2026-05-31T04:01:16Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/357032026-02-03T11:05:19Zcom_10630_2254col_10630_37953

IRIS: Efficient Visualization, Data Analysis and Experiment Management for Wireless Sensor Networks Figura, Richard Ceriotti, Matteo Yen Shih, Chia Mulero-Pázmány, Margarita Cristina Fu, Songwei Daidone, Roberta Jungen, Sascha Negro, Juan-José Marrón, Pedro José Datos - Protección - Efectos de las innovaciones tecnológicas Drones WSN Cooperating objects 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. 2024-12-17T09:45:32Z 2024-12-17T09:45:32Z 2014 journal article VoR 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 https://hdl.handle.net/10630/35703 10.4108/ue.1.3.e4 eng open access application/pdf EUDL Digital Library