Implementation of You Only Look Once (YOLO) Technology and Reinforcement Learning for Web-Based Project Monitoring

Project monitoring is an important element in project management that aims to ensure project implementation in accordance with the plan, schedule, budget, and objectives that have been set. The ineffectiveness of project monitoring can cause various problems, such as delays, cost overruns, inappropriate quality of results, and poor communication between stakeholders. To address these issues, technological advances such as YOLO (You Only Look Once) and Reinforcement Learning (RL) offer innovative solutions through real-time visual detection and data-driven automated decision making. This research aims to develop a web-based project monitoring system that integrates YOLO to detect activities in the field, such as workers and heavy equipment, and RL to provide optimal recommendations for resource management. The implementation of the system is expected to increase efficiency, reduce risk, and support more accurate decision making. Based on previous research, the adoption of AI technology in project monitoring is proven to reduce operational costs and increase productivity. This web-based system is designed to provide flexibility and accessibility, allowing users to monitor projects in real-time through an interactive interface. The expected outcome of this research is the creation of an effective technological solution to improving the efficiency of construction project management, as supported by the findings of previous research that shows the great potential of AI in the construction sector.