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The Concept of Big Data Management with Various Transportation Systems Sources as a Key Role in Smart Cities Development

Author

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  • Tomasz Dudek

    (Faculty of Engineering and Economics of Transport, Maritime University of Szczecin, Wały Chrobrego 1-2, 70-500 Szczecin, Poland)

  • Artur Kujawski

    (Faculty of Engineering and Economics of Transport, Maritime University of Szczecin, Wały Chrobrego 1-2, 70-500 Szczecin, Poland)

Abstract

An increasing number of devices and their communication with each other generates huge amounts of data. The efficiency of processing such large and heterogeneous data is crucial for extracting the reliable and consistent information that is needed for the effective management of smart cities within the field of transport. Data heterogeneity and volume as well as its integration and analytics are big challenges for decision-makers. The development of urban agglomerations is largely dependent on the proper management of such data. Therefore, this paper explores the role of these data repositories, their acquisition from different sources, and the ways to combine them. The main goal of this paper is to propose a concept of Smart City management based on Big Data Analytics and technology related to UAVs (Unmanned Aerial Vehicle) which may reduce costs and resource consumption. The presented concept includes successive data generation and collection, data type identification, problem and requirement identification, filtering, classification, pre-processing, and data optimization, as well as decision support analysis. A key part of this analysis utilizes computer algorithms, such as Speeded Up Robust Features (SURF) and Thresholding and Blob detection, to develop a multi-camera image recognition system for freight transport management and logistics in smart cities. The objective is to design a system that optimizes the route planning and time of vehicle passage on selected road sections, ultimately leading to the reduction of emissions. During the study, data obtained from multiple sources were compared, and the analysis uncovered different results for the same assumptions. We discuss the reasons for these variances. Overall, the results obtained in the analysis indicated that it is necessary to correct the predictions of the multi-camera image recognition system with additional methods and algorithms.

Suggested Citation

  • Tomasz Dudek & Artur Kujawski, 2022. "The Concept of Big Data Management with Various Transportation Systems Sources as a Key Role in Smart Cities Development," Energies, MDPI, vol. 15(24), pages 1-13, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9506-:d:1004008
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    References listed on IDEAS

    as
    1. Outay, Fatma & Mengash, Hanan Abdullah & Adnan, Muhammad, 2020. "Applications of unmanned aerial vehicle (UAV) in road safety, traffic and highway infrastructure management: Recent advances and challenges," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 116-129.
    2. Patrick Mikalef & Ilias O. Pappas & John Krogstie & Michail Giannakos, 2018. "Big data analytics capabilities: a systematic literature review and research agenda," Information Systems and e-Business Management, Springer, vol. 16(3), pages 547-578, August.
    3. Kinga Kijewska & João Guilherme Costa Braga França & Leise Kelli de Oliveira & Stanislaw Iwan, 2022. "Evaluation of Urban Mobility Problems and Freight Solutions from Residents’ Perspectives: A Comparison of Belo Horizonte (Brazil) and Szczecin (Poland)," Energies, MDPI, vol. 15(3), pages 1-22, January.
    4. Cezary Stępniak & Dorota Jelonek & Magdalena Wyrwicka & Iwona Chomiak-Orsa, 2021. "Integration of the Infrastructure of Systems Used in Smart Cities for the Planning of Transport and Communication Systems in Cities," Energies, MDPI, vol. 14(11), pages 1-19, May.
    5. repec:ipt:iptwpa:jrc47967 is not listed on IDEAS
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