Ontology-Based Knowledge Model to Support Construction Noise Control in China

Abstract

Construction noise control (CNC) is the process of identifying potential noise emissions and establishing noise-abatement plans to mitigate pollution impacts, a process that requires interdisciplinary knowledge and project-specific information. This study introduces an ontological approach to structure all known information on noise control with regard to construction operations, aiming to improve access to knowledge relating to CNC planning. More importantly, information that can be used to analyze the potential influences of noise-abatement measures in terms of costs, schedules, and technical rules is also considered in order to facilitate integrated decision making by outlining various outcomes for each alternative. Literature and expert reviews were conducted to identify the critical concepts and interrelationships between the method statement and the noise-control plan. Consequently, an ontology-based semantic model for CNC planning is presented as a modeling framework, which could be further enriched with more operational knowledge considering the specific purpose of an individual CNC plan. The prototype is applied to excavation construction to illustrate how CNC knowledge can be stored and reused through ontological and semantic web techniques.