Pi 5 Multi Agent Reinforcement Learning HVAC
Raspberry Pi 5 Multi-Agent Reinforcement Learning HVAC Kit – Train AI to Manage Building Zones & Energy
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Picture a building where every zone learns your cooling preferences, then fights for its share of a limited energy budget — until they all learn to cooperate. This kit puts that research-grade concept on your desk: five independent ESP32 sensors and relay modules negotiate power usage through a central Raspberry Pi 5 coordinator, running real multi-agent reinforcement learning algorithms.
What You'll Build
You will assemble and program a complete MARL HVAC testbed. Each of the five ESP32 boards reads a DHT22 temperature/humidity sensor and controls a relay (simulating zone cooling). The Raspberry Pi 5 runs the negotiation layer, enforcing a global energy cap while agents optimise local comfort. The result is a live dashboard showing how independent RL agents converge on an efficient, fair policy — a miniature of how modern smart buildings manage energy.
What You'll Learn
- Implement independent Q-learning or policy gradient agents on each ESP32 zone node
- Design a shared energy budget negotiation algorithm using the Pi 5 as central coordinator
- Deploy a distributed sensor-actuator network with ESP32, DHT22, and 5V relay modules
- Optimise building HVAC behaviour for both thermal comfort and energy efficiency
Kit Contents
| Component | Quantity |
|---|---|
| Raspberry Pi 5 8GB | 1 |
| NVMe SSD 512GB | 1 |
| ESP32 Dev Board | 5 |
| DHT22 | 5 |
| 5V Relay Module | 5 |
| Pi 5 M.2 HAT+ | 1 |
| USB-C PSU | 1 |
| MicroUSB Cable | 5 |
| M-M Wires | 30 |
Why Buy This Kit Instead of Sourcing Parts Separately
| Factor | Sourcing Separately | Compoden Kit |
|---|---|---|
| Compatibility checks | You verify every part | Pre-tested as a system |
| Build support | Forums and scattered tutorials | AI companion trained on this exact project |
| Time to first working build | Days of debugging | Hours, with step-by-step guidance |
| Shipping coordination | Multiple sellers, multiple delays | One shipment from Bengaluru in 3-5 days |
Who This Kit Is For
Engineering students tackling Smart India Hackathon challenges in AI and IoT, B.Tech ECE/EEE majors exploring multi-agent systems for industrial projects, and final-year students building NPTEL-aligned or Capstone prototypes at IITs, NITs, VIT, or BITS. The architecture is also directly relevant to research in decentralised building management and energy-aware computing.
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.
What if I get stuck during the build?
Scan the QR code to start the AI companion that was trained on this exact MARL setup; it understands wiring, agent code, and debugging. If you need human help, we're on WhatsApp within minutes.
Do I need prior experience with RL or multi-agent systems?
Some familiarity with Python and basic machine learning concepts will help you move faster, but the AI companion explains the RL agent setup, training loop, and negotiation protocol step by step. Beginners with strong coding fundamentals can follow along.
Can this setup control real HVAC equipment?
The kit uses 5V relay modules to simulate zone cooling, so you can safely switch low-power loads like fans or LED indicators. For full HVAC integration, the relays can drive contactors, but that requires electrical safety knowledge beyond the kit scope.
Can I run this with only one or two zones instead of five?
Yes, the architecture scales down naturally. You can begin with a single ESP32 sensor node and the Pi 5 coordinator, then add up to five zones as you become comfortable. The AI companion includes configuration notes for partial deployments.
Multiple RL agents on Pi 5 control building zones independently while negotiating shared energy budget — MARL HVAC optimisation.
What's in this kit
- Raspberry Pi 5 8GB
- NVMe SSD 512GB
- ESP32 Dev Board x5
- DHT22 x5
- 5V Relay Module x5
- Pi 5 M.2 HAT+
- USB-C PSU
- MicroUSB Cable x5
- M-M Wires x30
Shipping Information
- Prepaid Orders: ₹75 for orders up to ₹999, FREE shipping above ₹999
- COD Orders: ₹125 shipping + ₹50 COD fee = ₹175 total
- Delivery Timeline: Dispatch in 1-2 days, delivery in 2-7 days depending on location
Returns & Warranty
- 7-Day Return: Manufacturing defects only (approval required)
- Warranty: 7 days from delivery
- Non-Returnable: Batteries, consumables, cut wires, clearance items