Yilun Wang, Yu Zheng, and Tong Liu
This demonstration presents a noise map of New York City, based on four ubiquitous data sources: 311 complaint data, social media, road networks, and Point of Interests (POIs). The noise situation of any location in the city, consisting of a noise pollution indicator and a noise composition, is derived through a contextaware tensor decomposition approach we proposed in . Moreover, our demo highlights two components: a) ranking locations based on inferred noise indicators in various settings, e.g., on the weekdays (or weekends), in a time slot (or overall time), and in a noise category (or all categories); b) revealing the distribution of noises over different noise categories in a location.
|Published in||UbiComp 2014|
|Publisher||ACM – Association for Computing Machinery|
Yu Zheng, Tong Liu, Yilun Wang, Yanchi Liu, and Yanmin Zhu. Diagnosing New York City’s Noises with Ubiquitous Data, ACM, September 2014.
Tong Liu, Yu Zheng, Lubin Liu, Yanchi Liu, and Yanmin Zhu. Methods for Sensing Urban Noises, May 2014.