Drain Clog Detector using Tensor Flow

Detection of clogs can be done through a number of techniques, like using gas sensors or internal mechanisms, But i also can be done by soundwaves, as we know that knocking on a tube where it's opened is different sound from that happened when being closed. we train a model the sound patterns o

Project Title

Drain Clog Detector using Tensor Flow

Project Area of Specialization

Internet of Things

Project Summary

Detection of clogs can be done through a number of techniques, like using gas sensors or internal mechanisms, But i also can be done by soundwaves, as we know that knocking on a tube where it's opened is different sound from that happened when being closed. we train a model the sound patterns occurring on tube surface during clogs as well as those patterns occurs in opened pipes, to detect clogs.

Our idea is to let home owners as well as enterprises like city/compounds maintenance departments and specialized service providers to have an efficient and intelligent system that alerts whoever in charge as early as possible to take action, which contributes in enriching smart cities with an important feature.

Project Objectives

• Clog detecting through Sound waves
• Low cost system to detect clog

Project Implementation Method

Project has three phases, gathering data, learning and prediction. Sound of clogged and opened pipe will be captured and model will be trained. 

water pipe will be connected to hardware and sound sensor. Hardware reads the sensor value and send it back to Cloud.

This has been done for 10 mins for a blocked tube, then another 10 mins for a tube that isn't blocked.

To detect the water sound inside the pipe, a sound sensor will be attached. However Raspberry Pi 3 doesn't have Analog GPIO. To handle this issue we will use Arduino as Arduino has analog GPIO. 

A machine learning algorithm classify the readings into two classes, developed using R applying the Fisher rules , where class 1 represents open mode, and class two represents clog mode.

we will collect 20 minutes of readings, 10 for open mode, and 10 for clog mode, each minute of data was stored in different file and was represented by a vector, and labeled with matching mode, each file contains 60000 readings (60 seconds * 1000 milliseconds).

Benefits of the Project

• Easy clog detection
• Low Cost
• Time Saving
• 24/7 monitoring 

Technical Details of Final Deliverable

This project will decrease maintance cost, Clogged drains not only can bring your home to a halt, but will consume additional costs from our pockets, 10k on average is cost of clearing a clogged drain according to HomeAdvisor, in addition to hidden costs of damaged carpets, wooden furniture.

Final Deliverable of the Project

Hardware System

Core Industry

IT

Other Industries

Others

Core Technology

Artificial Intelligence(AI)

Other Technologies

Internet of Things (IoT)

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com