Automatic Segregation of Household Waste using Machine Learning Approaches

Abstract

Waste management (WM) refers to the activities and actions, which must be completed from start to conclusion of the project. Waste might be in the form of a gas, a liquid, or a solid. A variety of approaches are employed to deal with diverse types of rubbish, including industrial, biological, and household waste. Plastics, glassware, cardboard, papers, bio garbage, and other household waste are trash. No garbage may be recycled or sorted into biological materials utilising Raspberry Pi in household activities. The primary aim of this project is to automatically segregate the household waste into biodegradable and non-biodegradable waste such as plastics and metals. Recycling and land-filling are used to demolish garbage as part of waste management. This work depicts a viable waste management system design based on machine learning. The proposed approach uses an algorithm to categorise biodegradable and non-degradable waste. The signal from the IR sensor is continuously transmitted to detect the existence of obstructions. When the waste is thrown into the bin, the receiver picks up the reflected signal from the waste and begins the process with the Raspberry Pi. In turn, the DC motor is activated by running a programme that rotates the motor forward. The conveyor belt rotates smoothly because to two DC motors. The garbage is recognised by the sensors connected in series near the conveyor belt because both DC motors operate in the forward direction.