Ahmad Lotfi

Ahmad Lotfi

Professor

School of Science & Technology

Staff Group(s)
Computing and Technology

Role

  • Professor of Computational Intelligence and leading the Computational Intelligence and Applications (CIA) Research Group
  • Postgraduate Research Tutor for the School of Science and Technology. Professor Lotfi is responsible for:
    • reviewing all research students' progress
    • delivery of the research methodology module for all such students
    • postgraduate induction and open events
    • contributing to the admission and interview process and to many short courses and workshops specifically designed for these students
  • Chair of the College of Arts and Science Research Degrees Committee
  • Module leader and teaches on modules:
    • Robotics & Cybernetics (ITEC40071)
    • Internet Applications Development (SOFT20171)
    • Internet Applications Programming (SOFT20181)

Career overview

Professor Lotfi received his BSc. and MTech. in control systems from Isfahan University of Technology, Iran and Indian Institute of Technology, India respectively. He received his PhD degree in Learning Fuzzy Systems from University of Queensland, Australia in 1995.

Professor Lotfi joined Nottingham Trent University in 1996 as a Research Fellow to continue his research and later on in 2000 he became a member of the academic staff.

More information about Professor Lotfi's research and teachings are available from his personal page.

Research areas

Professor Lotfi is the leader of the Computational Intelligence and Applications Research Group (CIA).

Areas of research interest 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.
  • GPS Tracking for School Buses: This 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.

Opportunities to carry out postgraduate research towards an MPhil /PhD exist in all of the areas identified above. Further information may be obtained from the NTU Doctoral School.

External activity

  • Member of the editorial board and Associate Editor, Soft Computing (Springer)
  • Member of the editorial board, Journal of Ambient Intelligence and Smart Environments
  • Chair of Ambient Intelligence Task Force, IEEE Computational Intelligence Society
  • Member of IEEE System, Man and Cybernetics Technical Committee on Soft Computing
  • Member of International Programme Committee – 5th International Conference on Pervasive and Embedded Computing and Communication Systems, Angers, France, 11-13 February 2015
  • Member of International Programme Committee – 4th International Conference on Sensor Networks, Angers, France, 11-13 February 2015
  • Member of International Programme Committee - 11th International Conference on Intelligent Environments, Prague, Czech Republic, 15-17 July 2015
  • Member of International Programme Committee - 6th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA 2013), Rhodes Island, Greece, 29-31 May 2013
  • Posters and Short Paper Chair and a member of the organising committee, 9th International Conference on Intelligent Environments, Athens, Greece, 16-17 July 2013
  • 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

Sponsors and collaborators

Current and recent research is being conducted with the collaboration, funding and/or support of:

Recent research funding includes:

  • iCarer, TSB and EPSRC through Ambient Assisted Living (AAL) joint programme £207,012 (€254,624) (2013-2016) (Principal Investigator)
  • Knowledge Transfer Partnership with Nottingham City Homes Ltd., £48,450 (2012-2013) (Principal Investigator)
  • School of Science and Technology QR Funding, £17,000, (2010-2011) (Co Investigator)
  • School of Science and Technology QR Funding, £7,000, (2009-2010) (Principal Investigator)
  • SIS (Stimulating Innovation for Success), £10,000 - Just Checking, (2008-2009) (Principal Investigator)
  • SIS (Stimulating Innovation for Success), £20,000 - School Bus Transport Network, (2007-2008) (Co Investigator)
  • Medici Fellowship, £36,000 (2006-2007)

Publications

Intelligent synthetic composite indicators with application. Alshami A, Lotfi A, Coleman S, Soft Computing, 2013

Behavioural pattern identification and prediction in intelligent environments. Mahmoud S, Lotfi A and Langensiepen C, Applied Soft Computing, 2013, 13 (4), 1813-1822

Investigating occupant behaviour to improve energy efficiency in social housing. Lotfi A, Jalil LI and Al-Habaibeh A in Proceedings of Intelligent Environments conference, Athens, Greece, July 2013

Smart homes for the elderly dementia sufferers: Identification and prediction of abnormal behaviour. Lotfi A, Langensiepen C, Mahmoud S, Akhlaghinia MJ, Journal of Ambient Intelligence and Humanized Computing, 2012, 3 (3),205-218

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 and Lotfi A, International Journal of Information Acquisition, 2009, 6 (3), 147-157

Occupant behaviour prediction in ambient intelligence computing environment. Akhlaghinia MJ, Lotfi A, Langensiepen C and Sherkat N, International Journal of Uncertain Systems, 2008, 2 (2)

Novel fuzzy logic controllers with self-tuning capability. Teng FC, Lotfi A, Chung Tsoi A, Journal of Computers, 2008, 3 (11)

See all of Ahmad Lotfi's publications...

Press expertise

Professor Lotfi is able to talk to the press regarding the following:

  • Assistive technology
  • Global Positioning System (GPS)
  • Smart devices
  • Robotics
  • Assistive robots
  • Monitoring
  • Ambient assisted living
  • Dementia- assistive technologies
  • Intelligent environments