IRIS: Efficient Visualization, Data Analysis and Experiment Management for Wireless Sensor Networks

Figura, R, Ceriotti, M, Yen Shih, C, Mulero Pazmany, MC, Fu, S, Daidone, R, Jungen, S, Negro, J and Marrón, P (2014) IRIS: Efficient Visualization, Data Analysis and Experiment Management for Wireless Sensor Networks. EAI Endorsed Transactions on Ubiquitous Environments, 1 (3). ISSN 2032-9377

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Abstract

The design of ubiquitous computing environments is challenging, mainly due to the unforeseeable impact of real-world environments on the system performance. A crucial step to validate the behavior of these systems is to perform in-field experiments under various conditions. We introduce IRIS, an experiment management and data processing tool allowing the definition of arbitrary complex data analysis applications. While focusing on Wireless Sensor Networks, IRIS supports the seamless integration of heterogeneous data gathering technologies. The resulting flexibility and extensibility enable the definition of various services, from experiment management and performance evaluation to user-specific applications and visualization. IRIS demonstrated its effectiveness in three real-life use cases, offering a valuable support for in-field experimentation and development of customized applications for interfacing the end user with the system.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Natural Sciences and Psychology (closed 31 Aug 19)
Publisher:	EAI
Date of acceptance:	10 October 2014
Date of first compliant Open Access:	22 February 2018
Date Deposited:	22 Feb 2018 12:19
Last Modified:	04 Sep 2021 10:44
DOI or ID number:	10.4108/ue.1.3.e4
URI:	https://ljmu-9.eprints-hosting.org/id/eprint/8117

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