Using FML and fuzzy technology in adaptive ambient intelligent environments

Ambient Intelligence (AmI, shortly) gathers best re-sults from three key technologies, Ubiquitous Computing, Ubiq-uitous Communication, and Intelligent User Friendly Inter-faces. The functional and spatial distribution of tasks is a natu-ral thrust to employ multi-agent paradigm to design and imple-ment AmI environments. Two critical issues, common in most of applications, are (1) how to detect in a general and efficient way context from sensors and (2) how to process contextual in-formation in order to improve the functionality of services. In this work we experiment a framework where hybrid techniques (distributed fuzzy control, mobile agents, fuzzy rules induction algorithms) are mixed to gain flexibility and uniformity.

[1]  I. Jahnich,et al.  Service-based access to distributed embedded devices through the open service gateway , 2004, 2nd IEEE International Conference on Industrial Informatics, 2004. INDIN '04. 2004.

[2]  Bob DuCharme XML: The Annotated Specification , 1998 .

[3]  M. Delgado,et al.  A methodology to model fuzzy systems using fuzzy clustering in a rapid-prototyping approach , 1998, Fuzzy Sets Syst..

[4]  Derek A. Linkens,et al.  Rule-base self-generation and simplification for data-driven fuzzy models , 2004, Fuzzy Sets Syst..

[5]  Yuhui Shi,et al.  Combinations of evolutionary algorithms and fuzzy systems: a survey , 1999, 18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397).

[6]  Emile H. L. Aarts,et al.  Ambient intelligence: a multimedia perspective , 2004, IEEE MultiMedia.

[7]  Bill N. Schilit,et al.  Disseminating active map information to mobile hosts , 1994, IEEE Network.

[8]  Ebrahim Mamdani,et al.  Applications of fuzzy algorithms for control of a simple dynamic plant , 1974 .

[9]  Karl Johan Åström,et al.  Adaptive feedback control , 1987, Proc. IEEE.

[10]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[11]  Giovanni Acampora,et al.  Fuzzy control interoperability and scalability for adaptive domotic framework , 2005, IEEE Transactions on Industrial Informatics.

[12]  Tzung-Pei Hong,et al.  Induction of fuzzy rules and membership functions from training examples , 1996, Fuzzy Sets Syst..

[13]  Giovanni Acampora,et al.  Using Fuzzy Technology in Ambient Intelligence Environments , 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..