A Classable Indexing of Data Condensed Semantically from Physically Massive Data Out of Sensor Networks on the Rove

Abstract

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.