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