Geostatistical Modelling of the Scallop Density Distribution in Shark Bay, Western Australia from Survey Data
Document Type
Conference Proceeding
Faculty
Faculty of Computing, Health and Science
School
School of Engineering
RAS ID
5704
Abstract
In this paper we propose a strategy based on antecedent values provided by each sensor for detecting their malicious activity. We compare at each time moment the sensor’s output with its estimated value computed by a robust autoregressive neural predictor. In case that the difference between the two values is higher then a chosen threshold, the sensor node becomes suspicious and a decision block is activated.
Comments
Mueller, U., Dickson, J., Kangas, M., & Caputi, N. (2008). Geostatistical Modelling of the Scallop Density Distribution in Shark Bay, Western Australia from Survey Data. Geostats 2008: Proceedings of the Eigth International Geostatistics Congress.