TinyML HVAC Monitor Kit with Arduino Nano - Predict Failures
TinyML HVAC Monitor Kit: Predict Failures with Arduino Nano & MPU6050
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Tackle predictive maintenance for HVAC systems by deploying a machine learning model trained on your PC directly to an Arduino Nano. This advanced kit lets you build a compact, battery-powered monitor that classifies vibration and environmental sensor data in real time with 96% accuracy, enabling early detection of compressor or fan imbalances-ideal for industrial IoT capstones and Smart India Hackathon hardware tracks.
What You'll Build
You'll assemble a portable device that attaches to an air handling unit or chiller. Using the MPU6050 accelerometer/gyroscope and DHT22 temperature/humidity sensor, the Nano captures data, runs a pre-trained TinyML model, and shows the classification result-normal operation, early imbalance, or critical fault-on the OLED display. All enclosed in a rugged ABS box for field testing.
What You'll Learn
- Training a TinyML classification model using Edge Impulse or TensorFlow Lite Micro on your PC
- Deploying an optimized model to an Arduino Nano with limited flash and RAM
- Interfacing MPU6050 and DHT22 sensors over I2C for multi-modal data capture
- Implementing real-time inference on an embedded device and visualizing results on an OLED
Kit Contents
| Component | Quantity |
|---|---|
| Arduino Nano | 1 |
| MPU6050 | 1 |
| DHT22 | 1 |
| 0.96in OLED | 1 |
| 3.7V LiPo 500mAh | 1 |
| TP4056 Module | 1 |
| 4.7k? Resistors | 5 |
| 100nF Capacitors | 5 |
| PCB Prototype Board | 2 |
| ABS Enclosure Box | 1 |
| Soldering Iron | 1 |
| Solder Wire | 1 |
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 kit is built for final-year B.Tech students of ECE, EEE, or Mechatronics tackling industrial IoT capstone projects, Smart India Hackathon teams aiming for hardware tracks, and young engineers at IIT, NIT, VIT, or BITS Pilani who want hands-on experience deploying TinyML on microcontrollers. If you need a working predictive maintenance demo for your resume or hackathon pitch, this is your project.
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?
Our AI companion, accessed via the QR code, walks you through model training and deployment step-by-step. If needed, you can also reach us on WhatsApp for personal guidance.
Do I need prior machine learning experience?
Some familiarity with Python is helpful for training the model on your PC, but the AI companion provides a ready-to-use notebook. The embedded C++ code for the Nano is pre-written and well-commented.
Can I modify the model for other industrial equipment?
Absolutely. The kit's framework is intentionally generic; by collecting your own data, you can retrain the TinyML model to classify faults in pumps, conveyors, or generators. The AI companion includes tips on data capture.
How long does the battery last during continuous monitoring?
With the 500mAh LiPo and optimized sleep intervals, the monitor can run for approximately 8-10 hours of continuous classification, perfect for a single shift of fieldwork or a day-long hackathon demo.
HVAC - Tiny ML model trained on PC deployed to Nano. Classifies sensor data in real time with 96% accuracy.
What's in this kit
Choose your assembly option:
- Soldering Kit - 25W soldering iron, 60/40 solder wire, flux, and small perfboard for permanent assembly.
- Breadboard Combo - 800-point full-size breadboard with 65-piece jumper wire pack for solderless prototyping.
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