Adil Khan 1 year ago
AdiKhanOfficial #FYP Ideas

Autonomous dirt detection vacuum cleaner

Cleaning has been one of the most important tasks in everyday human activity and it has always been a time consuming process. Our proposed idea is an autonomous robot that can detect dirt and then clean the surface. In this system, we used new ways of methods to reduce the cost, we used every basic

Project Title

Autonomous dirt detection vacuum cleaner

Project Area of Specialization

Artificial Intelligence

Project Summary

Cleaning has been one of the most important tasks in everyday human activity and it has always been a time consuming process. Our proposed idea is an autonomous robot that can detect dirt and then clean the surface. In this system, we used new ways of methods to reduce the cost, we used every basic model of hardware like Raspberry Pi as the core of Robotic operating system and camera for dirt detection. Our project can assist people at home who are too busy. Robotic vacuum cleaners in the market are expensive, the main objective of our project is to provide affordable autonomous vacuum cleaners for common users.

Project Objectives

The main objective is to identify and design an autonomous robot that will assist people at home who are too busy for daily or weekly floor cleaning, especially for family with children. In particular for the elderly who live by themselves and do not have the strength or ability to clean. Robotic vacuum cleaners in the market are expensive and inefficient in terms of cleaning time and cleanness. The main objective of our project is to provide affordable autonomous vacuum cleaner for common users.

Project Implementation Method

Our project is Autonomous dirt detection vacuum cleaner. The purpose of our project is to detect dirt automatically by camera, when dirt has been detected, vacuum will start. Our project needs some fast processing module which can detect dirt as fast as possible. So, we are using raspberry pi 3b+ for our project.

Our project is broken into several parts. In our project, we worked on different parameters of dirt by Python language in Raspberry pi 3b+. When we start our project, the camera will be turned on and start searching for a Dirt, whenever any object comes in front of the camera of Raspberry Pi. It will sense it or detect it as a dirt or not dirt. If that object comes in the parameters which are the proof for a dirt then it will say yes it’s a ‘DIRT’, then vacuum will start, otherwise it will show ‘NOT DIRT’.

Benefits of the Project

Benefits of this project:

  • It detects dirt automatically, you will not have to hold the machine.
  • The size of this machine is compact, it can be use for cupboard cleaning.
  • This machine consume less power.
  • This machine is affordable as compared to market.
  • This machine can be used by children and elder people as they do not have the strength or ability to clean.

Technical Details of Final Deliverable

Our final deliverable project is mainly based on raspberry pi, camera, ultra sonic sensor, vacuum. We are using Python language and open cv 4.4 for dirt detection.

Following are some tachnical details of Raspberry pi.

  • Quad Core 1.2GHz Broadcom BCM2837 64bit CPU.

  • 1GB RAM.

  • BCM43438 wireless LAN and Bluetooth Low Energy (BLE) on board.

  • 100 Base Ethernet.

  • 40-pin extended GPIO.

  • 4 USB 2 ports.

  • 4 Pole stereo output and composite video port.

  • Full size HDMI.

  • CSI camera port for connecting a Raspberry Pi camera.

  • DSI display port for connecting a Raspberry Pi touchscreen display.

  • Micro SD port for loading your operating system and storing data.

  • Upgraded switched Micro USB power source up to 2.5A.

Following are some technical details of Raspberrypi camera.

  • 5MP Omnivision 5647 Camera Module.
  • Still Picture Resolution: 2592 x 1944.
  • Video: Supports 1080p @ 30fps, 720p @ 60fps and 640x480p 60/90 Recording.
  • 15-pin MIPI Camera Serial Interface - Plugs Directly into the Raspberry Pi Board.
  • Size: 20 x 25 x 9mm.
  • Weight 3g.
  • Fully Compatible with many Raspberry Pi cases.

For obstacle avoidance, we are using Ultrasonic sensor because it can measure the distance to an object by using sound waves. It measures distance by sending out a sound wave at a specific frequency and listening for that sound wave to bounce back. Ultrasonic sensors are characterized by their reliability. They have a level measurement with millimetre precision.

Final Deliverable of the Project

Hardware System

Core Industry

Manufacturing

Other Industries

IT

Core Technology

Robotics

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Affordable and Clean Energy, Responsible Consumption and Production

Required Resources

Item Name Type No. of Units Per Unit Cost (in Rs) Total (in Rs)
Raspberry pi 3 b+ Equipment160006000
Camera Equipment118001800
Memory card Equipment1800800
Chassis Equipment1700700
Pi casing Equipment1400400
Tyres Equipment450200
Motors Equipment4100400
Battery Equipment1700700
Ultrasonic sensor Equipment1200200
Vacuum Equipment1600600
Glue gun Miscellaneous 1600600
Glue stick Miscellaneous 42080
Cutter Miscellaneous 15050
Bunch of wires Equipment1300300
Total in (Rs) 12830
If you need this project, please contact me on contact@adikhanofficial.com
0
136
Online Face Recognition System Using Gaussian Naive Bayes Machine Lear...

Since faces are a part of inherent identities of people, or most probably there can be a d...

1675638330.png
Adil Khan
1 year ago
IOT Virtual Doctor Robot

We are going to make a Doctor robot that will assist doctors in handling the patients and...

1675638330.png
Adil Khan
1 year ago
False News Detector

The objective of this project is to provide a complete, reliable, and efficient system tha...

1675638330.png
Adil Khan
1 year ago
Integrated Smart Shopping Cart

Introduction: In the modern world, supermarkets employ shopping trolleys/baskets, in...

1675638330.png
Adil Khan
1 year ago
Development Of Retro-fit Electric Bike

Fossil fuels have been a significant part of creating today?s world, and as the population...

1675638330.png
Adil Khan
1 year ago