Usage of reality mining in location based activity recognition

The most important changes may come, however, from the fact that mobile phones can be used for reality mining. Their reality mining functionality is mostly latent at this point, but already these devices are being used to measure population flows into cities and slums, to map the movement of populations during emergencies, to identify neighbourhoods where social services are inadequate. The reality mining functionality of mobile phone networks is what governments in countries such as India are using to track terrorists, and they claim that the vast majority of captured terrorists have been identified through mobile phone transactions. The ability of mobile phone networks to identify unusual patterns of movement and communication. We can also use reality mining of mobile phone GPS data, call logs, and email records to better understand the “traffic” within an organization. Analysis of these digital traces allows a detailed picture of face to face, voice, and digital communication patterns. These patterns, in turn, allow us a new level of insight into the problems of industry and government, including building customer relationships, resource management, transportation, and public health. In our studies of many different types of companies, we have found that the trade off between face-to-face and email communication is a critical predictor of both productivity and job satisfaction. In fact, variations in these patterns can account for more than 30 percent of the differences in productivity between different parts of the same company! Patterns of change within these communication networks are also a critical predictor of creative productivity, accounting for up to 40 percent of differences in creative output.4 In short, reality mining is beginning to provide the capacity to collect and analyze data about people with a breadth and depth that was previously inconceivable. Current work using reality mining techniques is underway in a variety of applications. For example, reality mining studies of voice, communications, and mobility patterns have already demonstrated the ability to screen for depression, infer quality-of-life metrics, and develop financial indexes for individual neighbourhoods [4].