Safe Campus

Campus safety has always been a focus of public concern, and the current situation remains severe. In primary and secondary schools, various safety issues have led to frequent abnormal accidents among students. These heart-rending incidents have repeatedly served as a wake-up call for us. Crowded corridors causing injuries to students, chasing and playing during breaks causing cuts or fractures, being pricked by pencil tips in class, getting burned during experiments, drowning and death – such unexpected incidents are hard to prevent. How to promptly detect and handle emergencies both inside and outside the campus has become the core issue that current campus safety management urgently needs to solve.

The traditional manual monitoring method is unable to cope with the challenges of campus security. The campus is densely populated, and students have relatively weak self-protection abilities. Moreover, safety hazards often have sudden and covert characteristics, such as campus violence, bullying, and personnel congestion behaviors. Only relying on human efforts is insufficient to achieve comprehensive and timely monitoring. With the intelligent AI perception technology of Agiegiview, real-time analysis of human movement and behavior can be conducted, and risks can be promptly warned, providing efficient security guarantees for the campus. It is not only applicable to the prevention of malicious incidents but also can effectively reduce the occurrence of daily accidents, truly achieving the goal of “a safe campus”.

In the safe campus system of Agiegiview, each technical component forms an efficient and collaborative closed loop: High-definition cameras deployed in areas such as teaching buildings, playgrounds, and canteens collect video streams in real time, which are then transmitted stably to the edge computing multi-modal AI gateway through industrial-grade switches. This gateway acts as the “intelligent frontline”, using deep learning algorithms to conduct millisecond-level real-time analysis of the video streams, accurately identifying risks such as overcrowding, violent behavior, and regional intrusions. The processed structured data and warning information are then transmitted synchronously through the switch to the backend: The hard disk recorder is responsible for the storage and retrospective management of massive videos, while the monitoring host integrates the analysis results from the AI gateway and implements visual alerts and dispatching and handling instructions on the central management platform. When the system detects an anomaly (such as a fall in the stairwell or violation of regulations in the laboratory), the platform will automatically trigger audible and visual alarms and push information to the mobile terminals of security personnel, achieving a rapid response closed loop of “end-to-edge-to-cloud” three-level interaction.