Spatio-temporal enabled urban decision-making process modeling and visualization under the cyber-physical environment

Abstract

Urban management is increasingly dependent on the construction of cyber-physical systems, which have been widely deployed in multiple fields, including agriculture, transportation, and health care. Cyber-physical systems provide a large volume of big sensory data. Thus, the application of big data for urban emergency decision-making has become a challenge. Traditional decision-making models are unable to overcome several technical problems, including spatio-temporal information support and access to real-time service for disaster management and emergency response. In this paper, we propose a spatio-temporal enabled urban decision-making process modeling method in the cyber-physical environment and discuss the development off our basic metadata components, the definition of eleven-tuple information description structure. A prototype system is designed for modeling registering, management, visualization, and other functions. Decision-making processes are implemented as composite process chains through three phases, i.e., decision-making process modeling, instantiation of the decision-making process chain and execution of the decision-making process chain. For application to gas leak events, the decision-making process is executed to confirm the feasibility of the proposed decision-making process modeling method and the flexibility of the eleven-tuple information structure.