{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T21:45:08Z","timestamp":1781127908124,"version":"3.54.1"},"reference-count":80,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T00:00:00Z","timestamp":1733702400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Advancements in 3D modelling technology have facilitated more immersive and efficient solutions in spatial planning and user-centred design. In healthcare systems, 3D modelling is beneficial in various applications, such as emergency evacuation, pathfinding, and localization. These models support the fast and efficient planning of evacuation routes, ensuring the safety of patients, staff, and visitors, and guiding them in cases of emergency. To improve urban modelling and planning, 3D representation and analysis are used. Considering the advantages of 3D modelling, this study proposes a framework for 3D indoor navigation and employs a multiphase methodology to enhance spatial planning and user experience. Our approach combines state-of-the art GIS technology with a 3D hybrid model. The proposed framework incorporates federated learning (FL) along with edge computing and Internet of Things (IoT) devices to achieve accurate floor-level localization and navigation. In the first phase of the methodology, Quantum Geographic Information System (QGIS) software was used to create a 3D model of the building\u2019s architectural details, which are required for efficient indoor navigation during emergency evacuations in healthcare systems. In the second phase, the 3D model and an FL-based recurrent neural network (RNN) technique were utilized to achieve real-time indoor positioning. This method resulted in highly precise outcomes, attaining an accuracy rate over 99% at distances of no less than 10 metres. Continuous monitoring and effective pathfinding ensure that users can navigate safely and effectively during emergencies. IoT devices were connected with the building\u2019s navigation software in Phase 3. As per the performed analysis, it was observed that the proposed framework provided 98.7% routing accuracy between different locations during emergency situations. By improving safety, building accessibility, and energy efficiency, this research addresses the health and environmental impacts of modern technologies.<\/jats:p>","DOI":"10.3390\/ijgi13120445","type":"journal-article","created":{"date-parts":[[2024,12,9]],"date-time":"2024-12-09T10:11:47Z","timestamp":1733739107000},"page":"445","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A 3D Model-Based Framework for Real-Time Emergency Evacuation Using GIS and IoT Devices"],"prefix":"10.3390","volume":"13","author":[{"given":"Noopur","family":"Tyagi","sequence":"first","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2370-9384","authenticated-orcid":false,"given":"Jaiteg","family":"Singh","sequence":"additional","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saravjeet","family":"Singh","sequence":"additional","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura 140401, Punjab, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9058-7869","authenticated-orcid":false,"given":"Sukhjit Singh","family":"Sehra","sequence":"additional","affiliation":[{"name":"Department of Physics & Computer Science, Wilfrid Laurier University, Waterloo, ON N2L 3C5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,9]]},"reference":[{"key":"ref_1","first-page":"103066","article-title":"3D Building Interior Modelling for Navigation in Emergency Response Applications","volume":"114","author":"Boguslawski","year":"2022","journal-title":"Int. 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