Traffic Accident Data Analysis: Patterns and Hotspots
Traffic mishaps posture a critical open wellbeing issue, causing over 1.19 million passings yearly and coming about in serious wounds and financial misfortunes all inclusive. This audit synthesizes later headways in activity mishap information investigation, centering on distinguishing designs and mishap hotspots utilizing factual, machine learning, and profound learn- ing strategies. The audit emphasizes the significance of combining spatial investigation, highlight extraction, and prescient modeling to progress street security. It moreover talks about the challenges of information quality, show generalization, and the integration of differing information sources. This paper points to supply a roadmap for future inquire about within the field of activity mishap forecast and avoidance.
Authors
- Gayatri Bhanadari
- Kishan Gopale
- Gunjan Ahirrao
- Nivas Bidave
- Nikita Hajare
Institutions
- International Institute of Information Technology (IN)
- Jnana Deepa, Institute of Philosophy and Theology (IN)
Publication Details
- Journal
- International Research Journal on Advanced Engineering Hub (IRJAEH)
- Published
- 2025-05-05
- DOI
- https://doi.org/10.47392/irjaeh.2025.0297
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00