Pi 5 Multimodal IoT Fusion Research — Deploy a Transformer‑Based Anomaly Detection System at the Edge

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

Instead of relying on unimodal streams that miss subtle correlations, you’ll fuse live camera feeds, high‑fidelity I2S audio, and environmental sensor data from a wireless ESP32 mesh into a compact vision‑audio transformer running directly on a Raspberry Pi 5. The result is a research‑grade anomaly detection engine that catches deviations invisible to single‑mode baselines — ideal for industrial monitoring, smart campus experiments, or hackathon prototypes.

What You'll Build

You’ll assemble a self‑contained edge inference station: the Pi Camera Module 3 captures video, the INMP441 mic streams audio, and two ESP32 boards relay four sensor readings over a low‑latency mesh. All streams feed into a transformer model optimised for the Pi 5’s NPU‑like acceleration and stored on a 512GB NVMe SSD via the M.2 HAT+. The kit delivers a reproducible research platform that demonstrates multimodal fusion outperforming unimodal baselines in real‑time anomaly scoring.

What You'll Learn

• Deploying a vision‑audio transformer on Raspberry Pi 5 with hardware‑aware optimisations
• Ingesting I2S digital audio and synchronising it with camera frames in a unified pipeline
• Building an ESP32‑based sensor mesh that transmits temperature, humidity, motion, and light data over Wi‑Fi
• Profiling model latency and throughput with NVMe storage for continuous dataset logging

Kit Contents

Why Buy This Kit Instead of Sourcing Parts Separately

Who This Kit Is For

Designed for B.Tech ECE/EEE final‑year students, M.Tech researchers, and Smart India Hackathon participants who need to demonstrate multimodal intelligence at the edge. The advanced sensor fusion and transformer workflow also fits IIT/NIT/VIT/BITS capstone projects, ATL Tinkering Lab mentors pushing beyond beginner kits, and anyone building a strong portfolio in applied AIoT.

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.