An Internet of Things-Based Trash Can Monitoring System

Abstract

Everyday people throw trash in trash cans, both in private and public cans. Hence, trash cans become one of the objects needed by community. When a trash can is full or produces bad odor, it may disturb the surrounding community. When people want to throw trash but the can is full, they usually throw it everywhere. When trash produces bad odor, it can disturb sense of smell and may cause diseases to surrounding community. Naïve Bayes is one of the supervised data mining algorithms for classification. To predict a class, Naïve Bayes requires historical data to find the posterior of each class. The Internet of Things is a technology that involves a large number of processes and devices to improve the quality of life of people who use it and facilitate access to information and services provided. The trash can monitoring system is built using C and Python languages. C language is used to program the sensor device, while Python language is used to program the application. The database used in this system is MySQL. The system takes data from an MQ-4 gas sensor and an HC-SR04 ultrasonic sensor in the sensor device, which is installed in a trash can, to classify the condition of the trash can. Based on the results of accuracy performance evaluation, the accuracy with 60:40 data partition is 79%, 70:30 data partition is 78.9%, and 80:20 data partition is 79.1%.