ITR: Collaborative Research: Real-time Capture, Management and Reconstruction of Spatio-Temporal Events

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With the advances in embedded processors, low cost sensor technologies, and wireless communication, unprecedented amounts of diverse types of information about the real world and its activities are being generated. Much of the information is spatio-temporal in nature; concerning objects dispersed in space and time, and interacting and communicating with each other and their surroundings. An infrastructure that facilitates real-time capture, storage, processing, display, and analysis of the information generated will truly revolutionize a wide variety of application domains. Examples of domains that will benefit from this technology include avionics, ground traffic, commercial applications such as ship-ping and transportation, emergency response and disaster relief operations, physical phenomenon such as weather and storm tracking, forest fire tracking, migration patterns of animals/birds, command and control, smart environments, etc. Applications in the above domains require real-time monitoring, tracking and analysis of objects/events/phenomena in space and time. An integral component of such sensor enriched communication and information infrastructure is a database management technology that allows seamless access to information dispersed across a hierarchy of storage, communication and processing units - from sensor devices, where data originates, to large data banks where the information generated is stored for analysis and mining. This research will explore next generation database management system technology that provides effective support for information processing in highly distributed and dynamic sensor-enriched environments. The approach taken will be end-to-end - that is, research will be conducted on all aspects of the system ranging from representation, data modeling, query languages, data structures, query optimization, query processing, distribution, and concurrent accesses. A prototype database management infrastructure that supports highly dynamic geographically dispersed spatio-temporal data, multi-resolution representation of data, and provides effective support for visualization and analysis will be developed.