Anomaly Detection on Industrial Machine Kit with ESP32 + Sensor
ESP32-S3 Anomaly Detection Kit — Run One-Class SVM on Industrial Machines
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
With this kit, you’ll deploy a one-class SVM model on an ESP32-S3 that learns the normal vibration and current signature of a machine, then triggers an alert via GSM when it detects anomalies — exactly what predictive maintenance systems do on factory floors. Ideal for final-year engineering projects, Smart India Hackathon prototypes, or industrial IoT skill building.
What You'll Build
A self-contained anomaly detection unit that mounts near a motor or pump, collects ADXL345 vibration and INA219 current data, logs the baseline, and runs on-device SVM inference. When a deviation crosses threshold, the system sends an SMS alert and displays the fault on an OLED, while logging the event with a timestamp to microSD.
What You'll Learn
- Feature extraction from accelerometer and current sensor streams for anomaly detection
- Training a one-class SVM on a microcontroller and deploying it using TensorFlow Lite Micro
- Integrating RTC for accurate timestamping and microSD for data logging
- Implementing GSM-based remote alerting for industrial fault notifications
Kit Contents
| Component | Quantity |
|---|---|
| ESP32-S3 Dev Board | 1 |
| ADXL345 Accel | 1 |
| INA219 Current Sensor | 1 |
| DS3231 RTC | 1 |
| MicroSD Module | 1 |
| LM2596 Buck Converter | 1 |
| 0.96in OLED | 1 |
| SIM800L GSM | 1 |
| 1000µF 25V Caps | 2 |
| 100nF Caps | 10 |
| PCB Prototype Board | 2 |
| DIN Rail Enclosure | 1 |
| 12V 2A PSU | 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 engineering students in B.Tech ECE, EEE, or CSE who need a capstone project that demonstrates edge AI and IoT. It’s also ideal for Smart India Hackathon teams building industrial safety solutions, ATL Tinkering Lab mentors introducing predictive maintenance, and IIT/NIT/VIT/BITS students preparing for tech fests or internships.
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 included QR code connects you to an AI companion trained on this exact project, and you can reach us via WhatsApp for human assistance.
Do I need prior experience with machine learning?
The kit includes pre-trained model files and step-by-step instructions, but familiarity with Python and basic electronics will help you customize the anomaly detection thresholds.
Can this be used on a real industrial machine?
Yes, the DIN rail enclosure, buck converter, and robust sensor suite make it suitable for demonstration on small motors, pumps, or conveyors in a lab or light industrial setting.
How do I collect baseline data for the SVM?
The AI companion guides you through capturing normal operation data, extracting features, and training the one-class SVM using a provided Colab notebook or local script.
ADXL345 + INA219 current sensor feed a one-class SVM model on ESP32-S3. Flags deviation from baseline profile.
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