Indonesian Waste Database: Smart Mechatronics System

Abstract

Waste management is an essential component of urban management. As a waste solution, waste management is critical. The goal of this research is to develop a waste management database that is coupled with a mechatronic robot system. Compiling and gathering data on the sorts of garbage found in Indonesia is the starting point for this research. Indonesian waste is classified into six groups: cardboard, paper, metal, plastic, medical, and organic. The total images of the six groups are estimated at 1880 pictures. According to this picture database, Artificial Intelligence (AI) training was used to create the classification system. In the final AI process, the test method was performed using DenseNet121, DenseNet169, and DenseNet201. Testing using artificial intelligence DenseNet201 across 40 epochs yields the best 92,7% accuracy rate. Simultaneously with Artificial Intelligence testing, a mechatronic system is created as a direct implementation of the Artificial Intelligence output model. A four-servo arm robot with dc motor wheel mobility is included in the mechatronic system. According to these findings, the Indonesian waste database can be categorized correctly using Artificial Intelligence and the mechatronics system. This higher accuracy of the artificial intelligence model may be used to create a waste-sorting robot prototype.