Adaptive behaviour for a self-organising video surveillance system using a genetic algorithm
Publiceringsår
2021
Upphovspersoner
Saffre, Fabrice; Hildmann, Hanno
Abstrakt
Genetic algorithms (GA’s) are mostly used as an offline optimisation method to discover a suitable solution to a complex problem prior to implementation. In this paper, we present a different application in which a GA is used to progressively adapt the collective performance of an ad hoc collection of devices that are being integrated post-deployment. Adaptive behaviour in the context of this article refers to two dynamic aspects of the problem: (a) the availability of individual devices as well as the objective functions for the performance of the entire population. We illustrate this concept in a video surveillance scenario in which already installed cameras are being retrofitted with networking capabilities to form a coherent closed-circuit television (CCTV) system. We show that this can be conceived as a multi-objective optimisation problem which can be solved at run-time, with the added benefit that solutions can be refined or modified in response to changing priorities or even unpredictable events such as faults. We present results of a detailed simulation study, the implications of which are being discussed from both a theoretical and practical viewpoint (trade-off between saving computational resources and surveillance coverage).
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Teknologiska forskningscentralen VTT Ab
Saffre Fabrice
Publikationstyp
Publikationsform
Artikel
Moderpublikationens typ
Tidning
Artikelstyp
En originalartikel
Målgrupp
VetenskapligKollegialt utvärderad
Kollegialt utvärderadUKM:s publikationstyp
A1 Originalartikel i en vetenskaplig tidskriftPublikationskanalens uppgifter
Journal
Volym
14
Nummer
3
Artikelnummer
74
ISSN
Publikationsforum
Publikationsforumsnivå
1
Öppen tillgång
Öppen tillgänglighet i förläggarens tjänst
Ja
Öppen tillgång till publikationskanalen
Helt öppen publikationskanal
Licens för förläggarens version
CC BY
Parallellsparad
Nej
Övriga uppgifter
Vetenskapsområden
Matematik; Data- och informationsvetenskap
Nyckelord
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Språk
engelska
Internationell sampublikation
Ja
Sampublikation med ett företag
Nej
DOI
10.3390/a14030074
Publikationen ingår i undervisnings- och kulturministeriets datainsamling
Ja