How K-12 Schools Can Maximize their Investments in Video Surveillance
Reopening More Secure and Efficient Schools
Video surveillance cameras are a typical physical security fixture of K-12 schools, as a way of monitoring various spaces and facilities, such as gymnasiums, classrooms, hallways, playgrounds, playing fields, and administrative offices. From theft to vandalism, violence, and traffic violations, the physical security breaches of K-12 campuses are sometimes deterred by the presence of cameras – when this is not the case, the cameras can provide forensic evidence after an incident or medical emergency.
In recent years some school systems have discovered that video cameras capture a lot of valuable information that can offer multiple benefits to increase security and streamline school operations. Beyond just forensic data for post-incident investigations, video data can also be used for real-time alerting, resulting in increased situational awareness, improved response time to evolving situations, and the prevention of future operations or security problems by uncovering trends and patterns. However, in reality, most video camera footage is never used because manual review of video is too time-consuming and subject to human oversight or error. Fortunately, video content analytics software that is powered by Deep Learning and Artificial Intelligence can extract, identify, classify and index that valuable video metadata and present it in ways that make it searchable, actionable, and quantifiable.
Rapid review accelerates incident investigations
When a behavioral, criminal or medical incident occurs on a school campus, security and, sometimes, local law enforcement teams, turn to video footage to investigate. Video content analytics offers precise search and filter capabilities, which makes it possible for investigators to only review the relevant video footage, reducing the time it takes to comb through evidence and resolve investigations. System operators can search and review footage based on object class and attribute filters, such as, vehicle or person; speed, path, direction, and dwell time; and appearance similarity, as well as face and license plate recognition. If a student goes missing, for example, the system could be used to filter video across multiple cameras based on appearance similarity or face recognition to help limit video review to only instances of “female, child, red upper wear, blue lower wear,” or actual instances of the child’s face. This enables the school to trace the student’s steps and locate her whereabouts on campus.
Real-time alerts increase situational awareness
Another solution for locating the student would be to configure real time alerts for any detection of the missing student, based on face recognition or appearance similarity filters. In general, school security officers require real-time, actionable intelligence: what is happening now, and where. A video analytics system can be configured to trigger alerts for anomalous behavior in a scene, based on rules set by the operator. Real-time video analytic alert triggers include the following:
- Unexpected lighting changes at pre-set times of day or night. For example, if a light is turned on or off in a classroom, gymnasium, or office during a pre-selected time frame – such as after school hours – the system can trigger an alert to the surveillance operator, who can then assess the situation, and decide how to respond.
- People or object counts exceeding a pre-defined threshold. People-counting alerts can track and manage occupancy throughout a school campus. The system can count the number of people in a pre-defined area and alert staff in real-time if a crowd is forming in that part of the school. This is useful for monitoring congestion in hallways and outdoor pathways, and preventing violence, such as pushing, shoving, or fighting. This is of particular importance for schools reopening in the wake of the COVID 19 outbreak – or any public health crisis – for encouraging and enforcing physical distancing.
- Dwelling. Video content analytics can also detect dwell duration for a pre-defined camera view; the operator of the system can set a time threshold to detect abnormally long lingering of people or objects and, in this way, respond proactively to potential problems, such as a person or vehicle suspiciously lingering around the school perimeter, who may have malicious intent. Dwelling can also be an indication of someone having a medical emergency, which requires immediate intervention.
- Facial recognition of specific individuals included in a suspect watchlist or excluded from an authorized persons watchlist. Schools may consider using face recognition technology to monitor visitors and identify unrecognized people entering the school. Security can pre-compile a watchlist of approved staff and configure face recognition alerting to trigger notifications whenever an unidentified adult enters the building. Upon receiving this alert, the video surveillance operator can assess the situation, in real-time, to determine whether action or closer monitoring is necessary to maintain school safety. Similarly, the video analytics operator can configure a watchlist of individuals who should not be allowed on campus.
- License plate recognition for vehicles included or excluded in a pre-defined watchlist. If school administrators are concerned about previous incidents that involve particular vehicles, they can create a watchlist of those license plates, and the video analytics system can notify the surveillance system operators in real-time if that license plate appears in a video camera feed.
Visualize trend data for better planning
If school administrators prefer not to receive real-time alerts, they can simply review video analytics data aggregated over time in the form of customized reports and visual dashboards, including graphs, heatmaps, and histograms for demonstrating patterns and trends. Commonly, school administrators and security staff need to see vehicle and pedestrian traffic flows, so they can understand which areas of a campus (hallways, parking lots, roadways) experience traffic congestion and bottlenecks. Quantitative data helps school administrators research trends at their facilities, so they can make better decisions that are based on statistics rather than human observation. This results in less traffic, less crowding, happier parents and faculty, and a safer environment for all.
Using video content analytics to measure COVID-19 prevention compliance
The COVID-19 pandemic presents an urgent, new use for video surveillance and analytics: the ability to monitor compliance with public health measures, such as social distancing and wearing masks.
Video intelligence software can play an important role in those efforts. Firstly, it streamlines contact tracing by enabling the forensic review of video data. Video can be filtered to trace self-identified individuals throughout video, using face recognition and appearance similarity filters to easily understand where the infected individual was and with whom he or she interacted. In a case where a student or faculty member was diagnosed and provided a digital image of him or herself to the school, the facility would be able to seamlessly search all video footage over the relevant time period to discover if the person had been in contact with other students, faculty or staff or employees and, if so, for what duration of time. While protecting the anonymity of the diagnosed person, the school can still notify any people who were exposed, so they may self-quarantine, as recommended, to protect others from possible infection. The technology can also rule out those who have not been in close proximity to a diagnosed person, so they can be more at ease.
With proximity identification capabilities, video analytics software can also quantify and analyze distance between students or staff over time and location to identify general non-compliance with physical social distancing mandates. This can help school administrators gather anonymous statistical data about whether students and staff are complying with a rule to stay at least six feet apart from each other.
School systems can get more value from their existing video surveillance systems by complementing them with video content analytics systems. The powerful pairing of these technologies leads to more efficient school security operations, and safer schools for students, staff, and faculty.
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