Defining a Context Model for Smart Manufacturing

Sawilla, Swenja; Gerst, Naemi; Keller, Christine; Schlegel, Thomas

doi:10.1016/j.procs.2022.08.003

Cited by 2 publications

(1 citation statement)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These can be represented as open web standards including XML, RDF, and OWL. Swenja et al (2022) have used OWL to develop a context model that is composed of two sub-models. The Entity Model and the Instance Model are the sub-models of the context in the domain of smart manufacturing.…”

Section: Introductionmentioning

confidence: 99%

Augmenting context with power information for green context-awareness in smart environments

Mahmud,

Hussain

2024

Front. Comput. Sci.

View full text Add to dashboard Cite

The increase in the use of smart devices has led to the realization of the Internet of Everything (IoE). The heart of an IoE environment is a Context-Aware System that facilitates service discovery, delivery, and adaptation based on context classification. The context has been defined in a domain-dependent way, traditionally. The classical models of context have been focused on rich context and lack Cost of Context (CoC) that can be used for decision support. The authors present a philosophy-inspired mathematical model of context that includes confidence in activity classification of context, the actions performed, and the power information. Since a single recurring activity can lead to distinct actions performed at different times, it is better to record the actions. The power information includes the power consumed in the complete context processing and is a quality attribute of the context. Power consumption is a useful metric as CoC and is suitable for power-constrained context awareness. To demonstrate the effectiveness of the proposed work, example contexts are described, and the context model is presented mathematically in this study. The context is aggregated with power information, and actions and confidence on the classification outcome lead to the concept of situational context. The results show that the context gathered through sensor data and deduced through remote services can be made more rich with CoC parameters.

show abstract

Section: Introductionmentioning

confidence: 99%