Abstract: Smart construction management harnesses artificial intelligence (AI) to address inefficiencies and challenges in modern construction projects, enhancing scheduling, resource allocation, and decision-making processes. By leveraging AI technologies such as machine learning (ML), natural language processing (NLP), and computer vision, construction managers can optimize workflows, monitor progress in real-time, and predict potential issues before they occur.
This research explores how AI-driven tools transform key aspects of construction management, from improving safety and quality control to reducing costs and delays. Case studies highlight the practical applications of AI, including predictive maintenance, dynamic task adjustments, and automated inspections, demonstrating significant improvements in project outcomes. Despite its benefits, the adoption of AI in construction faces challenges such as data integration, high implementation costs, and the need for specialized skills. The paper discusses potential solutions to these challenges and outlines future opportunities for AI in smart construction management.
Keywords: Artificial Intelligence, Smart Construction Management, Machine Learning, Natural Language Processing, Computer Vision, Predictive Analytics, Resource Allocation, Real-Time Monitoring, Safety Management, Construction Optimization.
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