Accident prevention systeam using android application - Shinde Aman Pandurang; Gaikwad Anjali Navnath; Ingale Komal; Ligade Mayuri Balasaheb (JournalNX - A Multidisciplinary Peer Reviewed Journal, 2021)
Mostly, it is found that road accident happening are more frequent at certain specific locations i.e. black spot. The analysis of these black spot can help in identifying certain road accident factor that makes a road accident to occur frequently in that location. In this project we apply statistics analysis and data mining algorithms on the Fatal Accident dataset as an attempt to address this problem. Association rule mining is one of the popular data mining techniques that identify the causes of accident of road accident. In this project, we first applied k-means algorithm to group the accident locations into four levels, zero level, first level, second level and third level accident location. K-means algorithm takes accident level count as a factor to cluster the locations. Then we will use association rule mining to identify these locations. The rules show different factors associated with road accidents at different locations. For all this we will provide accident data that are issue from Nasik city commissioner office. Safety driving suggestions will be making based on accident data, association rules, classification model, and clusters obtained.