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Pi 5 Occupancy Based HVAC Controller
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Pi 5 Occupancy Based HVAC Controller

SKU: CDN-KIT-2379 Brand: Compoden Category: Electronics > AI IoT > Project Kits
Rs. 28,710.00
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Raspberry Pi 5 Occupancy Based HVAC Controller Kit — Build a Reinforcement Learning System That Predicts Room Occupancy and Saves 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.

Difficulty: Intermediate Build Time: 5-6 hrs Age: 15-21 Skill: Reinforcement Learning & IoT Control

Imagine an HVAC system that knows when a room is occupied and learns over time to adjust temperature just right — saving electricity without sacrificing comfort. This kit lets you build that exact system, using a Raspberry Pi 5, CO2 and PIR sensors to predict occupancy, and a Python RL agent that continuously improves HVAC setpoint decisions. Perfect for AI IoT projects, Smart India Hackathon, and B.Tech final years.

What You'll Build

You’ll assemble a sensor network that detects people in a room using PIR motion sensors and CO2 levels. The system streams data to the Pi, where a reinforcement learning model trains online to predict occupancy patterns and then controls two relays connected to a HVAC system — learning to anticipate needs and reduce energy waste. The result is a working smart thermostat prototype that demonstrates real AI driven energy savings.

What You'll Learn

  • How to interface MH-Z19 NDIR CO2 sensor with Raspberry Pi over UART
  • Using PIR motion sensors and DHT22 temperature/humidity sensors for multi-modal occupancy detection
  • Implementing a Q-learning reinforcement learning agent in Python to optimise HVAC setpoint actions
  • Deploying the model as a real-time controller with relay module for HVAC load switching

Kit Contents

Component Quantity
Raspberry Pi 5 4GB 1
MH-Z19 CO2 Sensor 1
HC-SR501 PIR 2
DHT22 2
5V Relay Module 2
NVMe SSD 128GB 1
Pi 5 M.2 HAT+ 1
USB-C PSU 1
M-M Wires 20

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

This intermediate kit is ideal for B.Tech ECE and EEE students exploring reinforcement learning and IoT based automation, as well as CBSE Class 12 students with a Python background. It’s also perfect for Smart India Hackathon teams tackling energy-efficiency challenges, and ATL Tinkering Labs aiming to demonstrate AI driven control systems.

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?

The AI companion provides immediate troubleshooting steps, and you can connect with our team on WhatsApp for personalised help.

Do I need prior experience with reinforcement learning?

No, the AI companion walks you through the RL concepts step by step, and the kit includes a Python framework with pre-written training logic.

Can this control an actual air conditioner or heater?

The kit includes two 5V relay modules that can switch low-voltage signals to control an actual HVAC system or a load like a fan/heater. For 220V AC loads, you’ll need an external contactor, which the relays can trigger.

What HVAC equipment is compatible?

The controller works with any system that accepts dry contact or low-voltage thermostat inputs, like split ACs with a wired remote terminal, central air handlers, or simple fan/heaters. You’ll need to understand your HVAC system’s wiring.

CO2 and PIR sensors on Pi 5 predict occupancy — RL agent adjusts HVAC setpoints to balance comfort and energy savings.

What's in this kit

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

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