Cloud and IoT based Smart Car Parking System by using Mamdani Fuzzy Inference System (MFIS)

T. Alyas, Gulzar Ahmad, Yousaf Saeed, Muhammad Asif, Umer Farooq, Asma Kanwal
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引用次数: 2

Abstract

Internet of Things (IoT) and cloud computing technologies have connected the infrastructure of the city to make the context-aware and more intelligent city for utility its major resources. These technologies have much potential to solve thechallenges of urban areas around the globe to facilitate the citizens. A framework model that enables the integration of sensor’s data and analysis of the data in the context of smart parking is proposed. These technologies use sensors anddevices deployed around the city parking areas sending real time data through the edge computers to the main cloud servers. Mobil-Apps are developed that used real time data, set from servers of the parking facilities in the city. Fuzzification is shown to be a capable mathematical approach for modeling city parking issues. To solve the city parking problems in cities a detailed analysis of fuzzy logic proposed systems is developed. This paper presents the resultsachieved using Mamdani Fuzzy Inference System to model complex smart parking system. These results are verified using MATLAB simulation.
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基于Mamdani模糊推理系统(MFIS)的云和物联网智能停车系统
物联网(IoT)和云计算技术连接了城市的基础设施,使城市具有上下文感知和更智能,以利用其主要资源。这些技术有很大的潜力来解决全球城市地区的挑战,为市民提供便利。提出了一种在智能停车环境下实现传感器数据集成和数据分析的框架模型。这些技术使用部署在城市停车场周围的传感器和设备,通过边缘计算机向主云服务器发送实时数据。移动应用程序的开发使用了实时数据,这些数据来自城市停车设施的服务器。模糊化是模拟城市停车问题的一种有效的数学方法。为了解决城市停车问题,对模糊逻辑提出的系统进行了详细的分析。本文介绍了利用Mamdani模糊推理系统对复杂智能停车系统进行建模的结果。通过MATLAB仿真验证了上述结果。
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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