AI Powered Analytics App for Visualizing Accident-Prone Areas

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AI Powered Analytics App for Visualizing Accident-Prone Areas

Harris, Preethi / Nambiar, Rajesh / Rajasekharan, Anand / Gupta, Bhavesh

Abstract Increasing urbanization over the years has resulted in exponential traffic rise and consequently the risk to drivers and passengers. Appropriate action is vital for safe driving under various road conditions. With the advent of intelligent vehicular systems, identification and notification of accident-prone zones while driving has become a hot topic. Data Analytics could improve driving safety in such regions and thereby save invaluable human lives. Warnings about accident-prone areas are usually notified using signboards which may be overlooked and have no significant impact while driving past these zones. At the outset analytics performed on the accident data could provide invaluable insights and thereby enable drivers to be more cautious while approaching or crossing these areas to facilitate safe journey. In this paper an App built on Artificial Intelligence (AI) Einstein platform performs analytics on data collected from sensors for major and minor accidents to visualize and share details of zones prone to major accidents via mobile App for the data stored in Salesforce Cloud. With the actual accident statistics not available or appropriately documented, a prototype to detect and collect spatial details of accidents has been developed using vibration sensor and Global Positioning System (GPS) on Ardunio. This simulation further facilitates drivers to determine major crash spots powered by Einstein AI on their mobile App.