3D indoor modeling and game theory based navigation for pre and post COVID-19 situation

被引:3
|
作者
Singh, Jaiteg [1 ]
Tyagi, Noopur [1 ]
Singh, Saravjeet [1 ]
Shah, Babar [2 ]
Ali, Farman [3 ]
Alzubi, Ahmad Ali [4 ]
Alkhanifer, Abdulrhman [5 ]
机构
[1] Chitkara Univ, Inst Engn & Technol, Punjab, India
[2] Zayed Univ, Coll Technol Innovat, Dubai, U Arab Emirates
[3] Sungkyunkwan Univ, Coll Comp & Informat, Sch Convergence, Dept Comp Sci & Engn, Seoul, South Korea
[4] King Saud Univ, Community Coll, Dept Comp Sci, Riyadh, Saudi Arabia
[5] King Saud Univ, Dept Comp Sci, Riyadh, Saudi Arabia
关键词
route planning; COVID-19; pandemic; game theory; simulation; localization;
D O I
10.3389/fpubh.2023.1301607
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
The COVID-19 pandemic has greatly affected human behavior, creating a need for individuals to be more cautious about health and safety protocols. People are becoming more aware of their surroundings and the importance of minimizing the risk of exposure to potential sources of infection. This shift in mindset is particularly important in indoor environments, especially hospitals, where there is a greater risk of virus transmission. The implementation of route planning in these areas, aimed at minimizing interaction and exposure, is crucial for positively influencing individual behavior. Accurate maps of buildings help provide location-based services, prepare for emergencies, and manage infrastructural facilities. There aren't any maps available for most installations, and there are no proven techniques to categorize features within indoor areas to provide location-based services. During a pandemic like COVID-19, the direct connection between the masses is one of the significant preventive steps. Hospitals are the main stakeholders in managing such situations. This study presents a novel method to create an adaptive 3D model of an indoor space to be used for localization and routing purposes. The proposed method infuses LiDAR-based data-driven methodology with a Quantum Geographic Information System (QGIS) model-driven process using game theory. The game theory determines the object localization and optimal path for COVID-19 patients in a real-time scenario using Nash equilibrium. Using the proposed method, comprehensive simulations and model experiments were done using QGIS to identify an optimized route. Dijkstra algorithm is used to determine the path assessment score after obtaining several path plans using dynamic programming. Additionally, Game theory generates path ordering based on the custom scenarios and user preference in the input path. In comparison to other approaches, the suggested way can minimize time and avoid congestion. It is demonstrated that the suggested technique satisfies the actual technical requirements in real-time. As we look forward to the post-COVID era, the tactics and insights gained during the pandemic hold significant value. The techniques used to improve indoor navigation and reduce interpersonal contact within healthcare facilities can be applied to maintain a continued emphasis on safety, hygiene, and effective space management in the long term. The use of three-dimensional (3D) modeling and optimization methodologies in the long-term planning and design of indoor spaces promotes resilience and flexibility, encouraging the adoption of sustainable and safe practices that extend beyond the current pandemic.
引用
收藏
页数:14
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