Top -- k Query Based Dynamic Scheduling for IoT-enabled Smart City Waste Collection

Smart Cities are being designed and built for comfortable human habitation. Among services that Smart Cities will offer is the environmentally-friendly waste/garbage collection and processing. In this paper, we motivate and propose an Internet of Things (IoT) enabled system architecture to achieve dynamic waste collection and delivery to processing plants or special garbage tips. In the past, waste collection was treated in a rather static manner using classical operations research approach. As proposed in this paper, nowadays, with the proliferation of sensors and actuators, as well as reliable and ubiquitous mobile communications, the Internet of Things (IoT) enables dynamic solutions aimed at optimizing the garbage truck fleet size, collection routes and prioritized waste pick-up. We propose a top -- k query based dynamic scheduling model to address the challenges of near real-time scheduling driven by sensor data streams. An Android app along with a user-friendly GUI is developed and presented in order to prove feasibility and evaluate a waste collection scenario using experimental data. Finally, the proposed models are evaluated on synthetic and real data from the city municipality of St. Petersburg, Russia. The models demonstrate consistency and correctness.