BeTelGeuse: A Platform for Gathering and Processing Situational Data
IEEE Pervasive Computing
GAMPS: compressing multi sensor data by grouping and amplitude scaling
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
OTM '09 Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond SAWSDL, and COMBEK 2009
WISS'10 Proceedings of the 2010 international conference on Web information systems engineering
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Mobile conveniences generate much of sensor data in company with the persons. Some of sensor data are required for processing at distant places in which the sensor data are aggregated, for capabilities of smartness. In the case of vehicles the sensor data are transmitted for malfunction detection and health monitoring of the vehicle in near future. The sensor data are substantially large in the amount of one vehicle's data by multiple kinds of sensors, and the amount of a number of vehicles' data gathered is huge to be received concurrently at some server. Further when the gathered data would be aggregated in one system, the management of the enormous data could determine the functionality of the system. In this work, a data abbreviation diminishes the amount to be transmitted, and data negating a valid extent consist the majority of data to be aggregated, exploiting the semantics of the sensor data gathered. This method is far different from the conventional compressions. The aggregated data are managed and displayed when necessary in one system tracing faulty cars in a region.