Sensing and Communication Coverage in Internet of Drone Things: Challenges and Opportunities
The Internet of Drone Things (IoDT) represents the convergence of unmanned aerial vehicles (UAVs) and the Internet of Things (IoT), forming a dynamic network capable of seamless data communication and real-time environmental sensing. This integration unlocks transformative applications across diverse sectors, including logistics, agriculture, surveillance, and smart cities, where drones interact with other connected devices, systems, and cloud platforms to optimize operations and enhance decision-making. This article investigates the challenges and opportunities inherent in integrating sensing and communication within the IoDT, with a particular focus on the role of integrated sensing and communication (ISAC) in enhancing IoDT capabilities. We explore how ISAC can facilitate autonomous tasks and revolutionize industries by enabling efficient data exchange and environmental monitoring. Key challenges discussed include network intelligence, real-time monitoring, ubiquitous connectivity, multi-source data integration, and cybersecurity risks. We also examine potential solutions, such as the application of large language models, digital twins, satellite connectivity, networked sensing, and federated learning to bolster security and improve system performance. Ultimately, the article emphasizes the need to address these challenges to fully unlock the potential of IoDT, enabling a sustainable low-altitude economy and improving operational efficiency across various domains.
Authors
- Zhiyong Feng (ORCID: https://orcid.org/0000-0001-5322-222X)
- Zexuan Wu (ORCID: https://orcid.org/0000-0003-3726-773X)
- Jianbin Mu
- Yang Zhang (ORCID: https://orcid.org/0000-0001-9120-3425)
- Haoyu Han (ORCID: https://orcid.org/0000-0002-1873-1907)
- Sai Huang (ORCID: https://orcid.org/0000-0002-5186-3362)
- Weixi Gu (ORCID: https://orcid.org/0009-0005-5986-5716)
- Yifan Zhang (ORCID: https://orcid.org/0000-0001-8882-4327)
- Weiwei Jiang (ORCID: https://orcid.org/0000-0003-0953-5047)
- Ao Liu (ORCID: https://orcid.org/0009-0008-9138-0059)
- Shang Liu
Institutions
- Beijing University of Posts and Telecommunications (CN)
- Beijing Academy of Artificial Intelligence (CN)
- Zhejiang University of Technology (CN)
Publication Details
- Journal
- IEEE Internet of Things Magazine
- Published
- 2025-06-24
- DOI
- https://doi.org/10.1109/iotm.001.2500023
- Citations
- 3
- Primary Topic
- UAV Applications and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 14.98
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Zhejiang Province