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Processing semantic IoT data using a prosumer approach for simulating scenarios on ambient intelligence environments

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Abstract

The creation, customization and maintenance of services are expensive tasks that need IT specialists but in many cases are simple services that could be created by domain experts without any knowledge in coding. This research work proposes the application of a prosumer model in order to ease the access to information and creation of new knowledge to domain experts without any experience in semantic ambient intelligence platforms nor programming skills. This paper presents a prosumer tool called DataQuest that enables the gathering and processing of data from AmI platforms based on ontologies using simple services. These services are then used to feed an AmI environment simulator, composed of a social simulator and a network simulator, to get more reliable simulations. An empirical study was carried out to demonstrate that, using the defined prosumer model, a domain expert with no programming knowledge can create simple services for his/her domain of expertise. A case study was performed where 18 domain experts created services using a prosumer tool comparing them with 12 developers that programmed the same services.

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Notes

  1. http://fiesta-iot.eu/.

  2. http://www.smartsantander.eu/.

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

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

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

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Acknowledgements

These results were supported by UPM’s ‘Programa Propio’, the Autonomous Region of Madrid through program MOSI-AGIL-CM (Grant P2013/ICE-3019, co-funded by EU Structural Funds FSE and FEDER) and also 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 Álvaro Sánchez-Picot.

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Sánchez-Picot, Á., Martín, D., Bordel, B. et al. Processing semantic IoT data using a prosumer approach for simulating scenarios on ambient intelligence environments. J Ambient Intell Human Comput 14, 75–86 (2023). https://doi.org/10.1007/s12652-021-03245-2

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