IRIS: Efficient Visualization, Data Analysis and Experiment Management for Wireless Sensor Networks
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Figura, Richard
Ceriotti, Matteo
Yen Shih, Chia
Mulero-Pázmány, Margarita Cristina
Fu, Songwei
Daidone, Roberta
Jungen, Sascha
Negro, Juan-José
Marrón, Pedro José
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EUDL Digital Library
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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.
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Figura R., Ceriotti M., Yen Shih C., Mulero-Pázmány M., Fu S., Daidone R., Jungen S., Negro J., Marrón P. (2014). IRIS: Efficient Visualization, Data Analysis and Experiment Management for Wireless Sensor Networks. EAI Endorsed Transactions on Ubiquitous Environments 14(3): e4. Pp 1-18. ISSN: 2032-9377. http://dx.doi.org/10.4108/ue.1.3.e4






