A hardware/software embedded agent for real-time control of ambient-intelligence environments

This paper presents the development of an embedded intelligent agent able to perform real-time control of ambient-intelligence environments. The system has been implemented as a system-on-programmable chip (SoPC) on a field programmable gate array (FPGA). The scheme used for realizing the intelligent agent is an adaptive neuro-fuzzy system (NFS) enhanced with a principal component analysis (PCA) pre-processor. The PCA pre-processing stage allows a reduction of the input dimensions (features) with no meaningful loss of modeling capability. As a consequence, the computational complexity of the system is significantly reduced, allowing its implementation on a single electronic device. The NFS-PCA agent has been tested with data obtained in a real ubiquitous computing environment test bed. Results obtained show that the agent is able to perform real-time control of the environment in a proactive and non-intrusive way, and also to adapt to changes of user's preferences in a life-long mode.

[1]  Maurizio Tomasella,et al.  Vision and Challenges for Realising the Internet of Things , 2010 .

[2]  Michael Friedewald,et al.  Science and Technology Roadmapping: Ambient Intelligence in Everyday Life (AmI@Life) , 2003 .

[3]  Juan Carlos Augusto,et al.  Ambient Intelligence: Concepts and applications , 2007, Comput. Sci. Inf. Syst..

[4]  Artemis Moroni,et al.  Vision and Challenges for Realising the Internet of Things , 2010 .

[5]  Anastasios I. Dounis,et al.  Advanced control systems engineering for energy and comfort management in a building environment--A review , 2009 .

[6]  Hani Hagras,et al.  A type-2 fuzzy embedded agent to realise ambient intelligence in ubiquitous computing environments , 2005, Inf. Sci..

[7]  Hani Hagras,et al.  A fuzzy embedded agent-based approach for realizing ambient intelligence in intelligent inhabited environments , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[8]  Faiyaz Doctor,et al.  A System-on-Chip Development of a Neuro–Fuzzy Embedded Agent for Ambient-Intelligence Environments , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[9]  Hani Hagras,et al.  A Speech Recognizer Based Intelligent Agent For Ambient Intelligent Environments , 2009, Intelligent Environments.

[10]  Hani Hagras,et al.  An Incremental Adaptive Life Long Learning Approach for Type-2 Fuzzy Embedded Agents in Ambient Intelligent Environments , 2007, IEEE Transactions on Fuzzy Systems.

[11]  Rob Williams Hardware/software co-design , 2006 .

[12]  Fariba Sadri,et al.  Ambient intelligence: A survey , 2011, CSUR.

[13]  Hani Hagras,et al.  An intelligent agent based approach for energy management in commercial buildings , 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

[14]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[15]  W. Press,et al.  Numerical Recipes: The Art of Scientific Computing , 1987 .