Traffic monitoring and urban mobility
Automated video analysis enables real-time safety
Viisights uses behavioural recognition for real-time threat detection and resource optimization, turning video footage into proactive urban security.
Advanced video analytics for real-time monitoring
Advanced video analytics enable real-time tracking of vehicles and behaviour to detect hazards, improve traffic flow, and support proactive safety.
Fewer false alarms and lower costs per stream
Viisights AI enhances safety via real-time behavioural analytics, reducing false alarms to ensure secure, multimodal access for active mobility.
Effective security requires real-time insights
Automated behavioural recognition replaces passive monitoring to detect hazards instantly, optimizing resources and ensuring safety for active travel.
Challenge addressed: Automated video analysis enables real-time safety
In today’s urban and business environment, ensuring public safety and security has become a priority for businesses and authorities worldwide. While vast networks of video surveillance devices are in place, the key challenge lies not in capturing footage but in automatically detecting, analysing, and tracking critical events in real-time. To address this, viisights developed an advanced behavioural recognition technology that enables proactive threat detection, loss prevention, and resource optimization across various sectors.
Solution implemented: Advanced video analytics for real-time monitoring
The technology achieves its objectives through advanced video analytics that enable real-time detection, classification, and monitoring of vehicles, human behaviour, and urban mobility patterns. By counting and classifying vehicles, tracking crowd density, and identifying abnormal behaviours or hazards such as accidents, congestion, and unauthorized access, the system provides critical insights and alerts. These capabilities enhance safety, improve traffic management, and support proactive decision-making in urban environments.
Results achieved: Fewer false alarms and lower costs per stream
This practice was implemented by integrating viisights wise™ and viisights IQ™ behavioural recognition analytics into existing surveillance systems to enhance A2PT infrastructure. The implementation focuses on real-time detection of critical events, transforming passive monitoring into a proactive safety tool.
It is considered a good practice because it aligns with several key objectives. It helps maintain the safety and reliability of walking and cycling access points through automated hazard detection. It also ensures passenger comfort and security across all journey stages by identifying abnormal behaviours or accidents in real time. Furthermore, it uses AI to generate robust evidence on travel patterns and behaviour, thereby improving multimodal performance.
The practice improved A2PT services by increasing processing speed and recall (Wise 3.0) while significantly reducing false alarms (IQ™ auto-learning technology). This creates a secure, welcoming environment, essential for encouraging the shift toward active and multimodal mobility.
Lessons learned: Effective security requires real-time insights
The implementation shows that the bottleneck in urban security is not video capturing, but the real-time analysis of vast data. For other regions, the key takeaway is to transition from passive surveillance to automated behavioural recognition. This enables proactive detection of hazards and accidents within critical timeframes. For A2PT goals, this automation is essential to optimize resources and ensure the high level of safety required to encourage walking and cycling.
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The project Active2Public Transport is supported by the Interreg Danube Region Programme project co-funded by the European Union. The project was initiated by the Austrian Federal Ministry of Innovation, Mobility and Infrastructure (BMIMI), Department II/6 in cooperation with klimaaktiv mobil – the Austrian Federal climate protection initiative on sustainable mobility.