IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i23p8174-d695962.html
   My bibliography  Save this article

Fog Computing Approach for Shared Mobility in Smart Cities

Author

Listed:
  • Raafat Aburukba

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates)

  • A. R. Al-Ali

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates)

  • Ahmed H. Riaz

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates)

  • Ahmad Al Nabulsi

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates)

  • Danayal Khan

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates)

  • Shavaiz Khan

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates)

  • Moustafa Amer

    (Department of Computer Science and Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates)

Abstract

Smart transportation a smart city application where traditional individual models are transforming to shared and distributed ownership. These models are used to serve commuters for inter- and intra-city travel. However, short-range urban transportation services within campuses, residential compounds, and public parks are not explored to their full capacity compared to the distributed vehicle model. This paper aims to explore and design an adequate framework for battery-operated shared mobility within a large community for short-range travel. This work identifies the characteristics of the shared mobility for battery-operated vehicles and accordingly proposes an adequate solution that deals with real-time data collection, tracking, and automated decisions. Furthermore, given the requirement for real-time decisions with low latency for critical requests, the paper deploys the proposed framework within the 3-tier computing model, namely edge, fog, and cloud tiers. The solution design considers the power consumption requirement at the edge by offloading the computational requests to the fog tier and utilizing the LoRaWAN communication technology. A prototype implementation is presented to validate the proposed framework for a university campus using e-bikes. The results show the scalability of the proposed design and the achievement of low latency for requests that require real-time decisions.

Suggested Citation

  • Raafat Aburukba & A. R. Al-Ali & Ahmed H. Riaz & Ahmad Al Nabulsi & Danayal Khan & Shavaiz Khan & Moustafa Amer, 2021. "Fog Computing Approach for Shared Mobility in Smart Cities," Energies, MDPI, vol. 14(23), pages 1-19, December.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:8174-:d:695962
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/23/8174/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/23/8174/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Böcker, Lars & Anderson, Ellinor & Uteng, Tanu Priya & Throndsen, Torstein, 2020. "Bike sharing use in conjunction to public transport: Exploring spatiotemporal, age and gender dimensions in Oslo, Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 389-401.
    2. Li, Haojie & Zhang, Yingheng & Ding, Hongliang & Ren, Gang, 2019. "Effects of dockless bike-sharing systems on the usage of the London Cycle Hire," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 398-411.
    3. Sun, Lishan & Wang, Shunchao & Liu, Shuli & Yao, Liya & Luo, Wei & Shukla, Ashish, 2018. "A completive research on the feasibility and adaptation of shared transportation in mega-cities – A case study in Beijing," Applied Energy, Elsevier, vol. 230(C), pages 1014-1033.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fatema Elwy & Raafat Aburukba & A. R. Al-Ali & Ahmad Al Nabulsi & Alaa Tarek & Ameen Ayub & Mariam Elsayeh, 2023. "Data-Driven Safe Deliveries: The Synergy of IoT and Machine Learning in Shared Mobility," Future Internet, MDPI, vol. 15(10), pages 1-18, October.
    2. Monika Wawer & Kalina Grzesiuk & Dorota Jegorow, 2022. "Smart Mobility in a Smart City in the Context of Generation Z Sustainability, Use of ICT, and Participation," Energies, MDPI, vol. 15(13), pages 1-30, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cheng, Long & Huang, Jie & Jin, Tanhua & Chen, Wendong & Li, Aoyong & Witlox, Frank, 2023. "Comparison of station-based and free-floating bikeshare systems as feeder modes to the metro," Journal of Transport Geography, Elsevier, vol. 107(C).
    2. Kim, Kyoungok, 2023. "Investigation of modal integration of bike-sharing and public transit in Seoul for the holders of 365-day passes," Journal of Transport Geography, Elsevier, vol. 106(C).
    3. Liu, Yixiao & Tian, Zihao & Pan, Baoran & Zhang, Wenbin & Liu, Yunqi & Tian, Lixin, 2022. "A hybrid big-data-based and tolerance-based method to estimate environmental benefits of electric bike sharing," Applied Energy, Elsevier, vol. 315(C).
    4. Hu, Yujie & Zhang, Yongping & Lamb, David & Zhang, Mingming & Jia, Peng, 2019. "Examining and optimizing the BCycle bike-sharing system – A pilot study in Colorado, US," Applied Energy, Elsevier, vol. 247(C), pages 1-12.
    5. Ding, Hongliang & Lu, Yuhuan & Sze, N.N. & Li, Haojie, 2022. "Effect of dockless bike-sharing scheme on the demand for London Cycle Hire at the disaggregate level using a deep learning approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 150-163.
    6. Yong Lei & Jun Zhang & Zhihua Ren, 2023. "A Study on Bicycle-Sharing Dispatching Station Site Selection and Planning Based on Multivariate Data," Sustainability, MDPI, vol. 15(17), pages 1-25, August.
    7. Ma, Xinwei & Ji, Yanjie & Yuan, Yufei & Van Oort, Niels & Jin, Yuchuan & Hoogendoorn, Serge, 2020. "A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 148-173.
    8. Sebastian Rühmann & Stephan Leible & Tom Lewandowski, 2024. "Interpretable Bike-Sharing Activity Prediction with a Temporal Fusion Transformer to Unveil Influential Factors: A Case Study in Hamburg, Germany," Sustainability, MDPI, vol. 16(8), pages 1-32, April.
    9. Ma, Xinwei & Zhang, Shuai & Wu, Tao & Yang, Yizhe & Yu, Jiajie, 2023. "Can dockless and docked bike-sharing substitute each other? Evidence from Nanjing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    10. Lovelace, Robin & Beecham, Roger & Heinen, Eva & Vidal Tortosa, Eugeni & Yang, Yuanxuan & Slade, Chris & Roberts, Antonia, 2020. "Is the London Cycle Hire Scheme becoming more inclusive? An evaluation of the shifting spatial distribution of uptake based on 70 million trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 1-15.
    11. Shang, Wen-Long & Chen, Jinyu & Bi, Huibo & Sui, Yi & Chen, Yanyan & Yu, Haitao, 2021. "Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis," Applied Energy, Elsevier, vol. 285(C).
    12. Yang, Hongtai & Huo, Jinghai & Bao, Yongxing & Li, Xuan & Yang, Linchuan & Cherry, Christopher R., 2021. "Impact of e-scooter sharing on bike sharing in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 23-36.
    13. Hua, Mingzhuang & Chen, Xuewu & Chen, Jingxu & Huang, Di & Cheng, Long, 2022. "Large-scale dockless bike sharing repositioning considering future usage and workload balance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    14. Böcker, Lars & Anderson, Ellinor, 2020. "Interest-adoption discrepancies, mechanisms of mediation and socio-spatial inclusiveness in bike-sharing: The case of nine urban regions in Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 266-277.
    15. Shahram Heydari & Garyfallos Konstantinoudis & Abdul Wahid Behsoodi, 2021. "Effect of the COVID-19 pandemic on bike-sharing demand and hire time: Evidence from Santander Cycles in London," Papers 2107.11589, arXiv.org.
    16. Carlos J. Rodríguez-Rad & María-Ángeles Revilla-Camacho & María-Elena Sánchez-del-Río-Vázquez, 2023. "Exploring the Intention to Adopt Sustainable Mobility Modes of Transport among Young University Students," IJERPH, MDPI, vol. 20(4), pages 1-16, February.
    17. Suzanne Maas & Paraskevas Nikolaou & Maria Attard & Loukas Dimitriou, 2021. "Heat, Hills and the High Season: A Model-Based Comparative Analysis of Spatio-Temporal Factors Affecting Shared Bicycle Use in Three Southern European Islands," Sustainability, MDPI, vol. 13(6), pages 1-21, March.
    18. Adu-Gyamfi, Gibbson & Song, Huaming & Obuobi, Bright & Nketiah, Emmanuel & Wang, Hong & Cudjoe, Dan, 2022. "Who will adopt? Investigating the adoption intention for battery swap technology for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    19. Tu, Wei & Santi, Paolo & Zhao, Tianhong & He, Xiaoyi & Li, Qingquan & Dong, Lei & Wallington, Timothy J. & Ratti, Carlo, 2019. "Acceptability, energy consumption, and costs of electric vehicle for ride-hailing drivers in Beijing," Applied Energy, Elsevier, vol. 250(C), pages 147-160.
    20. Chang, Ximing & Wu, Jianjun & Sun, Huijun & Correia, Gonçalo Homem de Almeida & Chen, Jianhua, 2021. "Relocating operational and damaged bikes in free-floating systems: A data-driven modeling framework for level of service enhancement," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 235-260.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:8174-:d:695962. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.