Threshold Based Data Aggregation Algorithm To Detect Rainfall Induced Landslides

Landslides are one of the environmental disasters that cause massive destruction of human life and infrastructure. Real time monitoring of a landslide prone areas are necessary to issue fore warning. To accomplish real time monitoring, massive amount of data have to be collected and analyzed within a short span of time. This work has developed a method for effective data collection and aggregation by implementing threshold alert levels. The sampling rates of threshold alert levels will determine amount of data collected and aggregated which will reduce the power consumption by each wireless sensor nodes. This work also helps to determine the appropriate sampling rates for each threshold level, and the expected number of data packets in the queue. The time delay in receiving the data packet at the analysis station can be determined by using the value of expected number of data packets in the queue.

• Type: Conference
• Year: 2008
• Where: ICWN
• Authors: Ramesh Maneesha, P. Ushakumari
• Keywords: Data Packets, ICWN 2008, Real Time Monitoring, Threshold Alert Levels, Wireless Networks