To create a Machine Learning-based Intelligent Traffic System that can monitor and regulate traffic flow efficiently. This system involves the use of cameras and sensors placed on roadways to collect real-time data on traffic flow and identify congestion points. The collected data is then processed and analyzed using machine learning algorithms to generate actionable insights that can be used to optimize traffic flow. One of the key benefits of this system is its ability to automatically adjust traffic signals to prioritize emergency vehicles such as ambulances during times of heavy traffic. This can significantly reduce response times and improve the chances of saving lives in emergency situations. Additionally, the system can provide real-time traffic updates to drivers via mobile apps or digital displays, allowing them to avoid congested areas and take alternative routes. The implementation of this system can also lead to a reduction in carbon emissions and fuel consumption by reducing the amount of time vehicles spend idling in traffic. Moreover, it can help to minimize road accidents caused by congestion and improve overall road safety.