Design And Implementation Of Crowd Sensing Based Environmental Pollution Reporting System

Currently,the environmental problem,such as urban air pollution,has become a major concern in our society,and the environmental pollution prevention requires the strong support of scientific technologies.As a new sensing paradigm of the Internet of Things,the "crowd sensing" utilizes users' mobile devices as basic sensing units to cooperatively complete large-scale sensing tasks through crowdsourcing on the mobile Internet,which provides a new and effective way for environment monitoring and pollution reporting.In this thesis we design and implement an environmental pollution reporting system based on the crowd sensing paradigm.First,we analyze the system requirements in detail,and discuss the two key problems faced by the system:target localization of polluction events,and authenticity verification of pollution images.For these two problems,we analyze the development situation of related technologies and the drawbacks of existing methods,and then propose a target localization method based on the fusion of multiple smarphone sensors as well as a secure and active image authenticity verification method.According to the requirements of the considered application scenarios,we provide a system overall design,and detailedly design and implement each module on Web server and Android smartphone.Finally,we test the function and performance of the system under real-world scenarios to verify that the system meets the requirements from various aspects.