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Secured Perimeter with Electromagnetic Detection and Tracking with Drone Embedded and Static Cameras

Authors :
Universidad de Sevilla. Departamento de Ingeniería Electrónica
Teixidó, Pedro
Gómez Galán, Juan Antonio
Caballero, Rafael
Pérez Grau, Francisco Javier
Hinojo Montero, José María
Muñoz Chavero, Fernando
Aponte, Juan
Universidad de Sevilla. Departamento de Ingeniería Electrónica
Teixidó, Pedro
Gómez Galán, Juan Antonio
Caballero, Rafael
Pérez Grau, Francisco Javier
Hinojo Montero, José María
Muñoz Chavero, Fernando
Aponte, Juan
Publication Year :
2021

Abstract

Perimeter detection systems detect intruders penetrating protected areas, but modern solutions require the combination of smart detectors, information networks and controlling software to reduce false alarms and extend detection range. The current solutions available to secure a perimeter (infrared and motion sensors, fiber optics, cameras, radar, among others) have several problems, such as sensitivity to weather conditions or the high failure alarm rate that forces the need for human supervision. The system exposed in this paper overcomes these problems by combining a perimeter security system based on CEMF (control of electromagnetic fields) sensing technology, a set of video cameras that remain powered off except when an event has been detected. An autonomous drone is also informed where the event has been initially detected. Then, it flies through computer vision to follow the intruder for as long as they remain within the perimeter. This paper covers a detailed view of how all three components cooperate in harmony to protect a perimeter effectively, without having to worry about false alarms, blinding due to weather conditions, clearance areas, or privacy issues. The system also provides extra information of where the intruder is or has been, at all times, no matter whether they have become mixed up with more people or not during the attack.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1367076390
Document Type :
Electronic Resource