Public security

New Tools to Alert on Active Shooter Attacks at Schools

First responders in the US have been coping with the growing challenges involved with school safety. Between 2010-2017 there were 52 active shooter attacks in US education institutions. Instead of waiting to deal with these events once they’ve already taken place, predictive analytics could prevent them from happening.

Predictive analytics are statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events.

Predictive analytics reviews data to predict the event early on by aggregating all a facility or organization’s current and historical data. The aggregation allows facility managers to review and monitor for trends or patterns so they can make informed predictions of events that may happen in the future.

For schools, this data can include attendance records, dates, times and locations of alarm notification, visitor logs, just as a few examples. Having the data all in one place helps to reveal patterns or trends that tell a story and give insight into incidents. As a result, staff, administrators and facility managers have access to essential information to take the proper steps to protect their buildings and most importantly students, according to securityinfowatch.com. 

Schools are already collecting all kinds of data, including attendance, tardiness, grades, trips to the nurse, suicide attempts, and more. When these data points are all compiled in one place or on one platform, they begin to reveal patterns that may have otherwise gone unnoticed.