
A Web-based Andhra University Spatial Information System (AUSIS) and a Building Information Extraction Model using WebGIS & Image Recognition Technique
Author(s) -
Boddepalli Navjoth
Publication year - 2021
Publication title -
international journal of information technology and applied sciences
Language(s) - English
Resource type - Journals
ISSN - 2709-2208
DOI - 10.52502/ijitas.v3i4.195
Subject(s) - university campus , computer science , attendance , world wide web , information retrieval , library science , economics , economic growth
A university campus is an intricate infrastructure. Especially new students, who are thereon for the first time, have a tough time orienting themselves and finding places. The campus of Andhra University occupies more than 422 acres (170.7 hectares). The campus has many different buildings. Every year, thousands of new students join the university. These students either take a campus commuter or walk around to get familiar with the campus compound. Visitors to Andhra University might have a hard time searching for a particular location on the campus. Every day, uncountable numbers of students, staff, and visitors move around the campus compound to perform tasks by walking, cycling, driving, or riding campus commuters. Even if there are maps at various points on the campus premises, users do not have continuous help to reach their destination. On these static maps, they can try to figure out a way to get to their target, but as soon as they start walking in the target direction, they have no help anymore. The main objective of this study is to develop a Spatial Information System for Andhra University (a Progressive Web App). Which provides several features like a voice-enabled optimal navigation solution, shows nearby places within campus premises, and a geo-tagged university (Geo-tagging of all entities within campus premises). To make the web application more operative, the application is appended with more features. For instance, a map shows statistical data with pie charts visualization (statistical data like monthly attendance), machine learning's image recognition model for extracting the building information from the digital or captured images.