A Supervised Machine Learning-Based Sound Identification for Construction Activity Monitoring and Performance Evaluation
The sound recognition technology, which has been adopted in diverse disciplines, has not received much attention in the construction industry. Since each working and operation activity on a construction site generates its distinct sound, its identification provides imperative information regarding work processes, task performance, and safety relevant issues. Thus, the accurate analysis of construction sound data is vital for construction project participants to monitor project procedures, make data-driven decisions, and evaluate task productivities.