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۱An Adaptive Kalman Based Data Filtering Technique for Wireless Sensor Networks
نویسنده(ها):
اطلاعات انتشار: World Applied Sciences Journal، بيست و نهم،شماره۱۱، ۲۰۱۴، سال
تعداد صفحات: ۵
The research field of wireless sensor networks is a challenging area of engineering and science. Sensor nodes encompass numerous small battery powered autonomous device. The deployment of sensor node is subject to various type of harsh environment. Once the node senses the event that has occurred in the particular place, it has to transmit the data. The sensed data is passed to the cluster head. The cluster head will perform data aggregation to eliminate the redundant data. The sensed information will contain the noise due to the certain environment factors. The noise may lead to inaccurate result which may cause serious problem. To overcome the problem we have presented an Adaptive Kalman Filter (AFK) by which the noise is removed by predicting and correcting factors. The prediction and correction is done based upon the estimated value. This process is repeated recursively until we get an accurate value. At final the information is passed to the base station by using a TDMA slot to avoid collision among data. Thus we will be getting an accurate data in the base station.
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