Smart CAPs for Smart Its - Context Detection for Mobile Users

Michahelles, Florian; Samulowitz, Michael

doi:10.1007/s007790200027

Cited by 11 publications

(11 citation statements)

References 13 publications

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“…Internet protocol Benedetto and Nardis (2006) Balasubramaniam and Indulska (2004), Bellavista, Corradi, and Foschini (2007), Marias, Prigouris, Papazafeiropoulos, Hadjiefthymiades, and Merakos (2004), Mcnair and Zhu (2004), Qing et al (2006), Rocha and Endler (2006), Yang, Wu, Yang, and Liu (2007) Sensing Brilingaitė and Jensen (2007), Gellersen, Schmidt, and Beigl (2002), Gellersen, Kortuem, Schmidt, and Beigl (2004), Goulev, Stead, Mamdani, and Evans (2004), Gross, Egla, andMarquardt (2006), Jonker, Persa, Caarls, de Jong, andLagendijk (2003), Knight et al (2007), Matsushita (2001), Michahelles and Samulowitz (2004), Pfeifer (2005), Schmidt and Laerhoven (2001), Xu, Fu, Lee, and Winter (2007), Zhong and Gilbert (2005) Network requirement Dixit (2002), Harter, Hopper, Steggles, Ward, and Webster (2002), Kanter (2002), Yang et al (2007) Network implementation Aguiar, Sarma, Bijwaard, Marchetti, and Pacyna (2007), Schmidt (2001), Cano, Ferrandez-Bell, andManzoni (2005), Gonzalez-Castano, Garcia-Reinoso, Gil-Castineira, Costa-Montenegro, and Pousada-Carballo (2005), Riva, Nadeem, Borcea, and Iftode (2007), Wang et al (2004) Table 7 References of middleware layer.…”

Section: Classification Criteria Referencesmentioning

confidence: 99%

Context-aware systems: A literature review and classification

Hong

Suh

Kim

2009

Expert Systems with Applications

489

277

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Section: Classification Criteria Referencesmentioning

confidence: 99%

Context-aware systems: A literature review and classification

Hong

Suh

Kim

2009

Expert Systems with Applications

489

277

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“…The work described in [24] focuses on a communication scheme for retrieving contextual information through autonomous sensors without centralized control. These sensors called Smart-Its [25], are aware of their sensing capabilities and can report them to their neighbors, if necessary.…”

Section: O N T E X T S E N S Ing Bas Ed On Collecting Knowledge Fromentioning

confidence: 99%

Context Awareness in Mobile Computing Environments

Anagnostopoulos

Tsounis

Hadjiefthymiades

2006

Wireless Pers Commun

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Abstract. In this article, we report software architectures for context awareness in mobile computing environments, sensor centric systems and discuss context modeling issues. Defining an architecture for supporting context-aware applications for mobile devices explicitly implies a scalable description of how to represent contextual information and which are the abstraction models capable of handling such information. Using sensors to retrieve contextual information (e.g., user location) leads to a sensor network scheme that provides services to the applications level. Operations for capturing, collating, storing, and disseminating contextual information at the lowest level and aggregating it into increasingly more abstract models qualify the context-aware systems. In this article, we introduce context aware systems in mobile computing environments, review the basic mechanisms underlying the operation of such systems, and discuss notable work and important architectures in the area.

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“…The authors in [6] also explore environmental detection with context-aware sensors. They explore pull and push communication schemes where smart Context-Aware Packets (sCAPs) capture information from different environmental sensors and allow devices to access the information.…”

Section: Related Workmentioning

confidence: 99%

Context-aware metadata creation in a heterogeneous mobile environment

Volgin

Hung

Vakili

et al. 2005

Proceedings of the International Workshop on Network and Operating Systems Support for Digital Audio and Video

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With an exponentially-growing amount of digital information, data management is becoming increasingly burdensome for an average user. We propose an enhancement to the existing mediamanagement techniques which utilizes the context available in the surrounding environment around the time a media file is created. This context information is associated with the file to provide enhanced data categorization and searching capabilities. A typical scenario considered in our design involves a heterogeneous environment where users capture digital images using cameraenabled mobile devices, such as iPAQs. Concurrently, these mobile agents also collect environmental data from a variety of sensors and other surrounding wirelessly-enabled devices. At the time of image capture, mobile devices collect and process environmental information, which is then associated with the digital image in the form of metadata. Association of the context with the image makes it possible to build user applications with context-based image classification and query facilities. Our system includes such a GUI application, which provides an image query mechanism based on metadata attributes collected at the time of a picture. Our preliminary evaluation of the system validates successful metadata creation and association with the media files and demonstrates the enhanced searching and classification capabilities using a GUI application.

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Smart CAPs for Smart Its - Context Detection for Mobile Users

Cited by 11 publications

References 13 publications

Context-aware systems: A literature review and classification

Context-aware systems: A literature review and classification

Context Awareness in Mobile Computing Environments

Context-aware metadata creation in a heterogeneous mobile environment

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