Build a Real-Time Server Room Temperature Monitor with Raspberry Pi Zero 2W and Edge 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.

When server rooms overheat, critical infrastructure falters. With this kit, you’ll build a compact, AI-powered temperature monitoring system that runs a TensorFlow Lite model locally on a Raspberry Pi Zero 2W to detect temperature anomalies in real time, then pushes results to an MQTT dashboard — exactly the kind of edge-to-cloud pipeline used in modern data centres.

What You'll Build

You’ll assemble a self-contained, Wi-Fi-connected temperature sensor that collects ambient temperature and humidity data via the DHT22, processes it through a pre-trained ML model on the Pi Zero 2W to flag abnormal readings, and publishes inference alerts to an MQTT broker for live dashboard visualization anywhere on the network.

What You'll Learn

• Configure and set up a Raspberry Pi Zero 2W for headless operation
• Read sensor data from a DHT22 and pre-process it for AI inference
• Deploy a TensorFlow Lite model for real-time temperature anomaly detection
• Publish processed results to an MQTT broker and visualize on a dashboard

Kit Contents

Why Buy This Kit Instead of Sourcing Parts Separately

Who This Kit Is For

This kit is designed for students pursuing CBSE Class 11–12 with IoT or AI electives, B.Tech ECE/EEE learners prototyping edge inference pipelines, and participants in Smart India Hackathon or ATL Tinkering Labs who need a reliable, all-in-one platform for data centre monitoring demos.

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.