{"id":4131,"date":"2015-09-11T09:00:00","date_gmt":"2015-09-11T16:00:00","guid":{"rendered":"https:\/\/blogs.msdn.microsoft.com\/msr_er\/2015\/09\/11\/meeting-the-data-challenges-of-urban-computing\/"},"modified":"2016-07-20T07:28:59","modified_gmt":"2016-07-20T14:28:59","slug":"meeting-the-data-challenges-of-urban-computing","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/research\/blog\/meeting-the-data-challenges-of-urban-computing\/","title":{"rendered":"Meeting the data challenges of urban computing"},"content":{"rendered":"

Many people living in the People\u2019s Republic of China and Hong Kong have a new habit: they check the air pollution index before venturing outside. Air quality has deteriorated rapidly in China, with nitrogen dioxide and particulate matter levels frequently\u00a0<\/sub>exceeding safety guidelines set by the World Health Organization.<\/span><\/p>\n

While poor air quality clearly impacts public health, many cities have a dearth of air-quality monitoring stations: there are just 35 in Beijing and 15 in Hong Kong, for example. This lack of monitoring stations hinders evidence-based decision-making and leads to harsh criticisms of the transparency and public relevance of China\u2019s official air pollution index.<\/span><\/p>\n

\"Researchers<\/p>\n

Researchers proposed that they could estimate air quality at locations not covered by monitoring stations by analyzing the relationship between urban dynamics data<\/span>.<\/span><\/p>\n

Since air pollution is highly location-dependent, a citywide air-quality monitoring system would require building many additional monitoring stations, a solution that is prohibitively expensive. And so there is a grim reality: people may diligently check the air pollution index, but they cannot really know the air quality in their specific locale.<\/span><\/p>\n

\u201cDo we have sufficient data to produce reliable air-quality metrics by using urban computing?\u201d Professor Victor Li (opens in new tab)<\/span><\/a>, chairman of information engineering and head of the department of Electrical and Electronic Engineering at the University of Hong Kong, posed this question to his research team. As luck would have it, while Li was challenging his researchers in Hong Kong, Microsoft Research Asia was launching a Call for Research Proposals dealing with urban computing. (Urban computing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces to address issues that major cities face, such as air pollution, excessive energy consumption, and traffic congestion.) Li promptly submitted a proposal, which came to the attention of Microsoft researcher Yu Zheng (opens in new tab)<\/span><\/a>, who has conducted extensive research on urban computing and was also looking into the issues surrounding urban air quality.<\/span><\/p>\n

As Li and his researchers were detailing the correlations between air pollution and various urban dynamics\u2014noting, for instance, that air quality and temperature are spatially correlated\u2014Yu and his team had concluded that a variety of urban big data could be used compensate for the lack of monitoring stations. Li and Yu decided to collaborate and drive more in-depth research.<\/span><\/p>\n