Estimation of Bus Arrival by Tracking and Analyzing the Users Real Time Location

High level business strategies are continuously being improved by changes in innovation. In the system, a number of methods have been shown to enhance the comfort and health of people's daily lives. The paper's major goal is to use cutting-edge GPS and IoT in Intelligent Transportation Systems. The bus could have been delayed for several reasons. Clogged roads, malfunctions, and bad weather are examples of these. People waiting at bus stops have no idea of the bus's delay or arrival time. These issues can be addressed by using Intelligent Transportation Systems (ITS) that use GPS and IoT in mobile applications to allow passengers to track the locations of their bus in real time They may also check the Estimated Time of Arrival of a certain bus, which is derived using machine learning techniques and takes into account environmental changes as well as other aspects such as traffic density and weather conditions, and follow their bus positions in real time. The main scope of this intelligent mobile app is to display the current area of a client's separate transportation in Google Maps along with the It is a Real-time tracking as if the source address of the transport is restored every second as scope of latitudes and longitudes, which are gained by customers by their app with the assistance of the Google Map API. This system can effectively address the problems related to bus timing transparency and arrival time forecasting. The buses are equipped with a real-time vehicle tracking module containing Real-time tracking with Transport global positioning (TPS). The traffic congestion in the current location of the bus and weather data are some of the factors used for the ETA prediction using the Distance Matrix API.