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--- pub:projects:ressconx [2013/06/17 05:18] – created gjn
+++ pub:projects:ressconx [2013/06/17 07:40] (current) – [Ressconx] gjn
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-====== Ressconx ======
+====== ResSConx ======
 Methods for Semantic Representation and Logical Reasoning in Context-Aware Systems (ResSConx)
@@ Line 16: / Line 16: @@
 Based on these observations, in this proposal we argue for the following research hypotheses:
-  - Context modeling methods should be semantic. Context information has to be represented, modeled and processed on a purely semantic level in order to capture the meaning and be relevant to the user. It also has to be adjusted and improved over time and situation, with well established machine learning methods.
+  - **Context modeling methods should be semantic**. Context information has to be represented, modeled and processed on a purely semantic level in order to capture the meaning and be relevant to the user. It also has to be adjusted and improved over time and situation, with well established machine learning methods.
-  - Context-based reasoning should be done on a logical level. Advanced reasoning schemes based on rules and processes can be effectively employed to reason about situations in which the components of a context-aware system operate. Multiple inference scenarios meeting diverse user needs have to be considered.
+  - **Context-based reasoning should be done on a logical level**. Advanced reasoning schemes based on rules and processes can be effectively employed to reason about situations in which the components of a context-aware system operate. Multiple inference scenarios meeting diverse user needs have to be considered.
-  - Design methods and deployment schemes should be context-driven. The design of a context-aware system should be model-driven, with models related to context representation and reasoning. Important deployment patterns for context-aware systems have to be identified.
+  - **Design methods and deployment schemes should be context-driven**. The design of a context-aware system should be model-driven, with models related to context representation and reasoning. Important deployment patterns for context-aware systems have to be identified.
-  - Context-oriented adaptability of a system is needed to meet expectations of diversified user base. We argue that context-oriented adaptation and user-centric perspective are features that bind together pervasive computing with mobile devices and distributed cloud-based and service-oriented software systems. Current features of multimodal interfaces need to be investigated and their potential exploited.
+  - **Context-oriented adaptability of a system is needed to meet expectations of diversified user base.** We argue that context-oriented adaptation and user-centric perspective are features that bind together pervasive computing with mobile devices and distributed cloud-based and service-oriented software systems. Current features of multimodal interfaces need to be investigated and their potential exploited.
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-.    Research project methodology
+==== Research project methodology ====
 The planned methodology will include both conceptual studies as well as experimental work in the form of proof-of-concept prototypes for the evaluation purposes. In order to achieve the project objectives, a number of methods will be used. They are well known to the authors who have successfully used them in their prior work.
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+==== Context-oriented Adaptation Case Studies ====
+The primary objective of this task is a careful study
+of selected classes of context-aware systems and well defined user interaction scenarios. The novelty of this attempt
+is that it emphasizes the system adaptation that will be achieved thanks to the proposed approach. In fact, we
+argue that context-oriented adaptation and user-centric perspective is what binds pervasive computing with ubiquitous
+mobile devices and distributed cloud-based and service-oriented software systems. The specific scenarios include:
+.** Distributed network of mobile devices that build up a pervasive environment.** We take into consideration
+hardware constraints, embedded devices, and soft-real time issues. We take the full advantage of the learning
+middleware that can adapt to habits of specific users and changing environment. We plan an evaluation setup that
+will consist of several smartphones, tablets and augmented reality glasses. In this environment the learning middleware capabilities will be tested and evaluated according to a device type and usage characteristics. Moreover,
+we will use a network server to gather, store and distribute the reference context data about the environment.
+. **Cloud-based web service environment**, where software agents play the dominant role. We will develop a
+service-oriented business applications that can be adapted in a number of ways, and the initial configuration is
+based on the deployment context. Then the adaptation allows for providing functionality tailored to the needs of
+specific users. We also focus on context-aware business objects and semantic web services composing a service
+mash-up. In this subtask we will use the network server a platform for web services as well as distribution of the
+context data.
+. **Ambient office environment,** using close range localization services such as Bluetooth of mobile devices (i.e.
+smartphones and tablets), to identify and localize personnel. We plan to use semantic memory tags implemented
+with either mobile devices or lightweight RFID infrastructure to describe the relevant objects in the environment.
+We also consider augmented reality interfaces, both lightweight (using cameras and screens of mobile devices)
+and in the form of augmented reality glasses to provide an adaptive and contextual user interface with knowledge
+fusion capabilities. The environment will be used for evaluating schemes of distributed and collaborative work
+of a team of persons supported by augmented reality setup.
 ===== News =====