SecurityWorldMarket

07/05/2020

Huperlab analytics solution reminds people to clean hands

Taipei, Taiwan

The solution checks if a person has moved to a specified position and stayed for a specified period of time to sanitise their hands before entering an area.

During the coronavirus pandemic, it has become increasingly important to keep away from the virus. For this very purpose, Huperlab is now introducing its Sanitizing Warning solution--a solution that uses 3D stereo vision intelligent technology to protect employees, customers and visitors from virus. The solution has already been installed in some hospitals.

The solution checks if a person has moved to a specified position and stayed for a specified period of time to sanitise their hands before entering an area. If a person does not follow the process, the system will alarm with its built-in speaker by playing a recorded audio, reminding the person to sanitise their hands before entering the area. The solution is able to work with or without an access control system.

The solution features an all-in-one AIoT smart camera, with built-in web server and 3D stereo vision intelligent technology. It does not need another PC to run the 3D stereo video analytics.

Huperlab has 10 years of experience developing 3D stereo cameras and 3D video analytics to overcome the accuracy issue for different critical weather conditions, such as sun light, shadow, rain, snow, fallen leaves, bugs and car headlights which are common scenarios in many real world cases especially in outdoor installations and main entrance door applications.

The company provides many high accuracy 3D video analytics solutions for different markets. For retail management, there is the 3D people counter, 3D area counter, 3D queue management and capacity management. For security and surveillance, there is the 3D virtual fence, 3D tailgating detection, 3D fall & stop detection, 3D secured zone, 3D air-lock room and 3D loitering detection. For transportation, the 3D vehicle counter, 3D bus people counter and 3D cyclist detection.


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