Developing Control Charts for Statistical Monitoring of a Dynamic Network of Emergency Service

Nowadays, statistical analysis and monitoring of networks and early detection of anomalies with a significant growth rate have received more attention than before in recent years. In the real world, there is a wide range of networks analyzed and improved through network monitoring solutions, such as transportation, supply-demand, financial exchanges, health care, as well as the social ones, the analysis of the results can be beneficial to the stakeholders. The basis of the research is on identifying and solving the real problem. In other words, a real problem is identified in the country and a methodology is developed to solve it. The case study is the monitoring of a network of centers that provide emergency services in cities. The nature of this network is dynamic, feature-based, directed and weighted. The results of this study show that by modeling complex systems as a network and its continuous monitoring, abnormal situations can be identified and managed early and crises in cities can be prevented.