FLIR has launched the FCB-Series AI, a thermal analytics camera designed for perimeter and site security in challenging weather and lighting conditions.
The camera combines a thermal sensor with sensitivity below 20 mK and onboard deep-learning video analytics. It is designed to detect and classify people and vehicles in environments where visible-light cameras may struggle, including low light, glare, fog and heavy rain.
The FCB-Series AI uses deep neural network (DNN) analytics to distinguish between human and vehicle movement and environmental factors such as foliage, rain or small animals, helping reduce false alarms sent to video management systems.
The device supports Nexus-enabled target geolocation, allowing integration with PTZ cameras for automated tracking across a site. The system is intended to operate within broader security ecosystems that may include thermal and visible cameras, radar and analytics platforms.
Five lens options are available, ranging from 18° to 50° field of view, in VGA and QVGA resolutions. This allows coverage of long perimeters, fence lines and irregular layouts.
With an IP67 rating, the camera is built for outdoor deployment in dust, rain and high-temperature environments.
The FCB-Series AI is positioned for use in small to medium commercial sites, campuses and industrial facilities, as well as remote and energy-sector installations such as solar farms and utilities.
