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

Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA) Pub Date : 2014-09-01 DOI:10.1109/ETFA.2014.7005174

Ioakeim K. Samaras, A. Arvanitopoulos, N. Evangeliou, J. Gialelis, S. Koubias

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引用次数: 11

Abstract

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.

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基于模糊规则和节能的无线传感器网络智能城市空闲停车位估算方法

提出了一种基于模糊规则的智能城市空闲停车位面积估算方法。特别是，对放置在停车场下方地面的无线传感器网络(WSN)的每个无线传感器点(WSM)上实现的模糊推理系统(FIS)的输出值进行了估计，观察到该系统分别需要8.9 kb和5kb的闪存和RAM。利用从无线传感器网络中获得的实际数值数据，建立了模糊规则。其次，利用网络模拟器2 (NS-2)获取WSMs电池能耗的仿真结果。为了模拟FIS输出值和电池能耗的误差，解决了数据拟合问题，对实际数据和仿真数据进行了三次多项式拟合。因此，形成了一个实值代价函数，并将其最小化以获得WSMs与采样周期之间距离的最优值，并以此为基础重新计算FIS的输出。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA)

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