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Stream/Area:
-
Subject:
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Paper ID:
10.55041/IJSREM.ICITES006
Volume:
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Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Unmanned Aerial Vehicles (UAVs) are used as an important element of smart construction and infrastructure management. These systems have been helpful for real time monitoring, site inspection, and safety assessment. The challenge is, however, optimization of energy consumption while maintaining a high data throughput in dynamic and resource constrained environments. This paper reviews several AI-driven approaches, such as deep reinforcement learning, multi-agent frameworks, and resource allocation techniques, which improve the efficiency of UAVs in construction applications. The review focuses on recent works from 2017 to 2024, selected through a structured methodology involving
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Publication Date
4/23/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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