Authors : R. Sathish Kumar, K. Lokesh, V. Shankar and S. Arun Kumar
Abstract: Localization of road accident hotspots where the number of accidents is above expected supported the quality values. The user will receive a notification while it localizes a disease within the encircling with the assistance of worldwide Positioning System (GPS). We use DBSCAN method which may be a two-dimensional coordinate which helps to record the accident location (Black Spots). On an average, nearly 2,48,000 road accidents were reported between January and June each year between 2014 and 2019. Around 53 crashes and loss of 17 lives are occurring in India every hour. However, though you’re careful on the roads does not imply that the opposite drivers also will do an equivalent. There are several incidences when the drivers aren’t wrong while driving. There are various methods like strict rules, heavy fines, use of speed detection devices, etc., are taken for reducing accidents but still accidents are happening. Folks that are driving aren’t conscious of spots where an accident usually happens. Though there are accident zone signs people while driving with maps won’t see those signs. To scale back these numbers of accidents, we proposed a idea of detecting the black spots, especially surrounding path we travel. However, this idea proposed for identification of the black spots requires accident data during an outsized note and since, the knowledge is time-consuming and casualty-intensive to accumulate. It are often very beneficial to present this method which may identify the black spots within a fast time, so on reduce the fatalities and achieve safe roads for travelling.
R. Sathish Kumar, K. Lokesh, V. Shankar and S. Arun Kumar, 2021. An Improved Scalable Approach to Detect Black Spots on Roads using DBSCAN Algorithm. Asian Journal of Information Technology, 20: 160-167.