RT Journal Article
T1 IRIS: Efficient Visualization, Data Analysis and Experiment Management for Wireless Sensor Networks
A1 Figura, Richard
A1 Ceriotti, Matteo
A1 Yen Shih, Chia
A1 Mulero-Pázmány, Margarita Cristina
A1 Fu, Songwei
A1 Daidone, Roberta
A1 Jungen, Sascha
A1 Negro, Juan-José
A1 Marrón, Pedro José
K1 Datos - Protección - Efectos de las innovaciones tecnológicas
AB 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.
PB EUDL Digital Library
YR 2014
FD 2014
LK https://hdl.handle.net/10630/35703
UL https://hdl.handle.net/10630/35703
LA eng
NO 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
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026