step guidance
Shipping coordination Multiple sellers, multiple delays One shipment from Bengaluru in 3-5 days

Who This Kit Is For

This kit is ideal for CBSE Class 11–12 students learning AI and IoT, B.Tech ECE/EEE undergraduates preparing for campus hackathons, ATL Tinkering Lab mentors seeking a working sound recognition demo, and anyone participating in Smart India Hackathon who needs a reliable Edge AI prototype with MQTT connectivity. It assumes no prior machine learning experience — Edge Impulse's graphical interface and the AI companion make the full workflow approachable.

Built and Backed by Compoden

Every 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.

What if I get stuck during the build?

Scan the QR code on the box to open the AI companion, trained on this circuit and code. It provides step-by-step debugging. If you still need help, WhatsApp us directly — we respond within a few hours.

Do I need a separate MQTT broker?

The kit includes instructions to use a free public broker like broker.hivemq.com or install Mosquitto on your laptop. We also show how to set up a private broker on a Raspberry Pi if you have one.

Can I add my own sound classes?

Yes. After building the kit, record new audio samples with the INMP441, upload them to Edge Impulse, and retrain the model. The AI companion walks you through data collection, training, and deployment.

Is this kit suitable for school competitions?

Absolutely. The project demonstrates on-device AI and real-world IoT alerting — strong scoring points at CBSE exhibitions, ATL marathons, and engineering hackathons. The pre-tested parts and guided build help you meet submission deadlines with confidence.

Edge Impulse audio classifier on ESP32-S3 detects glass break, alarm and baby cry — publishes class to MQTT.

What's in this kit

Shipping Information

  • Prepaid Orders: ₹75 for orders up to ₹999, FREE shipping above ₹999
  • COD Orders: ₹125 shipping + ₹50 COD fee = ₹175 total
  • Delivery Timeline: Dispatch in 1-2 days, delivery in 2-7 days depending on location

Returns & Warranty

  • 7-Day Return: Manufacturing defects only (approval required)
  • Warranty: 7 days from delivery
  • Non-Returnable: Batteries, consumables, cut wires, clearance items

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