Multimodal Anomaly Detection Kit for Raspberry Pi 5 - Fuse Vision, Audio & Sensor Data with a Transformer

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

Create a production-grade anomaly detection system that combines visual, acoustic, and environmental sensor streams using a transformer model on the Raspberry Pi 5. By fusing multiple modalities, you'll achieve significantly better fault detection than traditional single-sensor approaches-essential for smart manufacturing applications.

What You'll Build

You'll assemble a compact test bed with a camera, microphone, two ESP32 sensor nodes, and an NVMe SSD, then train and deploy a multimodal transformer to detect defects in real time. This portable setup can be demonstrated as a working QC inspection station for academic projects, hackathons, or prototype validation.

What You'll Learn

• Train a multimodal transformer model on fused vision, audio, and sensor data
• Configure a Raspberry Pi 5 with M.2 NVMe SSD for fast model inference
• Implement real-time anomaly detection with a Pi Camera and I2S microphone
• Integrate ESP32 wireless sensors to capture vibration/temperature readings and feed into the model

Kit Contents