A fuzzy rule-based and energy-efficient method for estimating the free size of parking places in smart cities by using wireless sensor networks

A fuzzy rule-based and energy-efficient method for estimating the free size of parking places in smart cities is proposed. In particular, the estimation is the output value of a fuzzy inference system (FIS) which was implemented on each wireless sensor mote (WSM) of a wireless sensor network (WSN) placed in the ground below the parking places and it was observed that it requires 8.9 Kbytes and 5 Kbytes of flash program memory and RAM respectively. Moreover, the fuzzy rules were formulated by using real numerical data obtained from the WSN. Next, the well known network simulator 2 (NS-2) was used for acquiring simulation results concerning the energy consumption of the battery of the WSMs. In order to model the error of the output value of the FIS and the energy consumption of the battery, a data fitting problem was solved and the cubic polynomial was fitted to the real and simulation data. As a result, a real-valued cost function was formed which was minimized to get the optimal values for the distance between the WSMs and the sampling period based on which the output of the FIS should be re-computed.