Wireless sensor networks for monitoring the environmental activities

The area of sensor network has a long history and many kind of sensor devices are used in various real life applications. Here, we introduce Wireless sensor network which when combine with other areas then plays an important role in analyzing the data of forest temperature, bioinformatics, water contamination, traffic control, telecommunication etc. Due to the advancement in the area of wireless sensor network and their ability to generate large amount of spatial/temporal data, always attract researchers for applying data mining techniques and getting interesting results. Wireless sensor networks in monitoring the environmental activities grows and this attract greater interest and challenge for finding out the patterns from large amount of spatial/temporal datasets. These datasets are generated by sensor nodes which are deployed in some tropical regions or from some wearable sensor nodes which are attached with wild animals in wild life centuries. Sensor networks generate continuous stream of data over time. So, Data mining techniques always plays a vital role for extracting the knowledge form large wireless sensor network data. In this paper, we present the detection of sensor data irregularities, Sensor data clustering, Pattern matching and their interesting results and with these results we can analyze the sensor node data in different ways.