Improving automated collection of Social Distancing data from camera feeds

新冠肺炎疫情给全球社会带来了前所未有的封锁。关于封锁的影响和效果的数据至关重要，原因如下：*流行病学建模需要了解社会中存在的互动的数量，以及每次干预后这些互动的变化。*封锁规则是新的、前所未有的，很难执行。因此，围绕合规性以及政府信息和执法战略的有效性存在着很大的不确定性。数据是决定下一步行动的关键。*警方承受着巨大的压力，他们的许多队伍处于孤立状态。能够针对社交互动数量较多的地区(&lt；200万)执行封锁措施非常重要。Viacity目前通过我们的智能传感器提供匿名道路使用数据。这是唯一可用的多模式数据源，可以提供有关英国各地行人、骑自行车者、汽车和商用车辆数量的准确数据。我们的数据已经成为政府分析封锁有效性的关键部分。在封锁后的头几周里，我们开发了传感器输出的新数据，它测量了行人之间的距离，并提供了2M次互动的统计数据。这种目前的方法不能提供足够的信息，使人们能够就确切的规则和封锁的执行做出更详细的决定。在这个项目中，我们将：*测量互动的持续时间--人们互动的时间越长，感染的风险就越高*为骑自行车的人以及骑自行车的人和行人之间的社会距离提供测量，以便政府能够了解哪些户外运动模式对社会距离更有效*希望对“家庭群体”和“陌生人”之间的互动之间的差异进行分类，这样收集的数据就不会被用来阻止目前被允许一起外出的“家庭群体”一起度过时间我们将把这些新的分析方法应用于我们现有的传感器网络，在英国16个城市提供超过450个数据馈送。这些数据将帮助政府计划取消封锁措施，并监测社会互动不会随着限制的取消而增长太快。

The Covid-19 Pandemic has brought about an unprecedented lockdown to global society. Data on the impact and effectiveness of the lockdown is critically important for the following reasons:* Epidemiology modelling needs to know the number of interactions that there are in society, and the change in these interactions following each intervention.* The lockdown rules are new, unprecedented and hard to enforce. As a result, there is a lot of uncertainty around compliance, and the effectiveness of government messaging and enforcement strategies. Data is critical in determining what the next move should be.* The police are under significant pressure, with many of their ranks in isolation. Being able to target lockdown enforcement to areas where there is a higher number of social interactions (<2m) is important.Vivacity currently provides anonymous road usage data from our smart sensors. This is the only available multi-modal data source which provides accurate data on the volume of pedestrians, cyclists, cars and commercial vehicles across the UK. Our data is already forming a key part of the Governments analysis on the effectiveness of the lockdown. In the first few weeks following the lockdown, we developed a new data output from the sensors, which measured the distance between pedestrians, and provided statistics on the number of <2m interactions. This current method does not give sufficient information to enable more detailed decisions to be made on the exact rules and enforcement of the lockdown. In this project we will: * Measurement of the duration of interactions - the longer people interact, the increased risk of infection* Provide social distancing measurement for cyclists, and between cyclists and pedestrians, so that the government can understand which outdoor exercise modes are more effective for social distancing* Look to classify the difference between "household groups" and interactions between "strangers", so that the data gathered is not used to discourage "household groups" who are currently allowed to go outside together from spending time together We will apply these new analysis methods to our existing network of sensors to provide over 450 data feeds across 16 cities in the UK. This data will help the Government plan the removal of the lockdown measures, and monitor that social interactions do not grow too quickly as restrictions are lifted.