In light of the many high-profile school tragedies that have scarred the US, strong safety and security for educational facilities has become paramount.
As a result, many universities and municipalities have increased security budgets for educational institutions in an effort to create the safest possible environment for students and staff.
Conventional access control and video surveillance systems are often the first solutions schools turn to. However, technological advances have provided schools with the opportunity to deploy innovative, leading-edge solutions to improve the effectiveness of existing security equipment and practices.
One such technology is the panoramic video surveillance camera, which delivers either 180- or 360-degree views of a location. Properly placed, these cameras can monitor an entire, wide area, eliminating blind spots.
Given the many benefits panoramic cameras offer, schools are increasingly deploying them in an effort to enhance security while also reducing equipment costs – covering more territory with fewer cameras reduces up-front equipment investment.
A drawback of video surveillance is that, regardless of how advanced a camera is, video must be monitored to be truly effective. Unfortunately, employing a person to actively monitor video feeds is often cost-prohibitive, meaning that most cameras are only used for post-incident investigation. This significantly limits their effectiveness for protecting schools.
AI could transform video surveillance into a proactive, rather than reactive, solution
Artificial intelligence (AI) could overcome this shortcoming and become a force multiplier, transforming video surveillance into a proactive, rather than reactive, solution. Advances in machine learning have improved video and data analytics to facilitate this shift.
For example, using the combination of analytics and machine learning, AI technology is capable of scanning video data from cameras to identify anomalies, such as certain behaviours, individuals who are not authorised to be in the building, objects left behind in an area and more.
As the AI solution continues to learn, it identifies actions or anomalies – or a combination thereof – that may indicate a potential threat or imminent attack. The solution then applies that learning to its ongoing scans, and can alert proper authorities instantly when one or more of those anomalies are detected.
This serves as an early warning system that enables a proactive response that could prevent an incident from occurring.
Integration with video and access control is another way AI can improve school safety and security. Based on the nature and severity of an anomaly detected in the video stream, an AI solution could automatically initiate a lockdown much more quickly than staff.
In an emergency, every second may count, and in some cases, video-initiated lockdowns could save lives.
The only limitation on potential uses of AI and machine learning solutions for boosting security and video surveillance may be the developers’ imagination.
It’s conceivable, for instance, that these technologies could be employed for use with unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) – also known as drones.
With these tools, security personnel could increase security personnel’s ability to cover and monitor large campuses. These solutions would also prove invaluable for providing law enforcement and first responders with situational awareness to ensure the safest, most effective response to incidents.
Because the nature of threats and risk schools and universities face is constantly evolving, the security solutions they employ must evolve along with them. By incorporating advanced video surveillance cameras in concert with video analytics, machine learning and AI technologies, schools can provide the most robust protection for students and staff.
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