Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2023 12:00 AM
End Date
7-1-2023 12:00 AM
Description
Data generated by sensors are often inaccurate due to calibrations, battery failure or network transmission errors among other issues. Fuzzy protoforms have been demonstrated as a successful tool for modeling data with uncertainty by providing, in addition, linguistic descriptions of the data that offers more relevant and sometimes hidden information. For this purpose, the data are modeled by fuzzy sets whose degree of truth in fuzzy sets is defined by membership functions. In this contribution,a software tool called Fuzzy IoT is presented for the descriptive analysis of sensor data streams through fuzzy protoforms. This software generate linguistic descriptions through the definition of ad hoc protoforms of data exported by different file of sensor data through the previous definition of a set of protoforms. A case study focusing on body temperature is illustrated to show the usefulness of the tool.
Recommended Citation
Martínez Mimbrera, Francisco Jesús; Montoro-Lendínez, Alicia; López Ruiz, José Luis; Damas Hermoso, Miguel; and Espinilla, Macarena, "FuzzyIoT - Platform for Descriptive Analysis of Sensor Data Stream" (2023). Hawaii International Conference on System Sciences 2023 (HICSS-56). 4.
https://aisel.aisnet.org/hicss-56/da/soft_computing/4
FuzzyIoT - Platform for Descriptive Analysis of Sensor Data Stream
Online
Data generated by sensors are often inaccurate due to calibrations, battery failure or network transmission errors among other issues. Fuzzy protoforms have been demonstrated as a successful tool for modeling data with uncertainty by providing, in addition, linguistic descriptions of the data that offers more relevant and sometimes hidden information. For this purpose, the data are modeled by fuzzy sets whose degree of truth in fuzzy sets is defined by membership functions. In this contribution,a software tool called Fuzzy IoT is presented for the descriptive analysis of sensor data streams through fuzzy protoforms. This software generate linguistic descriptions through the definition of ad hoc protoforms of data exported by different file of sensor data through the previous definition of a set of protoforms. A case study focusing on body temperature is illustrated to show the usefulness of the tool.
https://aisel.aisnet.org/hicss-56/da/soft_computing/4