University of Houston

University of Houston has various monitoring systems that feed information to Emergency Operations Centers for emergency decisions. Emergency decisions must be made utilizing the information available to Emergency Operations Center which is received from different sensors feeding the information. All the information systems in the University are disparate and do not communicate with each other. These enterprise systems are independent with no integrated view. Most of the systems operate on and store same information about campus and people while using various models appropriate to their operational needs. As the monitoring systems are not integrated with each other, it becomes difficult to estimate the level of emergency by considering the incidents occurring at the individual systems.

In this Thesis, we realized a data model design to enable an aggregation framework in time-sensitive decision support systems. We propose a framework for aggregating the data available through the information sources towards achieving an integrated view. The standard used for integrating the various systems is IF-MAP (Interface for Metadata Access Point) Standard. Using the Publish – Subscribe communication paradigm and aggregating the data based on time window and location, disparate data sources can be integrated and effective communication between the systems can be achieved which helps in taking the emergency decisions. The decision can now be based on effective utilization of all the systems involved in the particular incident. Aggregation has been performed on various sources of information like Police Dispatch system, card access system, video feeds and general facilities system at University of Houston.