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Context-Awareness for Mobile Computing & Sensing

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (15 March 2023) | Viewed by 1551

Special Issue Editors


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Guest Editor
LIUPPA, IUT of Bayonne, University of Pau and Adour Countries, 64000 Anglet, France
Interests: middleware; software architecture; dynamic adaptation; context-aware; autonomic applications and green computing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Engineering, Science and Technology Faculty, Valencian International University, 4600 Valencia, Spain
Interests: big data; data science; parallel and distributed computing; semantic web; mobile and sensing computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Context awareness is now a well-integrated purpose in many applications and research domains. Context-aware applications are able to “feel” and “observe” what happens in the environment, providing better responses, flexible interfaces, and more intelligent behaviors.  However, the increasing weight of IoT, Sensors, Mobile phones/computers as well as Edge/Fog paradigms, including the mobility of persons and devices still continue to raise new challenges in the context domain particularly with the inclusion of these mobility preoccupations. Thus, Mobile Computing and Sensors are a key application domain for the convergence of technological aspects for the development of context awareness solutions.

The objective of this Special Issue is to seek propositions at various levels of context-awareness for Mobile Computing and Sensors: integration of technological aspects (middleware, sensors/IoT, interactions, pervasive information systems, Deep Learning, etc.), design, distribution, semantic, heterogeneity, warehousing, inferences, evaluations and measures, quality, implementation, tests, etc., as well as the proposition of theoretical foundations related to research on combining solutions for developing context awareness solutions. This synergistic focus will enforce the engineering of intelligent and innovative solutions to guide their design and promote the development of new approaches (architectures, tools, and methodologies) for context awareness with mobile technologies.

Dr. Philippe Roose
Dr. Yudith Cardinale
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • context-awareness
  • convergence
  • heterogeneity
  • evaluation
  • mobility
  • sensors
  • IoT
  • design
  • the context in distributed systems
  • context aggregation
  • interactions and mobile interactions context
  • context modeling
  • machine learning for context awareness
  • machine learning for autonomic computing
  • distributed architecture for processing context information in mobile environments
  • sensor model
  • user context profile: location, people nearby, social situation, etc
  • physical context: lighting, noise levels, traffic conditions, and temperature
  • context and sustainability
  • smart* (home, city, etc.) context
  • state of (physical environment, computing system, user, environmental, etc.)
  • context-awareness middleware

Published Papers (1 paper)

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Research

14 pages, 2351 KiB  
Article
Building a COVID-Safe Navigation App Using a Meta-Model Based Context Server
by Manfred Wojciechowski and Patrick Pogscheba
Sensors 2022, 22(24), 9890; https://doi.org/10.3390/s22249890 - 15 Dec 2022
Viewed by 1102
Abstract
Building context-aware applications is an already widely researched topic. It is our belief that context awareness has the potential to supplement the Internet of Things, when a suitable methodology including supporting tools will ease the development of context-aware applications. We believe that a [...] Read more.
Building context-aware applications is an already widely researched topic. It is our belief that context awareness has the potential to supplement the Internet of Things, when a suitable methodology including supporting tools will ease the development of context-aware applications. We believe that a meta-model based approach can be key to achieving this goal. In this paper, we present our meta-model based methodology, which allows us to define and build application-specific context models and the integration of sensor data without any programming. We describe how that methodology is applied with the implementation of a relatively simple context-aware COVID-safe navigation app. The outcome showed that programmers with no experience in context-awareness were able to understand the concepts easily and were able to effectively use it after receiving a short training. Therefore, context-awareness is able to be implemented within a short amount of time. We conclude that this can also be the case for the development of other context-aware applications, which have the same context-awareness characteristics. We have also identified further optimization potential, which we will discuss at the conclusion of this article. Full article
(This article belongs to the Special Issue Context-Awareness for Mobile Computing & Sensing)
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