PSAM 16 - Paper Overview

PSAM 16 Conference Paper Overview

Welcome to the PSAM 16 Conference paper and speaker overview page.

Lead Author: John Russell Co-author(s): Carl Stern Carl_Stern@mgtsciences.com

Advancing Intrusion Detection Sensor Performance Using Deliberate Motion Analytics
Excessive Nuisance Alarm Rates (NAR) are a major issue for all exterior intrusion detection systems. Sites with problematic sensor systems can experience an excessive number of nuisance alarms per day as a result of weather, animals, and other natural occurrences causing security personnel to become complacent to sensor alarm, thereby undermining sensor system detection capability. All sites that are utilizing current commercial systems are believed to experience elevated NAR. In addition to being susceptible to nuisance alarms, the cost to purchase and install exterior sensors in security perimeters is very high. Sandia National Laboratories has developed a sensor algorithm that exploits deliberate motion to differentiate alarms caused by an intruder from those caused by other natural occurrences. The Deliberate Motion Analytics (DMA) algorithm is capable of fusing multiple sensors, such as radar, lidar, buried line sensors, microwaves, and video, to provide reliable detection. Preliminary results show that DMA will significantly reduce nuisance alarm rates even when sensors are set to very sensitive detection thresholds. This technology will allow the creation of next generation security architectures that will significantly drive down purchasing and installation costs by an estimated 50%.

Advancing Intrusion Detection Sensor Performance Using Deliberate Motion Analytics

Excessive Nuisance Alarm Rates (NAR) are a major issue for all exterior intrusion detection systems. Sites with problematic sensor systems can experience an excessive number of nuisance alarms per day as a result of weather, animals, and other natural occurrences causing security personnel to become complacent to sensor alarm, thereby undermining sensor system detection capability. All sites that are utilizing current commercial systems are believed to experience elevated NAR. In addition to being susceptible to nuisance alarms, the cost to purchase and install exterior sensors in security perimeters is very high. Sandia National Laboratories has developed a sensor algorithm that exploits deliberate motion to differentiate alarms caused by an intruder from those caused by other natural occurrences. The Deliberate Motion Analytics (DMA) algorithm is capable of fusing multiple sensors, such as radar, lidar, buried line sensors, microwaves, and video, to provide reliable detection. Preliminary results show that DMA will significantly reduce nuisance alarm rates even when sensors are set to very sensitive detection thresholds. This technology will allow the creation of next generation security architectures that will significantly drive down purchasing and installation costs by an estimated 50%.

PSAM 16 Conference Paper Overview

Welcome to the PSAM 16 Conference paper and speaker overview page.

Paper JL284 Preview

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