Infrastructure management decision-making with condition data generated by remote sensors: a time series framework

Abstract

Recent developments in remote sensing and communications technologies allow agencies to install sensors within infrastructure facilities, such as pavement segments and bridges in order to collect condition-related data in real-time. In theory, such data can be processed, analyzed and displayed on-line as a key component for maintenance, and repair decision-making. The reality facing public works agencies that have adopted these technologies is that vast amounts of data related to the structural and functional condition of infrastructure are accumulated, but not used to address management needs. The research presented herein, therefore, is to develop methodological tools to support the management of transportation infrastructure systems given recent developments in facility-condition data collection technologies. In particular, the objectives of this research study are to develop tools that will allow agencies to process and exploit the data to support IM\&R decision-making, and to provide a framework to evaluate different strategies for deploying sensing technologies.