IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i4p421-d93860.html
   My bibliography  Save this article

A Review of Smart Cities Based on the Internet of Things Concept

Author

Listed:
  • Saber Talari

    (C-MAST, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilhã, Portugal)

  • Miadreza Shafie-khah

    (C-MAST, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilhã, Portugal
    Department of Industrial Engineering, University of Salerno, 84084 Fisciano (SA), Italy)

  • Pierluigi Siano

    (Department of Industrial Engineering, University of Salerno, 84084 Fisciano (SA), Italy)

  • Vincenzo Loia

    (Department of Management & Innovation Systems, University of Salerno, 84084 Fisciano (SA), Italy)

  • Aurelio Tommasetti

    (Department of Management & Innovation Systems, University of Salerno, 84084 Fisciano (SA), Italy)

  • João P. S. Catalão

    (C-MAST, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilhã, Portugal
    INESC TEC and Faculty of Engineering of the University of Porto, R. Dr. Roberto Frias, 4200-465 Porto, Portugal
    INESC-ID, Instituto Superior Técnico, University of Lisbon, Av. Rovisco Pais, 1, 1049-001 Lisbon, Portugal)

Abstract

With the expansion of smart meters, like the Advanced Metering Infrastructure (AMI), and the Internet of Things (IoT), each smart city is equipped with various kinds of electronic devices. Therefore, equipment and technologies enable us to be smarter and make various aspects of smart cities more accessible and applicable. The goal of the current paper is to provide an inclusive review on the concept of the smart city besides their different applications, benefits, and advantages. In addition, most of the possible IoT technologies are introduced, and their capabilities to merge into and apply to the different parts of smart cities are discussed. The potential application of smart cities with respect to technology development in the future provides another valuable discussion in this paper. Meanwhile, some practical experiences all across the world and the key barriers to its implementation are thoroughly expressed.

Suggested Citation

  • Saber Talari & Miadreza Shafie-khah & Pierluigi Siano & Vincenzo Loia & Aurelio Tommasetti & João P. S. Catalão, 2017. "A Review of Smart Cities Based on the Internet of Things Concept," Energies, MDPI, vol. 10(4), pages 1-23, March.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:4:p:421-:d:93860
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/4/421/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/10/4/421/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shafie-khah, M. & Heydarian-Forushani, E. & Golshan, M.E.H. & Siano, P. & Moghaddam, M.P. & Sheikh-El-Eslami, M.K. & Catalão, J.P.S., 2016. "Optimal trading of plug-in electric vehicle aggregation agents in a market environment for sustainability," Applied Energy, Elsevier, vol. 162(C), pages 601-612.
    Full references (including those not matched with items on IDEAS)

    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. Homa Rashidizadeh-Kermani & Hamid Reza Najafi & Amjad Anvari-Moghaddam & Josep M. Guerrero, 2018. "Optimal Decision-Making Strategy of an Electric Vehicle Aggregator in Short-Term Electricity Markets," Energies, MDPI, vol. 11(9), pages 1-20, September.
    2. Xydas, Erotokritos & Marmaras, Charalampos & Cipcigan, Liana M., 2016. "A multi-agent based scheduling algorithm for adaptive electric vehicles charging," Applied Energy, Elsevier, vol. 177(C), pages 354-365.
    3. Heydarian-Forushani, E. & Golshan, M.E.H. & Shafie-khah, M., 2016. "Flexible interaction of plug-in electric vehicle parking lots for efficient wind integration," Applied Energy, Elsevier, vol. 179(C), pages 338-349.
    4. Mostafa Rezaeimozafar & Mohsen Eskandari & Mohammad Hadi Amini & Mohammad Hasan Moradi & Pierluigi Siano, 2020. "A Bi-Layer Multi-Objective Techno-Economical Optimization Model for Optimal Integration of Distributed Energy Resources into Smart/Micro Grids," Energies, MDPI, vol. 13(7), pages 1-25, April.
    5. Yu, Mengmeng & Lu, Renzhi & Hong, Seung Ho, 2016. "A real-time decision model for industrial load management in a smart grid," Applied Energy, Elsevier, vol. 183(C), pages 1488-1497.
    6. Bing Wang & Weiyang Liu & Min Wang & Wangping Shen, 2020. "Research on Bidding Mechanism for Power Grid with Electric Vehicles Based on Smart Contract Technology," Energies, MDPI, vol. 13(2), pages 1-17, January.
    7. DeForest, Nicholas & MacDonald, Jason S. & Black, Douglas R., 2018. "Day ahead optimization of an electric vehicle fleet providing ancillary services in the Los Angeles Air Force Base vehicle-to-grid demonstration," Applied Energy, Elsevier, vol. 210(C), pages 987-1001.
    8. Khaloie, Hooman & Abdollahi, Amir & Shafie-khah, Miadreza & Anvari-Moghaddam, Amjad & Nojavan, Sayyad & Siano, Pierluigi & Catalão, João P.S., 2020. "Coordinated wind-thermal-energy storage offering strategy in energy and spinning reserve markets using a multi-stage model," Applied Energy, Elsevier, vol. 259(C).
    9. Charilaos Latinopoulos & Aruna Sivakumar & John W. Polak, 2021. "Optimal Pricing of Vehicle-to-Grid Services Using Disaggregate Demand Models," Energies, MDPI, vol. 14(4), pages 1-27, February.
    10. Hajibandeh, Neda & Shafie-khah, Miadreza & Osório, Gerardo J. & Aghaei, Jamshid & Catalão, João P.S., 2018. "A heuristic multi-objective multi-criteria demand response planning in a system with high penetration of wind power generators," Applied Energy, Elsevier, vol. 212(C), pages 721-732.
    11. Aghajani, Saemeh & Kalantar, Mohsen, 2017. "Operational scheduling of electric vehicles parking lot integrated with renewable generation based on bilevel programming approach," Energy, Elsevier, vol. 139(C), pages 422-432.
    12. Shuang Gao & Jianzhong Wu & Bin Xu, 2019. "Controllability Evaluation of EV Charging Infrastructure Transformed from Gas Stations in Distribution Networks with Renewables," Energies, MDPI, vol. 12(8), pages 1-20, April.
    13. Tang, Yanyan & Zhang, Qi & Wen, Zongguo & Bunn, Derek & Martin, Jesus Nieto, 2022. "Optimal analysis for facility configuration and energy management on electric light commercial vehicle charging," Energy, Elsevier, vol. 246(C).
    14. Subramanian, Vignesh & Das, Tapas K., 2019. "A two-layer model for dynamic pricing of electricity and optimal charging of electric vehicles under price spikes," Energy, Elsevier, vol. 167(C), pages 1266-1277.
    15. Morteza Nazari-Heris & Mehdi Abapour & Behnam Mohammadi-Ivatloo, 2022. "An Updated Review and Outlook on Electric Vehicle Aggregators in Electric Energy Networks," Sustainability, MDPI, vol. 14(23), pages 1-24, November.
    16. Reihani, Ehsan & Motalleb, Mahdi & Thornton, Matsu & Ghorbani, Reza, 2016. "A novel approach using flexible scheduling and aggregation to optimize demand response in the developing interactive grid market architecture," Applied Energy, Elsevier, vol. 183(C), pages 445-455.
    17. Einolander, Johannes & Lahdelma, Risto, 2022. "Explicit demand response potential in electric vehicle charging networks: Event-based simulation based on the multivariate copula procedure," Energy, Elsevier, vol. 256(C).
    18. Perez-Diaz, Alvaro & Gerding, Enrico & McGroarty, Frank, 2018. "Coordination and payment mechanisms for electric vehicle aggregators," Applied Energy, Elsevier, vol. 212(C), pages 185-195.
    19. Will, Christian & Zimmermann, Florian & Ensslen, Axel & Fraunholz, Christoph & Jochem, Patrick & Keles, Dogan, 2023. "Can electric vehicle charging be carbon neutral? Uniting smart charging and renewables," Working Paper Series in Production and Energy 69, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    20. Vinicius Braga Ferreira da Costa & Gabriel Nasser Doyle de Doile & Gustavo Troiano & Bruno Henriques Dias & Benedito Donizeti Bonatto & Tiago Soares & Walmir de Freitas Filho, 2022. "Electricity Markets in the Context of Distributed Energy Resources and Demand Response Programs: Main Developments and Challenges Based on a Systematic Literature Review," Energies, MDPI, vol. 15(20), pages 1-43, October.

    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:10:y:2017:i:4:p:421-:d:93860. 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.