Smart City Gnosys
Smart city article details
| Title | Integrated Solutions For Uav-Assisted Iot Communications: Beam Selection And Wireless Mobile Ad Hoc Backhaul Network Design |
|---|---|
| ID_Doc | 31905 |
| Authors | Tamilselvi M. |
| Year | 2025 |
| Published | 3rd International Conference on Electronics and Renewable Systems, ICEARS 2025 - Proceedings |
| DOI | http://dx.doi.org/10.1109/ICEARS64219.2025.10940063 |
| Abstract | Unmanned Aerial Vehicles (UAVs), also called drones, are planes operated by unmanned aircraft and controlled remotely via built-in computers or remote control. Their applications span from surveillance to delivery, and even agriculture to communications. Battery life and range limitations may limit the operational time of UAVs. They can create privacy issues, security risks, and potential threats to air traffic and public safety if not properly regulated. NB-IoT networks are addressed by the USC-WBND approach using semi-permanent scheduling (SPS) and shorter transmission time intervals (TTI). Using a fixed 1ms TTI can reduce latency and allocate resources more efficiently while decreasing the number of OFDM symbols. Relay requests for scheduling resources are eliminated in SPS, resulting in reduced latency for devices with regular transmissions. Moreover, the user's information, login details, and device settings along with GPS tracking are all managed by a cloud-based display platform, which allows for tailored access and precise location tracking. By visualizing UAV distribution in 2D and 3D, it is possible to select the most suitable drone locations to minimize interference and enhance coverage. A 2D technique is concerned with determining height and location, while another 3D approach employs a game of matching to find the most suitable UAVs for different user densities and interference. This mathematical modeling and algorithm aim to find the best placement for UAVs, maximize coverage by IoT nodes, and provide optimal service quality. The proposed strategies improve network efficiency, reduce interference, and optimize the placement of data transmission relays, providing significant advances in smart city environments. The main issues in NB-IoT and UAV deployments are addressed through this comprehensive approach, which seeks to address network performance problems by enhancing connectivity and decreasing latency. IoT communication is a crucial aspect of smart city infrastructure, and its USC-WBND model architecture provides dependable communications solutions. Results are calculated by measuring the parameters like energy efficiency, packet drop, throughput, average delay, and network overhead. © 2025 IEEE. |
| Author Keywords | Internet of Things (IoT); Semi Permanent Scheduling (SPS); Shorter Transmission Time Intervals (TTI); Unmanned Aerial Vehicles (UAVs) |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
59296  | 0.899 | Al-Ahmed S.A.; Ahmed T.; Zhu Y.; Malaolu O.O.; Shakir M.Z. | Uav-Enabled Iot Networks: Architecture, Opportunities, And Challenges | Wireless Networks and Industrial IoT: Applications, Challenges and Enablers (2020) |
| 32085 | 0.894 | Eskandari M.; Savkin A.V. | Integrating Uavs And Riss In Future Wireless Networks: A Review And Tutorial On Iots And Vehicular Communications | Future Internet, 16, 12 (2024) |
| 59315 | 0.888 | Jan M.A.; Hassan S.A.; Jung H. | Uavs: Communication Aspects And Cellular Service Provisioning | Drones in Smart-Cities: Security and Performance (2020) |
| 48347 | 0.886 | Wu Z.; Jiang W.; Liu A.; Zhang Y.; Han H.; Mu J.; Liu S.; Gu W.; Zhang Y.; Huang S.; Feng Z. | Sensing And Communication Coverage In Internet Of Drone Things: Challenges And Opportunities | IEEE Internet of Things Magazine, 8, 4 (2025) |
| 53791 | 0.882 | Han S.I. | Survey On Uav Deployment And Trajectory In Wireless Communication Networks: Applications And Challenges | Information (Switzerland), 13, 8 (2022) |
| 61944 | 0.882 | Saad W.; Bennis M.; Mozaffari M.; Lin X. | Wireless Communications And Networking For Unmanned Aerial Vehicles | Wireless Communications and Networking for Unmanned Aerial Vehicles (2020) |
| 59308 | 0.878 | Al-Turjman F.; Abujubbeh M.; Malekloo A.; Mostarda L. | Uavs Assessment In Software-Defined Iot Networks: An Overview | Computer Communications, 150 (2020) |
| 7400 | 0.872 | Aloqaily M.; Bouachir O.; Al Ridhawi I.; Tzes A. | An Adaptive Uav Positioning Model For Sustainable Smart Transportation | Sustainable Cities and Society, 78 (2022) |
| 59264 | 0.872 | Gi, F; Zhu, XT; Mang, G; Kadoch, M; Li, W | Uav Network And Lot In The Sky For Future Smart Cities | IEEE NETWORK, 33, 2 (2019) |
| 40866 | 0.871 | Darem A.A.; Alkhaldi T.M.; Alhashmi A.A.; Mansouri W.; Alghawli A.S.A.; Al-Hadhrami T. | Optimizing Resource Allocation For Enhanced Urban Connectivity In Leo-Uav-Ris Networks | Journal of King Saud University - Computer and Information Sciences, 36, 10 (2024) |