Implementation, Management and Analysis of User Groups of GSM Database

The most widely used mobile computing device today is the Mobile phone, can be used not only for voice and data communications but also as a computing device running context aware applications. In this paper we present a model that based on GSM data base. The objective of this paper identifies user groups based on places visited by a user, date, time, longitude and latitude. This information can be used by applications for the detection of users, user context, discovering of groups and relation between them using clustering technique for data sets of data mining. This paper explores how coarse-grained GSM data from mobile phones can be used to recognize high-level properties of user mobility, and daily step count. We demonstrate that even without knowledge of observed cell tower locations, we can recognize mobility modes that are useful for several application domains. Our mobility detection system was evaluated with GSM traces from the everyday lives of three data collectors.