Energy Management Systems in Smart City IoT Networks

Authors

  • Eisa Abdolmaleki Department of Applied Mathematics, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran. https://orcid.org/0009-0009-6355-6587
  • Nadia Ghasemabadi Department of Computer Engineering, Ayandegan Institute of Higher Education, Tonekabon, Iran. https://orcid.org/0009-0002-0943-1993
  • Sushant Poudel * School of Computer Science Engineering, KIIT University, Bhubaneswar, India.

https://doi.org/10.48313/siot.v3i2.256

Abstract

Energy Management Systems (EMS) play a vital role in smart city infrastructures by efficiently regulating and optimising energy usage in urban environments. With the rapid expansion of the Internet of Things (IoT) networks, smart cities increasingly rely on connected devices to manage energy in sectors like transportation, lighting, and utilities. However, while IoT integration facilitates real-time data exchange and enhances operational efficiency, it also poses challenges in energy management, such as scalability, interoperability, security, and cost-effectiveness. This paper explores the design and implementation of EMS in smart city IoT networks, highlighting recent advancements and ongoing challenges. A comprehensive literature review identifies key energy optimisation techniques, such as machine learning-based predictive analytics, adaptive load balancing, and the use of blockchain for secure and interoperable communication among devices. To address challenges in scalability and security, we propose a distributed EMS framework that leverages blockchain for decentralised communication and Artificial Intelligence (AI) for predictive energy demand management. Our proposed framework includes a mathematical model that dynamically adjusts power distribution according to predicted demand patterns, enabling both energy savings and demand-response adaptability. A simulation of the proposed EMS demonstrates its potential for significant improvements in energy efficiency and resilience against cyber threats. The results suggest that integrating AI-driven optimisation and secure, scalable communication protocols can provide a robust foundation for EMS in smart city IoT networks. This study aims to inform future research and development efforts in sustainable urban energy management, providing a roadmap for cities to achieve energy-efficient, secure, and cost-effective IoT-based solutions.

Keywords:

Energy management systems, Smart city, IoT networks, Sustainability, Optimisation

References

  1. [1] Mishra, P., & Singh, G. (2023). Energy management systems in sustainable smart cities based on the internet of energy: A technical review. Energies, 16(19), 6903. https://doi.org/10.3390/en16196903
  2. [2] Martí, M., Garcia-Rubio, C., & Campo, C. (2019). Performance evaluation of CoAP and MQTT_SN in an IoT environment. In Proceedings (Vol. 31, No. 1, p. 49). MDPI. https://doi.org/10.3390/proceedings2019031049
  3. [3] Carrera, B., Peyrard, S., & Kim, K. (2021). Meta-regression framework for energy consumption prediction in a smart city: A case study of Songdo in South Korea. Sustainable Cities and Society, 72, 103025. https://doi.org/10.1016/j.scs.2021.103025
  4. [4] Jiang, P., Van Fan, Y., & Klemeš, J. J. (2021). Impacts of COVID-19 on energy demand and consumption: Challenges, lessons and emerging opportunities. Applied Energy, 285, 116441. https://doi.org/10.1016/j.apenergy.2021.116441
  5. [5] Alsamhi, S. H., Almalki, F. A., Al-Dois, H., Ben Othman, S., Hassan, J., Hawbani, A., … & Saleh, H. (2021). Machine learning for smart environments in B5G networks: Connectivity and QoS. Computational intelligence and neuroscience, 2021(1), 6805151. https://doi.org/10.1155/2021/6805151
  6. [6] Park, L., Lee, C., Kim, J., Mohaisen, A., & Cho, S. (2019). Two-stage IoT device scheduling with dynamic programming for energy Internet systems. IEEE Internet of Things Journal, 6(5), 8782–8791. https://doi.org/10.1109/JIOT.2019.2923432
  7. [7] Arévalo, P., & Jurado, F. (2024). Impact of artificial intelligence on the planning and operation of distributed energy systems in smart grids. Energies, 17(17), 4501. https://doi.org/10.3390/en17174501
  8. [8] Reyna, A., Martín, C., Chen, J., Soler, E., & Díaz, M. (2018). On blockchain and its integration with IoT. Challenges and opportunities. Future Generation Computer Systems, 88, 173-190. https://doi.org/10.1016/j.future.2018.05.046
  9. [9] Tariq, N., Qamar, A., Asim, M., & Khan, F. A. (2020). Blockchain and smart healthcare security: a survey. Procedia Computer Science, 175, 615–620. https://doi.org/10.1016/j.procs.2020.07.089
  10. [10] Yang, Q., & Wang, H. (2021). Privacy-preserving transactive energy management for IoT-aided smart homes via blockchain. IEEE Internet of Things Journal, 8(14), 11463–11475. https://doi.org/10.1109/JIOT.2021.3051323
  11. [11] Albouq, S. S., Abi Sen, A. A., Almashf, N., Yamin, M., Alshanqiti, A., & Bahbouh, N. M. (2022). A survey of interoperability challenges and solutions for dealing with them in IoT environment. IEEe Access, 10, 36416–36428. https://doi.org/10.1109/ACCESS.2022.3162219
  12. [12] Nikpour, M., Yousefi, P. B., Jafarzadeh, H., Danesh, K., Shomali, R., Asadi, S., … & Ahmadi, M. (2025). Intelligent energy management with IoT framework in smart cities using intelligent analysis: An application of machine learning methods for complex networks and systems. Journal of Network and Computer Applications, 235, 104089. https://doi.org/10.1016/j.jnca.2024.104089
  13. [13] Kim, J., & Kim, K.-I. (2020). Data-driven hybrid model and operating algorithm to shave peak demand costs of building electricity. Energy and Buildings, 229, 110493. https://doi.org/10.1016/j.enbuild.2020.110493

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Published

2026-06-10

Issue

Vol. 3 No. 2 (2026): Smart Internet of Things

Section

Articles

How to Cite

Abdolmaleki, E. ., Ghasemabadi, N. ., & Sushant Poudel. (2026). Energy Management Systems in Smart City IoT Networks. Smart Internet of Things, 3(2), 70–82. https://doi.org/10.48313/siot.v3i2.256

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