Suicide Risk Assessment from AI-powered Video Surveillance: An Interpretable Framework for Prevention in Metro Stations
arXiv:2605.22904v1 Announce Type: cross Abstract: Understanding and monitoring human behavior in metro stations play an important role in supporting suicide prevention efforts, where early identification of high-risk situations can enable timely intervention. This requires assessing suicide risk from a surveillance video by jointly reasoning about the behavior of each passenger, his/her spatial context, and temporal dynamics. However, this assessment using videos captured by surveillance cameras is challenging, as it demands accurate perception of human motion, understanding of platform geomet
The proliferation of advanced AI computer vision capabilities combined with existing surveillance infrastructure is making autonomous behavioral analysis feasible for public safety applications.
This development indicates a growing capability for AI to autonomously monitor and interpret complex human behavior in public spaces, raising immediate ethical and privacy concerns alongside potential benefits for public safety.
The deployment of AI-powered video surveillance for suicide risk assessment would transform public safety protocols by introducing proactive, automated intervention capabilities based on behavioral analysis.
- · Public transportation authorities
- · AI surveillance technology providers
- · Emergency services
- · Mental health support organizations
- · Privacy advocates
- · Individuals preferring anonymity in public
- · Civil liberties organizations
AI systems will be deployed to monitor public spaces for specific high-risk human behaviors.
Public discourse will intensify around the ethical implications of constant AI monitoring and the balance between public safety and individual privacy.
The technology could be expanded to identify other 'undesirable' behaviors, potentially leading to a panopticon effect in urban environments.
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Read at arXiv cs.AI