Page 32 - Campus Security & Life Safety, October 2018
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ADVANCED TECHNOLOGY
Even for incidents involving individuals who have exhibited no prior warning signs, machine learning offers end users the capability to spot suspicious behaviors that could be an indicator of a potential attack. Say, for instance, a campus has a clear backpack or even a no backpack policy and someone shows up carrying a duffle bag or rifle case, AI-powered surveillance software would be able to quickly deter- mine that such behavior is abnormal for the campus and alert the proper authorities. Once AI software has been given an opportunity to study a dataset over a period of time, it can easily identify when an anomaly occurs.
Another benefit of deploying AI in schools is that it provides return- on-investment beyond security, which is something that has proved elusive for much of the rest of the industry.
ALTERNATIVE USES FOR SECURITY AI ON CAMPUS
Although the primary application of AI and machine-learning solu- tions today is to bolster the effectiveness of video surveillance systems and those tasked with monitoring them, the use cases for this technol- ogy continue to evolve. Among these include robotics in the form of unmanned ground vehicles (UGVs), unmanned aerial vehicles (UAVs), more commonly referred to as drones, and various standalone solutions, such as stationary towers.
Robotics are not only a cost-effective force multiplier given their relatively low deployment costs compared to human guards and police officers, but they can also serve a multitude of purposes beyond just video surveillance. Imagine, for typical day-to-day operations, having a tower outfitted with a number of megapixel cameras and/or high resolution touchscreen monitor that could serve as an emergency communications station and also provide a variety of information, such as bus routes and campus maps. During an actual emergency or when the school is closed, however, the tower could serve as an exten- sion of the video surveillance system and leverage AI to identify peo- ple, vehicles, etc.
The same also holds true for UGVs and UAVs. Whereas in the past human operators would be needed to analyze and make decisions
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based on the information collected via video and other security sen- sors, robots with built-in AI capabilities can now process data and make determinations about what is and what is not a security risk on their own and thereby reduce the demand on human capital. In the wake of the shootings at Parkland and Santa Fe, Texas, there has been a push among lawmakers across the nation to increase the number of police officers and security personnel patrolling the halls and cam- puses of K-12 schools, but having additional manpower is an expensive proposition and much more so over the long-term when compared to using AI-powered unmanned vehicles.
MOVING BEYOND SECURITY
The uses of AI also do not have to just be limited to security within the education market but could be expanded upon to become a solution to improve the overall learning environment. In schools where cameras have been placed in the classroom to ensure appropriate behavior from students and faculty, AI is already being leveraged to help improve teacher development.
Rather than have a person serve as an intrusive classroom observer, surveillance footage can be utilized to help staff see what teaching strategies and methodologies are the most effective for their students. Some may argue that having video cameras in classrooms creates an uncomfortable environment and is invasive but it doesn’t have to be viewed as a tool of “Big Brother.” Rather, it should be seen as an oppor- tunity to keep students and teachers safe, while also serving to help teaches strive for excellence.
AI and machine learning are undoubtedly going to be a critical part of video surveillance moving forward and
it’s incumbent upon schools to learn how they
can take advantage of it to improve safety and
boost the effectiveness of teachers and educa- tional experiences of students.
Jumbi Edulbehram is the Regional President, Americas for OnCam.
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