Smart City Application: Internet of Things (IoT)

Technologies Based Smart Waste Collection Using Data

Mining Approach and Ant Colony Optimization

Zeki ORALHAN¹, Burcu ORALHAN², and Yavuz YİĞİT³

¹Department of Electrical Electronics Engineering, Erciyes University, Kayseri, Turkey

²Department of Business Administration, Nuh Naci Yazgan University, Kayseri, Turkey

³Techno Park Center of Erciyes University, Kayseri, Turkey

Abstract: Globally today, Living in urban areas is more preferred than in living rural areas. This situation creates many problem for urban living. One of the big problem is waste management in urban areas. Optimizing waste collection has become very important phenomenon for being smart city. In this study, we aimed to optimize waste collection for reduce both cost of collection and pollution effect of environment. We designed a garbage container integrated sensors for measuring fill level of container, temperature, and ratio of carbon dioxide inside the container. We transmitted all information to our waste management software based Internet of Things (IoT) technologies. According to the ant colony algorithm, most efficient waste collection route delivered to garbage truck drivers’ cellular enabled smart tablet. We used data mining approach to forecast when garbage container can reach highest level, and the planning of garbage container placement. We applied this smart waste collection management system in a town where is in Kayseri, Turkey. In first step we applied for 200 Items (garbage containers) in the town that has 548.028 population and urban living ratio is 100%. Before smart waste management system 200 garbage containers was collecting by garbage trucks in a static route. After we had applied smart waste management system, containers were collected by garbage truck in dynamic route. Smart waste management system significantly decreased the trucks’ oil cost, carbon emissions, traffic, truck wear, noise pollution, environmental pollution, and work hours. The system presented approximately 30% with in direct cost savings in waste collection.

Keywords: Ant colony optimization, data mining, IoT smart device, smart city, smart waste management

Received July 29, 2016; accepted December 29, 2016