Bird Call Identifier Kit - Edge Impulse Audio Classifier on ESP32-S3

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

Imagine a tiny device that listens to its surroundings and instantly tells you when a glass breaks, a smoke alarm shrieks, or a baby cries - all through an AI model running on a microcontroller. This kit puts that power in your hands. Built around the ESP32-S3 and Edge Impulse, it's the same workflow field biologists use to train devices that identify bird calls in dense forests, adapted here to a practical home-safety project. You'll capture real audio, label it, train a neural network, and deploy it to hardware that reacts in real time while publishing alerts via MQTT.

What You'll Build

You'll assemble a compact sound classification system that listens continuously through an I2S MEMS microphone. When it detects any of three trained sounds - glass break, alarm, or baby cry - it lights a red LED and buzzes a piezo element for immediate local alert. Simultaneously, the detected class is published through MQTT, so you can log events or trigger actions on other devices. The same firmware architecture can be repurposed to identify bird calls in wildlife surveys simply by retraining the model with your own audio samples.

What You'll Learn

• Capturing high-fidelity audio with the INMP441 I2S microphone and streaming it to Edge Impulse
• Preprocessing raw audio into spectrograms that a neural network can interpret
• Training an audio classification model using Edge Impulse's web-based studio - no coding required
• Deploying the inference model to an ESP32-S3 and coding logic that drives LEDs and buzzer based on live predictions

Kit Contents

Why Buy This Kit Instead of Sourcing Parts Separately

Who This Kit Is For

This kit is designed for CBSE Class 11-12 students exploring AI syllabi, B.Tech ECE/EEE undergraduates building smart sensor projects, and ATL Tinkering Lab participants experimenting with tinyML. Wildlife researchers and conservation engineers can use it as a rapid prototyping tool for acoustic monitoring - replacing hours of manual listening with an edge device that logs specific bird calls to an MQTT server. If you've taken part in Smart India Hackathon and want to ground your IoT idea in real on-device machine learning, this kit moves you from concept to demonstrable prototype in an afternoon.

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.