Browsing by Author "Weeraddana, D. M"

Filter results by typing the first few letters
Now showing 1 - 3 of 3
  • Thumbnail Image
    PublicationOpen Access
    Dempster–Shafer information filtering framework: Temporal and spatio-temporal evidence filtering
    (IEEE, 2015-06-04) Weeraddana, D. M; Kulasekere, E. C; Walgama, K. S
    This paper presents an information processing framework for distributed sensor networks. The framework is capable of directly processing temporally and spatially distributed multimodality sensor data to extract information buried in the noise clutter. Moreover, we introduce distributed algorithms to implement spatio-temporal filtering applications in grid sensor networks within the context of the framework. The proposed framework is based on the belief notions in Dempster-Shafer (DS) evidence theory and evidence filtering method. Further analysis is done by exploiting a fire propagation scenario when high noise is present in the sensed data. We compare intuitively appealing results against DS fusion method to grant further credence to the proposed framework.
  • Thumbnail Image
    PublicationEmbargo
    Dempster–Shafer information filtering framework: Temporal and spatio-temporal evidence filtering
    (IEEE, 2015-06-04) Weeraddana, D. M; Kulasekere, E. C; Walgama, K. S
    This paper presents an information processing framework for distributed sensor networks. The framework is capable of directly processing temporally and spatially distributed multimodality sensor data to extract information buried in the noise clutter. Moreover, we introduce distributed algorithms to implement spatio-temporal filtering applications in grid sensor networks within the context of the framework. The proposed framework is based on the belief notions in Dempster-Shafer (DS) evidence theory and evidence filtering method. Further analysis is done by exploiting a fire propagation scenario when high noise is present in the sensed data. We compare intuitively appealing results against DS fusion method to grant further credence to the proposed framework.
  • Thumbnail Image
    PublicationOpen Access
    Dempster-Shafer Information Filtering in Multi-Modality Wireless Sensor Networks
    (publications.waset.org, 2013-07-27) Weeraddana, D. M; Walgama, K. S; Kulasekere, E. C
    A framework to estimate the state of dynamically varying environment where data are generated from heterogeneous sources possessing partial knowledge about the environment is presented. This is entirely derived within Dempster-Shafer and Evidence Filtering frameworks. The belief about the current state is expressed as belief and plausibility functions. An addition to Single Input Single Output Evidence Filter, Multiple Input Single Output Evidence Filtering approach is introduced. Variety of applications such as situational estimation of an emergency environment can be developed within the framework successfully. Fire propagation scenario is used to justify the proposed framework, simulation results are presented.