TensorFlow Predictive Maintenance Node Pro
Real-Time Predictive Maintenance with TensorFlow and Arduino Portenta X8
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
Build a powerful industrial predictive maintenance node that uses TensorFlow to detect anomalies in vibration and current patterns. The Arduino Portenta X8’s dual-core architecture runs a full Linux environment on the Cortex-A53 to train models using historical data, while the Cortex-M4 executes inference in real time on live sensor streams. This kit simulates the exact setup used in factories to predict bearing failures and motor degradation.
What You'll Build
You will assemble a DIN rail-mounted predictive maintenance node that monitors rotating machinery. The system continuously captures 3-axis vibration data via two ADXL345 accelerometers and current draw through an ACS712 sensor, timestamps it with a DS3231 RTC, and logs everything to a microSD card. Once trained, the embedded TensorFlow model detects anomalies and can trigger alerts before costly downtime occurs.
What You'll Learn
- Train a TensorFlow model on Linux using vibration and current datasets
- Deploy a TensorFlow Lite Micro model on the Cortex-M4 for real-time inference
- Interface industrial sensors (accelerometers, hall-effect current) with Arduino Portenta
- Build a self-contained DIN rail IoT node with reliable power management
Kit Contents
| Component | Quantity |
|---|---|
| Arduino Portenta X8 | 1 |
| Portenta Max Carrier | 1 |
| ADXL345 Accel | 2 |
| ACS712 20A | 1 |
| DS3231 RTC | 1 |
| MicroSD Module | 1 |
| LM2596 Buck Converter | 1 |
| 100nF Caps | 10 |
| PCB Prototype Board | 2 |
| DIN Rail Enclosure | 1 |
| 24V 3A 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 advanced kit is designed for working engineers, industrial IoT developers, and B.Tech/M.Tech researchers in ECE, EEE, and mechanical engineering. It’s ideal for Smart India Hackathon teams tackling predictive maintenance challenges, professionals prototyping Industry 4.0 solutions, and faculty at institutions like IITs, NITs, VIT, and BITS seeking a hands-on lab tool for TinyML coursework.
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 walks you through troubleshooting step by step, and you can send a WhatsApp message for human support if needed.
What machinery can this node monitor?
It works with any rotating equipment like motors, pumps, fans, and compressors. The accelerometers bolt onto bearing housings and the current sensor clamps around a power lead.
Do I need prior TensorFlow experience?
Some familiarity with Python and machine learning concepts helps, but the AI companion guides you through dataset preparation, model training on the Portenta X8’s Linux side, and conversion to TensorFlow Lite Micro.
Can I connect this node to a cloud platform?
The Portenta X8 offers Wi-Fi and Ethernet connectivity; the build companion includes instructions for pushing inference results to cloud services like AWS IoT Core or Azure IoT Hub via MQTT.
TensorFlow on Linux A53 trains on vibration + current data. M4 runs inference model on new data in real time.
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