Staff profiles

Ambient and Computational Intelligence Research Group

Research Students:

• Sawsan Mahmoud
• Saifullizam Puteh
• Hasan Alkhadafe
• Anthony Ntaki
• Ahmad Al Shami

Areas of research include computational intelligence, ambient intelligence, ambient assisted living, intelligent environments, pervasive technologies related to assisted environment, robot tracking and learning and adaptive fuzzy systems.

• Ambient and Computational Intelligence: The combination of Wireless Sensor Network technology and computer intelligence techniques is used to make an inhabited environment with predictive capabilities. In such an intelligent inhabited environment the occupancy of different areas can be monitored continuously to adapt a technique in order to predict the future occupancy of different areas in the environment. One of the most important applications of this predictive feature is to assist elderly people to live independently; safe and in control. Research in this area will enable us to work and live in smarter environments. Furthermore, smart appliances providing often tremendous environmental, economical and social benefits for a variety of critical services. These services include: assistive control systems for elderly and disabled people; industrial and environmental monitoring; bio-informatics and security; home and office automation; and robotics and sensor network application.
• Robot Tracking and Eye Gaze: This research investigates the use of eye-gaze tracking in controlling the navigation of mobile robots remotely through a purpose built interface. Controlling mobile robots from a remote location requires the operator to continuously monitor the status of the robot through some sort of feedback system. Assuming that a vision-based feedback system is used such as video cameras mounted onboard the robot; this requires the eyes of the operator to be engaged in the monitoring process throughout the whole duration of the operation. Meanwhile, the hands of the operator need to be engaged, either partially or fully, in the driving task using any input devices. Therefore, the aim of this research is to build a vision based interface that enables the operator to monitor as well as control the navigation of the robot using only his/her eyes as inputs to the system since the eyes are to be engaged in performing some tasks anyway. This will free the hands of the operator for other tasks while controlling the navigation is done through an intelligent interaction interface using eye-gaze tracking. More details is available from this link.
• GPS Tracking for School Buses: Our innovative technology keep parents informed of their children's location at any given time. Parents will know if their children have reached their schools with our without any delay and they should also know when exactly will be expecting them back home. The system will work closely with schools and bus service providers to optimise their limited resources and communicate the information to parents and local authorities. More information is available from the Schools Transport website.
• Learning and Adaptive Fuzzy Systems: The main advantage of a fuzzy inference system is its ability to utilise information expressed in linguistic form. Up until quite recently, the design of a fuzzy inference system is very much an art. The designer considers the knowledge accumulated and crafts the membership function(s) and/or the inference mechanism in the system. Often, these membership functions are fixed once the design process has terminated. It would be desirable to have a fuzzy inference system whose membership function parameters can be "adapted'' or "learned'' from input and output data.

Selected publications

• Smart Homes for the Elderly Dementia Sufferers: Identification and Prediction of Abnormal Behaviour, Lofti A, Langensiepen C, Mahmoud S, Aklaghinia MJ, Journal of Intelligence and Humanized Computing, 2011.
• Use of gesture recognition to control household devices for older people, Langensiepen C, Lotfi A, Higgins S, Journal of Assistive Technologies, 2010, 4, 4.
• Information Acquisition Using Eye-Gaze Tracking for Person-Following with Mobile Robots, Latif HO, Sherkat N, Lotfi A, International Journal of Information Acquisition, 2009, 6, 3.
• Occupant Behaviour Prediction in Ambient Intelligence Computing Environment. Akhlaghinia M J, Lotfi A, Langensiepen C and Sherkat N,International Journal of Uncertain Systems, 2008, 2, 2.
• Single Occupancy Simulator for Ambient Intelligence Environment. Akhlaghinia M J, Lotfi A, Langensiepen C and Sherkat N, Journal of Internet Technology, 2008, 9, 4, 333-338.

• Chair of the organising committee, the 7th IEEE International Conference on Intelligent Environments – IE’11, Nottingham, July 2011.
• Member of International Programme Committee - 2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), Paris, April 2011.
• Member of International Programme Committee, IEEE International Symposium on Intelligent Agents (IA 2011), Paris, France, 11-15 April, 2011.
• Member of the organising committee – IEEE International Conference of Fuzzy Systems - FUZZ-IEEE2007 – London, UK, 23-26 July 2007.
• Invited talk in the Institute of Engineering, Sheffield Hallam University, January 2011.
• Member of International Programme Committee, Global Congress on Intelligent Systems (GCIS 2010), Wuhan, China, 16-17 December, 2010.
• Member of Programme Committee, The 6th International Conference on Intelligent Environments (IE'10), Kuala Lumpur, Malaysia, 19-21 July 2010.
• Member of International Programme Committee, 16th International Conference on Soft Computing (MENDEL'10), Brno, Czech Republic, 23-25 June 2010.

Opportunities to carry out postgraduate research towards an MPhil/PhD or MSc by research exist in all the areas identified above.

Further information may be obtained from the University Graduate School.

Links

• More information about my research and teachings are available from my personal page.