Citilog was the first company to introduce video-based automatic incident detection in 1997. In 2019 Citilog introduced the first incident management analytics module based on Deep Learning technology, CT-ADL. The solution is aiming at enhancing the performances of its automatic incident detection video analytics solution.
“The results have been more than encouraging from the start with reduction of false alarms by a factor ten. Early adopters have already converted their critical road infrastructures to make their operations more efficient”, said Jonas Svensson, CEO, Tagmaster.
During 2021 major projects have been deployed that use the Deep Learning technology on a very large scale. 700 cameras have been installed with edge-analytics for the ITS Egypt project, covering freeways around Cairo, and demonstrated great efficiency. 350 cameras also installed with edge-analytics have been used on a large road infrastructure project in Hong Kong aimed at detecting roadway incidents and accidents but also at collecting traffic data.
“These two projects demonstrate how artificial intelligence contributes to making videoanalytics viable on large-scale projects. This opens new opportunities for road authorities to deploy automatic incident detection on highways, bridges and ring roads whereas most deployments have been historically in tunnels”, said Eric Toffin, CEO, Citilog.
Citilog, acquired by Tagmaster in April 2021, has today a broad portfolio of cutting-edge algorithms, based on Deep Learning, that can be used as both edge solutions and cloud-based solutions. Citilog is focusing on four application areas – incident management, traffic efficiency, traffic statistic and remote parking enforcement.