Waste Segregation Conveyor using Raspberry Pi

Ask For Price

Description

Waste Segregation Conveyor using Raspberry Pi

 OBJECTIVE:

The objective of this system is to provide a technology-oriented, low-cost, waste segregation system using Raspberry pi.


ABSTRACT:

The paper provides an efficient and simple method for solid waste separation using a conveyor. In India, degradable and non-degradable wastes in streets are separated by humans. Hence humans are facing a lot of communicable diseases. It can be used to segregate different types of solid waste such as metal, wet and dry. Sensors are used for recognizing different kinds of waste after receiving this information, the object is pushed from the conveyor to the corresponding bin. This can be done by adding an ultrasonic sensor to detect the position of the object. This setup can be efficiently used anywhere such as in industrial areas or waste collecting and segregating centers.     


INTRODUCTION:

The Smart City represents a hot topic nowadays in terms of improving living conditions. Considering mainly the situation in the European Union, the EU national governments and also private companies are investing every year a significant amount of their budgets in research, development, and implementation of the concept of Smart City. Domestic waste creates pollution when it is being dumped in open space and keeps rotting, spreading odor thereby causing air and land pollution. If the garbage is dumped near water bodies it causes water pollution too. Waste is the main cause of environmental pollution in both developed and developing countries. The environmental impact due to improper treatment and disposal of waste can be devastating. Many types of waste, if treated and used properly can not only reduce pollution but also serve as a main source of energy.


EXISTING SYSTEM:

  • Garbage is collected by the human
  • Waste level monitoring systems
  • Unsegregated waste dumping.

DISADVANTAGES:

  • This leads to health issues for human
  • Cant able separate exactly
  • Need to give salary to human
  • Man can make a mistake

PROPOSED SYSTEM:

Waste is segregated using a conveyor, metal, wet and dry waste can be segregated using this setup. Sensors are used for identifying types of waste. The conveyor has three flaps that will push the waste out of the conveyor into a waste bin. The ultrasonic sensor is used for placing the position of the object on the conveyor to push it into the correct bin based on metal, wet and IR sensor information.


ADVANTAGES :

  • It can work in hazardous environments.
  • It is fully automated 
  • It can be programmed according to varying needs.
  • It can do repetitive tasks, so it is both time and cost-efficient

BLOCK DIAGRAM:

Waste Segregation Conveyor using Raspberry Pi
Waste Segregation Conveyor using Raspberry Pi

BLOCK DIAGRAM DESCRIPTION:

  • In this project, we use a raspberry pi as a controlling device
  • Sensors and conveyor are connected with this raspberry pi 
  • Sensors give output to raspberry pi
  • According to the output, raspberry pi controls the conveyor (DC motor).

HARDWARE REQUIREMENTS:

  • Raspberry Pi
  • Metal sensor 
  • Ultrasonic sensor
  • Moisture sensor
  • IR sensor 
  • DC motor

SOFTWARE REQUIREMENTS:

  • Programming platform: Python IDE  
  • Raspberry pi OS: Raspbian Jessie
  • Programming language: Python

REFERENCES  :

[1] A. Bhargava and A. Kumar, “Arduino controlled robotic arm,” 2017 International conference of Electronics, Communication, and Aerospace Technology (ICECA), Coimbatore, 2017, pp. 376-380. 

[2] V. Patidar and R. Tiwari, “Survey of robotic arm and parameters,” 2016 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, 2016, pp. 1-6. 

[3] A. R. F. Quiros, A. C. Abad, and E. P. Dadios, “Object locator and collector robotic arm using artificial neural networks,” 2015 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), Cebu City, 2015, pp. 1-6. 

[4] K. Jahnavi and P. Shivraj, “Teaching and learning robotic arm model,” 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), Kannur, 2017, pp. 1570-1575. 

[5] Le Kang, Jayant Kumar, Peng Ye, Yi Li, David Doermann, “Convolutional neural networks for document image classification”, 2014 22nd International Conference on Pattern Recognition.

Customer Reviews

There are no reviews yet.

Be the first to review “Waste Segregation Conveyor using Raspberry Pi”

Your email address will not be published. Required fields are marked *