Fuzzy Centrality Analysis for Smart City Trajectories

Abstract

Space entities in smart city are directly concerned with the detection, location and identification of people to ensure safety and comfort requirements. A variety of sensors, actuators and appropriate analytical methods and architecture are proposed to process large data volume from sensor networks and to discover knowledge patterns to act accordingly. In this work, a solution based on fuzzy centrality to monitor and control the strategy of analyzing persons movement of people in intelligent spatial entities based on trajectories gathered from outdoor spaces, is proposed. We used structural analysis techniques and fuzzy graphs to determine the fuzzy centrality of trajectories. The fuzzy centrality developed in this paper is based on the lattice of fuzzy transitive relations max-min or max- The modeling of the outdoor trajectories is also an undeniable contribution of this work. Our meta-model integrates the OGC CityGML to represent and enable the exchange of geoinformations necessary for the construction and operation of outdoor navigation systems to produce person’s trajectories. We also describe the framework based on microservices to carry out this work.