Quantitative evaluation of public spaces using crowd replication
Quantitative evaluation of public spaces using crowd replication
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DOI：
10.1145/2996913.2996946
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发表时间：
2016-10
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影响因子：
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通讯作者：
Samuli Hemminki;Keisuke Kuribayashi;S. Konomi;Petteri Nurmi;Sasu Tarkoma
中科院分区：
文献类型：
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作者：
Samuli Hemminki;Keisuke Kuribayashi;S. Konomi;Petteri Nurmi;Sasu Tarkoma
我们建议人群复制作为一个低努力，易于实施和成本效益的机制，量化的使用，活动和社交的公共空间。人群复制结合了移动的传感、直接观察和数学建模，以实现公共空间的资源高效和准确量化。人群复制背后的核心思想是仪器的研究人员调查一个公共空间与传感器嵌入在商品设备和从事他/她模仿人们使用的空间。通过将收集到的传感器数据与直接观测和群体模型相结合，可以将单个传感器轨迹概括为捕获更大群体的行为。我们验证使用人群复制作为一种数据收集机制，通过一个典型的大都市城市空间内进行的实地研究。我们的评估结果表明，人群复制准确地捕捉到真实的人类动态（从人群复制和视觉监控估计的指标之间的相关性为0.914），并捕捉到的数据是代表的人在公共空间内的行为。
We propose crowd replication as a low-effort, easy to implement and cost-effective mechanism for quantifying the uses, activities, and sociability of public spaces. Crowd replication combines mobile sensing, direct observation, and mathematical modeling to enable resource efficient and accurate quantification of public spaces. The core idea behind crowd replication is to instrument the researcher investigating a public space with sensors embedded on commodity devices and to engage him/her into imitation of people using the space. By combining the collected sensor data with a direct observations and population model, individual sensor traces can be generalized to capture the behavior of a larger population. We validate the use of crowd replication as a data collection mechanism through a field study conducted within an exemplary metropolitan urban space. Results of our evaluation show that crowd replication accurately captures real human dynamics (0.914 correlation between indicators estimated from crowd replication and visual surveillance) and captures data that is representative of the behavior of people within the public space.