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From past to present human-machine interfaces evolve toward adaptivity.pdf (3.861Mb)
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Title
From Past to Present: Human-Machine Interfaces Evolve Toward Adaptivity
Author
Carrera-Rivera, Angela
Larrinaga, Felix
Lasa, Ganix
Reguera-Bakhache, Daniel
Author (from another institution)
Unamuno, Gorka
Research Group
Centro de Innovación en Diseño
Análisis de datos y ciberseguridad
Ingeniería del software y sistemas
Other institutions
Ideko (Spain)
Version
Postprint
Rights
© 2025 The Author(s)
Access
Embargoed access
URI
https://hdl.handle.net/20.500.11984/6816
Publisher’s version
https://doi.org/10.1007/978-3-031-71697-3_7
Published at
Future Perspectives on Human-Computer Interaction Research: Towards the Year 2030 
Publisher
Springer Nature
Keywords
ODS 8 Trabajo decente y crecimiento económico
ODS 9 Industria, innovación e infraestructura
Abstract
Human–machine interfaces (HMI) facilitate communication between humans and machines, and their importance has increased in modern technology. However, traditional HMIs are often static and do not adap ... [+]
Human–machine interfaces (HMI) facilitate communication between humans and machines, and their importance has increased in modern technology. However, traditional HMIs are often static and do not adapt to individual user preferences or behavior. Adaptive User Interfaces (AUIs) have become increasingly important in providing personalized user experiences. Machine-learning techniques have gained traction in User Experience (UX) research to provide smart adaptations that can reduce user cognitive load. This chapter focuses on the development of adaptive HMIs within industrial contexts, offering a structured framework. It provides an overview of the past and present of HMIs and AUIs, while also outlining prospects for future research. The framework, enhanced by user interactions and Context-Aware Recommendation Systems (CARS), aims to provide tailored adaptations, thereby improving overall UX. A case study highlights real-time remote monitoring in smart factories, improving the ease of use and ease of decision making. The study demonstrates the framework usage in addressing real-world HMI, discussing results, challenges, and limitations. [-]
Funder
Comisión Europea
Gobierno Vasco
Gobierno Vasco
Program
H2020-MSCA-ITN-2018
Ikertalde Convocatoria 2022-2025
Ikertalde Convocatoria 2022-2023
Number
814078
IT1676-22
IT1519-22
Award URI
https://doi.org/10.3030/814078
Sin información
Sin información
Project
Digital Manufacturing and Design Training Network (DIMAND)
Grupo de sistemas inteligentes para sistemas industriales. IKERTALDE 2022-2025
Ingeniería de Software y Sistemas. IKERTALDE 2022-2023
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