International Journal of Forensic Research(IJFR)

Department of Legal Medicine, Shiga University of Medical Science, Setatsukinowacho, AN Holdings Co., Nishinomiya, Hyogo, Shiga, Japan

Publications

• Research Article   
  From Post-Mortem to Prevention: Redefining “Invisible” Pedestrians Through ISO 26262 and Multi-Modal AI
  Author(s): Nick Barua*
  
  Pedestrians in non-upright postures—those who have fallen due to medical emergencies, intoxication, or primary collisions— represent a significant yet underserved demographic in automotive safety research. Despite the proliferation of Advanced Driver- Assistance Systems (ADAS), forensic data suggests that “low-profile” humans remain largely invisible to standard monocular and LiDAR-based detection systems. This opinion piece argues for a paradigm shift in vehicle safety, moving from post-mortem forensic analysis to proactive prevention through the integration of ISO 26262 functional safety standards and multi-modal AI architectures. By leveraging the Advanced Falling Object Detection System (AFODS), which utilises YOLOv7-Tiny for spatial detection and MFCC-based audio classification for verification, detection accuracy for prone individuals can be significantly.. Read More»
  

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