Skip to main content

Advertisement

Log in

A Contemporary Survey on IoT Based Smart Cities: Architecture, Applications, and Open Issues

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Internet of Things (IoT) is one of the emerging technologies, which is widely used across the globe. As the idea of a smart city was founded, IoT has been acknowledged as the key foundation in smart city paradigms. Technology makes a person smart, and to make the world smart, we have to make the country smart. To make the country smart, we have to make cities smart and to make smart cities, we have to be smart. In short, to create a smart environment, one must be equipped and familiar with the current trends. The integration of various smart devices and systems facilitates IoT for a smart city. The interdependent and interwoven nature of smart cities puts notable legislative, socioeconomic, and technical challenges for integrators, organizations, and designers committed to administrating these novel entities. The goal of this paper is to illustrate a contemporary survey of IoT-based smart cities with their potential, current trends and developments, amenity architecture, application area, real-world involvement, and open challenges. In addition, key elements with potential implementation constraints and integration of various IoT-based application areas that play a key role in building a smarter city have also been discussed. This extensive study contributes a useful panorama on various key points and gives a critical direction for forthcoming investigations. This study will also provide a reference point for practitioners and academics in the near future.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Rathore, M. M., Ahmad, A., Paul, A., & Rho, S. (2016). Urban planning and building smart cities based on the internet of things using big data analytics. Computer Networks, 101, 63–80.

    Article  Google Scholar 

  2. Zhu, C., Leung, V. C., Shu, L., & Ngai, E. C. H. (2015). Green internet of things for smart world. IEEE Access, 3, 2151–2162.

    Article  Google Scholar 

  3. Atzori, L., Iera, A., & Morabito, G. (2011). Siot: Giving a social structure to the internet of things. IEEE Communications Letters, 15(11), 1193–1195.

    Article  Google Scholar 

  4. Bi, Z., Da, X. L., & Wang, C. (2014). Internet of things for enterprise systems of modern manufacturing. IEEE Transactions on Industrial Informatics, 10(2), 1537–1546.

    Article  Google Scholar 

  5. Ketu, S., & Mishra, P. K. (2021). Internet of Healthcare Things: A contemporary survey. Journal of Network and Computer Applications, 192, 103179.

    Article  Google Scholar 

  6. Botta, A., De Donato, W., Persico, V., & Pescapé, A. (2016). Integration of cloud computing and internet of things: A survey. Future Generation Computer Systems, 56, 684–700.

    Article  Google Scholar 

  7. Jaradat, M., Jarrah, M., Bousselham, A., Jararweh, Y., & Al-Ayyoub, M. (2015). The internet of energy: Smart sensor networks and big data management for smart grid. Procedia Computer Science, 56, 592–597.

    Article  Google Scholar 

  8. Srivastava, A., & Mishra, P. K. (2019). State-of-the-art prototypes and future propensity stem on internet of things. International Journal of Recent Technology and Engineering (IJRTE), 8(4), 2672–2683.

    Article  Google Scholar 

  9. Kyriazis, D., Varvarigou, T., White, D., Rossi, A. and Cooper, J. (2013). Sustainable smart city IoT applications: Heat and electricity management & Eco-conscious cruise control for public transportation. In 2013 IEEE 14th International Symposium on" A World of Wireless, Mobile and Multimedia Networks"(WoWMoM) (pp. 1–5). IEEE.

  10. Abosaq, N. H. (2019). Impact of privacy issues on smart city services in a model smart city. International Journal of Advanced Computer Science and Applications, 10(2), 177–185.

    Article  Google Scholar 

  11. Picon, A. (2019). Smart cities, privacy and the pulverisation/reconstruction of individuals. Eur. Data Prot. L. Rev., 5, 154.

    Article  Google Scholar 

  12. de Amorim, W. S., Deggau, A. B., do Livramento Gonçalves, G., da Silva Neiva, S., Prasath, A. R., & de Andrade, J. B. S. O. (2019). Urban challenges and opportunities to promote sustainable food security through smart cities and the 4th industrial revolution. Land Use Policy, 87, 104065.

  13. Awad, A. I., Furnell, S., Hassan, A. M., & Tryfonas, T. (2019). Special issue on security of IoT-enabled infrastructures in smart cities. Ad hoc networks, 92, 101850.

    Article  Google Scholar 

  14. Jameel, T., Ali, R., & Ali, S. (2019). Security in modern smart cities: An information technology perspective. In 2019 2nd International Conference on Communication, Computing and Digital systems (C-CODE) (pp. 293–298). IEEE.

  15. Vitunskaite, M., He, Y., Brandstetter, T., & Janicke, H. (2019). Smart cities and cyber security: Are we there yet? A comparative study on the role of standards, third party risk management and security ownership. Computers & Security, 83, 313–331.

    Article  Google Scholar 

  16. Evans, L. (2018). The privacy parenthesis: Private and public spheres, smart cities and big data. In Creating Smart Cities (pp. 194–204). Routledge.

  17. Ainane, N., Ouzzif, M., & Bouragba, K. (2018). Data security of smart cities. In Proceedings of the 3rd International Conference on Smart City Applications (pp. 1–13).

  18. Bernardes, M. B., de Andrade, F. P., & Novais, P. (2018). Smart Cities, data and right to privacy: a look from the Portuguese and Brazilian experience. In Proceedings of the 11th International Conference on Theory and Practice of Electronic Governance (pp. 328–337).

  19. Alandjani, G. (2018). Features and potential security challenges for IoT enabled devices in smart city environment. International Journal of Advanced Computer Science and Applications, 9(8), 231–238.

    Article  Google Scholar 

  20. Chatterjee, S., Kar, A. K., & Gupta, M. P. (2017). Critical success factors to establish 5G network in smart cities: Inputs for security and privacy. Journal of Global Information Management (JGIM), 25(2), 15–37.

    Article  Google Scholar 

  21. Hiller, J. S., & Blanke, J. M. (2016). Smart cities, big data, and the resilience of privacy. Hastings LJ, 68, 309.

    Google Scholar 

  22. de Fuentes, J. M., González-Manzano, L., Serna-Olvera, J., & Veseli, F. (2017). Assessment of attribute-based credentials for privacy-preserving road traffic services in smart cities. Personal and Ubiquitous Computing, 21(5), 869–891.

    Article  Google Scholar 

  23. Liu, J. K., Choo, K. K. R., Huang, X., & Au, M. H. (2017). Special issue on security and privacy for smart cities. Personal and Ubiquitous Computing, 21(5), 775–775.

    Article  Google Scholar 

  24. Liao, W., Luo, C., Salinas, S., & Li, P. (2017). Efficient secure outsourcing of large-scale convex separable programming for big data. IEEE Transactions on Big Data, 5(3), 368–378.

    Article  Google Scholar 

  25. Ismagilova, E., Hughes, L., Rana, N. P., & Dwivedi, Y. K. (2020). Security, privacy and risks within smart cities: Literature Review and development of a smart city interaction framework. Information Systems Frontiers, 1–22.

  26. Baryshev, G. K., Tutnov, I. A., & Karasevich, A. M. (2016). The prospect and risks of using gas-combined cycle heating in the domestic sector of smart cities. In Proceedings of the International Conference on Electronic Governance and Open Society: Challenges in Eurasia (pp. 4–8).

  27. Waedt, K., Ciriello, A., Parekh, M., & Bajramovic, E. (2016). Automatic assets identification for smart cities: Prerequisites for cybersecurity risk assessments. In 2016 IEEE International Smart Cities Conference (ISC2) (pp. 1–6). IEEE.

  28. Efthymiopoulos, M. P. (2016). Cyber-security in smart cities: The case of Dubai. Journal of Innovation and Entrepreneurship, 5(1), 11.

    Article  Google Scholar 

  29. Li, H., Zhu, H., & Jun, B. (2015). Guest editorial: Security and privacy of P2P networks in emerging smart city. Peer-to-Peer Networking and Applications, 8(6), 1023.

    Article  MathSciNet  Google Scholar 

  30. Zhu, Y., & Zuo, J. (2015). Research on security construction of smart city. International Journal of Smart Home, 9(8), 197–204.

    Article  Google Scholar 

  31. Elmaghraby, A. S., & Losavio, M. M. (2014). Cyber security challenges in smart cities: Safety, security and privacy. Journal of Advanced Research, 5(4), 491–497.

    Article  Google Scholar 

  32. Khan, Z., Pervez, Z., & Ghafoor, A. (2014). Towards cloud based smart cities data security and privacy management. In 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing (pp. 806–811). IEEE.

  33. Ferraz, F. S., & Ferraz, C. A. G. (2014). More than meets the eye in smart city information security: Exploring security issues far beyond privacy concerns. In 2014 IEEE 11th Intl Conf on Ubiquitous Intelligence and Computing and 2014 IEEE 11th Intl Conf on Autonomic and Trusted Computing and 2014 IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (pp. 677–685). IEEE.

  34. Pérez-Martínez, P. A., Martínez-Ballesté, A., & Solanas, A. (2013). Privacy in Smart Cities-A Case Study of Smart Public Parking. In PECCS (pp. 55–59).

  35. Li, W., Chao, J., & Ping, Z. (2012). Security structure study of city management platform based on cloud computing under the conception of smart city. In 2012 Fourth International Conference on Multimedia Information Networking and Security (pp. 91–94). IEEE.

  36. Moustaka, V., Theodosiou, Z., Vakali, A., Kounoudes, A., & Anthopoulos, L. G. (2019). Εnhancing social networking in smart cities: Privacy and security borderlines. Technological Forecasting and Social Change, 142, 285–300.

    Article  Google Scholar 

  37. Noh, J. H., & Kwon, H. Y. (2019). A study on smart city security policy based on blockchain in 5G age. In 2019 International Conference on Platform Technology and Service (PlatCon) (pp. 1–4). IEEE.

  38. Mora, O. B., Rivera, R., Larios, V. M., Beltrán-Ramírez, J. R., Maciel, R., & Ochoa, A. (2018). A use case in cybersecurity based in Blockchain to deal with the security and privacy of citizens and Smart Cities Cyberinfrastructures. In 2018 IEEE International Smart Cities Conference (ISC2) (pp. 1–4). IEEE.

  39. Ramos, L. F. M., & Silva, J. M. C. (2019). Privacy and data protection concerns regarding the use of blockchains in smart cities. In Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance (pp. 342–347).

  40. Alromaihi, S., Elmedany, W., & Balakrishna, C. (2018). Cyber security challenges of deploying IoT in smart cities for healthcare applications. In 2018 6th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW) (pp. 140–145). IEEE.

  41. de Fuentes, J. M., Gonzalez-Manzano, L., Solanas, A., & Veseli, F. (2018). Attribute-based credentials for privacy-aware smart health services in iot-based smart cities. Computer, 51(7), 44–53.

    Article  Google Scholar 

  42. Huang, Q., Wang, L., & Yang, Y. (2017). Secure and privacy-preserving data sharing and collaboration in mobile healthcare social networks of smart cities. Security and Communication Networks, 2017.

  43. Alamaniotis, M., Tsoukalas, L. H., & Buckner, M. (2016). Privacy-driven electricity group demand response in smart cities using particle swarm optimization. In 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 946–953). IEEE.

  44. Sanduleac, M., Eremia, M., Toma, L., Alacreu, L., Pons, L., Cresta, M., & Paulucci, M. (2016). Energy ecosystem in smart cities—Privacy and security solutions for citizen's engagement in a multi-stream environment. In 2016 IEEE International Smart Cities Conference (ISC2) (pp. 1–4). IEEE.

  45. Karasevich, A. M., Tutnov, I. A., & Baryshev, G. K. (2016). The prospects of application of information technologies and the principles of intelligent automated systems to manage the security status of objects of energy supply of smart cities. In Proceedings of the International Conference on Electronic Governance and Open Society: Challenges in Eurasia (pp. 9–14).

  46. Chatterjee, S., & Kar, A. K. (2018). Effects of successful adoption of information technology enabled services in proposed smart cities of India. Journal of Science and Technology Policy Management.

  47. Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Dwivedi, Y., & Weerakkody, V. (2017). Assessing consumers’ intention to adopt mobile internet services in the Kingdom of Saudi Arabia.

  48. Van Zoonen, L. (2016). Privacy concerns in smart cities. Government Information Quarterly, 33(3), 472–480.

    Article  Google Scholar 

  49. van Heek, J., Aming, K., & Ziefle, M. (2016). How fear of crime affects needs for privacy & safety: Acceptance of surveillance technologies in smart cities. In 2016 5th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS) (pp. 1–12). IEEE.

  50. Cilliers, L., & Flowerday, S. (2015). The relationship between privacy, information security and the trustworthiness of a crowdsourcing system in a smart city. In HAISA (pp. 243–255).

  51. Belanche-Gracia, D., Casaló-Ariño, L. V., & Pérez-Rueda, A. (2015). Determinants of multi-service smartcard success for smart cities development: A study based on citizens’ privacy and security perceptions. Government Information Quarterly, 32(2), 154–163.

    Article  Google Scholar 

  52. Cilliers, L., & Flowerday, S. (2014). Information security in a public safety, participatory crowdsourcing smart city project. In World Congress on Internet Security (WorldCIS-2014) (pp. 36–41). IEEE.

  53. Slade, E. L., Williams, M. D., & Dwivedi, Y. (2013). Extending UTAUT2 to explore consumer adoption of mobile payments. UKAIS, 36.

  54. Rana, N. P., Luthra, S., Mangla, S. K., Islam, R., Roderick, S., & Dwivedi, Y. K. (2019). Barriers to the development of smart cities in Indian context. Information Systems Frontiers, 21(3), 503–525.

    Article  Google Scholar 

  55. Yang, F., & Xu, J. (2018). Privacy concerns in China’s smart city campaign: The deficit of China’s Cybersecurity Law. Asia & the Pacific Policy Studies, 5(3), 533–543.

    Article  Google Scholar 

  56. Velásquez, W., Munoz-Arcentales, A., Yanez, W., & Salvachúa, J. (2018). Resilient smart cities: An approach of damaged cities by natural risks. In 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 591–597). IEEE.

  57. Habibzadeh, H., Soyata, T., Kantarci, B., Boukerche, A., & Kaptan, C. (2018). Sensing, communication and security planes: A new challenge for a smart city system design. Computer Networks, 144, 163–200.

    Article  Google Scholar 

  58. Rosadi, S. D., & Kristyan, S. A. (2017). Privacy challenges in the application of smart city in Indonesia. In 2017 International Conference on Information Technology Systems and Innovation (ICITSI) (pp. 405–409). IEEE.

  59. Baig, Z. A., Szewczyk, P., Valli, C., Rabadia, P., Hannay, P., Chernyshev, M., & Syed, N. (2017). Future challenges for smart cities: Cyber-security and digital forensics. Digital Investigation, 22, 3–13.

    Article  Google Scholar 

  60. AlDairi, A. (2017). Cyber security attacks on smart cities and associated mobile technologies. Procedia Computer Science, 109, 1086–1091.

    Article  Google Scholar 

  61. Vattapparamban, E., Güvenç, İ., Yurekli, A. İ., Akkaya, K., & Uluağaç, S. (2016). Drones for smart cities: Issues in cybersecurity, privacy, and public safety. In 2016 International Wireless Communications and Mobile Computing Conference (IWCMC) (pp. 216–221). IEEE.

  62. Dhungana, D., Engelbrecht, G., Parreira, J. X., Schuster, A., & Valerio, D. (2015). Aspern smart ICT: Data analytics and privacy challenges in a smart city. In 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT) (pp. 447–452). IEEE.

  63. Ferraz, F. S., & Ferraz, C. A. G. (2014). Smart city security issues: depicting information security issues in the role of an urban environment. In 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing (pp. 842–847). IEEE.

  64. Galdon-Clavell, G. (2013). (Not so) smart cities?: The drivers, impact and risks of surveillance-enabled smart environments. Science and Public Policy, 40(6), 717–723.

    Article  Google Scholar 

  65. Techatassanasoontorn, A. A., & Suo, S. (2010). Exploring risks in smart city infrastructure projects: Municipal broadband initiatives. In PACIS (p. 82).

  66. Kitchin, R., & Dodge, M. (2019). The (in) security of smart cities: Vulnerabilities, risks, mitigation, and prevention. Journal of Urban Technology, 26(2), 47–65.

    Article  Google Scholar 

  67. Li, J., Zhang, W., Dabra, V., Choo, K. K. R., Kumari, S., & Hogrefe, D. (2019). AEP-PPA: An anonymous, efficient and provably-secure privacy-preserving authentication protocol for mobile services in smart cities. Journal of Network and Computer Applications, 134, 52–61.

    Article  Google Scholar 

  68. Abi Sen, A. A., Eassa, F. A., & Jambi, K. (2017). Preserving privacy of smart cities based on the fog computing. In International Conference on Smart Cities, Infrastructure, Technologies and Applications (pp. 185–191). Springer, Cham.

  69. Gheisari, M., Wang, G., Khan, W. Z., & Fernández-Campusano, C. (2019). A context-aware privacy-preserving method for IoT-based smart city using software defined networking. Computers & Security, 87, 101470.

    Article  Google Scholar 

  70. Huerta, J., & Salazar, P. (2018). Audit process framework for data protection and privacy compliance using artificial intelligence and cognitive services in smart cities. In 2018 IEEE International Smart Cities Conference (ISC2) (pp. 1–7). IEEE.

  71. Han, J., Li, Y., & Chen, W. (2019). A lightweight and privacy-preserving public cloud auditing scheme without bilinear pairings in smart cities. Computer Standards & Interfaces, 62, 84–97.

    Article  Google Scholar 

  72. Krichen, M., & Alroobaea, R. (2019). A new model-based framework for testing security of iot systems in smart cities using attack trees and price timed automata. 570–577.

  73. Khedr, A. M., Osamy, W., Salim, A., & Salem, A. (2019). Privacy preserving data mining approach for IoT based WSN in smart city. International Journal of Advanced Computer Science and Applications, 10(8), 555–563.

    Article  Google Scholar 

  74. Roldan, L. R., Trujillo, A. E., Miyatake, M. N., & Chano, J. (2019). Color watermarking based on DCT and YCbCr color space for privacy preservation in smart cities. In Proceedings of the 2019 3rd International Conference on Digital Signal Processing (pp. 119–123).

  75. Peters, F., Hanvey, S., Veluru, S., Mady, A. E. D., Boubekeur, M., & Nuseibeh, B. (2018). Generating privacy zones in smart cities. In 2018 IEEE International Smart Cities Conference (ISC2) (pp. 1–8). IEEE.

  76. ten Berg, K., Spil, T. A., & Effing, R. (2019). The privacy paradox of utilizing the internet of things and Wi-Fi tracking in smart cities. In International Working Conference on Transfer and Diffusion of IT (pp. 364–381). Springer.

  77. Xie, J., Tang, H., Huang, T., Yu, F. R., Xie, R., Liu, J., & Liu, Y. (2019). A survey of blockchain technology applied to smart cities: Research issues and challenges. IEEE Communications Surveys & Tutorials, 21(3), 2794–2830.

    Article  Google Scholar 

  78. Yilei, C., & Leyou, Z. (2019). Privacy preserving ciphertext-policy attribute-based broadcast encryption in smart city. The Journal of China Universities of Posts and Telecommunications, 1, 4.

    Google Scholar 

  79. Al-Dhubhani, R., Mehmood, R., Katib, I., & Algarni, A. (2017). Location privacy in smart cities era. In International Conference on Smart Cities, Infrastructure, Technologies and Applications (pp. 123–138). Springer.

  80. Gope, P., Amin, R., Islam, S. H., Kumar, N., & Bhalla, V. K. (2018). Lightweight and privacy-preserving RFID authentication scheme for distributed IoT infrastructure with secure localization services for smart city environment. Future Generation Computer Systems, 83, 629–637.

    Article  Google Scholar 

  81. Krichen, M., Cheikhrouhou, O., Lahami, M., Alroobaea, R., & Maâlej, A. J. (2017). Towards a model-based testing framework for the security of internet of things for smart city applications. In International Conference on Smart Cities, Infrastructure, Technologies and Applications (pp. 360–365). Springer, Cham.

  82. Stromire, G., & Potoczny-Jones, I. (2018). Empowering smart cities with strong cryptography for data privacy. In Proceedings of the 1st ACM/EIGSCC Symposium on Smart Cities and Communities (pp. 1–7).

  83. Sucasas, V., Mantas, G., Althunibat, S., Oliveira, L., Antonopoulos, A., Otung, I., & Rodriguez, J. (2018). A privacy-enhanced OAuth 2.0 based protocol for Smart City mobile applications. Computers & Security, 74, 258–274.

    Article  Google Scholar 

  84. Wibowo, S. (2018, October). Enriching digital government readiness indicators of RKCI assessment with advance https assessment method to promote cyber security awareness among smart cities in Indonesia. In 2018 International Conference on ICT for Smart Society (ICISS) (pp. 1–4). IEEE.

  85. Witti, M., & Konstantas, D. (2018). A secure and privacy-preserving Internet of Things framework for smart city. In Proceedings of the 6th International Conference on Information Technology: IoT and Smart City (pp. 145–150).

  86. Antonopoulos, K., Petropoulos, C., Antonopoulos, C. P., & Voros, N. S. (2017). Security data management process and its impact on smart cities' wireless sensor networks. In 2017 South Eastern European Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM) (pp. 1–8). IEEE.

  87. Beltran, V., Martinez, J. A., & Skarmeta, A. F. (2017). User-centric access control for efficient security in smart cities. In 2017 Global Internet of Things Summit (GIoTS) (pp. 1–6). IEEE.

  88. García, C. G., Meana-Llorián, D., G-Bustelo, B. C. P., Lovelle, J. M. C., & Garcia-Fernandez, N. (2017). Midgar: Detection of people through computer vision in the Internet of Things scenarios to improve the security in Smart Cities, Smart Towns, and Smart Homes. Future Generation Computer Systems, 76, 301–313.

    Article  Google Scholar 

  89. Ferdowsi, A., Saad, W., Maham, B., & Mandayam, N. B. (2017). A Colonel Blotto game for interdependence-aware cyber-physical systems security in smart cities. In Proceedings of the 2nd International Workshop on Science of Smart City Operations and Platforms Engineering (pp. 7–12).

  90. Lai, J., Mu, Y., Guo, F., Susilo, W., & Chen, R. (2017). Fully privacy-preserving and revocable ID-based broadcast encryption for data access control in smart city. Personal and Ubiquitous Computing, 21(5), 855–868.

    Article  Google Scholar 

  91. Guo, J., Ma, J., Li, X., Zhang, J., & Zhang, T. (2017). An attribute-based trust negotiation protocol for D2D communication in smart city balancing trust and privacy. Journal of Information Science and Engineering, 33(4), 1007–1023.

    MathSciNet  Google Scholar 

  92. Luo, X., Ren, Y., Hu, J., Wu, Q., & Lou, J. (2017). Privacy-preserving identity-based file sharing in smart city. Personal and Ubiquitous Computing, 21(5), 923–936.

    Article  Google Scholar 

  93. Song, W. T., Hu, B., & Zhao, X. F. (2017). Optimizing LWE-based FHE for better security and privacy protection of smart city. Journal of Information Science & Engineering, 33(4).

  94. Shen, J., Liu, D., Liu, Q., He, D., & Sun, X. (2017). An Enhanced Cloud Data Storage Auditing Protocol Providing Strong Security and Efficiency for Smart City. Journal of Information Science & Engineering, 33(4).

  95. Zang, L., Yu, Y., Xue, L., Li, Y., Ding, Y., & Tao, X. (2017). Improved dynamic remote data auditing protocol for smart city security. Personal and Ubiquitous Computing, 21(5), 911–921.

    Article  Google Scholar 

  96. Xiao, J., Wang, Z., Chen, Y., Liao, L., Xiao, J., Zhan, G., & Hu, R. (2017). A sensitive object‐oriented approach to big surveillance data compression for social security applications in smart cities. Software: Practice and Experience, 47(8), 1061–1080.

  97. Avgerou, A., Nastou, P. E., Nastouli, D., Pardalos, P. M., & Stamatiou, Y. C. (2016). On the deployment of citizens’ privacy preserving collective intelligent eBusiness models in smart cities. International Journal of Security and Its Applications, 10(2), 171–184.

    Article  Google Scholar 

  98. Lepinski, M., Levin, D., McCarthy, D., Watro, R., Lack, M., Hallenbeck, D., & Slater, D. (2016). Privacy-enhanced android for smart cities applications. In Smart City 360° (pp. 66–77). Springer.

  99. Sucasas, V., Mantas, G., Radwan, A., & Rodriguez, J. (2016). An OAuth2-based protocol with strong user privacy preservation for smart city mobile e-Health apps. In 2016 IEEE International Conference on Communications (ICC) (pp. 1–6). IEEE.

  100. Mazhelis, O., Hämäläinen, A., Asp, T., & Tyrväinen, P. (2016). Towards enabling privacy preserving smart city apps. In 2016 IEEE International Smart Cities Conference (ISC2) (pp. 1–7). IEEE.

  101. Patsakis, C., Laird, P., Clear, M., Bouroche, M., & Solanas, A. (2015). Interoperable privacy-aware e-participation within smart cities. Computer, 48(1), 52–58.

    Article  Google Scholar 

  102. Cagliero, L., Cerquitelli, T., Chiusano, S., Garino, P., Nardone, M., Pralio, B., & Venturini, L. (2015). Monitoring the citizens' perception on urban security in Smart City environments. In 2015 31st IEEE International Conference on Data Engineering Workshops (pp. 112–116). IEEE.

  103. Burange, A. W., & Misalkar, H. D. (2015). Review of Internet of Things in development of smart cities with data management & privacy. In 2015 International Conference on Advances in Computer Engineering and Applications (pp. 189–195). IEEE.

  104. Sen, M., Dutt, A., Agarwal, S., & Nath, A. (2013). Issues of privacy and security in the role of software in smart cities. In 2013 International Conference on Communication Systems and Network Technologies (pp. 518–523). IEEE.

  105. Strategic Opportunity Analysis of the Global Smart City Market. Available online: http://www.egr.msu.edu/~aesc310-web/resources/SmartCities/Smart%20City%20Market%20Report%202.pdf (accessed on 15 July 2019).

  106. Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660.

    Article  Google Scholar 

  107. Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: A survey. Computer networks, 54(15), 2787–2805.

    Article  MATH  Google Scholar 

  108. Internet of Things in 2020: Roadmap for the Future. Available online: http://www.smart-systemsintegration.org/public/documents/publications/Internet-of-Things_in_2020_EC-EPoSS_Workshop_Report_2008_v3.pdf (accessed on 15 July 2019).

  109. Six Technologies with Potential Impacts on US Interests Out to 2025. Available online: https://fas.org/irp/nic/disruptive.pdf (accessed on 15 July 2019).

  110. Alamri, A., Ansari, W. S., Hassan, M. M., Hossain, M. S., Alelaiwi, A., & Hossain, M. A. (2013). A survey on sensor-cloud: architecture, applications, and approaches. International Journal of Distributed Sensor Networks, 9(2), 917923.

    Article  Google Scholar 

  111. Kosmatos, E. A., Tselikas, N. D., & Boucouvalas, A. C. (2011). Integrating RFIDs and smart objects into a unifiedinternet of things architecture. Advances in Internet of Things, 1(01), 5.

    Article  Google Scholar 

  112. Rawat, P., Singh, K. D., Chaouchi, H., & Bonnin, J. M. (2014). Wireless sensor networks: A survey on recent developments and potential synergies. The Journal of supercomputing, 68(1), 1–48.

    Article  Google Scholar 

  113. Zanella, A., Bui, N., Castellani, A., Vangelista, L., & Zorzi, M. (2014). Internet of things for smart cities. IEEE Internet of Things journal, 1(1), 22–32.

    Article  Google Scholar 

  114. Medagliani, P., Leguay, J., Duda, A., Rousseau, F., Duquennoy, S., Raza, S., Ferrari, G., Gonizzi, P., Cirani, S., Veltri, L. & Monton, M., (2014). Internet of things applications-from research and innovation to market deployment.

  115. Elmangoush, A., Alhazmi, A., Magedanz, T., Schuch, W., Estevez, C., Ehijo, A., Wu, J., Nguyen, T., Ventura, N., Mwangama, J. & Mukudu, N. (2015). October. towards unified smart city communication platforms. In Proceedings of the Workshop on Research in Information Systems and Technologies, Chillán, Chile (Vol. 16).

  116. IEEE-SA—IEEE Get 802 Program—802.15: Wireless PANs. Available online: https://standards.ieee.org/about/get/802/802.15.html (accessed on 15 July 2019).

  117. Shafie-khah, M., Heydarian-Forushani, E., Osório, G. J., Gil, F. A., Aghaei, J., Barani, M., & Catalão, J. P. (2015). Optimal behavior of electric vehicle parking lots as demand response aggregation agents. IEEE Transactions on Smart Grid, 7(6), 2654–2665.

    Article  Google Scholar 

  118. Li, X., Lu, R., Liang, X., Shen, X., Chen, J., & Lin, X. (2011). Smart community: An internet of things application. IEEE Communications Magazine, 49(11), 68–75.

    Article  Google Scholar 

  119. Stratigea, A. (2012). The concept of ‘smart cities’. Towards community development?. Netcom. Réseaux, Communication et Territoires, (26–3/4), pp. 375–388.

  120. Neyestani, N., Damavandi, M.Y., Shafie-khah, M. & Catalão, J.P. (2015). Modeling the PEV traffic pattern in an urban environment with parking lots and charging stations. In 2015 IEEE Eindhoven PowerTech (pp. 1–6). IEEE.

  121. Yazdani-Damavandi, M., Moghaddam, M. P., Haghifam, M. R., Shafie-khah, M., & Catalão, J. P. (2015). Modeling operational behavior of plug-in electric vehicles’ parking lot in multienergy systems. IEEE Transactions on Smart Grid, 7(1), 124–135.

    Article  Google Scholar 

  122. Neyestani, N., Damavandi, M. Y., Shafie-Khah, M., Contreras, J., & Catalão, J. P. (2014). Allocation of plug-in vehicles’ parking lots in distribution systems considering network-constrained objectives. IEEE Transactions on Power Systems, 30(5), 2643–2656.

    Article  Google Scholar 

  123. Lee, S., Yoon, D. & Ghosh, A. (2008). Intelligent parking lot application using wireless sensor networks. In CTS (pp. 48–57).

  124. Niyato, D., Hossain, E., & Camorlinga, S. (2009). Remote patient monitoring service using heterogeneous wireless access networks: Architecture and optimization. IEEE Journal on Selected Areas in Communications, 27(4), 412–423.

    Article  Google Scholar 

  125. The Urban Internet of Things. Available online: http://datasmart.ash.harvard.edu/news/article/the-urbaninternet-of-things-727 (accessed on 15 July 2019).

  126. 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, 162, 601–612.

    Article  Google Scholar 

  127. Li, X., Shu, W., Li, M., Huang, H. Y., Luo, P. E., & Wu, M. Y. (2008). Performance evaluation of vehicle-based mobile sensor networks for traffic monitoring. IEEE Transactions on Vehicular Technology, 58(4), 1647–1653.

    Google Scholar 

  128. Maisonneuve, N., Stevens, M., Niessen, M.E., Hanappe, P. & Steels, L., (2009) Citizen noise pollution monitoring. In Proceedings of the 10th Annual International Conference on Digital Government Research: Social Networks: Making Connections between Citizens, Data and Government (pp. 96–103). Digital Government Society of North America.

  129. Wang, J. T., Chen, D. B., Chen, H. Y., & Yang, J. Y. (2012). On pedestrian detection and tracking in infrared videos. Pattern Recognition Letters, 33(6), 775–785.

    Article  Google Scholar 

  130. Damen, D., & Hogg, D. (2011). Detecting carried objects from sequences of walking pedestrians. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(6), 1056–1067.

    Article  Google Scholar 

  131. Calavia, L., Baladrón, C., Aguiar, J. M., Carro, B., & Sánchez-Esguevillas, A. (2012). A semantic autonomous video surveillance system for dense camera networks in smart cities. Sensors, 12(8), 10407–10429.

    Article  Google Scholar 

  132. Leadership in Enabling and Industrial Technologies—Horizon 2020—European Commission. Available online: http://programmes/horizon2020/en/h2020-section/leadership-enabling-and-industrial technologies (accessed on 15 July 2019).

  133. Ballon, P., Glidden, J., Kranas, P., Menychtas, A., Ruston, S. &Van Der Graaf, S. (2011). Is there a need for a cloud platform for european smart cities. In eChallenges e-2011 Conference Proceedings, IIMC International Information Management Corporation (pp. 1–7).

  134. Suciu, G., Vulpe, A., Halunga, S., Fratu, O., Todoran, G. & Suciu, V. (2013). May. Smart cities built on resilient cloud computing and secure internet of things. In 2013 19th International Conference on Control Systems and Computer Science (pp. 513–518). IEEE.

  135. Ketu, S. & Mishra, P.K. (2021). Cloud, Fog and Mist Computing in IoT: An Indication of Emerging Opportunities. IETE Technical Review, pp. 1–12.

  136. Petrolo, R., Mitton, N., Soldatos, J., Hauswirth, M. & Schiele, G. (2014). Integrating wireless sensor networks within a city cloud. In 2014 Eleventh Annual IEEE International Conference on Sensing, Communication, and Networking Workshops (SECON Workshops) (pp. 24–27). IEEE.

  137. Chen, S.Y., Lai, C.F., Huang, Y.M. & Jeng, Y.L. (2013). Intelligent home-appliance recognition over IoT cloud network. In 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC) (pp. 639–643). IEEE.

  138. Han, D. M., & Lim, J. H. (2010). Smart home energy management system using IEEE 802.15.4 and zigbee. IEEE Transactions on Consumer Electronics, 56(3), 1403–1410.

    Article  Google Scholar 

  139. Ye, X. & Huang, J. (2011). A framework for cloud-based smart home. In Proceedings of 2011 International Conference on Computer Science and Network Technology (Vol. 2, pp. 894–897). IEEE.

  140. Martirano, L. (2011). A smart lighting control to save energy. In Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems (Vol. 1, pp. 132–138). IEEE.

  141. Castro, M., Jara, A.J. & Skarmeta, A.F. (2013). Smart lighting solutions for smart cities. In 2013 27th International Conference on Advanced Information Networking and Applications Workshops (pp. 1374–1379). IEEE.

  142. Siano, P., & Sarno, D. (2016). Assessing the benefits of residential demand response in a real time distribution energy market. Applied Energy, 161, 533–551.

    Article  Google Scholar 

  143. Siano, P. (2014). Demand response and smart grids—A survey. Renewable and sustainable energy reviews, 30, 461–478.

    Article  Google Scholar 

  144. Graditi, G., Ippolito, M. G., Lamedica, R., Piccolo, A., Ruvio, A., Santini, E., Siano, P., & Zizzo, G. (2015). Innovative control logics for a rational utilization of electric loads and air-conditioning systems in a residential building. Energy and Buildings, 102, 1–17.

    Article  Google Scholar 

  145. Siano, P., Graditi, G., Atrigna, M., & Piccolo, A. (2013). Designing and testing decision support and energy management systems for smart homes. Journal of Ambient Intelligence and Humanized Computing, 4(6), 651–661.

    Article  Google Scholar 

  146. Strategic Plan for the IEA Demand-Side Management Programme 2008–2012. Available online: http://www.ieadsm.org/wp/files/Exco%20File%20Library/Participation/Final%20strategy%202008-2012.pdf (accessed on 15 July 2019).

  147. Arasteh, H. R., Moghaddam, M. P., Sheikh-El-Eslami, M. K., & Abdollahi, A. (2013). Integrating commercial demand response resources with unit commitment. International Journal of Electrical Power & Energy Systems, 51, 153–161.

    Article  Google Scholar 

  148. Balijepalli, V.M., Pradhan, V., Khaparde, S.A. & Shereef, R.M. (2011). Review of demand response under smart grid paradigm. In ISGT2011-India (pp. 236–243). IEEE.

  149. Koutsopoulos, I. & Tassiulas, L. (2011). Control and optimization meet the smart power grid: Scheduling of power demands for optimal energy management. In Proceedings of the 2nd International Conference on Energy-efficient Computing and Networking (pp. 41–50). ACM.

  150. Parvania, M., & Fotuhi-Firuzabad, M. (2010). Demand response scheduling by stochastic SCUC. IEEE Transactions on Smart Grid, 1(1), 89–98.

    Article  Google Scholar 

  151. Electricity Technology Roadmap: Meeting the Critical Challenges of the 21st Century Roadmap2003.Available online: http://mydocs.epri.com/docs/CorporateDocuments/StrategicVision/Roadmap2003.pdf (accessed on 15 July 2019).

  152. Arritt, R. F., & Dugan, R. C. (2011). Distribution system analysis and the future smart grid. IEEE Transactions on Industry Applications, 47(6), 2343–2350.

    Article  Google Scholar 

  153. Jaradat, M., Jarrah, M., Jararweh, Y., Al-Ayyoub, M. & Bousselham, A. (2014). Integration of renewable energy in demand-side management for home appliances. In 2014 International Renewable and Sustainable Energy Conference (IRSEC) (pp. 571–576). IEEE.

  154. Ketu, S. & Mishra, P.K. (2021). Scalable kernel-based SVM classification algorithm on imbalance air quality data for proficient healthcare. Complex & Intelligent Systems, pp. 1–19.

  155. Ketu, S. & Mishra, P.K. (2021). Empirical analysis of machine learning algorithms on imbalance electrocardiogram based arrhythmia dataset for heart disease detection. Arabian Journal for Science and Engineering, pp. 1–23.

  156. Ketu, S. & Mishra, P.K. (2021). Hybrid classification model for eye state detection using electroencephalogram signals. Cognitive Neurodynamics, pp. 1–18.

  157. Ketu, S., & Mishra, P. K. (2021). Enhanced Gaussian process regression-based forecasting model for COVID-19 outbreak and significance of IoT for its detection. Applied Intelligence, 51(3), 1492–1512.

    Article  Google Scholar 

  158. Ketu, S., & Mishra, P. K. (2020). A hybrid deep learning model for COVID-19 prediction and current status of clinical trials worldwide. Computers, Materials. Continua, 66(2), 1896–1919.

    Article  Google Scholar 

  159. Srivastava, A., & Mishra, P. K. (2021). A survey on WSN issues with its heuristics and meta-heuristics solutions. Wireless Personal Communications, 121(1), 745–814.

    Article  Google Scholar 

  160. Ketu, S. & Mishra, P.K., (2020). Performance Analysis of Machine Learning Algorithms for IoT-Based Human Activity Recognition. In Advances in Electrical and Computer Technologies (pp. 579–591). Springer, Singapore.

  161. Ketu, S., & Mishra, P. K. (2022). India perspective: CNN-LSTM hybrid deep learning model-based COVID-19 prediction and current status of medical resource availability. Soft Computing, 26(2), 645–664.

    Article  Google Scholar 

  162. Zhu, Z., Tang, J., Lambotharan, S., Chin, W.H. & Fan, Z. (2012). An integer linear programming based optimization for home demand-side management in smart grid. In 2012 IEEE PES Innovative Smart Grid Technologies (ISGT) (pp. 1–5). IEEE.

  163. Nguyen, H.K., Song, J.B. and Han, Z. (2012). Demand side management to reduce peak-to-average ratio using game theory in smart grid. In 2012 Proceedings IEEE INFOCOM Workshops (pp. 91–96). IEEE.

  164. Saber, A. Y., & Venayagamoorthy, G. K. (2010). Plug-in vehicles and renewable energy sources for cost and emission reductions. IEEE Transactions on Industrial Electronics, 58(4), 1229–1238.

    Article  Google Scholar 

  165. Zhabelova, G., & Vyatkin, V. (2011). Multiagent smart grid automation architecture based on IEC 61850/61499 intelligent logical nodes. IEEE Transactions on Industrial Electronics, 59(5), 2351–2362.

    Article  Google Scholar 

  166. Yun, M. and Yuxin, B. (2010). Research on the architecture and key technology of internet of things (IoT) applied on smart grid. In 2010 International Conference on Advances in Energy Engineering (pp. 69–72). IEEE.

  167. Gross, P. N., Huang, B., Ierome, S., Isaac, D. F., & Kressner, A. (2012). Machine learning for the New York City power grid. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(2), 328–345.

    Article  Google Scholar 

  168. Krishnan, S., & Balasubramanian, T. (2016). Traffic flow optimization and vehicle safety in smart cities. Traffic, 5(5).

  169. Ouerhani, N., Pazos, N., Aeberli, M., Senn, J., & Gobron, S. (2015). Dynamic street light management–towards a citizen centered approach. In Proceedings of the 3rd International Conference on Hybrid City, Athens, Greece (pp. 17–19).

  170. Parvez, I., Sarwat, A. I., Wei, L., & Sundararajan, A. (2016). Securing metering infrastructure of smart grid: A machine learning and localization based key management approach. Energies, 9(9), 691.

    Article  Google Scholar 

  171. Ertugrul, Ö. F., & Kaya, Y. (2016). Smart city planning by estimating energy efficiency of buildings by extreme learning machine. In 2016 4th International Istanbul Smart Grid Congress and Fair (ICSG) (pp. 1–5). IEEE.

  172. Garcia-Font, V., Garrigues, C., & Rifà-Pous, H. (2016). A comparative study of anomaly detection techniques for smart city wireless sensor networks. Sensors, 16(6), 868.

    Article  Google Scholar 

  173. Valerio, L., Passarella, A., & Conti, M. (2016). Hypothesis transfer learning for efficient data computing in smart cities environments. In 2016 IEEE International Conference on Smart Computing (SMARTCOMP) (pp. 1–8). IEEE.

  174. Fleury, A., Vacher, M., & Noury, N. (2009). SVM-based multimodal classification of activities of daily living in health smart homes: Sensors, algorithms, and first experimental results. IEEE Transactions on Information Technology in Biomedicine, 14(2), 274–283.

    Article  Google Scholar 

  175. Longstaff, B., Reddy, S., & Estrin, D. (2010). Improving activity classification for health applications on mobile devices using active and semi-supervised learning. In 2010 4th International Conference on Pervasive Computing Technologies for Healthcare (pp. 1–7). IEEE.

  176. He, X., Huang, T., Li, C., Che, H., & Dong, Z. (2015). A recurrent neural network for optimal real-time price in smart grid. Neurocomputing, 149, 608–612.

    Article  Google Scholar 

  177. Dedinec, A., Filiposka, S., Dedinec, A., & Kocarev, L. (2016). Deep belief network based electricity load forecasting: An analysis of Macedonian case. Energy, 115, 1688–1700.

    Article  Google Scholar 

  178. Tian, Y., & Pan, L. (2015). Predicting short-term traffic flow by long short-term memory recurrent neural network. In 2015 IEEE international conference on smart city/SocialCom/SustainCom (SmartCity) (pp. 153–158). IEEE.

  179. Aryal, J., & Dutta, R. (2015). Smart city and geospatiality: Hobart deeply learned. In 2015 31st IEEE International Conference on Data Engineering Workshops (pp. 108–109). IEEE.

  180. Liang, V. C., Ma, R. T., Ng, W. S., Wang, L., Winslett, M., Wu, H., & Zhang, Z. (2016). Mercury: Metro density prediction with recurrent neural network on streaming CDR data. In 2016 IEEE 32nd International Conference on Data Engineering (ICDE) (pp. 1374–1377). IEEE.

  181. Niu, X., Zhu, Y., Cao, Q., Zhang, X., Xie, W., & Zheng, K. (2015). An online-traffic-prediction based route finding mechanism for smart city. International Journal of Distributed Sensor Networks, 11(8), 970256.

    Article  Google Scholar 

  182. Fang, H., & Hu, C. (2014). Recognizing human activity in smart home using deep learning algorithm. In Proceedings of the 33rd Chinese Control Conference (pp. 4716–4720). IEEE.

  183. Google, “Prediction api,” (Accessed on July 2020). [Online]. Available: https://cloud.google.com/prediction/

  184. Ferrucci, D., Brown, E., Chu-Carroll, J., Fan, J., Gondek, D., Kalyanpur, A. A., & Schlaefer, N. (2010). Building watson: An overview of the DeepQA project. AI magazine, 31(3), 59–79.

    Article  Google Scholar 

  185. Amazon, “Amazon machine learning,” (Accessed on July 2020). [Online]. Available: https://aws.amazon.com/machinelearning/

  186. BigML, “BigML API documentation,” (Accessed on July 2020). [Online]. Available: https://bigml.com/api

  187. Microsoft, “Introduction to machine learning in the cloud,” (Accessed on July 2020). [Online]. Available: https://docs.microsoft.com/en-us/azure/machinelearning/

  188. Amsterdam Smart City. Available online: https://amsterdamsmartcity.com/ (accessed on 15 July 2019).

  189. Lee, J.H. and Hancock, M., (2012). Toward a framework for smart cities: A comparison of Seoul, San Francisco and Amsterdam. Research Paper, Yonsei University and Stanford University.

  190. Smart City | Servei de Premsa | El Web de la Ciutat de Barcelona. Available online: http://ajuntament.barcelona.cat/premsa/tag/smart-city/ (accessed on 15 July 2019).

  191. Bakıcı, T., Almirall, E., & Wareham, J. (2013). A smart city initiative: The case of Barcelona. Journal of the Knowledge Economy, 4(2), 135–148.

    Article  Google Scholar 

  192. Lee, J., & Miller, H. J. (2018). Measuring the impacts of new public transit services on space-time accessibility: An analysis of transit system redesign and new bus rapid transit in Columbus, Ohio, USA. Applied Geography, 93, 47–63.

    Article  Google Scholar 

  193. Wood, E.W., Rames, C.L., Muratori, M., Srinivasa Raghavan, S. and Young, S.E. (2018). Charging electric vehicles in smart cities: An EVI-Pro analysis of columbus, ohio (No. NREL/TP-5400–70367). National Renewable Energy Lab.(NREL), Golden, CO (United States).

  194. Pellicer, S., Santa, G., Bleda, A.L., Maestre, R., Jara, A.J. and Skarmeta, A.G. (2013). A global perspective of smart cities: A survey. In 2013 Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (pp. 439–444). IEEE.

  195. DeMaio, P. J. (2003). Smart bikes: Public transportation for the 21st century. Transportation Quarterly, 57(1), 9–11.

    Google Scholar 

  196. Mohammed, F., Idries, A., Mohamed, N., Al-Jaroodi, J. and Jawhar, I. (2014). Opportunities and challenges of using UAVs for dubai smart city. In 2014 6th International Conference on New Technologies, Mobility and Security (NTMS) (pp. 1–4). IEEE.

  197. Kaur, M.J. and Maheshwari, P. (2016). Building smart cities applications using IoT and cloud-based architectures. In 2016 International Conference on Industrial Informatics and Computer Systems (CIICS) (pp. 1–5). IEEE.

  198. Lécué, F., Tallevi-Diotallevi, S., Hayes, J., Tucker, R., Bicer, V., Sbodio, M., & Tommasi, P. (2014). Smart traffic analytics in the semantic web with STAR-CITY: Scenarios, system and lessons learned in Dublin City. Web Semantics: Science, Services and Agents on the World Wide Web, 27, 26–33.

    Article  Google Scholar 

  199. Cardullo, P., & Kitchin, R. (2019). Being a ‘citizen’in the smart city: Up and down the scaffold of smart citizen participation in Dublin Ireland. GeoJournal, 84(1), 1–13.

    Article  Google Scholar 

  200. Tei, K. and Gürgen, L. (2014). ClouT: Cloud of things for empowering the citizen clout in smart cities. In 2014 IEEE World Forum on Internet of Things (WF-IoT) (pp. 369–370). IEEE.

  201. Yonezawa, T., Matranga, I., Galache, J.A., Maeomichi, H., Gurgen, L. & Shibuya, T. (2015). A citizen-centric approach towards global-scale smart city platform. In 2015 International Conference on Recent Advances in Internet of Things (RIoT) (pp. 1–6). IEEE.

  202. Stern, P. C. (2000). New environmental theories: Toward a coherent theory of environmentally significant behavior. Journal of Social Issues, 56(3), 407–424.

    Article  Google Scholar 

  203. Armağan, V. (2018). Dijital Dönüşüm Sürecinde Akıllı Şehirler ve E-Devlet Platformu. Journal of Communication Theory & Research/Iletisim Kuram ve Arastirma Dergisi, (46).

  204. Mah, D. N. Y., van der Vleuten, J. M., Hills, P., & Tao, J. (2012). Consumer perceptions of smart grid development: Results of a Hong Kong survey and policy implications. Energy Policy, 49, 204–216.

    Article  Google Scholar 

  205. Low, S. M. (Ed.). (1999). Theorizing the city: the new urban anthropology reader. Rutgers University Press.

    Google Scholar 

  206. Galperina, L. P., Girenko, A. T., & Mazurenko, V. P. (2016). The concept of smart economy as the basis for sustainable development of Ukraine. International Journal of Economics and Financial Issues, 6(8S), 307–314.

    Google Scholar 

  207. Boreiko, O. & Teslyuk, V. (2016). Developing a controller for registering passenger flow of public transport for the smart city system. Bocтoчнo-Eвpoпeйcкий жypнaл пepeдoвыx тexнoлoгий, 6(3), 40–46.

  208. Hernández-Muñoz, J.M., Vercher, J.B., Muñoz, L., Galache, J.A., Presser, M., Gómez, L.A.H. and Pettersson, J. (2011). Smart cities at the forefront of the future internet. In The future internet assembly (pp. 447–462). Springer, Berlin, Heidelberg.

  209. Monzon, A. (2015). Smart cities concept and challenges: Bases for the assessment of smart city projects. In 2015 International Conference on Smart Cities and Green ICT Systems (SMARTGREENS) (pp. 1–11). IEEE.

  210. Washburn, D., Sindhu, U., Balaouras, S., Dines, R. A., Hayes, N., & Nelson, L. E. (2009). Helping CIOs understand “smart city” initiatives. Growth, 17(2), 1–17.

    Google Scholar 

  211. Angelidou, M. (2014). Smart city policies: A spatial approach. Cities, 41, S3–S11.

    Article  Google Scholar 

  212. Paskaleva, K. A. (2009). Enabling the smart city: The progress of city e-governance in Europe. International Journal of Innovation and Regional Development, 1(4), 405–422.

    Article  Google Scholar 

  213. Komninos, N., Pallot, M., & Schaffers, H. (2013). Special issue on smart cities and the future internet in Europe. Journal of the Knowledge Economy, 4(2), 119–134.

    Article  Google Scholar 

  214. Morandi, C., Rolando, A., & Di Vita, S. (2016). From smart city to smart region: Digital services for an Internet of Places. Berlin: Springer International Publishing.

    Book  Google Scholar 

  215. Deakin, M. (Ed.). (2013). Smart cities: governing, modelling and analysing the transition. Routledge.

    Google Scholar 

  216. Mehmood, Y., Ahmad, F., Yaqoob, I., Adnane, A., Imran, M., & Guizani, S. (2017). Internet-of-things-based smart cities: Recent advances and challenges. IEEE Communications Magazine, 55(9), 16–24.

    Article  Google Scholar 

  217. Cowley, R., Joss, S., & Dayot, Y. (2018). The smart city and its publics: Insights from across six UK cities. Urban Research & Practice, 11(1), 53–77.

    Article  Google Scholar 

  218. Strickland, E. (2011). Cisco bets on South Korean smart city. IEEE Spectrum, 48(8), 11–12.

    Article  Google Scholar 

  219. Chourabi, H., Nam, T., Walker, S., Gil-Garcia, J.R., Mellouli, S., Nahon, K., Pardo, T.A. & Scholl, H.J. (2012). Understanding smart cities: An integrative framework. In 2012 45th Hawaii International Conference on System Sciences (pp. 2289–2297). IEEE.

  220. Hall, R.E., Bowerman, B., Braverman, J., Taylor, J., Todosow, H. & Von Wimmersperg, U. (2000). The vision of a smart city (No. BNL-67902; 04042). Brookhaven National Lab., Upton, NY (US).

  221. Doran, D., Gokhale, S. & Dagnino, A. (2013). Human sensing for smart cities. In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 1323–1330). ACM.

  222. Doran, D., Severin, K., Gokhale, S., & Dagnino, A. (2016). Social media enabled human sensing for smart cities. AI Communications, 29(1), 57–75.

    Article  MathSciNet  Google Scholar 

  223. Carvalho, L., & Campos, J. B. (2013). Developing the PlanIT Valley: A view on the governance and societal embedding of u-eco city pilots. International Journal of Knowledge-Based Development, 4(2), 109–125.

    Article  Google Scholar 

  224. Ojo, A., Curry, E. & Janowski, T. (2014). Designing next generation smart city initiatives-harnessing findings and lessons from a study of ten smart city programs.

  225. Gaffney, C., & Robertson, C. (2018). Smarter than smart: Rio de Janeiro’s flawed emergence as a smart city. Journal of Urban Technology, 25(3), 47–64.

    Article  Google Scholar 

  226. Barrionuevo, J. M., Berrone, P., & Ricart, J. E. (2012). Smart cities, sustainable progress. IESE Insight, 14(14), 50–57.

    Article  Google Scholar 

  227. Lee, J. H., Hancock, M. G., & Hu, M. C. (2014). Towards an effective framework for building smart cities: Lessons from Seoul and San Francisco. Technological Forecasting and Social Change, 89, 80–99.

    Article  Google Scholar 

  228. Zheng, Y., Rajasegarar, S. & Leckie, C. (2015). Parking availability prediction for sensor-enabled car parks in smart cities. In 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) (pp. 1–6). IEEE.

  229. Trencher, G. P., Yarime, M., & Kharrazi, A. (2013). Co-creating sustainability: Cross-sector university collaborations for driving sustainable urban transformations. Journal of Cleaner Production, 50, 40–55.

    Article  Google Scholar 

  230. Henkes, H., Bose, A., Felber, S., Miloslavski, E., Berg-Dammer, E., & Kühne, D. (2002). Endovascular coil occlusion of intracranial aneurysms assisted by a novel self-expandable nitinol microstent (Neuroform). Interventional Neuroradiology, 8(2), 107–119.

    Article  Google Scholar 

  231. Abas, K., Porto, C., & Obraczka, K. (2014). Wireless smart camera networks for the surveillance of public spaces. Computer, 47(5), 37–44.

    Article  Google Scholar 

  232. Griffith, B., Vaughan, J. & Telford, M. (2017). Map: sanctuary cities, counties, and states. Center for Immigration Studies. Last modified February, 10.

  233. Cheng, B., Longo, S., Cirillo, F., Bauer, M. & Kovacs, E. (2015). Building a big data platform for smart cities: Experience and lessons from santander. In 2015 IEEE International Congress on Big Data (pp. 592–599). IEEE.

  234. Vlahogianni, E. I., Kepaptsoglou, K., Tsetsos, V., & Karlaftis, M. G. (2016). A real-time parking prediction system for smart cities. Journal of Intelligent Transportation Systems, 20(2), 192–204.

    Article  Google Scholar 

  235. Park, J. Y., Kim, D. J., & Lim, Y. (2008). Use of smart card data to define public transit use in Seoul. South Korea. Transportation Research Record, 2063(1), 3–9.

    Article  Google Scholar 

  236. Yigitcanlar, T., & Lee, S. H. (2014). Korean ubiquitous-eco-city: A smart-sustainable urban form or a branding hoax? Technological Forecasting and Social Change, 89, 100–114.

    Article  Google Scholar 

  237. Liu-qin, C. H. E. N. (2011). Smart city: new hot spot of global urban development. Journal of Qingdao University of Science and Technology (Social Sciences), 27(1), 8–16.

    Google Scholar 

  238. Yin, C., Xiong, Z., Chen, H., Wang, J., Cooper, D., & David, B. (2015). A literature survey on smart cities. Science China Information Sciences, 58(10), 1–18.

    Article  Google Scholar 

  239. Harrison, C. & Donnelly, I.A. (2011). A theory of smart cities. In Proceedings of the 55th Annual Meeting of the ISSS-2011, Hull, UK (Vol. 55, No. 1).

  240. Bhati, A., Hansen, M., & Chan, C. M. (2017). Energy conservation through smart homes in a smart city: A lesson for Singapore households. Energy Policy, 104, 230–239.

    Article  Google Scholar 

  241. Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart cities: Definitions, dimensions, performance, and initiatives. Journal of urban technology, 22(1), 3–21.

    Article  Google Scholar 

  242. Shwayri, S. T. (2013). A model Korean ubiquitous eco-city? The politics of making Songdo. Journal of Urban Technology, 20(1), 39–55.

    Article  Google Scholar 

  243. Letaifa, S. B. (2015). How to strategize smart cities: Revealing the SMART model. Journal of Business Research, 68(7), 1414–1419.

    Article  Google Scholar 

  244. Angelidou, M. (2016). Four European smart city strategies. Int’l J. Soc. Sci. Stud., 4, 18.

    Google Scholar 

  245. Giffinger, R., & Gudrun, H. (2010). Smart cities ranking: an effective instrument for the positioning of the cities? ACE: Architecture City and Environment, 4(12), 7–26.

    Google Scholar 

  246. Belbachir, A.N. ed., (2010). Smart cameras (Vol. 2). Springer.

  247. Laursen, L. (2019). City saves money, attracts businesses with smart city strategy. Available online: https://www.technologyreview.com/s/532511/barcelonas-smart-city-ecosystem/ (accessed on 15 July 2019).

  248. TMBAPP (Metro Bus Barcelona) | Apps | iTunes | apps4BCN | All the Apps You Need for Barcelona! Available online: http://apps4bcn.cat/en/app/tmbapp-metro-bus-barcelona/111 (accessed on 15 July 2019).

  249. Transport & Traffic | IOS | The Best App Selection for Barcelona | Apps4bcn | All the Apps You Need for Barcelona! Available online: http://apps4bcn.cat/en/apps/index/Category:transport-i-tr-nsit (accessed on 15 July 2019).

  250. UrbanStep Barcelona | Apps | iTunes | apps4BCN | All the Apps You Need for Barcelona! Available online:http://apps4bcn.cat/en/app/urbanstep-barcelona/110 (accessed on 15 July 2019).

  251. ICT Regulation Toolkit. Available online: http://www.ictregulationtoolkit.org/practice_note?practice_note_id=3244 (accessed on 15 July 2019).

  252. Writer, S. B.-S. (2019). Staff modest gains in first six months of santa Cruz’s predictive police program. Available online: http://www.santacruzsentinel.com/article/zz/20120226/NEWS/120227300 (accessed on 15 July 2019).

  253. The Internet of Everything for Cities. Available online: http://pie.pascalobservatory.org/sites/default/ files/ioe-smart-city_pov.pdf (accessed on 15 July 2019).

  254. Anthopoulos, L.G. and Fitsilis, P. (2015). Understanding smart city business models: a comparison. In Proceedings of the 24th International Conference on World Wide Web (pp. 529–534). ACM.

  255. Smart City Pilot Projects, Scaling Up or Fading Out? Experiences from Amsterdam. Available online: http://www.hva.nl/urban-management/over-um/nieuws/content/nieuwsberichten/2016/3/willem-van-winden-discussion.html (accessed on 15 July 2019).

  256. Christidis, K., & Devetsikiotis, M. (2016). Blockchains and smart contracts for the internet of things. Ieee Access, 4, 2292–2303.

    Article  Google Scholar 

  257. He, W., Yan, G., & Da, X. L. (2014). Developing vehicular data cloud services in the IoT environment. IEEE Transactions on Industrial Informatics, 10(2), 1587–1595.

    Article  Google Scholar 

  258. Petrolo, R., Loscri, V., & Mitton, N. (2017). Towards a smart city based on cloud of things, a survey on the smart city vision and paradigms. Transactions on Emerging Telecommunications Technologies, 28(1), e2931.

    Article  Google Scholar 

  259. Lazarescu, M. T. (2013). Design of a WSN platform for long-term environmental monitoring for IoT applications. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 3(1), 45–54.

    Article  Google Scholar 

  260. Mitton, N., Papavassiliou, S., Puliafito, A., & Trivedi, K. S. (2012). Combining Cloud and sensors in a smart city environment. EURASIP Journal on Wireless Communications and Networking, 2012(1), 1–10.

    Article  Google Scholar 

  261. Atkins, C., Koyanagi, K., Tsuchiya, T., Miyosawa, T., Hirose, H. & Sawano, H. (2013). A Cloud service for end-user participation concerning the Internet of Things. In 2013 International Conference on Signal-Image Technology & Internet-Based Systems (pp. 273–278). IEEE.

  262. Corsar, D., Edwards, P., Velaga, N.R., Nelson, J.D. & Pan, J.Z. (2011). Addressing the Challenges of Semantic Citizen-Sensing. In Proceedings of the 4th International Workshop on Semantic Sensor Networks. CEUR-WS.

  263. Amin, R., Sherratt, R. S., Giri, D., Islam, S. H., & Khan, M. K. (2017). A software agent enabled biometric security algorithm for secure file access in consumer storage devices. IEEE Transactions on Consumer Electronics, 63(1), 53–61.

    Article  Google Scholar 

  264. Choi, H. S., Lee, B., & Yoon, S. (2016). Biometric authentication using noisy electrocardiograms acquired by mobile sensors. IEEE Access, 4, 1266–1273.

    Article  Google Scholar 

  265. Lei, A., Cruickshank, H., Cao, Y., Asuquo, P., Ogah, C. P. A., & Sun, Z. (2017). Blockchain-based dynamic key management for heterogeneous intelligent transportation systems. IEEE Internet of Things Journal, 4(6), 1832–1843.

    Article  Google Scholar 

  266. Dorri, A., Kanhere, S.S., Jurdak, R. and Gauravaram, P. (2017). Blockchain for IoT security and privacy: The case study of a smart home. In 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) (pp. 618–623). IEEE.

  267. Sharma, P. K., Chen, M. Y., & Park, J. H. (2017). A software defined fog node based distributed blockchain cloud architecture for IoT. IEEE Access, 6, 115–124.

    Article  Google Scholar 

  268. Dousti, M. S., & Jalili, R. (2016). An efficient statistical zero-knowledge authentication protocol for smart cards. International Journal of Computer Mathematics, 93(3), 453–481.

    Article  MathSciNet  MATH  Google Scholar 

  269. Abdallah, A., & Shen, X. S. (2016). A lightweight lattice-based homomorphic privacy-preserving data aggregation scheme for smart grid. IEEE Transactions on Smart Grid, 9(1), 396–405.

    Article  Google Scholar 

  270. Dua, A., Kumar, N., Das, A. K., & Susilo, W. (2017). Secure message communication protocol among vehicles in smart city. IEEE Transactions on Vehicular Technology, 67(5), 4359–4373.

    Article  Google Scholar 

  271. Li, R., Song, T., Capurso, N., Yu, J., Couture, J., & Cheng, X. (2017). IoT applications on secure smart shopping system. IEEE Internet of Things Journal, 4(6), 1945–1954.

    Article  Google Scholar 

  272. La, Q. D., Quek, T. Q., Lee, J., Jin, S., & Zhu, H. (2016). Deceptive attack and defense game in honeypot-enabled networks for the internet of things. IEEE Internet of Things Journal, 3(6), 1025–1035.

    Article  Google Scholar 

  273. Sedjelmaci, H., Senouci, S. M., & Taleb, T. (2017). An accurate security game for low-resource IoT devices. IEEE Transactions on Vehicular Technology, 66(10), 9381–9393.

    Article  Google Scholar 

  274. Xiao, L., Li, Y., Han, G., Liu, G., & Zhuang, W. (2016). PHY-layer spoofing detection with reinforcement learning in wireless networks. IEEE Transactions on Vehicular Technology, 65(12), 10037–10047.

    Article  Google Scholar 

  275. Lee, W.H. and Lee, R.B. (2015). Multi-sensor authentication to improve smartphone security. In 2015 International conference on information systems security and privacy (ICISSP) (pp. 1–11). IEEE.

  276. Xing, K., Hu, C., Yu, J., Cheng, X., & Zhang, F. (2017). Mutual privacy preserving $ k $-means clustering in social participatory sensing. IEEE Transactions on Industrial Informatics, 13(4), 2066–2076.

  277. Olejnik, K., Dacosta, I., Machado, J.S., Huguenin, K., Khan, M.E. & Hubaux, J.P. (2017). Smarper: Context-aware and automatic runtime-permissions for mobile devices. In 2017 IEEE Symposium on Security and Privacy (SP) (pp. 1058–1076). IEEE.

  278. Aminanto, M. E., Choi, R., Tanuwidjaja, H. C., Yoo, P. D., & Kim, K. (2017). Deep abstraction and weighted feature selection for Wi-Fi impersonation detection. IEEE Transactions on Information Forensics and Security, 13(3), 621–636.

    Article  Google Scholar 

  279. Kim, S. H., Ko, I. Y., & Kim, S. H. (2017). Quality of private information (qopi) model for effective representation and prediction of privacy controls in mobile computing. Computers & Security, 66, 1–19.

    Article  Google Scholar 

  280. Tao, M., Zuo, J., Liu, Z., Castiglione, A., & Palmieri, F. (2018). Multi-layer cloud architectural model and ontology-based security service framework for IoT-based smart homes. Future Generation Computer Systems, 78, 1040–1051.

    Article  Google Scholar 

  281. Xu, G., Cao, Y., Ren, Y., Li, X., & Feng, Z. (2017). Network security situation awareness based on semantic ontology and user-defined rules for Internet of Things. IEEE Access, 5, 21046–21056.

    Article  Google Scholar 

  282. Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014). Sensing as a service model for smart cities supported by internet of things. Transactions on emerging telecommunications technologies, 25(1), 81–93.

    Article  Google Scholar 

  283. Akyildiz, I. F., Melodia, T., & Chowdury, K. R. (2007). Wireless multimedia sensor networks: A survey. IEEE Wireless Communications, 14(6), 32–39.

    Article  Google Scholar 

  284. Zhao, F. (2010). Sensors meet the cloud: Planetary-scale distributed sensing and decision making. In 9th IEEE International Conference on Cognitive Informatics (ICCI'10) (pp. 998–998). IEEE.

  285. Kim, J. H., & Shcherbakova, A. (2011). Common failures of demand response. Energy, 36(2), 873–880.

    Article  Google Scholar 

  286. Alcaraz, C. & Lopez, J. (2010). A security analysis for wireless sensor mesh networks in highly critical systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 40(4), 419–428.

  287. Ketu, S. & Agarwal, S. (2015). Performance enhancement of distributed K-Means clustering for big Data analytics through in-memory computation. In 2015 Eighth International Conference on Contemporary Computing (IC3) (pp. 318–324). IEEE.

  288. Ketu, S., Prasad, B.R. & Agarwal, S. (2015). Effect of corpus size selection on performance of map-reduce based distributed k-means for big textual data clustering. In Proceedings of the Sixth International Conference on Computer and Communication Technology 2015 (pp. 256–260). ACM.

  289. Ketu, S., Kumar Mishra, P. & Agarwal, S. (2020). Performance analysis of distributed computing frameworks for big data analytics: Hadoop Vs Spark. Computación y Sistemas, 24(2).

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shwet Ketu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ketu, S., Mishra, P.K. A Contemporary Survey on IoT Based Smart Cities: Architecture, Applications, and Open Issues. Wireless Pers Commun 125, 2319–2367 (2022). https://doi.org/10.1007/s11277-022-09658-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-022-09658-2

Keywords

Navigation