Applications and Challenges in Video Surveillance via Drone: A Brief Survey
Abstract
Our society is moving quickly towards smart homes and smart cities, requiring more and more deployment of Internet of Things (IoT) devices. To achieve smart urbanization, continuous surveillance is necessary. Research about video surveillance via Closed-Circuit Television (CCTV) cameras is in play for decades but poses different problems, i.e., limited area coverage, no location sharing, and tracking capabilities. On the other hand, vision sensors mounted on drones are more scalable and flexible with more comprehensive surveillance coverage. But at the same time, drones also encounter several challenges, such as limited processing and power resources, trembling camera effects in the video feed, disturbance in transmission signals, etc. Drones surveillance lacks the researcher's attentiveness, and therefore, we collect the related literature and confer their practical viewpoint broadly. This article focuses on video surveillance using drones in object detection and tracking, video summarization, persistent monitoring of the target, search and rescue operation in a hostile environment, traffic management in smart cities, and disaster management in an apocalyptic situation. This brief survey sheds light on the research gaps and profound insights of the methods used in the mentioned articles by opening up future research tracks for the Computer Vision (CV) enthusiasts using Unmanned Aerial Vehicles (UAV).
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Inherent problems of drones are significant challenges such as limited flight duration due to short battery lifetime, limited CPU resource and memory, and security concerns.
“Despite the beneficial use of drones in smart cities, the inherent problems of drones are also significant challenges such as limited flight duration due to short battery lifetime, limited CPU resource and memory, and security concerns [7,155,156].”
From A Survey of Video Surveillance Systems in Smart City (2023) · cites this paper as [7]
Cites
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Shakeri, R., Al-Garadi, M. A., Badawy, A., Mohamed, A., Khattab, T., Al-Ali, A. K., Harras, K. A., & Guizani, M. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2924143 · Cited by 295 · see citing works
A comprehensive survey of multi-view video summarization
Hussain, T., Muhammad, K., Ding, W., Lloret, J., Baik, S. W., & de Albuquerque, V. H. C. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2020.107567 · Cited by 159 · see citing works
Convolutional SVM Networks for Object Detection in UAV Imagery
Bazi, Y., & Melgani, F. (2018) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2018.2790926 · Cited by 158 · see citing works
UAV exploitation: A new domain for cyber power
Hartmann, K., & Giles, K. (2016) · doi:10.1109/cycon.2016.7529436 · Cited by 101 · see citing works
Simultaneously Detecting and Counting Dense Vehicles From Drone Images
Li, W., Li, H., Wu, Q., Chen, X., & Ngan, K. N. (2019) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2019.2899548 · Cited by 96 · see citing works
A Review On Marine Search And Rescue Operations Using Unmanned Aerial Vehicles
Yeong, S. P., King, L. M., & Dol, S. S. (2015) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.1107671 · Cited by 83 · see citing works
A Collision-Free Surveillance System Using Smart UAVs in Multi Domain IoT
Kim, H., & Ben‐Othman, J. (2018) · IEEE Communications Letters · doi:10.1109/lcomm.2018.2875477 · Cited by 70 · see citing works
Persistent Tracking for Wide Area Aerial Surveillance
Prokaj, J., & Medioni, G. G. (2014) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2014.155 · Cited by 61 · see citing works
Persistent Aerial Tracking system for UAVs
Mueller, M. F., Sharma, G., Smith, N., & Ghanem, B. (2016) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2016.7759253 · Cited by 58 · see citing works
Multiple UAVs-based Surveillance and Reconnaissance System Utilizing IoT Platform
Park, J.-H., Choi, S.-C., Ahn, I.-Y., et al. (2019) · International Conference on Electronics, Information, and Communication (ICEIC) · doi:10.23919/elinfocom.2019.8706406 · Cited by 37 · see citing works
Real-Time Detection, Tracking and Classification of Multiple Moving Objects in UAV Videos
Baykara, H. C., Bıyık, E., Gül, G., Onural, D., Öztürk, A. S., & Yildiz, I. (2017) · IEEE International Conference on Tools with Artificial Intelligence (ICTAI) · doi:10.1109/ictai.2017.00145 · Cited by 32 · see citing works
A Framework for Knowing Who is Doing What in Aerial Surveillance Videos
Yang, F., Sakti, S., Wu, Y., & Nakamura, S. (2019) · IEEE Access · doi:10.1109/access.2019.2924188 · Cited by 17 · see citing works
A computer-vision approach to traffic analysis over intersections
Lira, G. S., Kokkinogenis, Z., Rossetti, R. J. F., et al. (2016) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2016.7795530 · Cited by 9 · see citing works
Visual Search on Aerial Imagery as Support for Finding Lost Persons
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Accurate coverage summarization of UAV videos
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A Survey of Video Surveillance Systems in Smart City
Myagmar-Ochir, Y., & Kim, W. (2023) · Electronics · doi:10.3390/electronics12173567 · Cited by 134 · see citing works
“Despite the beneficial use of drones in smart cities, the inherent problems of drones are also significant challenges such as limited flight duration due to short battery lifetime, limited CPU resource and memory, and security concerns [7,155,156].”
Background
- Authors
- Dilshad, N., Hwang, J., Song, J., & Sung, N.
- Affiliations
- Sejong University (KR)
- Venue
- 2020 International Conference on Information and Communication Technology Convergence (ICTC)
- Publisher
- IEEE
- Published
- 2020-10-21
- Pages
- 728-732
- OpenAlex
- W3116690515
- Cited by
- 139
- References
- 17
- Citations by year
- 2026: 17 · 2025: 32 · 2024: 31 · 2023: 35 · 2022: 16 · 2021: 8
- FWCI
- 4.55
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Conference on Information and Communication Technology Convergence (ICTC) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Physical Sciences › Engineering › Aerospace Engineering › UAV Applications and Optimization
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- unmanned aerial vehicles, object detection, object tracking, video summarization, persistent surveillance, search and rescue, traffic management, disaster management, smart cities, Internet of Things, camera shake
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