Smart EDIFICE — Smart EveryDay interoperating future devICEs

In the last years, a lot of attention has been paid to Internet of Things (IoT): everyday life objects, thanks to the advanced technological features added to them, are becoming “smarter”. Regarding this new and potentially disruptive field, it is important to take into account the primary role that the user has in these ecosystems. IoT applications will be used by different kinds of people, with different needs and different abilities. Therefore, one crucial aspect is the ease of use and interaction with objects, which should be optimized in order to guarantee a better user experience and hide the complexity of technologies running behind the scene. This paper proposes a goal-oriented, cooperative platform able to determine and perform the set of tasks necessary to achieve the objectives expressed by users immersed in a smart environment. We can think of this platform as a middleware between users, who express their needs in the form of triggers and actions (i.e. the components of a “goal”), and those objects which are able to meet the goal. The platform can determine, by using semantic information, the possible plans (in the form of communication flows among objects) to accomplish the given goal. Filtering operations along with the plan selection are done taking into account “historical” data regarding objects' power consumption and user feedback.

[1]  Diane J. Cook,et al.  A Multi-agent Approach to Controlling a Smart Environment , 2006, Designing Smart Homes.

[2]  Michael C. Mozer,et al.  Lessons from an Adaptive Home , 2005 .

[3]  Rik Van de Walle,et al.  Capturing the functionality of Web services with functional descriptions , 2012, Multimedia Tools and Applications.

[4]  Qun Ni Service Composition in Ontology enabled Service Oriented Architecture for Pervasive Computing , 2005 .

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

[6]  Laurent Vercouter,et al.  Flexible Composition of Smart Device Services , 2005, PSC.

[7]  F. Mattern From Smart Devices to Smart Everyday Objects ∗ ( Extended Abstract ) , 2003 .

[8]  John Davidson,et al.  Ogc® sensor web enablement:overview and high level achhitecture. , 2007, 2007 IEEE Autotestcon.

[9]  Rik Van de Walle,et al.  Survey of Semantic Description of REST APIs , 2014 .

[10]  Kanda Runapongsa Saikaew,et al.  A review and comparison of rule languages and rule-based inference engines for the Semantic Web , 2013, 2013 International Computer Science and Engineering Conference (ICSEC).

[11]  Nati Herrasti,et al.  GENIO: an ambient intelligence application in home automation and entertainment environment , 2005, sOc-EUSAI '05.

[12]  Antonio Puliafito,et al.  AllJoyn Lambda: An architecture for the management of smart environments in IoT , 2014, 2014 International Conference on Smart Computing Workshops.

[13]  Shie Chen Appliance simulation models for the evaluation of energy management policies , 2014 .

[14]  Juan Carlos Augusto,et al.  Ambient Intelligence—the Next Step for Artificial Intelligence , 2008, IEEE Intelligent Systems.

[15]  George Percivall,et al.  Ogc® sensor web enablement:overview and high level achhitecture. , 2007 .

[16]  Amit P. Sheth,et al.  SA-REST: Semantically Interoperable and Easier-to-Use Services and Mashups , 2007, IEEE Internet Computing.

[17]  William C. Mann,et al.  The Gator Tech Smart House: a programmable pervasive space , 2005, Computer.

[18]  Luis Bermudez,et al.  Open Geospatial Consortium OGC ® Engineering Report: Water Information Services Concept Development Study , 2011 .

[19]  Kishor S. Trivedi,et al.  Combining Cloud and sensors in a smart city environment , 2012, EURASIP J. Wirel. Commun. Netw..

[20]  Hani Hagras,et al.  Creating an ambient-intelligence environment using embedded agents , 2004, IEEE Intelligent Systems.

[21]  Gerd Kortuem,et al.  Sensor Networks or Smart Artifacts? An Exploration of Organizational Issues of an Industrial Health and Safety Monitoring System , 2007, UbiComp.