School Security Management Based on the Power of Vision AI and NVIDIA Jetson Inferencing

In an era where ensuring the safety of our children is paramount, school security has become a top priority for educators, parents, and communities alike. Once considered sanctuaries of innocence, the hallowed halls of learning are now under a new and sobering reality: the need to fortify them against potential threats. In this rapidly evolving landscape, traditional security measures alone no longer suffice. The escalating challenges faced by schools, from unauthorized intrusions to evolving safety concerns, demand a sophisticated approach. This is where advanced technology, particularly the cutting-edge capabilities of computer vision and NVIDIA Jetson, steps in.

Challenge

There could be complex challenges that appear during the daily operation on campus. On the one hand, External threats, including concealed weapons detection, suspicious behavior analysis, and dwelling time monitoring, demand cutting-edge technology and robust algorithms for swift responses.

Internally, issues like overcrowding and student safety, encompassing incidents like falls and crowd-related risks are the core problems plaguing managers. Identifying possible dangerous situations and intervening in advance should be a very effective security measure.

Solution

The system begins by ingesting live video feeds from multiple IP cameras strategically placed throughout the areas that should be paying attention to, such as school premises (e.g.: University-owned and/or operated property and buildings; Rooms and labs containing high-value equipment or information) or public spaces (eg: Cash-handling areas where money is exchanged, such as ATMs and cashier locations; restaurant and book store). All of these developing pipelines can be easily constructed on the Lumeo platform.

Continuous video analytics internally

The whole system can be powered by NVIDIA Jetson Orin NX for video data processing. Typically one single edge device can hold around 10 IP cameras with fluent frame rates. It tracks students’ actions such as intrusion, loitering, tailgating, fighting, falling, running, smoking, and mobile phone usage. What is also important is to detect the crowd situation in real time with an object detection algorithm, combined with DNN for density estimation. When a potentially concerning behavior is detected, the system triggers real-time alerts to security personnel or automated response systems.

External visitors checking

Using advanced appearance recognition algorithms, the system counts and classifies individuals within the camera’s field of view at the entrance/exit on campus. Once a person is recognized, the system initiates tracking, continuously monitoring their movements and location. Weapon-shape object detection can also provide values for early identification of potential hazards for authorities. In response to alerts, security personnel can take immediate action, such as dispatching on-site security personnel or law enforcement to the location of the incident. Automated responses, such as activating alarms or access control mechanisms, can be initiated to mitigate threats.

Get started with our wiki to try the video analytics developing pipelines on the Lumeo platform with your Jetson Edge device!


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