RLS-2020A

The REDSCAN mini-Pro RLS-2020A has been designed with connectivity and network security in mind. RLS-2020A is ONVIF compliant allowing it to seamlessly integrate with other devices in the security network system. It is also compliant with enhanced security networks including HTTPS, SNMPv3, IEEE802.1X, providing you with a secure connection.

The latest LiDAR sensor is built to adapt to your specific site needs. Choose from various mounting options, including wall, ceiling, and pole mounts, enabling both horizontal and vertical detection. In horizontal mode RLS-2020V can protect roofs, skylights and ceilings; in vertical mode it can create virtual walls to protect assets, facades and protect narrow areas around buildings or perimeters. If you require a longer area to be protected, the extended detection range allows up to 30m 95-degrees coverage.

The detection area can be divided in up to 8 independent zones, and for each of them the object target size, sensitivity and output can be customised. It gives great flexibility to adapt the settings depending on the zones location and level of threat.

Count on RLS-2020V to detect intrusions even in the harshest conditions and complete darkness. It's designed to work in the coldest temperatures of up to -40°C to scorching 60°C heat, while also not being affected by rain, snow, wind or light changes. The REDSCAN mini-Pro ensures resistance against environmental factors, guaranteeing consistent and accurate performance in extreme weather.

Photos and map images can be used to overlap the detection area for better situational awareness. Either “Scan area” or “object position” can be sent to ONVIF compliant software/devices when an alarm occurs.

Real-time analysis and filtering of events based on a certain logic helps security teams be more efficient and prioritise their response to the most critical incidents. For instance, to alert if the target is walking in a certain direction or accessing an unathorised area, such as a tunnel entrance. 

REDSCAN uses anonymised 2D data to detect the position, size and movement of objects without relying on identifiable images of people. This helps organisations protect sensitive areas while reducing the amount of personal data collected.