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Networked Unmanned Aerial Vehicles for Surveillance and Monitoring: A Survey
Open accessAbstract
As a typical cyber-physical system, networked unmanned aerial vehicles (UAVs) have received much attention in recent years. Emerging communication technologies and high-performance control methods enable networked UAVs to operate as aerial sensor networks to collect more complete and consistent information with significantly improved mobility and flexibility than traditional sensing platforms. One of the main applications of networked UAVs is surveillance and monitoring, which constitute essential components of a well-functioning public safety system and many industrial applications. Although the existing literature on surveillance and monitoring UAVs is extensive, a comprehensive survey on this topic is lacking. This article classifies publications on networked UAVs for surveillance and monitoring using the targets of interest and analyzes several typical problems on this topic, including the control, navigation, and deployment optimization of UAVs. The related research gaps and future directions are also presented.
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“For instance, leveraging algorithms like the Firefly algorithm can aid in rapidly estimating flood levels and spread rates [148].”
From A Survey of Video Surveillance Systems in Smart City (2023) · cites this paper as [148]
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Savkin, A. V., & Verma, S. C. (2024) · IEEE Conference on Industrial Electronics and Applications (ICIEA) · doi:10.1109/iciea61579.2024.10664913
Self-citationMALE UAV LONGITUDINAL STABILITY DETERMINATION USING WIND TUNNEL DATA
Adhynugraha, M. I., Megawanto, F. C., Octaviany, S. V., Budiarti, D. H., Muliadi, J., Nami, O. F., & Wibowo, S. S. (2024) · Jurnal Teknosains · doi:10.22146/teknosains.89420
Improved YOLOv5s lightweight substation defect identification and detection model
He, D., Xiong, J., Lin, S., Yang, Y., Qian, J., & Huang, J. (2025) · doi:10.1117/12.3057438
AoI-Constrained Scheduling for Information Freshness Over Unreliable Channels
Jia, Z., Fan, H., Gu, X., Li, B., Wang, W., & Liu, Q. (2025) · International Workshop on Quality of Service · doi:10.1109/iwqos65803.2025.11143377
Anti-Jamming based on Beam-Steering Antennas and Intelligent UAV Swarm Behavior
Silva, T., & Grilo, A. (2025) · IEEE International Conference on Communication, Networks and Satellite (COMNETSAT) · doi:10.1109/comnetsat68601.2025.11324847
Drone-Based Computer Vision System for Anti-Poaching Surveillance in Protected Forests
Vinayagam, P., Kanagamalliga, S., Rakshan, R., & Seshakumar, S. (2025) · International Conference on Innovative Data Communication Technologies and Application (ICIDCA) · doi:10.1109/icidca66325.2025.11280306
Metadata
- Authors
- Li, X., & Savkin, A. V.
- Affiliations
- UNSW Sydney (AU)
- Corresponding author
- Savkin, Andrey V.
- Venue
- Future Internet
- Publisher
- MDPI AG
- Published
- 2021-07-02
- Volume
- 13
- Issue
- 7
- Pages
- 174
- ISSN
- 1999-5903 (ISSN-L)
- OpenAlex
- W3174708786
- Cited by
- 107
- References
- 116
- Citations by year
- 2026: 8 · 2025: 23 · 2024: 30 · 2023: 16 · 2022: 22 · 2021: 8
- FWCI
- 9.79
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Future Internet (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Australian Research Council (NULL)
- Australian Government (AUSMURIB000001)
- ONR MURI (N00014-19-1-2571)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › UAV Applications and Optimization
- Physical Sciences › Engineering › Control and Systems Engineering › Distributed Control Multi-Agent Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Robotic Path Planning Algorithms
- Keywords
- UAV surveillance, UAV monitoring, cyber-physical systems, UAV control, UAV navigation, UAV deployment optimization, public safety
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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