Neutrosophic Framework for Assessment Challenges in Smart Sustainable Cities based on IoT to Better Manage Energy Resources and Decrease the Urban Environment's Ecological Impact

Samah Ibrahim Abdel, Aal
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引用次数: 1

Abstract

Sustainable smart cities based on the Internet of Things (IoT) technology provide promising prospects for improving quality of life. However, in order to facilitate the widespread implementation of IoT-based smart city solutions, there is a need to concern about data privacy and security, standardization, interoperability, scalability, and sustainability. Reducing the environmental effect of urban activities, optimizing the management of energy resources, and designing novel services and solutions for inhabitants are all examples of how the smart city concept is inextricably linked to sustainability. There is a need to assess challenges in smart sustainable cities based on IoT. This paper intended to introduce a new neutrosophic framework for assessment challenges in smart sustainable cities based on IoT for better-managing energy resources and decreasing the urban environment's ecological impact. The proposed framework used nine criteria and five alternatives. Also, the proposed framework applied the neutrosophic Weighted Product Method (WPM) to compute the weights of criteria and rank challenges. Moreover, the proposed framework integrated the single-valued neutrosophic set to deal with uncertain data. The results indicated that the proposed framework can handle uncertain data and give more effective results in assessing challenges in smart sustainable cities based on IoT to better manage energy resources and decrease the urban environment's ecological impact.
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基于物联网的可持续智慧城市挑战评估中性框架,以更好地管理能源和减少城市环境的生态影响
基于物联网(IoT)技术的可持续智慧城市为提高生活质量提供了广阔的前景。然而,为了促进基于物联网的智慧城市解决方案的广泛实施,需要关注数据隐私和安全、标准化、互操作性、可扩展性和可持续性。减少城市活动对环境的影响,优化能源管理,为居民设计新颖的服务和解决方案,这些都是智慧城市概念与可持续发展密不可分的例子。有必要评估基于物联网的智能可持续城市的挑战。本文旨在介绍一个新的中性框架,用于评估基于物联网的智能可持续城市面临的挑战,以更好地管理能源资源,减少城市环境的生态影响。拟议的框架使用了9个标准和5个备选方案。此外,该框架还应用了中性加权积法(WPM)来计算标准的权重并对挑战进行排序。此外,该框架还集成了单值嗜中性集来处理不确定数据。结果表明,该框架可以处理不确定数据,并为基于物联网的智慧可持续城市的挑战评估提供更有效的结果,以更好地管理能源资源,减少城市环境的生态影响。
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