Smart City Gnosys

Smart city article details

Title Strategies And Tools For Big Data Analytics In Smart City Environments: Algorithms And Data Types
ID_Doc 53139
Authors Rai A.; Kumar R.; Kumar N.; Fatima S.
Year 2025
Published Advances in Electronics, Computer, Physical and Chemical Sciences
DOI http://dx.doi.org/10.1201/9781003616252-74
Abstract Smart cities produce extensive data that can be analyzed using big data analytics to provide valuable insights for decision-making. This study assesses the current state of big data analytics in smart cities through a systematic literature review (SLR), examining the algorithms, data types, and tools employed. A synthesis of fifteen articles from reputable databases like IEEE Xplore, Scopus, ScienceDirect, and SpringerLink reveals that algorithms such as ANN, Markov, and graph mining require enhancements to manage the vast volume, variety, and velocity of data in smart cities effectively. Social media data emerges as a crucial data type for informed decision-making in this context. Among tools, Hadoop stands out for its robustness in storing and analyzing diverse data types, while Spark excels in processing large volumes of data at high speed. The proposed pseudocode offers a framework for implementing big data analytics in smart cities, aiding in addressing specific challenges and generating actionable insights for decision-makers. © 2024 selection and editorial matter, Dr. Saiyed Salim Sayeed, Prof. Hemant Kumar Sharma, Dr. Pramod Kumar Yadav, Dr. Brijesh Mishra; individual chapters, the contributors.
Author Keywords Big data; Hadoop; Prisma; smart city; systematic literature review


Similar Articles


Id Similarity Authors Title Published
50087 View0.916Soomro K.; Bhutta M.N.M.; Khan Z.; Tahir M.A.Smart City Big Data Analytics: An Advanced ReviewWiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9, 5 (2019)
35039 View0.909Karimi, Y; Kashani, MH; Akbari, M; Mahdipour, ELeveraging Big Data In Smart Cities: A Systematic ReviewCONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 33, 21 (2021)
17263 View0.907Kousis A.; Tjortjis C.Data Mining Algorithms For Smart Cities: A Bibliometric AnalysisAlgorithms, 14, 8 (2021)
3261 View0.904Osman, AMSA Novel Big Data Analytics Framework For Smart CitiesFUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 91 (2019)
12015 View0.902Singh Rathore S.P.; Vishnubhai Dalabhai C.; Babubhai Patel C.K.; Sharma R.; Mathur A.; Yadav A.Big Data Analytics For Smart CitiesProceedings - IEEE 2024 1st International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024 (2024)
35360 View0.9Gubareva R.; Lopes R.P.Literature Review On The Smart City Resources Analysis With Big Data MethodologiesSN Computer Science, 5, 1 (2024)
12034 View0.899El Alaoui I.; Gahi Y.; Messoussi R.; Todoskoff A.; Kobi A.Big Data Analytics: A Comparison Of Tools And ApplicationsLecture Notes in Networks and Systems, 37 (2018)
56704 View0.898Mirza N.M.; Ali A.; Ishak M.K.The Scheduling Techniques In The Hadoop And Spark Of Smart Cities Environment: A Systematic ReviewBulletin of Electrical Engineering and Informatics, 13, 1 (2024)
36039 View0.897Althabahi M.H.; Ahmad Jan M.; Brik B.; Foufou S.Machine Learning-Based Big Data Analytics In Smart Cities: A Survey Of Current Trends And Future Research DirectionsProceedings - 2024 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2024 (2024)
40173 View0.894Ulusar U.D.; Ozcan D.G.; Al-Turjman F.Open Source Tools For Machine Learning With Big Data In Smart CitiesEAI/Springer Innovations in Communication and Computing (2020)