Abstract

Discrete Event Simulation (DES) is an effective method to study cyclic and uncertain projects at the operation level. However, qualified DES results highly depend on the input data quality. This paper describes a simulation-enabled context-aware Decision Support System (DSS) based on sensor fusion to model earthwork operations realistically. The DSS backbone is a DES continually updated using real-time data. The information on earthmoving operations is exchanged between reality and DES using GPS and equipment-mounted cameras. The equipment spatiotemporal data and shovel-mounted cameras enhance the DES quality (i.e., locational and contextual awareness) by providing timely information about task durations, load types, and bucket teeth status. Sensor data is fused and fed into the DES model to replicate the earthmoving project. The proposed method is successfully implemented and validated in a large-scale earthmoving case study. The developed DES is proven promising as a reliable DSS for enhancing resource allocation and time-cost reduction.

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