Optimisation of Sensor distribution to support Activity Recognition
Given the challenges placed on today’s society as a result of the ever increasing size of the population coupled with the increased prevalence of long term chronic diseases efforts are being made to identify new and emerging solutions for the delivery and management of health and social care provision. Within these new approaches the use of Information and Communication Technologies to create and support smart environments are being recognised as one possible solution to address the aforementioned challenges. Within smart environments sensors are viewed as being the fundamental component. The data which they generate are used as input to decision support models which in turn facilitate appropriate actuator actions [1]. The positioning, amount(s) and field of view(s) of sensors is therefore a fundamental characteristic of a smart environment. Contemporary smart environment sensor distribution is aligned to either a) a total coverage approach, or b) a human assessment approach.
This Project will extend upon previous work in this area [2] and will aim to develop the appropriate tools and models to support the development and evaluation of a novel paradigm for the optimisation of sensor distributions within smart environments taking into account the mobile nature of the sensing technology. In the first instance investigations should address visualisation tools to encapsulate the requirements of the smart environment in addition to considering the effects of mobile devices and sensing technologies. This information will form the basis for an optimisation algorithm which will automatically identify the optimal positioning of sensors within the smart environment based on their field of view, location and environmental conditions.
It is anticipated that the developed models will be evaluated within the smart environment located within the School of Computing and Mathematics.(http://serg.ulster.ac.uk/)
[1] S. Helal, W. Mann, H. El-Zabadani, J. King, Y. Kaddoura, E. Jansen, “The Gator Tech Smart House: a programmable pervasive space,” Computer, Vol 38, 3, pp. 50 – 60, 2005.
[2] Poland, M.P., Nugent, C.D., Wang, H., Chen. L.: ‘Spatial-Frequency Data Acquisition using Rotational Invariant Pattern Matching in Smart Environments’. Annals of Telecommunications - Annales des Telecommunications, Vol 65, 9-10, pp. 557 – 570, 2010.
Personnel Involved
First Supervisor: Nugent, CD Professor
Second Supervisor: Chen, L Dr
Collaboration: This project does not involve collaboration with another establishment