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Journal articles on the topic 'Context aware applications'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Siham, Belhadi, and Merzougui Rachid. "Design and implementation of a context-aware health service platform (CAHS)." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 6 (2019): 4993–5005. https://doi.org/10.11591/ijece.v9i6.pp4993-5005.

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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 execu

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2

Urnes, Tore, Arne S. Hatlen, Pål S. Malm, and Øystein Myhre. "Building Distributed Context-Aware Applications." Personal and Ubiquitous Computing 5, no. 1 (2001): 38–41. http://dx.doi.org/10.1007/s007790170027.

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3

Vassev, Emil, and Son Vuong. "Context-Aware Systems and Applications." Mobile Networks and Applications 19, no. 2 (2014): 210–11. http://dx.doi.org/10.1007/s11036-014-0502-2.

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Vassev, Emil, and Vangalur Alagar. "Context-Aware Systems and Applications." Mobile Networks and Applications 19, no. 5 (2014): 583–84. http://dx.doi.org/10.1007/s11036-014-0531-x.

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Bottazzi, Dario, Tarik Taleb, Mohsen Guizani, and Abdelhakim Senhaji Hafid. "Supporting context-aware applications for eldercare." Journal of Communications and Networks 13, no. 2 (2011): 95–101. http://dx.doi.org/10.1109/jcn.2011.6157408.

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6

Cheng, Ningning, Shaxun Chen, Xianping Tao, Jian Lu, and Guihai Chen. "A model for context‐aware applications." International Journal of Pervasive Computing and Communications 4, no. 4 (2008): 428–39. http://dx.doi.org/10.1108/17427370810932178.

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7

Dey, Anind K., and Jennifer Mankoff. "Designing mediation for context-aware applications." ACM Transactions on Computer-Human Interaction 12, no. 1 (2005): 53–80. http://dx.doi.org/10.1145/1057237.1057241.

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Papakonstantinou, Stelios, and Vesna Brujic-Okretic. "Framework for context-aware smartphone applications." Visual Computer 25, no. 12 (2009): 1121–32. http://dx.doi.org/10.1007/s00371-009-0391-8.

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9

Milic, E. M., and D. Stojanovic. "EgoSENSE: A Framework for Context-Aware Mobile Applications Development." Engineering, Technology & Applied Science Research 7, no. 4 (2017): 1791–96. https://doi.org/10.5281/zenodo.844297.

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This paper presents a context-aware mobile framework (or middleware), intended to support the implementation of context-aware mobile services. The overview of basic concepts, architecture and components of context-aware mobile framework is given. The mobile framework provide acquisition and management of context, where raw data sensed from physical (hardware) sensors and virtual (software) sensors are combined, processed and analyzed to provide high-level context and situation of the user to the mobile context-aware applications in near real-time. Using demo mobile health application, its most

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10

Svahn, Fredrik, and Ola Henfridsson. "Situated Knowledge in Context-Aware Computing." International Journal of Advanced Pervasive and Ubiquitous Computing 1, no. 3 (2009): 23–41. http://dx.doi.org/10.4018/japuc.2009090802.

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A central feature of ubiquitous computing applications is their capability to automatically react on context changes so as to support users in their mobility. Such context awareness relies on models of specific use contexts, embedded in ubiquitous computing environments. However, since most such models are based merely on location and identity parameters, context-aware applications seldom cater for users’ situated knowledge and experience of specific contexts. This is a general user problem in well-known, but yet dynamic, user environments. Drawing on a sequential multimethod study of in-car n

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11

Elazhary, Hanan, Alaa Althubyani, Lina Ahmed, Bayan Alharbi Alharbi, Norah Alzahrani, and Reem Almutairi. "Context Management for Supporting Context-aware Android Applications Development." International Journal of Interactive Mobile Technologies (iJIM) 11, no. 4 (2017): 186. http://dx.doi.org/10.3991/ijim.v11i4.6952.

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<p class="0abstract">Building context-aware mobile applications is one of the most ambitious areas of research. Such applications can change their behavior according to context or perform specific tasks in specific contexts. Regardless of the application, all context-aware mobile applications share the need to retrieve and process context information. This paper presents a Context Management tool for the Android platform (ACM). ACM allows easy access to internal on-board mobile sensors and hardware features extracting corresponding raw data. Raw context is processed into higher-level mor

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12

Chim, Soo-Jong, and Yong Ik Yoon. "Two-Level Context Adaptation Method for Context-Aware Applications." KIPS Transactions:PartA 12A, no. 6 (2005): 477–84. http://dx.doi.org/10.3745/kipsta.2005.12a.6.477.

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13

Ponce, Victor, and Bessam Abdulrazak. "Context-Aware End-User Development Review." Applied Sciences 12, no. 1 (2022): 479. http://dx.doi.org/10.3390/app12010479.

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Context-aware application development frameworks enable context management and environment adaptation to automatize people’s activities. New technologies such as 5G and the Internet of Things (IoT) increase environment context (from devices/services), making functionalities available to augment context-aware applications. The result is an increased deployment of context-aware applications to support end-users in everyday activities. However, developing applications in context-aware frameworks involve diverse technologies, so that it traditionally involves software experts. In general, context-

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14

McLamore, Eric S., Geisianny Moreira, Diana C. Vanegas, and Shoumen Palit Austin Datta. "Context-Aware Diagnostic Specificity (CADS)." Biosensors 12, no. 2 (2022): 101. http://dx.doi.org/10.3390/bios12020101.

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15

Schilit, B. N., D. M. Hilbert, and J. Trevor. "Context-aware communication." IEEE Wireless Communications 9, no. 5 (2002): 46–54. http://dx.doi.org/10.1109/mwc.2002.1043853.

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16

Nadoveza, Dražen, and Dimitris Kiritsis. "Concept for Context-Aware Manufacturing Dashboard Applications." IFAC Proceedings Volumes 46, no. 9 (2013): 204–9. http://dx.doi.org/10.3182/20130619-3-ru-3018.00103.

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17

Devarakonda, G. K. Mohan. "DEVICE ENABLED ARCHITECTURE FOR CONTEXT AWARE APPLICATIONS." International Journal of Advanced Research in Computer Science 8, no. 8 (2017): 214–16. http://dx.doi.org/10.26483/ijarcs.v8i8.4600.

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18

Gonzalez Boix, Elisa, Christophe Scholliers, Wolfgang De Meuter, and Theo D’Hondt. "Programming mobile context-aware applications with TOTAM." Journal of Systems and Software 92 (June 2014): 3–19. http://dx.doi.org/10.1016/j.jss.2013.07.031.

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19

Rehman, Kasim, Frank Stajano, and George Coulouris. "An Architecture for Interactive Context-Aware Applications." IEEE Pervasive Computing 6, no. 1 (2007): 73–80. http://dx.doi.org/10.1109/mprv.2007.5.

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20

Mayrhofer, René, Hedda R. Schmidtke, and Stephan Sigg. "Security and trust in context-aware applications." Personal and Ubiquitous Computing 18, no. 1 (2012): 115–16. http://dx.doi.org/10.1007/s00779-012-0630-2.

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21

Toch, Eran. "Crowdsourcing privacy preferences in context-aware applications." Personal and Ubiquitous Computing 18, no. 1 (2012): 129–41. http://dx.doi.org/10.1007/s00779-012-0632-0.

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22

Moench, Tobias, Rocco Gasteiger, Gabor Janiga, Holger Theisel, and Bernhard Preim. "Context-aware mesh smoothing for biomedical applications." Computers & Graphics 35, no. 4 (2011): 755–67. http://dx.doi.org/10.1016/j.cag.2011.04.011.

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23

Wolfgang Kaltz, J., Jürgen Ziegler, and Steffen Lohmann. "Context-aware Web Engineering: Modeling and Applications." Revue d'intelligence artificielle 19, no. 3 (2005): 439–58. http://dx.doi.org/10.3166/ria.19.439-458.

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24

Johnson, S. "A framework for mobile context-aware applications." BT Technology Journal 25, no. 2 (2007): 106–11. http://dx.doi.org/10.1007/s10550-007-0033-5.

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25

Lozano, María, José Gallud, and Philippe Palanque. "Mobile Context-Aware Applications for Ubiquitous Computing." JUCS - Journal of Universal Computer Science 16, no. (15) (2010): 1927–28. https://doi.org/10.3217/jucs-016-15.

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26

Deeba K. and Saravanaguru R. A. K. "Context Reasoning for Predicting Gestational Diabetes Mellitus Using CA-RETE Algorithm." International Journal of e-Collaboration 17, no. 4 (2021): 41–59. http://dx.doi.org/10.4018/ijec.2021100104.

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Today, IoT-related applications play an important role in scientific world development. Context reasoning emphasizes the perception of various contexts by means of collection of IoT data which includes context-aware decision making. Context-aware computing is used to improve the abilities of smart devices and is increased by smart applications. In this paper, context-aware for the internet of things middleware (CAIM) architecture is used for developing a rule-based system using CA-RETE algorithm. The objective of context-aware systems are concentrated on 1) context reasoning methodologies and

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27

van Kranenburg, H., M. S. Bargh, S. Iacob, and A. Peddemors. "A context management framework for supporting context-aware distributed applications." IEEE Communications Magazine 44, no. 8 (2006): 67–74. http://dx.doi.org/10.1109/mcom.2006.1678112.

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28

Zaplata, Sonja, Matthias Meiners, and Winfried Lamersdorf. "Designing future-context-aware dynamic applications with structured context prediction." Software: Practice and Experience 43, no. 10 (2011): 1185–204. http://dx.doi.org/10.1002/spe.1126.

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29

Haider, Hadi Abbas, Sahib Oleiwi Suha, and Rasheed Abdulshaheed Haider. "Designing and configuring context-aware semantic web applications." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 5 (2020): 2549~2559. https://doi.org/10.12928/TELKOMNIKA.v18i5.15277.

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Context-aware services are attracting attention of world as the use of web services are rapidly growing. We designed an architecture of context-aware semantic web which provides on demand flexibility and scalability in extracting and mining the research papers from well-known digital libraries i.e. ACM, IEEE and SpringerLink. This paper proposes a context-aware administrations system, which supports programmed revelation and incorporation of setting dependent on Semantic Web administrations. This work has been done using the python programming language with a dedicated library for the semantic

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30

Zhao, Xinyou, and Toshio Okamoto. "Adaptive multimedia content delivery for context-aware u-learning." International Journal of Mobile Learning and Organisation 5, no. 1 (2011): 46. http://dx.doi.org/10.1504/ijmlo.2011.038691.

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31

Burceanu, Elena, Ciprian Dobre, and Valentin Cristea. "Adaptive Distributed Data Storage for Context-Aware Applications." Journal of Telecommunications and Information Technology, no. 4 (December 30, 2013): 58–69. http://dx.doi.org/10.26636/jtit.2013.4.1240.

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Context-aware computing is a paradigm that relies on the active use of information coming from a variety of sources, ranging from smartphones to sensors. The paradigm usually leads to storing large volumes of data that need to be processed to derive higher-level context information. The paper presents a cloud-based storage layer for managing sensitive context data. To handle the storage and aggregation of context data for context-aware applications, Clouds are perfect candidates. But a Cloud platform for context-aware computing needs to cope with several requirements: high concurrent access (a

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32

Chien, Been-Chian, and Shiang-Yi He. "A Generic Context Interpreter for Pervasive Context-Aware Systems." International Journal of Handheld Computing Research 2, no. 2 (2011): 65–77. http://dx.doi.org/10.4018/jhcr.2011040105.

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Developing pervasive context-aware systems to construct smart space applications has attracted much attention from researchers in recent decade. Although many different kinds of context-aware computing paradigms were built of late years, it is still a challenge for researchers to extend an existing system to different application domains and interoperate with other service systems due to heterogeneity among systems This paper proposes a generic context interpreter to overcome the dependency between context and hardware devices. The proposed generic context interpreter contains two modules: the

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33

Zon, Michael, Guha Ganesh, M. Jamal Deen, and Qiyin Fang. "Context-Aware Medical Systems within Healthcare Environments: A Systematic Scoping Review to Identify Subdomains and Significant Medical Contexts." International Journal of Environmental Research and Public Health 20, no. 14 (2023): 6399. http://dx.doi.org/10.3390/ijerph20146399.

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Context awareness is a field in pervasive computing, which has begun to impact medical systems via an increasing number of healthcare applications that are starting to use context awareness. The present work seeks to determine which contexts are important for medical applications and which domains of context-aware applications exist in healthcare. A systematic scoping review of context-aware medical systems currently used by patients or healthcare providers (inclusion criteria) was conducted between April 2021 and June 2023. A search strategy was designed and applied to Pub Med, EBSCO, IEEE Ex

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34

Zafar, Waseeq Ul Islam, Muhammad Atif Ur Rehman, Farhana Jabeen, Byung-Seo Kim, and Zobia Rehman. "Context-Aware Naming and Forwarding in NDN-Based VANETs." Sensors 21, no. 14 (2021): 4629. http://dx.doi.org/10.3390/s21144629.

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Vehicular ad-hoc network (VANET) is a technology that allows ubiquitous mobility to mobile users. Inter-vehicle communication is an integral component of intelligent transportation systems that enables a wide variety of applications where vehicles interact and cooperate with each other, from safety applications to non-safety applications. VANETs applications have different needs (e.g., latency, reliability, delivery priorities, etc.) in terms of delivery effectiveness. In the last decade, named data networking (NDN) gained the attention of the research community for effective content retrieval

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35

López, Juan, and Montserrat Sendín. "Multi-Purpose Infrastructure for Delivering and Supporting Mobile Context-Aware Applications." JUCS - Journal of Universal Computer Science 16, no. (15) (2010): 2081–98. https://doi.org/10.3217/jucs-016-15-2081.

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The use of contextual information in mobile devices is receiving increasing attention in mobile and ubiquitous computing research. An important requirement for mobile development today is that devices should be able to interact with the context. In this paper we present a series of contributions regarding previous work on context-awareness. In the first place, we describe a client-server architecture that provides a mechanism for preparing target non context-aware applications in order to be delivered as context-aware applications in a semi-automatic way. Secondly, the framework used in the se

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36

Rivero-Rodriguez, Alejandro, Paolo Pileggi, and Ossi Antero Nykänen. "Mobile Context-Aware Systems: Technologies, Resources and Applications." International Journal of Interactive Mobile Technologies (iJIM) 10, no. 2 (2016): 25. http://dx.doi.org/10.3991/ijim.v10i2.5367.

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Mobile applications often adapt their behavior according to user context, however, they are often limited to consider few sources of contextual information, such as user position or language. This article reviews existing work in context-aware systems (CAS), e.g., how to model context, and discusses further development of CAS and its potential applications by looking at available information, methods and technologies. Social Media seems to be an interesting source of personal information when appropriately exploited. In addition, there are many types of general information, ranging from weathe

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37

Kumar, Bimal Aklesh, Bibhya Sharma, and Elisa Yumi Nakagawa. "Architectural Support for Context-Aware Mobile Learning Applications." Education and Information Technologies 27, no. 3 (2021): 3723–41. http://dx.doi.org/10.1007/s10639-021-10771-1.

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38

Lupiana, Dennis. "Architectural Solutions for Context-Aware Applications: KoDA Prototype." International Journal for Information Security Research 9, no. 1 (2019): 831–38. http://dx.doi.org/10.20533/ijisr.2042.4639.2019.0095.

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39

Jung, Heon-Man, and Jung-Hyun Lee. "OSGi based Service Middleware for Context-Aware Applications." KIPS Transactions:PartC 13C, no. 6 (2006): 691–700. http://dx.doi.org/10.3745/kipstc.2006.13c.6.691.

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40

Kulkarni, D., and A. Tripathi. "A Framework for Programming Robust Context-Aware Applications." IEEE Transactions on Software Engineering 36, no. 2 (2010): 184–97. http://dx.doi.org/10.1109/tse.2010.11.

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41

Luo, Jianchao, and Hao Feng. "A Framework for NFC-based Context-aware Applications." International Journal of Smart Home 9, no. 1 (2015): 111–22. http://dx.doi.org/10.14257/ijsh.2015.9.1.12.

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42

Belcastro, Loris, Fabrizio Marozzo, and Paolo Trunfio. "A scalable middleware for context-aware mobile applications." International Journal of Ad Hoc and Ubiquitous Computing 31, no. 2 (2019): 112. http://dx.doi.org/10.1504/ijahuc.2019.100082.

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43

Marozzo, Fabrizio, Paolo Trunfio, and Loris Belcastro. "A scalable middleware for context-aware mobile applications." International Journal of Ad Hoc and Ubiquitous Computing 31, no. 2 (2019): 112. http://dx.doi.org/10.1504/ijahuc.2019.10021754.

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44

Diaz, Ricardo Alfredo Cajo, Mihaela Ghita, Dana Copot, Isabela Roxana Birs, Cristina Muresan, and Clara Ionescu. "Context Aware Control Systems: An Engineering Applications Perspective." IEEE Access 8 (2020): 215550–69. http://dx.doi.org/10.1109/access.2020.3041357.

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45

Abbas, Haider Hadi, Suha Sahib Oleiwi, and Haider Rasheed Abdulshaheed. "Designing and configuring context-aware semantic web applications." TELKOMNIKA (Telecommunication Computing Electronics and Control) 18, no. 5 (2020): 2549. http://dx.doi.org/10.12928/telkomnika.v18i5.15277.

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46

Motamedi, Mohammad, Felix Portillo, Mahya Saffarpour, Daniel Fong, and Soheil Ghiasi. "Octopus: Context-Aware CNN Inference for IoT Applications." IEEE Embedded Systems Letters 12, no. 1 (2020): 1–4. http://dx.doi.org/10.1109/les.2019.2915257.

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47

Ahmad, Enas, Maha Alaslani, Fahad R. Dogar, and Basem Shihada. "Location-Aware, Context-Driven QoS for IoT Applications." IEEE Systems Journal 14, no. 1 (2020): 232–43. http://dx.doi.org/10.1109/jsyst.2019.2893913.

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48

Ceri, Stefano, Florian Daniel, Maristella Matera, and Federico M. Facca. "Model-driven development of context-aware Web applications." ACM Transactions on Internet Technology 7, no. 1 (2007): 2. http://dx.doi.org/10.1145/1189740.1189742.

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49

Yu, Lian, Wei-Tek Tsai, and Gian Perrone. "Testing Context-Aware Applications Based on Bigraphical Modeling." IEEE Transactions on Reliability 65, no. 3 (2016): 1584–611. http://dx.doi.org/10.1109/tr.2016.2575444.

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50

Vahdat-Nejad, Hamed, Azam Ramazani, Tahereh Mohammadi, and Wathiq Mansoor. "A survey on context-aware vehicular network applications." Vehicular Communications 3 (January 2016): 43–57. http://dx.doi.org/10.1016/j.vehcom.2016.01.002.

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