Data Mining and Visualization to Understand Accident-Prone Areas

Autor: Md. Mashfiq Rizvee, Amiruzzaman, Md. Rajibul Islam
Rok vydání: 2021
Předmět:
Zdroj: Algorithms for Intelligent Systems ISBN: 9789811605857
DOI: 10.1007/978-981-16-0586-4_12
Popis: In this study, we present both data mining and information visualization techniques to identify accident-prone areas, most accident-prone time, day, and month. Also, we surveyed among volunteers to understand which visualization techniques help non-expert users to understand the findings better. Findings of this study suggest that most accidents occur in the dusk (i.e., between 6 and 7 pm), and on Fridays. Results also suggest that most accidents occurred in October, which is a popular month for tourism. These findings are consistent with social information and can help policymakers, residents, tourists, and other law enforcement agencies. This study can be extended to draw broader implications.
Databáze: OpenAIRE