A special report in the April 19, 2014, issue of The Economist predicted that 70 percent of China's population—some 1 billion people—will live in cities by 2030. While China's urban growth offers a higher standard of living to many citizens, it also creates serious problems.
Among these urban problems, noise pollution ranks among the most pervasive, as factories, construction projects and vehicles produce a cacophony of unwholesome sounds, with deleterious effects on the mental and physical well-being of city dwellers. Unfortunately, existing tools fail to track simultaneous sources of noise pollution accurately in real time, leaving researchers with an incomplete picture of the problem and how to address it. Clearly, researchers need a better way of tracking urban noise.
Creating a noise map with smartphones
With funding from Microsoft Research Asia, investigators in the Department of Computer Science and Engineering at Shanghai Jiao Tong University, led by Professor Yanmin Zhu, are developing NoiseSense, a service that will map urban noises by using crowdsourced noise measurements from smartphone users. They envision a noise-mapping service that will allow anyone to query the noise level in any urban area in the world. More importantly, NoiseSense could give authorities the information needed to devise and implement effective noise-abatement strategies.
Accelerating urban informatics with Microsoft Azure
A future in which smartphone users willingly measure noise levels and a super computer system stands ready to crunch the resulting avalanche of data may seem idealistic, but it is exactly what Zhu and his team are striving to achieve. Having spent six months at Microsoft Research Asia as the recipient of a Young Faculty Program award, Zhu was familiar with the company's research into the burgeoning field of urban informatics. Thus he was well positioned to apply for one of the grants offered by the Microsoft Azure for Research Award program—and delighted when his team's proposal was one of only 25 Asian submissions (out of 60) to be funded. Taking advantage of the grant of free cloud-computing service on Microsoft Azure, Zhu's team cleared the hurdle of managing large-scale noise data.
"I have really enjoyed our collaborations with Microsoft Research Asia in the past two years," says Zhu. "I benefit a lot from many Microsoft academic programs including, but not limited to, the Accelerating urban informatics with Microsoft Azure program, Microsoft Azure for Research program and Microsoft Research AsiaYoung Faculty program. Furthermore, a couple of my graduate students have been well trained through this noise sensing project and one of my students received a Microsoft Research Asia Fellowship Finalist award last year. I look forward to more in-depth collaborations with Microsoft in the future."
The urban computing initiative
Zhu's team has made significant progress with the help of Microsoft Azure and the support of Microsoft Research Asia. They have developed a system prototype for a real-time, fine-grained noise-mapping service on Microsoft Azure, and they have created noise-measuring smartphone apps for both Windows Phone and Android operating systems.
Yu Zheng, a lead researcher at Microsoft Research, has worked closely with Zhu on the noise-mapping project, sharing his experience and expertise in the field of urban informatics. In fact, Zheng piloted Microsoft Research's Urban Computing project, which has promoted computing applications designed to improve many aspects of city life, including urban transportation, air quality and energy consumption, as well as noise pollution.
Noise mapping and other urban computing research programs represent just a small percentage of the numerous ways that big data and computing can contribute to a better life for city dwellers. Researchers are only in the early days of exploiting the power and potential of urban computing—and we're excited to be part of this momentous adventure.
—Kangping Liu, Senior Research Program Manager, Microsoft Research
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Source: Smartphone app takes aim at noise pollution
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