Spatiotemporal Context Modelling in Pervasive Context-Aware Computing Environment: A Logic Perspective

Ameyed, Darine; Miraoui, Moeiz; Tadj, Chakib

doi:10.14569/ijacsa.2016.070454

Cited by 3 publications

(3 citation statements)

References 22 publications

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“…Spatiotemporal extent is used in many applications for smart environment. As in [15], authors proposed a preliminary formal spatiotemporal context modeling based on first order logic. In the system, simple context is described by logic model then complicated context is represented using Boolean operator to generate high level context.…”

Section: Related Workmentioning

confidence: 99%

A Dynamic Genetic-Based Context Modeling Approach in Internet of Things Environments

Ahmed¹,

El-aal²,

Ghali³

et al. 2019

IJATCSE

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Internet of Things (IoTs) enables entities every day to communicate and collaborate with each other for providing information, data and services to inhabitants and users. IoTs consists of a large number of smart devices that can generate immense amount of data with different types. These sensors raw data needs to be modeled in a certain structure before filtering and processing to provision context information. This process is called context modeling. Context modeling provides definition of how context data are structured and maintained through context aware system.However, employing model for every context type through context aware application is static and is specified by the application developer. The main problem in IoTs is that the structure of context data changes overtime, therefore static modeling cannot be adaptable for modeling these changes. In this paper, a new dynamic approach for context modeling based on genetic algorithm and satisfaction factor is proposed. Firstly, the proposed approach uses genetic algorithm to find the best matching between a set of contexts and a set of available context models. Secondly, it uses a satisfaction factor to calculate the satisfaction degree for each context with each available context model and select the context model with high satisfaction degree as the structure model of this context, dynamically. In addition, flexibility indicator property and context based are defined to measure the performance of the proposed approach. The results of conducted simulations show that the proposed approach achieves higher performance than static approach for context modeling.

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Section: Related Workmentioning

confidence: 99%

A Dynamic Genetic-Based Context Modeling Approach in Internet of Things Environments

Ahmed¹,

El-aal²,

Ghali³

et al. 2019

IJATCSE

View full text Add to dashboard Cite

show abstract

“…According to Mohan and Singh in [21], formal semantics of ORM and Context Modeling Language (CML) can be supplemented to provide integration with other implementations. Graphical modeling technique as its strength provides relationship modeling, flexible implementation and it is very useful for data storage and historic context store [23]. However, the limitations of graphical modelling technique include its complexity to retrieve information which requires obligatory configuration.…”

Section: Figure 4 Sample Entity Relations Graphical Modelmentioning

confidence: 99%

“…Perera et al in [36] surveyed high-level context modelling techniques and concluded that diversification of modelling techniques is the best way to provide efficient results which will lessen each other's weaknesses. Finally, [23] discussed the context modelling techniques and used logic based technique to model spatiotemporal context. They finally concluded that no modelling technique is ideal to be used in a standalone manner.…”

Section: Best Choice Techniquementioning

confidence: 99%

Activity Context Modeling in Context-Aware Environment

Opoku¹

2016

IJCATR

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Abstract:The explosion of mobile devices has fuelled the advancement of pervasive computing to provide personal assistance in this information-driven world. Pervasive computing takes advantage of context-aware computing to track, use and adapt to contextual information. The context that has attracted the attention of many researchers is the activity context. There are six major techniques that are used to model activity context. These techniques are key-value, logic-based, ontology-based, object-oriented, mark-up schemes and graphical. This paper analyses these techniques in detail by describing how each technique is implemented while reviewing their pros and cons. The paper ends with a hybrid modeling method that fits heterogeneous environment while considering the entire of modeling through data acquisition and utilization stages. The modeling stages of activity context are data sensation, data abstraction and reasoning and planning. The work revealed that mark-up schemes and object-oriented are best applicable at the data sensation stage. Key-value and object-oriented techniques fairly support data abstraction stage whereas the logic-based and ontology-based techniques are the ideal techniques for reasoning and planning stage. In a distributed system, mark-up schemes are very useful in data communication over a network and graphical technique should be used when saving context data into database.

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Using Probabilistic Temporal Logic PCTL and Model Checking for Context Prediction

Ameyed

Miraoui

Zaguia

et al. 2018

cai

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Spatiotemporal Context Modelling in Pervasive Context-Aware Computing Environment: A Logic Perspective

Cited by 3 publications

References 22 publications

A Dynamic Genetic-Based Context Modeling Approach in Internet of Things Environments

A Dynamic Genetic-Based Context Modeling Approach in Internet of Things Environments

Activity Context Modeling in Context-Aware Environment

Using Probabilistic Temporal Logic PCTL and Model Checking for Context Prediction

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