Application of dynamic time warping to the recognition of mixed equipment activities in cycle time measurement

Abstract

Analyzing and measuring construction equipment operation are key tasks for managing construction projects. In monitoring construction equipment operation, the cycle-time provides fundamental information. Traditional cycle-time measurement methods have been limited by requiring significant efforts such as additional observers, time, and cost. Thus, this study investigates the feasibility of measuring cycle times by using inertial measurement units (IMUs) embedded in a smartphone. Because the mixed activities of construction equipment involve simultaneous actions of multiple parts, they cause low accuracy in equipment activity classification and cycle-time measurement. To enhance the recognition of these mixed activities and translate the results into reliable cycle time measurements, a dynamic time warping (DTW) algorithm was applied and the DTW distances of IMU signals were used as additional features in activity classification. To test its feasibility, data was collected on-site and the excavator's operation was recorded via IMUs embedded in a smartphone attached to a cabin. Using DTW, the suggested method achieved 91.83% accuracy for cycle-time measurement. This result demonstrates an opportunity to use operators' prevalent mobile devices to measure and report their equipment's cycle times in a cost-effective and continuous manner.