A low cost fence impact classification system with neural networks

Author

de Vries, J.

Author_Institution

French South African Tech. Inst. in Electron., Pretoria

Volume

1

fYear

2004

fDate

17-17 Sept. 2004

Firstpage

131

Abstract

Due to a high rate in live stock theft and farm intrusions, securing property is a problem in South Africa. Research is necessary to investigate possible improvements. By analyzing the acoustical vibrations that are generated on a game farm or security fence during entry, intrusions can be detected. Owners of protected property can receive an early warning. Different type of intrusions can be distinguished since they generate different vibrations. A point sensor is used to detect vibrations generated at a distance from the sensor. This proposed system is part of a more elaborate farm information system and is not intended to function as a stand-alone security system

Keywords

acoustic signal processing; alarm systems; neural nets; safety systems; signal classification; vibration measurement; acoustical signal classification; farm information system; farm intrusions; fence mount sensors; game farm; intrusion detection; live stock theft; low cost fence impact classification system; neural networks; perimeter protection; point sensors; property security; security fence; vibration measurement; vibration sensors; Acoustic sensors; Acoustic signal detection; Africa; Cameras; Costs; Information security; Neural networks; Protection; Sensor systems; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

AFRICON, 2004. 7th AFRICON Conference in Africa

Conference_Location

Gaborone

Print_ISBN

0-7803-8605-1

Type

conf

DOI

10.1109/AFRICON.2004.1406647

Filename

1406647