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Prosumerization Approach to Semantic Ambient Intelligence Platforms

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Ubiquitous Computing and Ambient Intelligence (UCAmI 2017)

Abstract

Service creation and customization are expensive tasks that require specialists. In many cases these simple services could be implemented by domain experts with no programming abilities. This research work proposes the application of a prosumer model to facilitate access to information and creation of new knowledge to domain experts without experience in the use of semantic AmI platforms. This paper presents a prosumer tool called DataQuest to gather and analyze data from an AmI platform based on ontologies using simple services. An empirical study was carried out in order to demonstrate that, based on the defined prosumer model; a domain expert can create services with acceptable quality for a given domain. The authors performed a case study where 24 people used the prosumer tool to create simple services over a prosumer infrastructure for retrieving and analyzing data from a semantic AmI platform; the aim of this study consists of analyzing the quality of the services built and studying the effort needed to build prosumer services compared with traditional development.

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Notes

  1. 1.

    http://fiesta-iot.eu/.

  2. 2.

    http://www.smartsantander.eu/.

  3. 3.

    https://www.surrey.ac.uk/ics/.

  4. 4.

    https://mimove.inria.fr/soundcity/.

  5. 5.

    http://www.keti.re.kr/.

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Acknowledgement

The research leading to these results has received funding from FIESTA-IoT 1st Open Call and the Ministry of Economy and Competitiveness through SEMOLA project (TEC2015-68284- R).

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Correspondence to Diego Martín .

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Martín, D., Bordel, B., Alcarria, R., Sánchez-Picot, Á., de Rivera, D.S., Robles, T. (2017). Prosumerization Approach to Semantic Ambient Intelligence Platforms. In: Ochoa, S., Singh, P., Bravo, J. (eds) Ubiquitous Computing and Ambient Intelligence. UCAmI 2017. Lecture Notes in Computer Science(), vol 10586. Springer, Cham. https://doi.org/10.1007/978-3-319-67585-5_12

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  • DOI: https://doi.org/10.1007/978-3-319-67585-5_12

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  • Online ISBN: 978-3-319-67585-5

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