This project tracks WiFi signals from mobile devices to understand how people navigate through large indoor spaces and how their experience can be improved.
Supplying the individual information needs of online users is well understood but a new frontier is on the horizon. It is the servicing of information seekers in large indoor areas such as museums, corporate headquarters, airports, shopping malls, and university buildings. Here activities in the space drive and define demands for data and this is a new challenging area of research. Accurate information provision requires tracking of visitors that is both privacy preserving and practical.
Using the unexplored approach of passively tracking the Wi-Fi signals of mobile devices this project aims to create a system that can acquire, synthesize and derive location information to support indoor space management and deliver personalised content to users.
This project aims to:
- To develop a predictive heuristic model of goal-orientated way finding behaviour
- To establish a model of common information goals between cohorts of users
- To create an enhanced positioning system, integrating a behavioural model of way finding to supplement noisy or sporadic positioning fixes
- To develop a demonstrator search engine that retrieves relevant and contextually aware personalised information
This project is dedicated to finding an answer to the question: Do users, who navigate indoor spaces in similar ways, have unknowingly shared motivations and information needs; and can this commonality of purpose be tracked and exploited when delivering information to the individual?
This is a joint research venture between:
- RMIT School of Science
- RMIT School of Engineering
- RMIT SPACE Research Centre
- University of Melbourne Faculty of Architecture, Building and Planning and
- Viocorp Systems Intelligence Pty Ltd.