Kainan University, founded in 2000, is located in Taoyuan, Taiwan. It occupies an open area of nearly 17 hectares, and has 2500 students, 25 departments, 16 graduate schools and four master programs.
Kainan University, founded in 2000, is located in Taoyuan, Taiwan. It occupies an open area of nearly 17 hectares, and has 2500 students, 25 departments, 16 graduate schools and four master programs.
On the campus, the number of security guards was limited, and there were many places that were not being monitored. Traditional DVRs were not able to meet the surveillance needs, and Kainan University started looking for a security system to tighten up campus security. As megapixel cameras offer up to four to six times the image quality provided by analog cameras, the school hoped to deploy megapixel surveillance solutions for the campus.
Megapixel cameras offer significant benefits for surveillance operations. However, 90 megapixel cameras and the need for 60-day recordings presented many different issues for the system integrator, Sunshine Information, including the I/O performance of traditional NVR, integration of storage solutions and proven solutions that can assure end-to-end integration. To deal with these issues, Sunshine deployed Surveon's megapixel cameras, real-time VI engine, RAID NVR and enterprise VMS.
88 Surveon cameras have been installed for strategic monitoring of classrooms and hallways, as well as building entrances, pedestrian areas and campus grounds. They make use of Surveon's video analytics to configure recording. The facilities are split into three levels in an existing university building, with a dedicated 32-channel NVR, each archiving up to 60 days of surveillance footage for associated cameras
Surveon's RAID NVR makes capturing, analyzing, managing and searching video surveillance easier and faster. Its active VI detection has a preconfigured base for a number of scenarios, such as intrusion detection on the campus, examination of important gates or parking lot detection. The NVR distinguishes what's important from what is not, turning the raw surveillance videos into useful information. The recorded events are analyzed and labeled with details such as time, date, direction, color and size of the objects, etc.