@misc{10481/104644,
year = {2025},
month = {5},
url = {https://hdl.handle.net/10481/104644},
abstract = {The extraction and utilization of latent information from sensor data is gaining increasing prominence due to its potential for transforming decision-making processes across various sectors. Data mining techniques provide robust tools for analyzing large-scale data generated by advanced network management systems, offering actionable insights that drive operational efficiency and strategic improvements. However, the sheer volume of sensor data, combined with challenges related to real-world sensor deployment and user interaction, necessitates the development of advanced data fusion and processing frameworks. This paper presents an innovative automatic fusion and fuzzification methodology designed to integrate multi-source sensor data into coherent, high-quality intelligent outputs. By applying fuzzy logic, the proposed system enhances the interpretability and interoperability of complex sensor datasets. The approach has been validated in a real-world scenario within sensorized homes of Type II diabetic patients in Cabra (Córdoba, Spain), where it aids healthcare professionals in monitoring and optimizing patient routines. Experimental results demonstrate the system’s effectiveness in identifying and analyzing behavioral patterns, highlighting its potential to improve patient care through advanced sensor data fusion techniques.},
organization = {“ERDF A way of making Europe”},
organization = {“European Union NextGenerationEU/PRTR”},
organization = {Consejería de Universidad, Investigación e Innovación, Spain M.2 PDC_000756},
organization = {ERDF Andalusia Program 2021–2027},
organization = {European Union 101121309},
organization = {Universidad de Granada / CBUA},
organization = {MICIU/AEI, Spain/10.13039/501100011033 PID2021- 123960OB-I00, PDC2023-145863-I00, PID2021-127275OB-I00},
publisher = {Elservier},
keywords = {Data fusion},
keywords = {Sensor data},
keywords = {Sensor fuzzification},
keywords = {Smart healthcare},
title = {Fuzzy processing applied to improve multimodal sensor data fusion to discover frequent behavioral patterns for smart healthcare},
doi = {10.1016/j.inffus.2025.103307},
author = {Fernández Basso, Carlos Jesús and Díaz-Jiménez, David and López, Jose L. and Espinilla, Macarena},
}