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Probabilistic data structures in smart city: Survey, applications, challenges, and research directions
Journal of Ambient Intelligence and Smart Environments ( IF 1.8 ) Pub Date : 2022-07-25 , DOI: 10.3233/ais-220101
Mandeep Kumar 1 , Amritpal Singh 1
Affiliation  

Abstract

With the commencement of new technologies like IoT and the Cloud, the sources of data generation have increased exponentially. The use and processing of this generated data have motivated and given birth to many other domains. The concept of a smart city has also evolved from making use of this data in decision-making in the various aspects of daily life and also improvement in the traditional systems. In smart cities, various technologies work collaboratively; they include devices used for data collection, processing, storing, retrieval, analysis, and decision making. Big data storage, retrieval, and analysis play a vital role in smart city applications. Traditional data processing approaches face many challenges when dealing with such voluminous and high-speed generated data, such as semi-structured or unstructured data, data privacy, security, real-time responses, and so on. Probabilistic Data Structures (PDS) has been evolved as a potential solution for many applications in smart cities to complete this tedious task of handling big data with real-time response. PDS has been used in many smart city domains, including healthcare, transportation, the environment, energy, and industry. The goal of this paper is to provide a comprehensive review of PDS and its applications in the domains of smart cities. The prominent domain of the smart city has been explored in detail; origin, current research status, challenges, and existing application of PDS along with research gaps and future directions. The foremost aim of this paper is to provide a detailed survey of PDS in smart cities; for readers and researchers who want to explore this field; along with the research opportunities in the domains.



中文翻译:

智慧城市中的概率数据结构:调查、应用、挑战和研究方向

摘要

随着物联网和云等新技术的出现,数据生成的来源呈指数级增长。这些生成的数据的使用和处理激发并催生了许多其他领域。智慧城市的概念也从利用这些数据在日常生活的各个方面进行决策以及对传统系统的改进演变而来。在智慧城市中,各种技术协同工作;它们包括用于数据收集、处理、存储、检索、分析和决策制定的设备。大数据存储、检索和分析在智慧城市应用中发挥着至关重要的作用。传统的数据处理方法在处理海量、高速生成的数据时面临诸多挑战,例如半结构化或非结构化数据、数据隐私、安全、实时响应等等。概率数据结构 (PDS) 已发展成为智慧城市中许多应用程序的潜在解决方案,以完成处理大数据这一繁琐任务并进行实时响应。PDS 已用于许多智慧城市领域,包括医疗保健、交通、环境、能源和工业。本文的目的是全面回顾 PDS 及其在智慧城市领域的应用。对智慧城市的突出领域进行了详细探索;PDS 的起源、当前研究现状、挑战和现有应用以及研究差距和未来方向。本文的首要目的是对智慧城市中的 PDS 进行详细调查;对于想要探索该领域的读者和研究人员;以及该领域的研究机会。

更新日期:2022-07-27
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