Jožef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia.
Jožef Stefan International Postgraduate School (IPS), Jamova cesta 39, 1000 Ljubljana, Slovenia.
Sensors (Basel). 2022 Jul 27;22(15):5609. doi: 10.3390/s22155609.
The integration of infectious disease modeling with the data collection process is crucial to reach its maximum potential, and remains a significant research challenge. Ensuring a solid empirical foundation for models used to fill gaps in data and knowledge is of paramount importance. Personal wireless devices, such as smartphones, smartwatches and wireless bracelets, can serve as a means of bridging the gap between empirical data and the mathematical modeling of human contacts and networking. In this paper, we develop, implement, and evaluate concepts and architectures for advanced user-centric proximity estimation based on smartphone radio environment monitoring. We investigate innovative methods for the estimation of proximity, based on a person-radio-environment trace recorded by the smartphone, and define the proximity parameter. For this purpose, we developed a smartphone application and back-end services. The results show that, with the proposed procedure, we can estimate the proximity of two devices in terms of near, medium, and far distance with reasonable accuracy in real-world case scenarios.
传染病建模与数据收集过程的融合对于充分发挥其潜力至关重要，但这仍然是一个重大的研究挑战。确保用于填补数据和知识空白的模型有坚实的经验基础是至关重要的。个人无线设备，如智能手机、智能手表和无线手环，可以作为连接经验数据和人类接触与网络的数学建模之间差距的一种手段。在本文中，我们开发、实现和评估了基于智能手机无线电环境监测的先进以用户为中心的接近度估计的概念和架构。我们研究了基于智能手机记录的人员-无线电环境跟踪来估计接近度的创新方法，并定义了接近度参数。为此，我们开发了一个智能手机应用程序和后端服务。结果表明，通过所提出的方法，我们可以在真实场景中以合理的精度估计两个设备之间的近距离、中距离和远距离。
