Hello to all readers/writers, I have come up with another blog.

In this blog, we will see how Google Maps work and predict the routes and traffic. 

• There are millions of people who use Google Maps worldwide. Google Maps main use is to provide driving directions. Google Maps are flat maps that perform within a web browser. 

• Google Maps uses machine learning in a mixture of varied data references containing the aggregate location data, historical traffic contours, regional administration data, and real-time responses from users to indicate traffic.
• Google works along with DeepMind one of the Alphabet, occupied AI research labs that aims to work on improving the accuracy of its traffic prediction. With the help of GNN (Graph Neural Network ), a machine learning architecture has helped to reduce the percentage of the inaccuracy of the estimated time of arrivals (ETAs). 
• Maps also use predictive traffic models to examine the routes that are possible to receive big traffic. ETA(Estimated Time of Arrival) is nothing but sharing of the path as a text message, the ETA of the person who shares the location is mentioned through any smartphone like an android or iOS mobile, For eg: Sharing a live location via WhatsApp.
• SuperSegments is one of the terms in the GNN model used for route analysis for plotting routes. 
• Google's database obtains GPS data of users and analyses it in the feature of traffic predictions, route prediction, and traffic and reroute prediction. 
• Google Maps uses location data from users that are provided as input and are stored and retrieved to google maps' main service database server.
• One has to switch GPS mode on smartphones for starting the maps along with the mobile data network, users can use it in offline mode too. The navigation system starts according to the speed of the type of vehicle or if a person is walking. 
• Based on historic data(it includes the average time taken in general by vehicle reaching the destination on a specific day and time) and real-time data(based on GPS from smartphones knowing how fast the car is an estimate of time and distance to reach with directions ) faster routes can be estimated. 
• Google Maps consists of components that contribute to the working of maps that includes a base map, a partner program, street view vehicles, satellites, a crowdsourcing mechanism, and data processing.
• A base map is a graphical indication at a specified scale of selected essential map data.
•  A partner program in maps encourages local businesses to create an experience based on visitors' ratings for business promotion for advertisement purposes.
• Google uses information provided by satellite images about traffic, accidents, and local division of transport to improve the accuracy of Google maps to predict data. 
• Crowdsourcing is a tool that is used for enhancing the accuracy and quality of Maps. Here, additional information regarding the maps, location, ideas, speed, landmarks, and other data from some users can be mapped and added. 
• The data related to traffic, number of vehicles, and how fast the vehicle is analyzed. The undefined data is collected, and processed by Google maps when turned on. It removes freaks by using the algorithm that was set. It rather suggests the best-suited route for the ride. 

Google Maps is one of the largest and much-used navigation tools, and route mapping databases used all over the world. It aims at providing location services and improves the efficiency of the navigation product. 

Here, I end with the topic. Hope you find my blog interesting.

Thanks for reading my today's blog. Do read, like, and comment for any suggestions. Have an amazing day!