Method for vibration pollution assessment based on fuzzy evidence and its application in urban vibration pollution map

Abstract

Vibration pollution poses a significant threat to the physical and mental well-being of citizens, while also exhibiting an undeniable adverse effect on the sustainable development of cities. Consequently, there has been a notable rise in scholarly interest regarding this issue. The monitoring and evaluation of vibration pollution play an important role in vibration pollution control, providing a scientific basis for rational environment policy formulation. However, traditional vibration pollution monitoring is based on short-term observations at fixed locations with small sample sizes, which cannot truly reflect the overall long-term pollution situation of the entire region. At the same time, traditional vibration pollution assessment also overlooks the uncertainty of subjective reactions, including differences in individual feelings and ambiguity in conceptual judgments of vibration comfort. To address this issue, a novel vibration pollution control framework using crowd sensing for measurement, fuzzy set for assessment, Dempster-Shafer (DS) evidence theory for data fusion, and vibration pollution map for visualization, is proposed in this study. Using ubiquitous smartphones as sensing terminals, 5960 vibration records in real environments, including vibration signals, GPS, vibration comfort evaluations, and environmental factors, have been collected. Based on these data, the combination membership functions to evaluate single vibration pollution are established. Considering the time-varying nature of vibration pollution, an optimized DS evidence method for long-term vibration assessment is adopted. Finally, in order to verify the feasibility and effectiveness of the method proposed, a field test covering 18.55 km2 was conducted. Then, an example of the urban vibration pollution map is generated where the distribution of vibration pollution can be vividly displayed.