Mubaris Nadeem, Johannes Zenkert, Christian Weber, M. Fathi, Muhammad Hamza
{"title":"Smart UX-design for Rescue Operations Wearable - A Knowledge Graph Informed Visualization Approach for Information Retrieval in Emergency Situations","authors":"Mubaris Nadeem, Johannes Zenkert, Christian Weber, M. Fathi, Muhammad Hamza","doi":"10.1109/eIT57321.2023.10187320","DOIUrl":null,"url":null,"abstract":"This paper presents a knowledge graph-informed smart UX-design approach for supporting information retrieval for a wearable, providing treatment recommendations during emergency situations to health professionals. This paper describes requirements that are unique to knowledge graph-based solutions, as well as the direct requirements of health professionals. The resulting implementation is provided for the project, which main goal is to improve first-aid rescue operations by supporting artificial intelligence in situation detection and knowledge graph representation via a contextual-based recommendation for treatment assistance.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Electro Information Technology (eIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/eIT57321.2023.10187320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a knowledge graph-informed smart UX-design approach for supporting information retrieval for a wearable, providing treatment recommendations during emergency situations to health professionals. This paper describes requirements that are unique to knowledge graph-based solutions, as well as the direct requirements of health professionals. The resulting implementation is provided for the project, which main goal is to improve first-aid rescue operations by supporting artificial intelligence in situation detection and knowledge graph representation via a contextual-based recommendation for treatment assistance.