Mobis: A Distributed Paradigm for Mobile Sensor Data Analytics for Evaluating Environmental Exposure

Abstract

Continued advances and cost reduction in personal mobile devices such as smart phones made them widely used in daily-life practices. Mobile devices can be integrated with a growing set of cheap powerful embedded sensors that enable the emergence of mobile sensing applications, including healthcare, environmental monitoring and transportation. As the size of the sensor data continuously grows, managing the data becomes increasingly difficult using traditional database systems. This paper proposes a new framework for large-scale continuously changing mobile sensor data analysis. We discuss the emerging environmental sensing paradigms and opportunities to apply HBase and MapReduce for managing multiple sensor data in the environmental exposome domain. Moreover, we provide an architectural framework and present a concrete use case with a set of data models, spatio-temporal queries, and MapReduce functions.