SecurityWorldMarket

17/07/2024

Senstar offers 5 step guide on eliminating false alarms

Ottawa, Canada

The team at Senstar has investigated the common causes of nuisance alarms generated by outdoor perimeter intrusion detection sensors with a particular focus on those generated by fence sensors and intrusion-detecting video analytics. 

After deeper analysis, they came up with a five step set of general recommendations aimed at reducing or even defeating nuisance alarms once and for all, here we look at a summary of their findings.

1. Maintain you perimeter

A well-maintained perimeter is the first step in eliminating nuisance alarms. Perform a perimeter survey and identify potential security issues and risks, for example, the condition of the fence, the position of the surrounding buildings and trees, and if used, ensure the coverage of the cameras is complete and unobstructed.

2. Work with industry experts

Before deciding on any specific technology, look for system integrators, consultants and vendors with proven track records. When deployed in the real-world, security systems need to contend with a wide variety of potential nuisance alarm sources. Experienced security professionals in your particular domain can help as they should understand the requirements. Ensure the installers, vendors and operators are certified and trained on the right systems. A poorly installed system will almost certainly generate a far higher number of nuisance alarms.

3. Select appropriate technology

While there are many types of sensor technologies that protect perimeters, some are niche solutions while others have a general appeal. The factors to consider when selecting a system should include, probability of detection – look for speed, reliability and accuracy; nuisance alarm rate – high rates of nuisance alarms can result in response complacency; ease of installation and can it be configured remotely; integration options - consider other technology that you might want to integrate with it such as VMS and cameras; consider the alarm communication methods, and ensure it includes things like mapping, precise alarm location - and other situational awareness tools.   

4. Conduct periodic site audits

An often-overlooked part of reducing nuisance alarms is periodic site audits. Over time, new site characteristics may be introduced that negatively affect the overall performance of the on-site systems. For example, almost all the points in step one should be regularly checked, fence condition, surrounding vegetation, new buildings, and new vehicle routes etc.

5. Eliminate common causes

During the testing or lifespan of any system, problems may arise. For systems to remain operating at maximum performance, they need to include the features and tools necessary for operators and technicians to quickly locate and resolve issues.

For intrusion sensors, several features are critical to address the causes of nuisance alarms, the first being covered in step 3, precise location reporting.  However, the system should also be able to deal with environmental disaggregation such as heavy winds, for example.  Ranging sensors like the Senstar Fiberpatrol, Flexzone, and the Senstar LM100 are able to recognise these disturbances as non-intrusions and so do not trigger an alarm. According to Senstar, Sensors should also include intelligent signal processing that recognises disturbances generated by environmental forces, sudden changes in lighting, and high-activity sources (e.g. traffic, trains, etc) and reject them accordingly.


Combined intelligence offers highest detection capabilities

For sites that suffer from frequent nuisance alarms or require the highest probability of detection possible, the Senstar team recommends its new Sensor Fusion Engine (part of the Senstar Symphony Common Operating Platform), a so-called breakthrough technology that synthesises data from separate systems to generate actionable information. More than just a simple Boolean logic integration, the sensor fusion engine accesses low level data from both fence sensors and video analytics to intelligently characterise potential risks. This data synthesis enables the system to achieve a level of performance that exceeds those of the individual sensors while defeating nuisance alarms once and for all.



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