Smart Fine Management System for Detecting and Predicting Traffic Violations in Sri Lanka

In the quickly changing digital environment of today, managing traffic infractions effectively is essential to maintaining the flow of traffic and road safety. This paper outlines a thorough traffic enforcement system created to solve Sri Lanka’s traffic management issues. By utilizing technologies like RFID, artificial intelligence, and geospatial mapping, the system may recognize violations automatically, forecast the actions of drivers, and identify high-risk regions for targeted enforcement. This research explains the system’s architecture, functionalities, and possible influence on traffic management practices through a thorough analysis of each system component, such as automated license information retrieval, dynamic point systems for penalties, and heat mapping for strategic resource allocation. The results emphasize how well the system works to strengthen law enforcement’s capabilities, allocate resources as efficiently as possible, and eventually raise nation’s road safety.

Authors

Institutions

Publication Details

Published
2024-10-24
DOI
https://doi.org/10.1109/iemcon62851.2024.11093536
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Smart Fine Management System for Detecting and Predicting Traffic Violations in Sri Lanka

D.S.P.M.V. De Silva, Deepthi Nanayakkara, Dasuni Nawinna, Narmada Gamage et al.
Traffic Prediction and Management Techniques
article

Smart Fine Management System for Detecting and Predicting Traffic Violations in Sri Lanka

D.S.P.M.V. De Silva, Deepthi Nanayakkara, Dasuni Nawinna, Narmada Gamage, R. M. U. R. Rathnayaka, Deshitha Withana
article en

Abstract

In the quickly changing digital environment of today, managing traffic infractions effectively is essential to maintaining the flow of traffic and road safety. This paper outlines a thorough traffic enforcement system created to solve Sri Lanka’s traffic management issues. By utilizing technologies like RFID, artificial intelligence, and geospatial mapping, the system may recognize violations automatically, forecast the actions of drivers, and identify high-risk regions for targeted enforcement. This research explains the system’s architecture, functionalities, and possible influence on traffic management practices through a thorough analysis of each system component, such as automated license information retrieval, dynamic point systems for penalties, and heat mapping for strategic resource allocation. The results emphasize how well the system works to strengthen law enforcement’s capabilities, allocate resources as efficiently as possible, and eventually raise nation’s road safety.

Sri Lanka Institute of Information Technology (LK)
Peace, Justice and strong institutions
Openalex Percentile: Top 68%
Traffic Prediction and Management Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.