Toward Organic Computing Approach for Cybernetic Responsive Environment

The developpment of the Internet of Things (IoT) concept revives Responsive Environments (RE) technologies. Nowadays, the idea of a permanent connection between physical and digital world is technologically possible. The capillar Internet relates to the Internet extension into daily appliances such as they become actors of Internet like any hu-man. The parallel development of Machine-to-Machine communications and Arti cial Intelligence (AI) technics start a new area of cybernetic. This paper presents an approach for Cybernetic Organism (Cyborg) for RE based on Organic Computing (OC). In such approach, each appli-ance is a part of an autonomic system in order to control a physical environment. The underlying idea is that such systems must have self-x properties in order to adapt their behavior to external disturbances with a high-degree of autonomy.

[1]  Juan Carlos Augusto,et al.  Management of Uncertainty and Spatio-Temporal Aspects for Monitoring and Diagnosis in a Smart Home , 2008 .

[2]  Alexander Klapproth,et al.  The Autonomic Computing Paradigm in Adaptive Building / Ambient Intelligence Systems , 2011, AmI.

[3]  Richard C. Simpson,et al.  Plans and Planning in Smart Homes , 2006, Designing Smart Homes.

[4]  Hartmut Schmeck,et al.  Organic Computing - A Paradigm Shift for Complex Systems , 2011, Organic Computing.

[5]  Juan Carlos Augusto,et al.  Learning patterns in ambient intelligence environments: a survey , 2010, Artificial Intelligence Review.

[6]  Duhart Clement,et al.  Wireless Sensor Network Cloud services: Towards a partial delegation , 2014, 2014 International Conference on Smart Communications in Network Technologies (SaCoNeT).

[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]  Otilia Kocsis,et al.  An intelligent user service architecture for networiked home environments , 2006 .

[9]  Wamberto Weber Vasconcelos,et al.  Agent-Based Management of Responsive Environments , 2005, AI*IA.

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

[11]  Juan Carlos Augusto,et al.  The Use of Temporal Reasoning and Management of Complex Events in Smart Homes , 2004, ECAI.

[12]  Bastin Tony Roy Savarimuthu,et al.  PRIMA 2013: Principles and Practice of Multi-Agent Systems , 2013, Lecture Notes in Computer Science.

[13]  Jian-Bo Yang,et al.  Management of Uncertainty and Spatio-Temporal Aspects for Monitoring and Diagnosis in a Smart Home , 2008, Int. J. Comput. Intell. Syst..

[14]  Vlado Stankovski,et al.  Application of Decision Trees to Smart Homes , 2006, Designing Smart Homes.

[15]  Cyrille Bertelle,et al.  A Resource Oriented Framework for Service Choreography over Wireless Sensor and Actor Networks , 2016, Int. J. Wirel. Inf. Networks.

[16]  Cyrille Bertelle,et al.  EMMA: A Resource Oriented Framework for Service Choreography over Wireless Sensor and Actor Networks , 2015, ArXiv.

[17]  Jörg Hähner,et al.  Trustworthy Organic Computing Systems: Challenges and Perspectives , 2010, ATC.

[18]  Hartmut Schmeck,et al.  Towards a generic observer/controller architecture for Organic Computing , 2006, GI Jahrestagung.

[19]  Cyrille Bertelle,et al.  Lightweight Distributed Adaptive Algorithm for Voting Procedures by Using Network Average Consensus , 2013, PRIMA.