Authors :
Sophie Uwho; Ifeoma B. Asianuba
Volume/Issue :
Volume 10 - 2025, Issue 6 - June
Google Scholar :
https://tinyurl.com/mrk2uv6c
DOI :
https://doi.org/10.38124/ijisrt/25jun1704
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 30 to 40 days to display the article.
Abstract :
The growing demand for urbanization has heightened the need for efficient systems to safeguard commuter safety,
particularly in the transportation industry. Advances in mobile technology, internet connectivity, and artificial intelligence
have transformed incident reporting from manual, post incident and eye witness reports into real-time data-driven
processes. This review examines the development, application, and efficacy of incident reporting systems, exploring their
various types and performing impact assessment on commuter safety. The study also identifies key challenges, including
privacy concerns, data reliability, and user engagement, that hinder the effectiveness of the aforementioned systems. This
study provides valuable insights into optimizing incident reporting systems for enhanced commuter safety by analyzing the
current technological innovations and highlighting future research opportunities.
Keywords :
Artificial Intelligence; Commuter Safety; Incident Reporting; Mobile Technology; Real-Time; Transportation.
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The growing demand for urbanization has heightened the need for efficient systems to safeguard commuter safety,
particularly in the transportation industry. Advances in mobile technology, internet connectivity, and artificial intelligence
have transformed incident reporting from manual, post incident and eye witness reports into real-time data-driven
processes. This review examines the development, application, and efficacy of incident reporting systems, exploring their
various types and performing impact assessment on commuter safety. The study also identifies key challenges, including
privacy concerns, data reliability, and user engagement, that hinder the effectiveness of the aforementioned systems. This
study provides valuable insights into optimizing incident reporting systems for enhanced commuter safety by analyzing the
current technological innovations and highlighting future research opportunities.
Keywords :
Artificial Intelligence; Commuter Safety; Incident Reporting; Mobile Technology; Real-Time; Transportation.