A WiFi-based occupancy sensing, modelling, and simulation method to ensure COVID-19 ventilation and social distancing norms at workplaces

随着各省计划重返工作岗位，我们将面临的一个新挑战是在室内实行安全的社交距离。政策，以界定可接受的居住密度和室内设计配置是必要的。与户外安全距离政策不同，这些政策还应考虑每人的通风要求，以尽量减少接触传染性气溶胶的风险。这些政策需要根据共享办公空间的高分辨率测量占用数据制定。为此，占用传感解决方案提供了一个尚未开发的机会，以制定政策建议和规范这些政策。 在这个项目中，一个研究小组将与两家专门从事占用传感解决方案的公司合作，研究来自真实的办公楼的高分辨率占用数据。该团队将开发一种基于代理的占用建模方法，以模拟各种办公室布局的室内占用模式。这一分析的结果将导致政策建议的占用密度和在线交互式工具，以模拟不同的占用密度和办公室布局的占用模式。该团队还将进行一项案例研究，展示使用基于WiFi的占用传感技术来调节卡尔顿大学行政办公楼的占用密度政策。 拟议中的研究将有助于我们重新启动经济的努力，同时最大限度地减少工作场所开始新疫情的风险。所制定的方法一旦被我们的伙伴采用，将有助于我们的知识型经济。一名博士后研究员和一名博士。学生将进行多学科研究，并在数据挖掘，可视化和居住者建模和模拟方面发展广受欢迎技能。

As provinces are planning for return-to-work, a new challenge that we will face is to practice safe social distancing indoors. Policies to define acceptable occupant densities and interior design configurations are needed. Unlike the safe distancing policies for outdoors, these policies should also consider per-person ventilation requirements to minimize the risk of exposure to infectious aerosols. These policies need to be developed upon high resolution measured occupancy data from shared office spaces. To this end, occupancy sensing solutions offer an untapped opportunity to develop policy recommendations and to regulate these policies. In this project, a team of researchers will partner with two firms specialized in occupancy sensing solutions and study high-resolution occupancy data from real office buildings. The team will develop an agent-based occupancy modelling approach to simulate indoor occupancy patterns for a variety of office layouts. The results of this analysis will lead to policy recommendations for occupant densities and an online interactive tool to simulate occupancy patterns for different occupant densities and office layouts. The team will also conduct a case study demonstrating the use of WiFi-based occupancy sensing technology to regulate occupant density policies in an administrative office building at Carleton University. The proposed research will contribute to our efforts to restart the economy while minimizing the risk of new outbreaks starting at workplaces. The methods developed, once adopted by our partners, will contribute to our knowledge-based economy. One postdoctoral researcher and one Ph.D. student will conduct multidisciplinary research and develop widely sought-after skills in data mining, visualization, and occupant modelling and simulation.