Tracking Moving Object using WSN and Compression

Studies in location-acquisition technologies, such as and wireless sensor networks (WSNs) and global positioning systems (GPSs), have fostered many novel applications like object tracking, environmental monitoring, and location-dependent service. These applications generate a huge amount of location data, and hence lead to transmission and storage challenges, especially in resource constrained environments like WSNs. To reduce the data volume, various algorithms have been proposed for data compression and data aggregation. However, the above works do not approach application-level semantics, such as the group relationships and movement patterns, in the location data. Natural phenomena show that many creatures from large social groups and move in regular patterns. However, previous works focus on finding the movement patterns of each single object or all objects. In this paper first propose an efficient predict, next algorithm to jointly identify group of moving objects and discover their movement patterns in wireless sensor networks. Then we propose compression algorithm known as merging algorithm to merge and compress the location data of group of moving objects.