Fine-Grained Air Pollution Data Enables Smart Living and Efficient Management

Yuxuan Liu, Xinyu Liu, Fanhang Man, Chenye Wu, Xinlei Chen

Abstract: Fine-grained air pollution data is essential for smart living and efficient city management. However, it is arduous to obtain accurate air pollution data with high spatial and temporal resolutions via mobile crowdsensing (MCS) under limited budgets. Thus, we propose FAD, a system fully using fine-grained air pollution data to provide diverse services. Moreover, a low-cost yet highly accurate portable sensing device is designed for MCS applications to enhance data resolutions. Finally, we demonstrate various FAD-based services for citizens and governments in the real world.