A Concise Review of Suicide Surveillance and Prevention Technologies on Bridges

Suicide prevention in high-risk public spaces, especially bridges, remains a critical global challenge. This systematic review synthesizes 28 studies published between 2020 and 2025, categorized into four thematic groups: 1) national and real-time surveillance systems, 2) AI-based prediction and ethical considerations, 3) smart surveillance and anomaly detection in public spaces, and 4) social, environmental, and behavioral interventions. Findings reveal a shift from traditional statistical monitoring to intelligent, real-time, multimodal systems integrating AI, machine learning, and computer vision. While national systems provide population-level insights, AI models enhance predictive capabilities but face ethical and integration challenges. Smart surveillance demonstrates high accuracy in detecting abnormal behaviors on bridges, yet lacks linkage with healthcare data. Social and environmental strategies remain minimally integrated with digital systems. The review highlights a research gap in fully integrated, proactive suicide prevention approaches. Insights from this study contribute to the design of bridge-specific surveillance systems that enable real-time detection, predictive alerting, and evidence-based decision-making for authorities.