The role of Deep Learning Video Analytics for reducing fare evasion in public transport
Transport managers can draw more value from their video surveillance networks by employing intelligent Video Analytics using AI and Deep Learning

Ticket inspector looks at a sequence of images showing fare evaders on Awaait's video analytics app (note: the scenes in the app are a simulation played by actors) A ticket inspector checks a fare infraction alert on the real-time fare evasion detection app developed by Awaait (note: the scenes in the app are a simulation played by actors)

Making better use the existing video networks Overcoming the challenge of manually analyzing video feeds from security cameras is one of the biggest tasks for companies and organizations that use video surveillance networks on their premises. Each surveillance network can include a number of cameras that generate a high volume of video data. This...

Deep Learning Video Analytics for protecting public transport revenues, assets, passengers and mobility
Fare evasion can finally be effectively tackled using AI-based Video Analytics through existing video surveillance networks

A ticket inspector checks screenshots of a fare evasion incident on the Awaait's real-time video analytics app A ticket inspector checks screenshots of a fare evasion incident on the Awaait's real-time video analytics app

Fare evasion is the act of traveling in public transport without paying for the ride. It is a problem in many public transit systems around the world, leading to a feeling of unfairness and insecurity among paying passengers, and causing losses in billions of dollars yearly. Some metro and commuter train operators deploy mass...