Published Paper Details:

: For the cities like Mumbai which says �Never sleep� and having a lot of problems regarding the traffic congestions, cities have to pay for it, in several ways such as more fuel consumption, longer traffic jams, time wastage, infrastructure damage, loss of lives and goods, health issues. A city like Delhi, is continuously undergoing major issues regarding traffic due to it�s narrow roads, hence it becomes mandatory to manage traffic. Narrow roads can easily cause devastating traffic jams which can lasts for hours. As we are already moving towards "Smart City", we have a high number of technologies, to help us reach our destination, examples can be of variety of ranges from Google maps, simple signs on roads of traffic related rules, and specifically some electronic equipment�s established by some private or government companies informing about weather conditions, time, traffic jams, routes etc. In our proposed system, we are going to use real time traffic data from CCTV cameras, we are going to processes that data using a Raspberry pi microcontroller, and by extracting meaningful information from real time traffic data such as vehicle types, density of traffic, emergency vehicles, such as ambulances, police vehicles etc. we are going to assign various traffic signal times according to density at that specific road. This we are going to achieve using IoT, Machine learning. We are going to use HAAR Cascade algorithm specifically for drawing boundaries around vehicles, and same algorithm will get used for vehicle identification