During the COVID-19 pandemic, policy makers at the Greater London Authority, the regional governance body of London, UK, are reliant upon prompt and accurate data sources. Large well-defined heterogeneous compositions of activity throughout the city are sometimes difficult to acquire, yet are a necessity in order to learn 'busyness' and consequently make safe policy decisions. One component of our project within this space is to utilise existing infrastructure to estimate social distancing adherence by the general public. Our method enables near immediate sampling and contextualisation of activity and physical distancing on the streets of London via live traffic camera feeds. We introduce a framework for inspecting and improving upon existing methods, whilst also describing its active deployment on over 900 real-time feeds.
翻译:在COVID-19大流行期间,大伦敦管理局(联合王国伦敦区域管理机构)的决策者依赖迅速和准确的数据来源,整个城市的活动有时很难获得定义明确的各种成分,但为了了解“动荡”,从而作出安全的政策决定,还是有必要的。在这个空间内,我们项目的一个组成部分是利用现有基础设施来估计一般公众对社会不稳定的遵守情况。我们的方法使活动几乎能够立即抽样和背景化,并通过现场交通摄像头供电在伦敦街头进行身体分流。我们引入了检查和改进现有方法的框架,同时描述其积极部署900多个实时供电。