Resource-constrained task assignment for event-driven sensing using public bicycles in smart cities. (2019) - Chang, Chiu-Ping; King, Chung-Ta
Many cities have provided public bicycle services to reduce traffic congestion and air pollution. Mobility of public bicycles makes them very suitable for event-driven sensing for smart cities, i.e., collecting data relevant to special events such as car accidents or street parades. The problem is how to assign a set of bicycles to best fulfil the sensing mission, considering the constrained storage, battery energy, and communication capability of bicycles. The problem is referred to as the resource-constrained task assignment for event-driven sensing (ReConTAES). The goal is to minimise the number of bicycles used, while balancing the energy consumption of the selected bicycles. We first formulate the problem as a mixed integer programming and then propose a set of greedy heuristics to solve the problem. We evaluate the proposed algorithms by using real trajectories to show their feasibility.