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Edge AI Anomaly Detection Node Variant 5 Kit with ESP32 + MPU6050
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Edge AI Anomaly Detection Node Variant 5 Kit with ESP32 + MPU6050

SKU: CDN-KIT-0570-SLD Brand: Compoden Category: Electronics > IoT & Connectivity > Project Kits
Rs. 3,330.00
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Build an Edge AI Anomaly Detection Node with ESP32 & MPU6050 – No Cloud Needed

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: Advanced Build Time: 15-20 hours Age: 25+ Skill: Edge AI deployment on microcontrollers

Industrial motors hum, pumps vibrate, and conveyor belts heat up — until a subtle drift in the data warns of impending failure. This kit lets you capture that warning locally with an ESP32 that runs a TensorFlow Lite model on sensor streams. It flags anomalies in vibration, temperature, and current in real time without ever sending raw data to the cloud. You’ll build a self-contained node that monitors rotating equipment, power distribution, or any asset where seconds matter.

What You'll Build

You’ll assemble and program an edge AI unit that samples data from an MPU6050 accelerometer, DHT22 temperature/humidity sensor, and ACS712 current sensor. A trained TFLite model runs on the ESP32 to score each reading against a learned baseline; when the score crosses a threshold, the OLED flashes a local alert. You can log the event over serial or keep it completely air-gapped — ideal for sensitive industrial environments.

What You'll Learn

  • Deploying a TensorFlow Lite Micro model on ESP32 for real-time inference
  • Fusing vibration, temperature, and current data into a single anomaly score
  • Training and quantizing an autoencoder or GMM model for embedded targets
  • Designing a power-optimized edge node with buck conversion and sensor conditioning

Kit Contents

Component Quantity
ESP32 Dev Board 1
MPU6050 1
DHT22 1
ACS712 5A 1
0.96in OLED 1
LM2596 Buck Converter 1
100nF Caps 10
4.7kΩ Resistors 5
PCB Prototype Board 2
Enclosure Box 1
5V 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

Early-career embedded engineers in IIoT and factory automation will find a ready platform for edge AI experimentation. It’s also a strong fit for final-year B.Tech ECE/EEE students working on predictive maintenance or Smart India Hackathon hardware challenges, and for ATL Tinkering Labs at IITs or NITs that need a reproducible, non-cloud-dependent anomaly detection setup.

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?

Scan the QR code on the box to access the AI companion that knows every sensor and line of code in this kit. You can also send pictures over WhatsApp and our team will help you debug.

Can I retrain the anomaly detection model with my own data?

Yes, the kit includes a training pipeline guide. You’ll collect sensor readings, label normal vs. anomalous windows, and quantize the model for ESP32 using TensorFlow Lite Converter.

What kind of anomalies can this node detect?

It catches shifts in vibration patterns (like imbalance or bearing wear), temperature spikes, and irregular current draw — all common precursors to motor or machinery failure.

Is soldering experience required?

Moderate soldering is involved to assemble the sensor board and OLED connections. The included soldering iron and wire make it possible to learn on the spot, but some prior practice is helpful.

ESP32 runs TensorFlow Lite anomaly detection model trained on sensor time series. Flags anomalies locally without cloud.

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

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