Design and Implementation of the Pervaho Middleware for Mobile Context-Aware Applications

2008 ◽  
Author(s):  
Patrick Eugster ◽  
Beno Garbinato ◽  
Adrian Holzer
Keyword(s):  
Context Aware ◽  
Design And Implementation ◽  
Mobile Context

scholarly journals Design and implementation of a Context-Aware Health Service Platform (CAHS)

2019 ◽  
Vol 9 (6) ◽  
pp. 4993
Author(s):  
Siham Belhadi ◽  
Rachid Merzougui
Keyword(s):  
Health Service ◽  
Context Awareness ◽  
Context Aware ◽  
Context Management ◽  
Context Sensitive ◽  
Dynamic Architecture ◽  
Design And Implementation ◽  
Situational Information ◽  
User Intervention ◽  
Health Applications

<p>Computers are no match to humans in deducing situational information from their environment and in using it in their interactions. The advent of the context-aware applications seems to offer a way out to the computer that is not context-sensitive. The context aware applications can adapt their behaviors according to the perceived context or situation, without explicit user intervention, thereby providing human-centric services. To simplify the complexity of developing applications, context aware framework, which introduces context awareness into the environment where the applications are executed, is highlighted to provide a homogeneous interface involving generic context management and adaptation solutions. This papier has focused on the design of Context-Aware Health Services (CAHS) platform, which provide a health applications framework embedded on mobile devices. Our proposed platform is capabilities for context manager and adaptations according to context changes. It is designed to base on the SOA principles for achieving a flexible and dynamic architecture.</p>

Reinforcement and Non-Reinforcement Machine Learning Classifiers for User Movement Prediction

2013 ◽  
pp. 218-237 ◽  
Author(s):  
Theodoros Anagnostopoulos
Keyword(s):  
Machine Learning ◽  
Classification Problem ◽  
Location Prediction ◽  
Context Aware ◽  
Resonance Theory ◽  
Self Organizing Maps ◽  
Adaptive Resonance ◽  
Proposed Model ◽  
On Line ◽  
Mobile Context

Mobile context-aware applications are required to sense and react to changing environment conditions. Such applications, usually, need to recognize, classify, and predict context in order to act efficiently, beforehand, for the benefit of the user. In this chapter, the authors propose a mobility prediction model, which deals with context representation and location prediction of moving users. Machine Learning (ML) techniques are used for trajectory classification. Spatial and temporal on-line clustering is adopted. They rely on Adaptive Resonance Theory (ART) for location prediction. Location prediction is treated as a context classification problem. The authors introduce a novel classifier that applies a Hausdorff-like distance over the extracted trajectories handling location prediction. Two learning methods (non-reinforcement and reinforcement learning) are presented and evaluated. They compare ART with Self-Organizing Maps (SOM), Offline kMeans, and Online kMeans algorithms. Their findings are very promising for the use of the proposed model in mobile context aware applications.

Context-Aware Presentation of Linked Data on Mobile

2018 ◽  
pp. 1940-1971
Author(s):  
Luca Costabello ◽  
Fabien Gandon
Keyword(s):  
Linked Data ◽  
Edit Distance ◽  
Research Question ◽  
Context Aware ◽  
Graph Edit Distance ◽  
Optimal Error ◽  
Presentation Level ◽  
Rdf Graphs ◽  
Mobile Context ◽  
Proper Context

In this paper the authors focus on context-aware adaptation for linked data on mobile. They split up the problem in two sub-questions: how to declaratively describe context at RDF presentation level, and how to overcome context imprecisions and incompleteness when selecting the proper context description at runtime. The authors answer their two-fold research question with PRISSMA, a context-aware presentation layer for Linked Data. PRISSMA extends the Fresnel vocabulary with the notion of mobile context. Besides, it includes an algorithm that determines whether the sensed context is compatible with some context declarations. The algorithm finds optimal error-tolerant subgraph isomorphisms between RDF graphs using the notion of graph edit distance and is sublinear in the number of context declarations in the system.

Pervasive Computing in the Supermarket

2012 ◽  
pp. 172-185 ◽  
Author(s):  
Darren Black ◽  
Nils Jakob Clemmensen ◽  
Mikael B. Skov
Keyword(s):  
Empirical Study ◽  
Real World ◽  
Context Awareness ◽  
Empirical Evaluation ◽  
Context Aware ◽  
Uniform Pattern ◽  
User Attention ◽  
Context Aware System ◽  
Mobile Context ◽  
Interactive Experience

Shopping in the real world is becoming an increasingly interactive experience as stores integrate various technologies to support shoppers. Based on an empirical study of supermarket shoppers, the authors designed a mobile context-aware system called the Context-Aware Shopping Trolley (CAST). The purpose of CAST is to support shopping in supermarkets through context-awareness and acquiring user attention, thus, the authors’ interactive trolley guides and directs shoppers in the handling and finding of groceries. An empirical evaluation showed that shoppers using CAST behaved differently than shoppers using a traditional trolley. Specifically, shoppers using CAST exhibited a more uniform pattern of product collection and found products more easily while travelling a shorter distance. As such, the study finds that CAST supported the supermarket shopping activity.

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