Theory and Practice of Interactive Maps Based on Machine Learning Algorithm

Abstract

This speculative proposes an approach towards enhancing the real time experience while using the Maps. It is an all-in-one for most of the information about a particular area, cities, states, countries, which include salient features like, ‘Crime Report’, ‘Population Density’, ‘Covid Cases’, ‘Average Temperature Change’, ‘Climate Change’, ’Sex Ratio’. The interactive maps assist us in conveying complicated information in a more straightforward manner. They help the user to have more engaging usage of application than regular static map. Interactive maps involve representing the maps which allows zoom in and zoom out, identifying the specific features by just hovering over the map without typing queries. The map also maintains highdefinition picture quality while zooming in. This is used to produce a summary and various ways to use or visualize data source on the map. The GSI (Global Information System) is used in interactive mapping to display pinpoint data on a map. The many tiers of geographical information are layered on top of each other using a layering approach. Unlike static maps, interactive maps offer a lot of characteristics that help to display a vast quantity of complex data more effectively.