Physical-social fusion to assist public services in the war against air pollution in China

Abstract

Many areas in China, e.g., Beijing-Tianjin-Hebei area, have been suffering from severe air pollution problem in recent years. The haze has jeopardized people's health and aroused deep concern from the public. To understand residents concerns better and leverage the power of the crowd, the government encourages organizations and individuals to participate in environmental protection activities. In this paper, we describe a decision supporting system with a set of algorithms implemented to extract insights from fused physical data (Air Quality Index, AQI) and social data (social buzz). The system provides insights for the government to closely improve its public services to curb the air pollution, including understanding the correlation between AQI and residents sentiment, spot and remove illegal sources of air pollution.