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dc.contributor.authorKangethe, Michael Maigwa Martin
dc.date.accessioned2013-02-19T08:10:37Z
dc.date.issued2012
dc.identifier.citationMasters of science in computer scienceen
dc.identifier.urihttp://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/10200
dc.description.abstractThis is the study and implementation of a mass population interaction surveillance technology framework, using the Radial Based Functions Algorithm using the Radio based (Cellular to be specific) network and to develop surveillance systems strategy. Which enables the efficient and automated identification of entity interactions and potential relationships between several entities and events based on a hierarchy of interactions? The scientific approach to this problem is to combine a modified variation of the Radial Basis Functions algorithm computing theory to develop a computing system that enables the tracking of individual entity’s relationship with others based on their interaction judged by their proximity to the entity of interest as the future of automated surveillance will not just include the collection of geographic and visual data but also intelligence on the particular entity’s interaction log information from activity patterns which can be mapped in an easy to present format to the interested parties.en
dc.language.isoenen
dc.publisherUniversity of Nairobien
dc.subjectSurveillanceen
dc.subjectradial based functionsen
dc.subjectcellular based networksen
dc.titleSurveillance strategy using a variance of radial based functions for cellular based networksen
dc.typeThesisen
local.publisherSchool of Computing and Informaticsen


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