From IoT Networks Deployment to Robust Location-Based Services Using the Digital Twin of a Building

被引:1
作者
Chambon, Aurelien [1 ]
Rachedi, Abderrezak [1 ]
Sahli, Abderrahim [2 ]
Mebarki, Ahmed [1 ,3 ]
机构
[1] Univ Gustave Eiffel, F-77454 Marne La Vallee, France
[2] Univ Gustave Eiffel, ESIEE Paris, F-77454 Marne La Vallee, France
[3] Nanjing Tech Univ, Nanjing 210037, Peoples R China
关键词
Digital twins; Databases; Internet of Things; Real-time systems; Computer architecture; Three-dimensional displays; Monitoring; Quality of service; Genetic algorithms; Smart buildings; Big Data; Location awareness; SYSTEMS;
D O I
10.1109/MIC.2024.3502631
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Although building information modeling (BIM) has been around for over five decades, its integration with Big Data generated by Internet of Things (IoT) networks has raised research interest. This fusion enables the digital twin of a building (DTB), a real-time virtual replica facilitating efficient location-based services, precise monitoring, and enhanced operational efficiency. Despite its alignment with the Smart City paradigm, widespread adoption is hindered by the initial investment for IoT network deployment. This article presents a comprehensive process, from optimizing IoT network deployment to implementing robust location-based services. A genetic algorithm leveraging the BIM database improves coverage by 44% compared to random deployments, while a multitier architecture based on deployed and roaming users' devices extends service availability to 80% of devices without Internet access, enhancing overall service quality by similar to 200%. Eventually, the versatility of DTB is showcased through the use case of indoor guidance services, concluding with potential research directions using the DTB.
引用
收藏
页码:32 / 38
页数:7
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