{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/101790"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/101790","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"VTQuestAR: An Augmented Reality Mobile Software Application for Virginia Tech Campus Visitors","abstract":"The main campus of Virginia Polytechnic Institute and State University (Virginia Tech) has more than 120 buildings. The campus visitors face problems recognizing a building, finding a building, obtaining directions from one building to another, and getting information about a building. The exploratory development research described herein resulted in an iPhone / iPad software application (app) named VTQuestAR that provides assistance to the campus visitors by using the Augmented Reality (AR) technology. The Machine Learning (ML) technology is used to recognize a sample of 31 campus buildings in real-time. The VTQuestAR app enables the user to have a visual interactive experience with those 31 campus buildings by superimposing building information on top of the building picture shown through the camera. The app also enables the user to get directions from the current location or a building to another building displayed on a 2D map as well as an AR map. The user can perform complex searches on 122 campus buildings by building name, description, abbreviation, category, address, and year built. The app enables the user to take multimedia notes during a campus visit. Our exploratory development research illustrates the feasibility of using AR and ML in providing much more effective assistance to visitors of any organization.","abstract_html":"The main campus of Virginia Polytechnic Institute and State University (Virginia Tech) has more than 120 buildings. The campus visitors face problems recognizing a building, finding a building, obtaining directions from one building to another, and getting information about a building. The exploratory development research described herein resulted in an iPhone / iPad software application (app) named VTQuestAR that provides assistance to the campus visitors by using the Augmented Reality (AR) technology. The Machine Learning (ML) technology is used to recognize a sample of 31 campus buildings in real-time. The VTQuestAR app enables the user to have a visual interactive experience with those 31 campus buildings by superimposing building information on top of the building picture shown through the camera. The app also enables the user to get directions from the current location or a building to another building displayed on a 2D map as well as an AR map. The user can perform complex searches on 122 campus buildings by building name, description, abbreviation, category, address, and year built. The app enables the user to take multimedia notes during a campus visit. Our exploratory development research illustrates the feasibility of using AR and ML in providing much more effective assistance to visitors of any organization.","abstract_has_math":false,"creators":["Yao, Zhennan"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Computer Science and Applications","degree_department":"Computer Science","school":null,"contributors":[],"advisors":[],"committee_chairs":["Balci, Osman"],"committee_members":["Zhang, Liqing","Barkhi, Reza"],"year":2021,"date_issued":"2021-01-07","date_published":"2021-01-07","updated_at":"2026-07-22T22:20:11Z","subjects":["Augmented reality","Core Data database","image recognition","iPhone / iPad software application","Machine learning"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:29021"],"render_values":[{"text":"vt_gsexam:29021","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/101790","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Balci, Osman"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Zhang, Liqing","Barkhi, Reza"]},{"key":"dc:contributor.department","label":"Department","values":["Computer Science"]},{"key":"dc:creator","label":"Author","values":["Yao, Zhennan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2021-01-08T09:01:31Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2021-01-08T09:01:31Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-01-07"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science and Applications"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Augmented reality","Core Data database","image recognition","iPhone / iPad software application","Machine learning"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:29021"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/101790"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The main campus of Virginia Polytechnic Institute and State University (Virginia Tech) has more than 120 buildings. The campus visitors face problems recognizing a building, finding a building, obtaining directions from one building to another, and getting information about a building. The exploratory development research described herein resulted in an iPhone / iPad software application (app) named VTQuestAR that provides assistance to the campus visitors by using the Augmented Reality (AR) technology. The Machine Learning (ML) technology is used to recognize a sample of 31 campus buildings in real-time. The VTQuestAR app enables the user to have a visual interactive experience with those 31 campus buildings by superimposing building information on top of the building picture shown through the camera. The app also enables the user to get directions from the current location or a building to another building displayed on a 2D map as well as an AR map. The user can perform complex searches on 122 campus buildings by building name, description, abbreviation, category, address, and year built. The app enables the user to take multimedia notes during a campus visit. Our exploratory development research illustrates the feasibility of using AR and ML in providing much more effective assistance to visitors of any organization."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["The main campus of Virginia Polytechnic Institute and State University (Virginia Tech) has more than 120 buildings. The campus visitors face problems recognizing a building, finding a building, obtaining directions from one building to another, and getting information about a building. The exploratory development research described herein resulted in an iPhone / iPad software application named VTQuestAR that provides assistance to the campus visitors by using the Augmented Reality (AR) and Machine Learning (ML) technologies. Our research illustrates the feasibility of using AR and ML in providing much more effective assistance to visitors of any organization."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["VTQuestAR: An Augmented Reality Mobile Software Application for Virginia Tech Campus Visitors"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Balci, Osman"],"dc:contributor.committeemember":["Zhang, Liqing","Barkhi, Reza"],"dc:contributor.department":["Computer Science"],"dc:creator":["Yao, Zhennan"],"dc:date.accessioned":["2021-01-08T09:01:31Z"],"dc:date.available":["2021-01-08T09:01:31Z"],"dc:date.issued":["2021-01-07"],"dc:description.abstract":["The main campus of Virginia Polytechnic Institute and State University (Virginia Tech) has more than 120 buildings. 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