The International Arab Journal of Information Technology (IAJIT)


Smart City Application: Internet of Things (IoT) Technologies Based Smart Waste Collection Using Data Mining Approach and Ant Colony Optimization

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.


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[16] Yigit T. and Unsal O., “Using the Ant Colony Algorithm for Real-Time Automatic Route of School Buses,” The International Arab Journal of Information Technology, vol. 13, no. 5, pp. 559-565, 2016. Zeki Oralhan received his B.Eng., degree and Ph.D. degree in Electrical Electronics Engineering from Erciyes University, Kayseri, Turkey. He works as a lecturer and manager of an information technology company. His research interests includes: brain computer interface, artificial intelligence, data mining, signal processing, and smart technologies products. Burcu Oralhan received her B.Eng., and M.Eng. degree in Industrial Engineering from Erciyes University, Kayseri, Turkey. She received her Ph.D. degree in Business Administrative Department from Cumhuriyet University. Currently, she is an Assistant Professor Dr. in Nuh Naci Yazgan University, Kayseri, Turkey. Her research interests includes: Statistical analysis, artificial intelligence, operational research, and data mining. Yavuz Yiğit graduated from College of software programming from Ankara University, Çankırı, Turkey. He currently works as a computer engineer in Erciyes University Techno Park Area. His research interests includes: Software programming, artificial intelligence, and data mining.