Server Room Temperature Monitor Kit with ESP32 + MPU6050
Server Room Temperature Monitor Kit with ESP32 & MPU6050 — ML-Powered Environmental Monitoring for Data Centres
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Data centres live and die by environmental stability. With this kit, you’ll build a self-contained monitor that doesn’t just log temperature and vibration — it trains a TensorFlow Lite model right on the ESP32-S3, then plots live loss and accuracy curves on a full-colour TFT display. No cloud, no laptop, no waiting. See exactly how your model learns from real sensor data as it happens.
What You'll Build
A deployable unit that continuously reads DHT22 temperature/humidity, MPU6050 accelerometer, and DS3231 RTC timestamps, stores data on a MicroSD card, and runs an on-device TFLite training loop. The 2.4‑inch ILI9341 screen shows a live dashboard with loss and accuracy curves, turning abstract ML concepts into visual feedback. By the end, you’ll have a working tool that can detect anomalies or predict trends in a server rack environment.
What You'll Learn
- Edge AI fundamentals — implement a complete TensorFlow Lite Micro training loop on ESP32-S3, optimise hyperparameters, and witness loss convergence in real time
- Sensor fusion — synchronise temperature, humidity, and 3‑axis acceleration data with precise RTC timestamps for reliable time-series datasets
- Custom TFT visualisation — render live ML metrics and sensor readings directly on the ILI9341 using efficient graphics primitives without external libraries
- Deployable system design — integrate power supply, MicroSD logging, and enclosure to create a field-ready monitoring device
Kit Contents
| Component | Quantity |
|---|---|
| ESP32-S3 Dev Board | 1 |
| MPU6050 | 1 |
| DHT22 | 1 |
| 2.4in TFT ILI9341 | 1 |
| DS3231 RTC | 1 |
| MicroSD Module | 1 |
| 4.7kΩ Resistors | 5 |
| 100nF Caps | 5 |
| PCB Prototype Board | 2 |
| 5V 2A PSU | 1 |
| 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
B.Tech ECE/EEE final‑year students tackling data centre monitoring for capstone projects or Smart India Hackathon. Early‑career IoT engineers prototyping edge ML solutions for industrial environments. Advanced hobbyists who want to understand on‑device training with real sensor data — not just inference. This kit assumes basic Arduino IDE experience and a willingness to dive into Python‑like TinyML code.
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 guides you through each wiring step, code upload, and calibration. If you need a human eye, message us on WhatsApp — we reply within hours.
Does this kit require prior machine learning experience?
You’ll learn as you build. The AI companion explains TFLite training loops, loss functions, and how to interpret the curves. No prior ML knowledge is needed, just comfort with the Arduino IDE.
Can I deploy this monitor in a real data center?
Yes, the enclosure and reliable components make it suitable for pilot deployments. The trained model can alert on anomalies, and data logs to MicroSD. For 24/7 production, consider industrial‑grade sensors.
The MPU6050 is included — can I modify the project to monitor vibration for predictive maintenance?
<Data Centre — ESP32-S3 runs TFLite training loop on sensor data. Loss and accuracy curves plotted live on TFT display.
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.
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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