I. Introduction
With an increase in the traffic population, we witnessed a phenomenal rise in road accidents in the past few years. According to the World Health Organization (WHO) [1], the loss is not only limited to humans but also affects the country's GDP. The officially reported road crashes are inspected mostly based on the macro circumstances, such as the vehicle's speed, the road's situation, etc. Close inspection of those macro circumstances reveals a series of micro-events, which are responsible for such fatalities. For example, suppose a driver hit the road divider and faced an injury while driving on a non-congested road. From the macro perspective, it may be due to the driver's amateurish driving or the vehicle's speed. Nevertheless, it is also possible that some unexpected obstacles (say, crossing pedestrians/animals) arrived out of sight. The driver deviated from his lane while decelerating to avoid colliding with them. Therefore, recording these micro-events are crucial in identifying the reasoning behind such accidents. Such contextual information, or micro-events, is crucial to obtain just-in-time in patrolling driving profiles on the go. This provides immediate evidence to the stakeholders like car insurance or app-cab companies to analyze the on-road driving behavior of their drivers and adjust insurance claims or schedule upcoming trips, respectively.