A NOVEL CROWD SENSING FRAMEWORK FOR URBAN COMPUTING APPLICATIONS
MetadataShow full item record
Driven by the proliferation of sensor-rich mobile devices, crowd sensing has emerged as a new paradigm of gathering information about the physical world. In crowd sensing applications, humans work as the sensor carriers or even the sensors, and report what they learn about the conditions of the surrounding environment, such as traffic conditions, broken public utilities, gas prices, weather conditions and air quality. Despite the large amount of data collected from the crowd sensing applications, there are several challenges which prevent us from obtaining useful knowledge. In this thesis, I present a novel framework to tackle some of the major challenges and demonstrate how crowd sensing can benefit urban computing applications.