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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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Publikationstyp

Publikationsform

Artikel

Moderpublikationens typ

Tidning

Artikelstyp

En originalartikel

Målgrupp

Vetenskaplig

Kollegialt utvärderad

Kollegialt utvärderad

UKM:s publikationstyp

A1 Originalartikel i en vetenskaplig tidskrift

Publikationskanalens uppgifter

Volym

14

Nummer

3

Artikelnummer

74

Publikationsforum

75024

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