Device-free Behavioural Analytics Using WiFi Signals

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By reflecting WiFi signals, human activities introduce discernible changes in the radio signals received by nearby WiFi access points. This project will develop signal processing and machine learning techniques to detect human behaviour in shopping malls, airports, and museums, by analysing large volume of radio signals pervasively available from in-situ WiFi infrastructure. The analytics will answer questions like: where the people spent most of the time, how many people are waiting in the queue, what activities are performed by the people and so on, which will empower the business owners to improve productivity and customer satisfaction.

The HDR should have the following technical skills and experiences: (i) 4-year Bachelor or preferably a Masters degree in Computer Science or Electrical Engineering, (ii) Good knowledge of WiFi networks, (iii) Basic knowledge of signal processing techniques and machine learning algorithms, (iv) high level of mathematical skills with practical experience in using MATLAB.

The HDR should be comfortable working in a team environment interacting with several other students and staff working in the same team. The HDR is required to collect extensive wifi data from large number of experiments involving human subjects. The HDR should be willing to travel to Europe and USA and spend part of the PhD program in international collaborators' labs.

Supervisory team
Mahbub
Hassan

Engineering
Computer Science and Engineering
Wen
Hu

Engineering
Computer Science and Engineering
Aruna
Seneviratne

Engineering
Electrical Engineering and Telecommunications
mahbub.hassan@unsw.edu.au