{"id":{"repo_id":"utc","oai_identifier":"oai:scholar.utc.edu:theses-1725"},"canonical_url":"https://search.dev.ndltd.org/etd/utc/oai:scholar.utc.edu:theses-1725","repository":{"repo_id":"utc","name":"University of Tennessee - Chattanooga","base_url":"https://scholar.utc.edu/do/oai/"},"display":{"title":"Data-fused urban mobility applications for smart cities","abstract":"Though vehicles are becoming more advanced with added safety feature technology, we must still rely on our own instincts and senses to make decisions. This thesis presents two applications that can be utilized by drivers, passengers, or pedestrians and allow a wider range of visibility during commutes. The first application uses the concept of see-through technology to assist the driver with a real-time augmented view of a traffic scene that in reality may be blocked by the vehicle in front. The second application presents a mobile application that utilizes two sources to gather the user's location information, one using absolute location from a Global Positioning System (GPS) enabled device and the other from merging the concepts of computer vision, object detection, and mono-vision depth calculation, and place each instance of an identified object on the mapping application. Currently, mapping items such as stores, accidents, and traffic conditions are very common, but this application takes into account the location of individual users to give a holistic view of people instead of places.","abstract_html":"Though vehicles are becoming more advanced with added safety feature technology, we must still rely on our own instincts and senses to make decisions. This thesis presents two applications that can be utilized by drivers, passengers, or pedestrians and allow a wider range of visibility during commutes. The first application uses the concept of see-through technology to assist the driver with a real-time augmented view of a traffic scene that in reality may be blocked by the vehicle in front. The second application presents a mobile application that utilizes two sources to gather the user's location information, one using absolute location from a Global Positioning System (GPS) enabled device and the other from merging the concepts of computer vision, object detection, and mono-vision depth calculation, and place each instance of an identified object on the mapping application. Currently, mapping items such as stores, accidents, and traffic conditions are very common, but this application takes into account the location of individual users to give a holistic view of people instead of places.","abstract_has_math":false,"creators":["Thompson, Rebekah"],"institution":"University of Tennessee at Chattanooga","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Sartipi, Mina","Wu, Dalei; Kandah, Farah","College of Engineering and Computer Science"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-09-01T07:00:00Z","date_published":"2019-09-01T07:00:00Z","updated_at":"2026-07-24T05:46:51Z","subjects":["Smart power grids","Intelligent transportation systems"],"languages":["English","eng"],"rights":[],"rights_urls":["https://rightsstatements.org/page/InC/1.0/?language=en"],"identifier_entries":[]},"links":{"outbound_url":"https://scholar.utc.edu/theses/571","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Sartipi, Mina","Wu, Dalei; Kandah, Farah","College of Engineering and Computer Science"]},{"key":"dc:creator","label":"Author","values":["Thompson, Rebekah"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-08-01T07:00:00Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2019-09-01T07:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["University of Tennessee at Chattanooga","Chattanooga (Tenn.)"]},{"key":"dc:relation","label":"Dc Relation","values":["Masters Theses and Doctoral Dissertations"]},{"key":"dc:type","label":"Dc Type","values":["Masters theses","Text"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Smart power grids","Intelligent transportation systems"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://rightsstatements.org/page/InC/1.0/?language=en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholar.utc.edu/theses/571"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Dept. of Computer Science and Engineering","M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."]},{"key":"dc:description.abstract","label":"Abstract","values":["Though vehicles are becoming more advanced with added safety feature technology, we must still rely on our own instincts and senses to make decisions. This thesis presents two applications that can be utilized by drivers, passengers, or pedestrians and allow a wider range of visibility during commutes. The first application uses the concept of see-through technology to assist the driver with a real-time augmented view of a traffic scene that in reality may be blocked by the vehicle in front. The second application presents a mobile application that utilizes two sources to gather the user's location information, one using absolute location from a Global Positioning System (GPS) enabled device and the other from merging the concepts of computer vision, object detection, and mono-vision depth calculation, and place each instance of an identified object on the mapping application. Currently, mapping items such as stores, accidents, and traffic conditions are very common, but this application takes into account the location of individual users to give a holistic view of people instead of places."]},{"key":"dc:title","label":"Title","values":["Data-fused urban mobility applications for smart cities"]}]}],"canonical_facts":{"dc:contributor":["Sartipi, Mina","Wu, Dalei; Kandah, Farah","College of Engineering and Computer Science"],"dc:creator":["Thompson, Rebekah"],"dc:date":["2018-08-01T07:00:00Z"],"dc:date.available":["2019-09-01T07:00:00Z"],"dc:description":["Dept. of Computer Science and Engineering","M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."],"dc:description.abstract":["Though vehicles are becoming more advanced with added safety feature technology, we must still rely on our own instincts and senses to make decisions. This thesis presents two applications that can be utilized by drivers, passengers, or pedestrians and allow a wider range of visibility during commutes. The first application uses the concept of see-through technology to assist the driver with a real-time augmented view of a traffic scene that in reality may be blocked by the vehicle in front. The second application presents a mobile application that utilizes two sources to gather the user's location information, one using absolute location from a Global Positioning System (GPS) enabled device and the other from merging the concepts of computer vision, object detection, and mono-vision depth calculation, and place each instance of an identified object on the mapping application. 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