Smart Waste Bins Using Ant Colony Algorithm with a Database

Abstract

In today's world, many people prefer urban living to rural living, which has resulted in several challenges in cities. One of the most significant issues is efficient waste management. To address this, we conducted a study to optimize waste collection in smart cities to minimize environmental impact and reduce costs. Our approach involved developing sensor-equipped garbage containers that could measure fill levels, temperature, and carbon dioxide levels. We then used IoT technology to transmit this data to waste management software. By applying the ant colony algorithm, we could deliver efficient waste collection routes that could be communicated to garbage truck drivers through tablets. We used data mining techniques to predict peak garbage levels and plan container placement. We implemented this system in Kayseri, Turkey, with 200 smart containers serving a population of 548,028. Before this, static routes were used for garbage collection. With the new system, dynamic routes were employed, which led to reduced costs, emissions, traffic, and pollution. The smart waste management system achieved around 30% cost savings while improving urban living conditions.