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HBMS Architecture

The HBMS architecture is based on a client-server architecture. At the client side we distinguish the mobile domains. On the server side are the modeling, reasoning, and ontology domains.

 

Modeling Domain

The Modling domain includes the HCM-L Modeler, which is a comprehensive modeling tool for HCM-L including syntax, semantics and consistency checking. HCM-L Modeler was developed using the meta modeling platform ADOxx (www.ADOxx.org) which implements the upper three layers of the OMG Meta Object Facility (MOF) [4,5,6].

On the third MOF layer the ADOxx® Meta2Model defines constructs such as Class, Relation Class, Endpoint, or Attribute.

The Meta1Model (on the MOF M2 layer) corresponds to the meta model of the language, a modeling tool is to be developed for, i.e. in our case the HCM-L meta model. For that purpose, the corresponding ADOxx tier provides the concept of library, representing a collection of meta models conforming to the Meta2Model and formulated in the ADOxx Library Language (ALL).
 
Models on MOF M1 layer (HCM-L models) are stored in a model repository, i.e. a generic model storage configured by a meta model library [5]. They can be exported in two formats, the ADOxx Description Language (ADL) or in XML [6].
 

 

Reasoning Domain

Figure shows the components of the proposed ambient support reasoning domain. First the HCM-L modeler is using to model and design the conceptual cognitive model, and then the required reasoning parameters will generated that will be added to the model in the HCM-L tool automatically. Finally,the model is exported in XML format as input for the answer set programming solver (i.e., its knowledge base). For the solver we using Clingo[2] as the back-end ASP solver. Clingo is an incremental ASP system implemented on top of clasp[3] and Gringo[1] solvers [7]. Clingo is written in C and runs under Windows and Linux.

 

Ontology Domain

The ontology domain serves as a container for  following model types:

  • Sequence
  • User Context
  • Task Context
  • Structural Context
  • Personal and Social Context
  • Environmental Context
  • Spatial Context

These model types are stored in the file system on the server by server-side processing using transformation techniques.

 

Mobile Domain

The mobile domain includes the ASP.Net process web application, which is hosted on the Microsoft Internet Information Services (IIS7) webserver. The XML-parser have been built inside the webserver, which transformed the XML-data for the ASP.Net-process; and the mobile phone applications built using jquery mobile (http://jquerymobile.com/) which communicates with the ASP.Net-process through HTTP request–response to obtain data and information.

 

tl_files/hbms/english/Uebersicht V28.jpg

 

This  figure shows how the mobile domain used the ASP.Net-process and a mobile application using jquery mobile which allows the same application to run in different mobile browsers.

 

References

1. Michael, J., Grießer, A., Strobl, T., Mayr, H.C.: Cognitive Modeling and Support for Am-bient Assistance. In: Kop, C. (ed.) UNISON 2012. LNBIP, vol. 137, Springer, Heidelberg (2013), pp 96–107
2. Michael, J., Mayr, H. C.: Conceptual Modeling for Ambient Assistance. In: W. Ng et al. (Eds.): ER 2013. LNCS 8217, Springer, Heidelberg (2013), pp 403-413
3. Karagiannis, D., Grossmann, W., Höfferer, P.: Open Model Initiative: A Feasibility Study. University of Vienna, Dpmt. of Knowledge Engineering (2002), http://www.openmodels.a
4. S. Batsakis and E.G.M. Petrakis. Sowl: spatio-temporal representation, reasoning and que-rying over the semantic web. In: Proc. 6th Int. Conf. on Semantic Systems (2010), ACM
5. King, B. et al.: Statistical reasoning in the behavioral sciences. Wiley.com (2011).
6. Batsakis, S., Petrakis, E.: "SOWL: spatio-temporal representation, reasoning and querying over the semantic web." In: Proc. 6th Int. Conf. on Semantic Systems. ACM (2010).
7. Al Machot, F. et al.: Real time complex event detection for resource-limited multimedia sensor networks. In: Proc. 8th IEEE Int. Conf. on Advanced Video and Signal-Based Sur-veillance (2011)