Smart Waste Management (Swm) System Using Iot and Machine Learning

Abstract

Waste Management refers to the activities and the actions that are required to manage waste
from its inception to its final disposal. Waste Management or waste disposal includes
collection, transport, treatment and disposal of waste, along with monitoring and regulation of
the waste management process. The waste can be solid, liquid or gas and the methods of
processing each waste is different from one another. Waste Management deals with industrial,
biological and household wastes. IoT applications in waste management are helping the people
and the cities alike in making the waste practices more sustainable. Optimizing the garbage
collection routes based on the filling of the disposal unit as measured by fill level sensors has
proved to be very useful. Transforming the waste management requires a deeper collaboration
between the government and the people. The amount of waste generated keeps on increasing
with the increasing population and advancements in science and technology. In 2017 the waste
generated was calculated to be around 267.8 million tons, approximately 4.51 pounds or an
individual per day. IoT provides a huge opportunity to reduce waste, lower the operating costs
involved in waste management and improves the quality of service. The proposed method can
be tested with various machine learning techniques such as linear regression, logistic
regression, support vector machine and random forest algorithm. The method using Random
forest algorithm gives the accuracy of about 72%. From the result obtained it is very well
understood that random forest is found to be better than other techniques.