HVAC Performance Monitor Kit v26 — Multi-Agent Reinforcement Learning on Raspberry Pi 5

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

Deploy five independent reinforcement learning agents on a Raspberry Pi 5, each controlling a building zone via ESP32 microcontrollers and relay modules. The agents learn to cool or heat independently yet collectively negotiate a shared energy budget — a real-world MARL optimisation challenge. Build the future of intelligent building automation on your desk.

What You'll Build

A fully functional HVAC simulator where DHT22 sensors feed temperature data to ESP32 nodes, each governed by a reinforcement learning agent running on the Pi’s NVMe-accelerated environment. The system adapts zone cooling/heating patterns in real time while respecting a hard energy envelope. By the end, you’ll have a configurable testbed to experiment with reward functions, bidding strategies, and decentralised control policies.

What You'll Learn

• Design and train multi-agent reinforcement learning (MARL) systems with independent reward functions and shared constraints.
• Deploy deep RL models on Raspberry Pi 5 with NVMe SSD for low-latency inference and policy updates.
• Interface ESP32 microcontrollers with sensors and relays over Wi-Fi using MQTT, creating a distributed control mesh.
• Implement energy-aware negotiation algorithms that balance local comfort against a global budget.

Kit Contents

Why Buy This Kit Instead of Sourcing Parts Separately

Who This Kit Is For

This kit is built for final-year B.Tech ECE/EEE students exploring multi-agent systems, Smart India Hackathon teams developing energy-optimisation prototypes, and AIoT researchers who need a reproducible hardware testbed. If you have completed intermediate Arduino or ESP32 projects and understand Python basics, you are ready to step into the advanced world of building-wide autonomous control.

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.