The increasing number of vehicles in cities can cause high volume of traffic, and implies that traffic congestion has become more critical nowadays. According to a survey, Mumbai is ranked 5th and Bangalore is ranked 10th in the world for cities with worst traffic. The main idea is to keep the same existing infrastructure without any major reconstruction and make delta changes in the system using the power of AI & ML which can produce a bigger impact.

Another problem which arises beacause of traffic congestion is the fatalities caused due to delay of emergency vehicles such as ambulance & fire brigade. In daily life, we often see that emergency vehicles face difficulty in passing through traffic. Approximately 30% of the deaths are caused due to delayed ambulance and one in ten patients dies on the way to hospitals.

TraffiKAI aims at providing solutions to the above stated issues by implementing powerful machine learning algorithms for Dynamic Traffic Signaling which sets the value of time allocated to each signal in a junction dynamically by calculating the density of traffic in each lane and intelligently allocating the least time to the lane which has least density and most time for the lane with the most density. TraffiKAI also has a machine learning model to identify the presence of any emergency vehicle in a lane either by processing a video or by identifying audio and priortising the lane in which the emergency vehicle is present.