In academic institutions and various other organizations, there is a huge diversity in activities performed by different individuals. These activities if tracked using can arrive as a vital source of information that can be used for developing various services. These services can be of different granularities concerning the final output. It can be a small scale activity-based user discrimination and profiling to the large-scale identification of activity-based groups. To develop these services, several teams within our group are working on Android application developments for gathering sensor logs from the smartphones and in parallel designing low power hardware devices that can capture these signals seamlessly. Moreover, in addition to these, there are teams in our group who are currently working on identifying various dynamics that occur in these activity-based groups in an organization.
A few snapshots of the work we have done:
- Snigdha Das, Dibya Jyoti Roy, Subrata Nandi, Sandip Chakraborty, and Bivas Mitra. 2017. UDAT: User Discrimination Using Activity-Time Information. In Proceedings of the 18th IEEE conference on Mobile Data Management. 352–355.
- Prof. Niloy Ganguly
- Dr. Bivas Mitra
- Dr. Sandip Chakraborty
- Snigdha Das
- Soumyajit Chatterjee