As the last decade has shown, schools and universities across the US need much better security management and campus monitoring than what is present today.

Mass school shootings and tragic life-loss can be prevented with the use of computer vision-based intruder detection tools on campuses.

The 2010s witnessed an unprecedented number of school shooting incidents across the US. Tragically, hundreds of innocent students, teachers and staff fell victim to such incidents. Poorly-managed security protocols and poor monitoring of school and university campuses are some of the main reasons for the repeated occurrence of such incidents. While adequate security training and practiced alertness can resolve the former problem, the use of AI and computer vision-based intrusion detection enables law enforcement agencies to deal with the latter.

Continuous Threat Detection

Once the algorithms in computer vision-based intrusion detection devices are trained and configured for operation, they can detect specific situations that may foreshadow near-future threats. Such systems rely on pattern recognition to evaluate whether a specific series of events—say, an unknown individual carrying a potentially dangerous concealed object—may lead to a campus shooting or a similar kind of attack. Once a potentially hostile system is pre-empted, the system alerts the security officers present on campus as well as nearby law enforcement officers.

Today, facial recognition and emotion recognition tools have developed to the point where a person’s facial expressions and gait can be scanned to predict whether they will potentially carry out a hostile attack or not. Additionally, computer vision-based object recognition systems also identify potential weapons carried by individuals entering a school, college or university campus.

Autonomous Intrusion Detection

Tasks such as relentless assessment of individuals and the objects they possess while they enter the school campus can be impossible to carry out for humans. AI and computer vision-based tools, on the other hand, can perform such tasks autonomously once they are set up for operation. Constant monitoring and intruder behavioral analysis enable security personnel in campuses to focus on other activities such as patrolling classrooms and corridors on every floor. Using this feature, security officers in a school can track threats even during the nighttime or times such as summer holidays when not many people are present on a given campus. Such alertness, even during “non-eventful” times, enables security officers to know if any object was brought and placed in classrooms, restrooms, and other places for future attacks.

While eliminating the causes of such unfortunate incidents will only be possible through legislative action, several avoidable deaths can be prevented if schools, colleges and universities invest in computer vision-based threat detection applications to protect their staff and students. Such tools are not even very expensive, especially when one factors in the sheer number of benefits they bring to the table.