AI-assisted Pipeline Diagnostics and Inspection w/ mmWave

Extract data items from a mmWave sensor, train a NN to diagnose pipeline defects, and inspect results w/ deformed pipe images on a web app.

May 23, 2023

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Components and supplies

4

Mini Pushbutton

1

Elecrow 8.8″ (1920*480) IPS Screen

1

5mm Common Anode RGB LED

1

Arduino Nano

1

PCBWay Custom PCB

1

LattePanda 3 Delta

1

Nicla Vision

1

Jumper Wires Standard

1

2.8″ 240x320 TFT LCD Touch Screen (ILI9341)

3

SparkFun Logic Level Converter - Bi-Directional

1

60GHz mmWave Sensor - Breathing and Heartbeat Module

3

Resistor 220 Ohm

1

Anycubic Kobra 2

Tools and machines

1

Soldering Iron

1

Hot Glue Gun

Apps and platforms

1

Thonny IDE

XAMPP Server

1

Arduino IDE

1

Fusion 360

1

KiCad

1

Ultimate Cura

1

Visual Studio 2017

1

Edge Impulse Studio

Project description

Code

AI_assisted_Pipeline_Diagnostics_run_model.ino

cpp

AI_assisted_Pipeline_Diagnostics_run_model.ino

AI_assisted_Pipeline_Diagnostics_data_collect.ino

cpp

AI_assisted_Pipeline_Diagnostics_data_collect.ino

Downloadable files

Custom parts and enclosures

Custom parts and enclosures

https://www.hackster.io/kutluhan-aktar/ai-assisted-pipeline-diagnostics-and-inspection-w-mmwave-d048c3#cad

Documentation

Schematics

Schematics

https://www.hackster.io/kutluhan-aktar/ai-assisted-pipeline-diagnostics-and-inspection-w-mmwave-d048c3#schematics

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Table of contents

Intro

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