The Integration of Drones and IoT in Smart City Networks

S. Ismail, Laith; Kareem Abass, Haithem; Ainura Nurmamatovna, Mitalipova; Bodnar, Nataliia; Alsaray, Ali

doi:10.22034/jipm.2025.728347

The Integration of Drones and IoT in Smart City Networks

Document Type : Original Article

Authors

Laith S. Ismail ¹

Haithem Kareem Abass ²

Mitalipova Ainura Nurmamatovna ³

Nataliia Bodnar ⁴

Ali Alsaray ⁵

¹ Al-Turath University, Baghdad 10013, Iraq

² Al-Mansour University College, Baghdad 10067, Iraq

³ Osh State University, Osh City 723500, Kyrgyzstan

⁴ Al-Rafidain University College Baghdad 10064, Iraq

⁵ Madenat Alelem University College, Baghdad 10006, Iraq

10.22034/jipm.2025.728347

Abstract

ABSTRACT
Background: Smart city technology solutions have recently ramped up the utilization of drones with Internet of Things (IoT) technologies for improving smart city systems. IoT sensors combined with real-time communication ad hoc network drones are also another area with great potential including traffic monitoring, environment management, disaster management, etc. Nevertheless, issues regarding energy consumption and density, the number of nodes that can be incorporated into the network, as well as the issue of avoiding collisions between the signal sent by one node with the signals that may be transmitted by other nodes are still observed as essential impediments to the wide application of WSNs.
Objective: The article seeks to propose and assess algorithms for operating drone-IoT systems whilst dealing with issues like energy efficiency, real-time data communication, avoiding mid-air collisions, and dealing with the increasing number of systems in crowded urban areas.
Methods: This study utilizes a two-time algorithm technique that was adopted from the prior study. The first algorithm provides a method for speed and position control of drones, ensuring that the distance between the drones is sufficient and not violable. The second algorithm is centered on energy reduction, which selects the precise energy usage by employing path planning in real time. The effectiveness of these algorithms was determined using simulation models with respect to metrics including latency, energy consumption, and scalability.
Results: The proposed system revealed the systems’ improvements in energy efficiency, fewer collisions, and strong scalability of drone management. Main conclusions possible to conclude during the experiment reveal the system’s generic aptitude to the different urban situations and its stability in changing traffic conditions.
Conclusion: The article presents a scalable and efficient solution for extending drone applications to smart cities using IoT platforms. In this way, the results can serve as the further theoretical and experimental base for investigating the trends of management and the infrastructure of cities.

Keywords

KEYWORDS: Smart cities

Internet of Things (IoT)

drones

UAVs

data analytics

urban infrastructure

traffic monitoring

IoT integration

real-time data

predictive maintenance

References

Abbas, N., Abbas, Z., Liu, X., Khan, S. S., Foster, E. D., and Larkin, S. (2023). A Survey: Future Smart Cities Based on Advance Control of Unmanned Aerial Vehicles (UAVs). Applied Sciences, 13 (17). https://doi.org/10.3390/app13179881.

Ali, H., Karim, S., Saab, M., Hassan, S., Bodnar, N., Ahmed, S., Mustafa, S., et al. (2024). Technological innovations and sustainability: Shaping the future of smart cities in urban planning. Edelweiss Applied Science and Technology, 8, 1992-2011. https://doi.org/10.55214/25768484.v8i4.1577

Alsamhi, S. H., Afghah, F., Sahal, R., Hawbani, A., Al-qaness, M. A. A., Lee, B., and Guizani, M. (2021). Green internet of things using UAVs in B5G networks: A review of applications and strategies. Ad Hoc Networks, 117, 102505. https://doi.org/10.1016/j.adhoc.2021.102505

Alshbatat, A. (2023). Development of Autonomous Hexacopter UAVs for Smart City Air Quality Management. Jordan Journal of Electrical Engineering, 9, 450. https://doi.org/10.5455/jjee.204-1673429561

Amodu, O. A., Nordin, R., Jarray, C., Bukar, U. A., Raja Mahmood, R. A., and Othman, M. (2023). A Survey on the Design Aspects and Opportunities in Age-Aware UAV-Aided Data Collection for Sensor Networks and Internet of Things Applications. Drones, 7 (4). https://doi.org/10.3390/drones7040260.

Asaamoning, G., Mendes, P., Rosário, D., and Cerqueira, E. (2021). Drone Swarms as Networked Control Systems by Integration of Networking and Computing. Sensors, 21 (8). https://doi.org/10.3390/s21082642.

Bisio, I., Garibotto, C., Haleem, H., Lavagetto, F., and Sciarrone, A. (2022). A Systematic Review of Drone Based Road Traffic Monitoring System. IEEE Access, 10, 101537-101555. https://doi.org/10.1109/ACCESS.2022.3207282

De Fazio, R., Dinoi, L. M., De Vittorio, M., and Visconti, P. (2022). A Sensor-Based Drone for Pollutants Detection in Eco-Friendly Cities: Hardware Design and Data Analysis Application. Electronics, 11 (1). https://doi.org/10.3390/electronics11010052.

Gohari, A., Ahmad, A. B., Rahim, R. B. A., Supa’at, A. S. M., Razak, S. A., and Gismalla, M. S. M. (2022). Involvement of Surveillance Drones in Smart Cities: A Systematic Review. IEEE Access, 10, 56611-56628. https://doi.org/10.1109/ACCESS.2022.3177904

Honcharenko, T., Khrolenko, V., Gorbatyuk, I., Liashchenko, M., Bodnar, N., and Sherif, N. H. (2024). Smart Integration of Information Technologies for City Digital Twins. 2024 35th Conference of Open Innovations Association (FRUCT). https://doi.org/10.23919/FRUCT61870.2024.10516358.

Hoque, M. A., Hossain, M., Noor, S., Islam, S. M. R., and Hasan, R. (2022). IoTaaS: Drone-Based Internet of Things as a Service Framework for Smart Cities. IEEE Internet of Things Journal, 9 (14), 12425-12439. https://doi.org/10.1109/JIOT.2021.3137362

Jawad, A. M., Qasim, N. H., Jawad H. M., Abu-Alshaeer, M. J., Nordinc, R., Gharghand, S. K. (2022). Near Field WPT Charging a Smart Device Based on IoT Applications. CEUR. https://ceur-ws.org/Vol-3149/paper7.pdf

Jghef, Y. S., Jasim, M. J., Ghanimi, H. M. A., Algarni, A. D., Soliman, N. F., El-Shafai, W., Zeebaree, S. R. M., et al. (2022). Bio-Inspired Dynamic Trust and Congestion-Aware Zone-Based Secured Internet of Drone Things (SIoDT). Drones, 6 (11). https://doi.org/10.3390/drones6110337.

Lucic, M. C., Bouhamed, O., Ghazzai, H., Khanfor, A., and Massoud, Y. (2023). Leveraging UAVs to Enable Dynamic and Smart Aerial Infrastructure for ITS and Smart Cities: An Overview. Drones, 7 (2). https://doi.org/10.3390/drones7020079.

Miao, Y., Hwang, K., Wu, D., Hao, Y., and Chen, M. (2023). Drone Swarm Path Planning for Mobile Edge Computing in Industrial Internet of Things. IEEE Transactions on Industrial Informatics, 19 (5), 6836-6848. https://doi.org/10.1109/TII.2022.3196392

Pavlenko, V., Ponomarenko, I., Morhulets, O., Osadchyi, V., Ponomarenko, D., and Hrygorevska, O. (2023). Using Artificial Intelligence to Control Drones. 2023 IEEE 7th International Conference on Methods and Systems of Navigation and Motion Control (MSNMC), 24-27 Oct. 2023. https://doi.org/10.1109/MSNMC61017.2023.10329033.

Qasim, N., Jawad, A., Jawad, H., Khlaponin, Y., and Nikitchyn, O. (2022). Devising a traffic control method for unmanned aerial vehicles with the use of gNB-IOT in 5G. Eastern-European Journal of Enterprise Technologies, 3, 53-59. https://doi.org/10.15587/1729-4061.2022.260084

Qasim, N., Jawad, A., and Majeed, M. (2023). The Usages of Cybersecurity in Marine Communications. Transport Development, 3 (18). https://doi.org/10.33082/td.2023.3-18.05

Qasim, N. H., and Jawad, A. M. (2024). 5G-enabled UAVs for energy-efficient opportunistic networking. Heliyon, 10 (12), e32660. https://doi.org/10.1016/j.heliyon.2024.e32660

Salunke, A. (2023). Enhancing Urban Traffic Management through Predictive Modelling and Drone-Captured Image Analysis for Smart Traffic Lights. https://doi.org/10.13140/RG.2.2.31014.70721

Silva, F. S. D., Neto, E. P., Oliveira, H., Rosário, D., Cerqueira, E., Both, C., Zeadally, S., et al. (2021). A Survey on Long-Range Wide-Area Network Technology Optimizations. IEEE Access, 9, 106079-106106. https://doi.org/10.1109/ACCESS.2021.3079095

Srivastava, Y., Virk, S., Ganguli, S., & Tripathi, S. (2022). Smart Cities and the Use of Internet of Drone Things (IoDT). Internet of Things, 33-45. https://doi.org/10.1201/9781003181613-3

Sun, M., Xu, X., Qin, X., and Zhang, P. (2021). AoI-Energy-Aware UAV-Assisted Data Collection for IoT Networks: A Deep Reinforcement Learning Method. IEEE Internet of Things Journal, 8 (24), 17275-17289. https://doi.org/10.1109/JIOT.2021.3078701

Tran, T.-H., and Nguyen, D.-D. (2022). Management and Regulation of Drone Operation in Urban Environment: A Case Study. Social Sciences, 11 (10). https://doi.org/10.3390/socsci11100474.

Yahuza, M., Idris, M. Y. I., Ahmedy, I. B., Wahab, A. W. A., Nandy, T., Noor, N. M., and Bala, A. (2021). Internet of Drones Security and Privacy Issues: Taxonomy and Open Challenges. IEEE Access, 9, 57243-57270. https://doi.org/10.1109/ACCESS.2021.3072030

Yu, S., Das, A. K., Park, Y., and Lorenz, P. (2022). SLAP-IoD: Secure and Lightweight Authentication Protocol Using Physical Unclonable Functions for Internet of Drones in Smart City Environments. IEEE Transactions on Vehicular Technology, 71 (10), 10374-10388. https://doi.org/10.1109/TVT.2022.3188769