Department of Computing Science, University of Alberta, Edmonton, AB T6G 2R3, Canada.
Sensors (Basel). 2020 Dec 12;20(24):7137. doi: 10.3390/s20247137.
The effectiveness of sensor-based applications for smart homes and smart buildings is conditioned upon the deployment configuration of their underlying sensors. Real-world evaluation of alternative possible sensor-deployment configurations is labor-intensive, costly, and time-consuming, which implies the need for a simulation-based methodology. In this work, we report on such a methodology that supports the modeling of indoor spaces, the activities of their occupants, and the behaviors of different types of sensors. We argue that, in order for a simulation to be useful for the purpose of evaluating a sensor deployment configuration, it has to generate realistic event streams of individual sensors over time, as well as realistic compositions of sensor events within a time window. We have evaluated our simulator for smart indoor spaces, SIMsis toolkit, in the context of our Smart-Condo ambient-assisted living platform, supporting the observation and analysis of activities of daily living (ADLs). Our findings indicate that SIMsis produces realistic agent traces and sensor readings, and has the potential to support the process of developing and deploying sensor-based applications.
基于传感器的智能家居和智能建筑应用的有效性取决于其底层传感器的部署配置。替代可能的传感器部署配置的实际评估是劳动密集型、昂贵且耗时的，这意味着需要基于仿真的方法。在这项工作中，我们报告了一种支持室内空间建模、其居住者活动以及不同类型传感器行为的方法。我们认为，为了使仿真能够用于评估传感器部署配置，它必须随时间生成单个传感器的现实事件流，以及在时间窗口内的传感器事件的现实组合。我们已经在我们的 Smart-Condo 辅助生活平台的上下文中评估了我们的智能室内空间模拟器 SIMsis 工具包，以支持对日常生活活动 (ADL) 的观察和分析。我们的研究结果表明，SIMsis 生成了现实的代理跟踪和传感器读数，并且有可能支持基于传感器的应用程序的开发和部署过程。
