What is it about?

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.

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Why is it important?

Big data analysis, retrieval, and processing are very important from the perspective of smart cities. Storage and retrieval of large volumes of unstructured data, especially when responses are required in real-time, remains a significant challenge for researchers. Identify the research areas, challenges, and application of PDS in smart cities.


This article provides a comprehensive and detailed knowledge of the domain to the reader of all levels either beginners or someone looking for a research problem in a particular sub-domain. The most explored domains of smart cities attract the attention of both researchers and industry; which includes Energy, Healthcare, and Transportation.

Mandeep Kumar
Dr BR Ambedkar National Institute of Technology

Read the Original

This page is a summary of: Probabilistic data structures in smart city: Survey, applications, challenges, and research directions, Journal of Ambient Intelligence and Smart Environments, July 2022, IOS Press,
DOI: 10.3233/ais-220101.
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