Safety intelligence toward safety management in a big-data environment: A general model and its application in urban safety management

Abstract

In recent years, safety intelligence, as a new area of safety science, has emerged as the backbone of safety management, thus receiving increasing research attention. Furthermore, big data and other related technologies have exerted considerable influence on safety intelligence and safety management. This study presents this influence of big data on safety intelligence sources, technologies, methodologies, and management systems, and an analysis of the challenges in traditional safety management. Safety intelligence is confirmed to be an important factor that influences safety management (particularly decision-making). A new research paradigm has emerged, namely, intelligence-led safety management (ILSM), which exemplifies the profound influence of safety intelligence on safety management. The value of ILSM and the function of big data in ILSM are also discussed in this study. Based on the concept, definition, connotation, and other relevant knowledge of safety intelligence, a model for ILSM in a big-data environment is proposed. The model involves safety information, data acquisition, and safety intelligence and ILSM processes, aiming to guide the implementation of ILSM in a big-data environment. In addition, an intelligent urban safety management system is mentioned as an application case.