Sustainable Design of Buildings using Semantic BIM and Semantic Web Services

In response to the growing concerns about climate change and the environment, sustainable design of buildings is increasingly demanded by building owners and users. However, fast evaluation of various design options and identification of the optimized design requires application of design analysis tools such as energy modeling, daylight simulations, and natural ventilation analysis software. Energy analysis requires access to distributed sources of information such as building element material properties provided by designers, mechanical equipment information provided by equipment manufacturers, weather data provided by weather reporting agencies, and energy cost data from energy providers. Gathering energy related information from different sources and inputting the information to an energy analysis application is a time consuming process. This causes delays and increases the time for comparing different design alternatives. This paper discusses how Semantic Web technology can facilitate information collection from several sources for energy analysis. Semantic Web enables sharing, accessing, and combining information over the Internet in a machine process-able format. This would free building designers to concentrate on building design optimization rather than spending time on data preparation and manual entry into energy analysis applications

A semantic event detection approach for soccer video based on perception concepts and finite state machines

A significant application area for automated video analysis technology is the generation of personalized highlights of sports events. Sports games are always composed of a range of significant events. Automatically detecting these events in a sports video can enable users to interactively select their own highlights. In this paper we propose a semantic event detection approach based on Perception Concepts and Finite State Machines to automatically detect significant events within soccer video. Firstly we define a Perception Concept set for soccer videos based on identifiable feature elements within a soccer video. Secondly we design PC-FSM models to describe semantic events in soccer videos. A particular strength of this approach is that users are able to design their own semantic events and transfer event detection into graph matching. Experimental results based on recorded soccer broadcasts are used to illustrate the potential of this approach

Context-adaptive learning designs by using semantic web services

IMS Learning Design (IMS-LD) is a promising technology aimed at supporting learning processes. IMS-LD packages contain the learning process metadata as well as the learning resources. However, the allocation of resources - whether data or services - within the learning design is done manually at design-time on the basis of the subjective appraisals of a learning designer. Since the actual learning context is known at runtime only, IMS-LD applications cannot adapt to a specific context or learner. Therefore, the reusability is limited and high development costs have to be taken into account to support a variety of contexts. To overcome these issues, we propose a highly dynamic approach based on Semantic Web Services (SWS) technology. Our aim is moving from the current data- and metadata-based to a context-adaptive service-orientated paradigm We introduce semantic descriptions of a learning process in terms of user objectives (learning goals) to abstract from any specific metadata standards and used learning resources. At runtime, learning goals are accomplished by automatically selecting and invoking the services that fit the actual user needs and process contexts. As a result, we obtain a dynamic adaptation to different contexts at runtime. Semantic mappings from our standard-independent process models will enable the automatic development of versatile, reusable IMS-LD applications as well as the reusability across multiple metadata standards. To illustrate our approach, we describe a prototype application based on our principles