Review on Energy Efficiency and Throughput Optimization in UAV Networks for AI-Driven Smart Construction

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 keyword-based searches, citation analysis, and relevance filtering from databases such as IEEE Xplore, Scopus, Web of Science, and Google Scholar. The paper covers the key aspects, including trajectory planning, UAV swarm coordination, and adaptive decision making for construction site monitoring. The review of current research gaps will be proposed for future directions on AI enhanced UAV systems in sustainable and energy efficient construction projects. Key Words: UAV-based construction monitoring, AI in construction, Energy efficiency optimization, Smart infrastructure, UAV communication networks, AI driven site management.