Izquierdo Doménech, Juan Jesús
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- PublicationEnvironment awareness, multimodal interaction, and intelligent assistance in industrial augmented reality solutions with deep learning(Springer-Verlag, 2024-05) Izquierdo Doménech, Juan Jesús; Linares Pellicer, Jordi Joan; Ferri Mollá, Isabel; Instituto Universitario Mixto de Tecnología de Informática; Departamento de Sistemas Informáticos y Computación; Escuela Politécnica Superior de Alcoy; Instituto Universitario Valenciano de Investigación en Inteligencia Artificial[EN] Augmented reality is increasingly used in various fields, especially industrial applications. Although augmented reality devices¿ characteristics and technological benefits are still evolving, augmented reality¿s clear advantages in facilitating mechanical tasks and improving operator performance have made it popular. In industrial settings, the human factor remains irreplaceable, but the evolution of artificial intelligence has allowed any activity on the shop floor to be given new semantic possibilities. Through a semantic layer, it is possible to interpret and validate the environment, provide multimodal interaction, and analyze and evaluate information to detect anomalies or risky situations. Deep learning has opened up new possibilities for existing augmented reality solutions, such as visual interpretation of the environment, natural language understanding for problem-solving, or automatic anomaly detection. This new intelligent layer minimizes unnecessary interactions with the environment, validates the operator¿s actions, and increases comfort, safety, and focus, making them more efficient in high cognitive level tasks. This work presents a general architecture based on a Semantic layer that relies on augmented reality systems and validates its advantages in a real industrial setting. Overall, integrating artificial intelligence and augmented reality solutions in industrial settings offers significant potential for improving productivity, safety, and worker satisfaction.
- PublicationTowards achieving a high degree of situational awareness and multimodal interaction with AR and semantic AI in industrial applications(Springer-Verlag, 2023-04) Izquierdo Doménech, Juan Jesús; Linares Pellicer, Jordi Joan; Orta López, Jorge; Instituto Universitario Mixto de Tecnología de Informática; Departamento de Sistemas Informáticos y Computación; Escuela Politécnica Superior de Alcoy; Instituto Universitario Valenciano de Investigación en Inteligencia Artificial; Universitat Politècnica de València[EN] With its various available frameworks and possible devices, augmented reality is a proven useful tool in various industrial processes such as maintenance, repairing, training, reconfiguration, and even monitoring tasks of production lines in large factories. Despite its advantages, augmented reality still does not usually give meaning to the elements it complements, staying in a physical or geometric layer of its environment and without providing information that may be of great interest to industrial operators in carrying out their work. An expert¿s remote human assistance is becoming an exciting complement in these environments, but this is expensive or even impossible in many cases. This paper shows how a machine learning semantic layer can complement augmented reality solutions in the industry by providing an intelligent layer, sometimes even beyond some expert¿s skills. This layer, using state-of-the-art models, can provide visual validation and new inputs, natural language interaction, and automatic anomaly detection. All this new level of semantic context can be integrated into almost any current augmented reality system, improving the operator¿s job with additional contextual information, new multimodal interaction and validation, increasing their work comfort, operational times, and security.
- PublicationLarge Language Models for in Situ Knowledge Documentation and Access With Augmented Reality(IMAI Software - International Journal of Interactive Multimedia and Artificial Intelligence, 2023-09) Izquierdo Doménech, Juan Jesús; Linares Pellicer, Jordi Joan; Ferri Mollá, Isabel; Instituto Universitario Mixto de Tecnología de Informática; Departamento de Sistemas Informáticos y Computación; Escuela Politécnica Superior de Alcoy; Instituto Universitario Valenciano de Investigación en Inteligencia Artificial[EN] Augmented reality (AR) has become a powerful tool for assisting operators in complex environments, such as shop floors, laboratories, and industrial settings. By displaying synthetic visual elements anchored in real environments and providing information for specific tasks, AR helps to improve efficiency and accuracy. However, a common bottleneck in these environments is introducing all necessary information, which often requires predefined structured formats and needs more ability for multimodal and Natural Language (NL) interaction. This work proposes a new method for dynamically documenting complex environments using AR in a multimodal, non-structured, and interactive manner. Our method employs Large Language Models (LLMs) to allow experts to describe elements from the real environment in NL and select corresponding AR elements in a dynamic and iterative process. This enables a more natural and flexible way of introducing information, allowing experts to describe the environment in their own words rather than being constrained by a predetermined structure. Any operator can then ask about any aspect of the environment in NL to receive a response and visual guidance from the AR system, thus allowing for a more natural and flexible way of introducing and retrieving information. These capabilities ultimately improve the effectiveness and efficiency of tasks in complex environments.
- PublicationMultimodal Assistance System for the Care of Individuals in Early Stages of Dependency Using Augmented Reality and Artificial Intelligence(Springer Cham, 2024-09-17) Ferri Mollá, Isabel; Izquierdo Doménech, Juan Jesús; Aliaga Torró, Carlos; Linares Pellicer, Jordi Joan; Instituto Universitario Mixto de Tecnología de Informática; Departamento de Sistemas Informáticos y Computación; Escuela Politécnica Superior de Alcoy; Instituto Universitario Valenciano de Investigación en Inteligencia Artificial[EN] The present work explores the potential offered by the integration of various technologies such as augmented reality and artificial intelligence in the field of home-based care for dependent individuals. The proposed system focuses on providing assistance for everyday questions posed by individuals with certain levels of dependency or by new caregivers. This will start from the user¿s interaction with a query about how to perform a specific action, accompanied by an image of their visual context and a manual detailing the routine, arrangement of the dependant¿s belongings, and general information about the dependant. This will return a step-by-step guided response on what should be done, along with a list of objects to use that appear in the image of their environment. These objects will subsequently be highlighted in augmented reality for more comprehensive and understandable information. This solution aims to improve and prolong the independence at home of individuals in the early stages of dependency or dementia, as well as to enhance the adaptation of caregivers to new home environments, thereby improving the quality of life for patients and the work of caregivers.
- PublicationSistema de gestión de incidencias municipal(Universitat Politècnica de València, 2015-02-02T15:23:47Z) Izquierdo Doménech, Juan Jesús; Llorca Alcón, Manuel; Instituto Universitario Mixto de Tecnología de Informática; Departamento de Informática de Sistemas y Computadores; Departamento de Sistemas Informáticos y Computación; Escuela Politécnica Superior de Alcoy; Instituto Universitario Valenciano de Investigación en Inteligencia Artificial[ES] Proyecto de creación de una aplicación para navegadores con el objetivo de gestionar las incidencias de una ciudad.
- PublicationDefinition of a Coordinated Project-Based Learning Teaching Guide at Computer Science Studies(IATED, International Association of Technology, Education and Development, 2021) Izquierdo Doménech, Juan Jesús; Jordán Prunera, Jaume Magí; Linares Pellicer, Jordi Joan; Silvestre Cerdà, Joan Albert; Sanchis Gisbert, Raquel; Departamento de Organización de Empresas; Instituto Universitario Mixto de Tecnología de Informática; Departamento de Sistemas Informáticos y Computación; Centro de Investigación en Gestión e Ingeniería de Producción; Escuela Politécnica Superior de Alcoy; Escuela Técnica Superior de Ingeniería Informática; Instituto Universitario Valenciano de Investigación en Inteligencia Artificial; Universitat Politècnica de València[EN] The well-known active methodology of Project-Based Learning (PBL) is being used more and more at different educational levels due to the large number of advantages it presents. PBL has demonstrated that increases students' motivation, develops their autonomy and capacity for self-criticism, reinforces the ability to exchange ideas and collaborate, and promotes creativity, among other advantages. Due to these benefits, several educational institutions are introducing the PBL methodology in their teaching-learning processes. The implementation phase of this type of methodology should be planned, managed, and carried out carefully, considering several aspects. One of utmost importance is to collect and register all the critical information related to the contents, materials and activities of the subjects participating in the coordinated project through the PBL methodology. In this sense, the objective of this paper is to propose the definition of a coordinated PBL Teaching Guide that includes all this relevant information; containing, mainly: (i) PBL Project description; (ii) recommended previous knowledge; (iii) learning objectives and outcomes; (iv) PBL model milestones; (v) PBL model planning; (vi) evaluation; and (vii) bibliography. Furthermore, this proposal will define the formal guidelines for students and lecturers to define and frame all the related aspects to carry out the proposed PBL model. The definition of the PBL Teaching Guide will be based on a case study that involves the following two subjects from the Computer Engineering Degree that are taught at the Escola Politècnica Superior d¿Alcoi (EPSA) - Universitat Politècnica de València (UPV): ¿Programming¿ and ¿Data Structures and Algorithms¿. This proposal has been developed in the context of an innovation and educational improvement project applied in the EPSA during the last two years, covering five degrees, 55 subjects, and more than 10 different PBL models.
- PublicationVirtual Reality and Language Models, a New Frontier in Learning(IMAI Software - International Journal of Interactive Multimedia and Artificial Intelligence, 2024-03) Izquierdo Doménech, Juan Jesús; Linares Pellicer, Jordi Joan; Ferri Mollá, Isabel; Instituto Universitario Mixto de Tecnología de Informática; Departamento de Sistemas Informáticos y Computación; Escuela Politécnica Superior de Alcoy; Instituto Universitario Valenciano de Investigación en Inteligencia Artificial[EN] The proposed research introduces an innovative Virtual Reality (VR) and Large Language Model (LLM) architecture to enhance the learning process across diverse educational contexts, ranging from school to industrial settings. Leveraging the capabilities of LLMs and Retrieval-Augmented Generation (RAG), the architecture centers around an immersive VR application. This application empowers students of all backgrounds to interactively engage with their environment by posing questions and receiving informative responses in text format and with visual hints in VR, thereby fostering a dynamic learning experience. LLMs with RAG act as the backbones of this architecture, facilitating the integration of private or domain-specific data into the learning process. By seamlessly connecting various data sources through data connectors, RAG overcomes the challenge of disparate and siloed information repositories, including APIs, PDFs, SQL databases, and more. The data indexes provided by RAG solutions further streamline this process by structuring the ingested data into formats optimized for consumption by LLMs. An empirical study was conducted to evaluate the effectiveness of this VR and LLM architecture. Twenty participants, divided into Experimental and Control groups, were selected to assess the impact on their learning process. The Experimental group utilized the immersive VR application, which allowed interactive engagement with the educational environment, while the Control group followed traditional learning methods. The study revealed significant improvements in learning outcomes for the Experimental group, demonstrating the potential of integrating VR and LLMs in enhancing comprehension and engagement in learning contexts. This study presents an innovative approach that capitalizes on the synergy between LLMs and immersive VR technology, opening avenues for a transformative learning experience that transcends traditional boundaries and empowers learners across a spectrum of educational landscapes.
- PublicationEnhancing Industrial Process Interaction Using Deep Learning, Semantic Layers, and Augmented Reality(Universitat Politècnica de València, 2024-06-24) Izquierdo Doménech, Juan Jesús; Linares Pellicer, Jordi Joan; Instituto Universitario Mixto de Tecnología de Informática; Departamento de Sistemas Informáticos y Computación; Escuela Politécnica Superior de Alcoy; Instituto Universitario Valenciano de Investigación en Inteligencia Artificial[ES] La Realidad Aumentada (Augmented Reality, AR) y su capacidad para integrar contenido sintético sobre una imagen real proporciona un valor incalculable en diversos campos; no obstante, la industria es uno de estos campos que más se puede aprovechar de ello. Como tecnología clave en la evolución hacia la Industria 4.0 y 5.0, la AR no solo complementa sino que también potencia la interacción humana con los procesos industriales. En este contexto, la AR se convierte en una herramienta esencial que no sustituye al factor humano, sino que lo enriquece, ampliando sus capacidades y facilitando una colaboración más efectiva entre humanos y tecnología. Esta integración de la AR en entornos industriales no solo mejora la eficiencia y precisión de las tareas, sino que también abre nuevas posibilidades para la expansión del potencial humano. Existen numerosas formas en las que el ser humano interactúa con la tecnología, siendo la AR uno de los paradigmas más innovadores respecto a cómo los usuarios acceden a la información; sin embargo, es crucial reconocer que la AR, por sí misma, tiene limitaciones en cuanto a la interpretación del contenido que visualiza. Aunque en la actualidad podemos acceder a diferentes librerías que utilizan algoritmos para realizar una detección de imágenes, objetos, o incluso entornos, surge una pregunta fundamental: ¿hasta qué punto puede la AR comprender el contexto de lo que ve? Esta cuestión se vuelve especialmente relevante en entornos industriales. ¿Puede la AR discernir si una máquina está funcionando correctamente, o su rol se limita a la presentación de indicadores digitales superpuestos? La respuesta a estas cuestiones subrayan tanto el potencial como los límites de la AR, impulsando la búsqueda de innovaciones que permitan una mayor comprensión contextual y adaptabilidad a situaciones específicas dentro de la industria. En el núcleo de esta tesis yace el objetivo de no solo dotar a la AR de una "inteligencia semántica" capaz de interpretar y adaptarse al contexto, sino también de ampliar y enriquecer las formas en que los usuarios interactúan con esta tecnología. Este enfoque se orienta particularmente a mejorar la accesibilidad y la eficiencia de las aplicaciones de AR en entornos industriales, que son por naturaleza restringidos y complejos. La intención es ir un paso más allá de los límites tradicionales de la AR, proporcionando herramientas más intuitivas y adaptativas para los operadores en dichos entornos. La investigación se despliega a través de tres artículos de investigación, donde se ha desarrollado y evaluado una arquitectura multimodal progresiva. Esta arquitectura integra diversas modalidades de interacción usuario-tecnología, como el control por voz, la manipulación directa y el feedback visual en AR. Además, se incorporan tecnologías avanzadas basadas en modelos de aprendizaje automática (Machine Learning, ML) y aprendizaje profundo (Deep Learning, DL) para extraer y procesar información semántica del entorno. Cada artículo construye sobre el anterior, demostrando una evolución en la capacidad de la AR para interactuar de manera más inteligente y contextual con su entorno, y resaltando la aplicación práctica y los beneficios de estas innovaciones en la industria.
- PublicationSupporting interaction in augmented reality assisted industrial processes using a CNN-based semantic layer(IEEE Computer Society, 2020-12-18) Izquierdo Doménech, Juan Jesús; Linares Pellicer, Jordi Joan; Orta López, Jorge; Instituto Universitario Mixto de Tecnología de Informática; Departamento de Sistemas Informáticos y Computación; Escuela Politécnica Superior de Alcoy; Instituto Universitario Valenciano de Investigación en Inteligencia Artificial[EN] Even though Augmented Reality (AR) is far from its maturity, we already have solutions and devices that give us an efficient technological frame in different industrial environments. Widely used mobile devices, such as tablets, or more specific ones, such as the current AR glasses available, are enough to offer solutions that improve many industrial processes; repairing, maintenance, plant control, product line reconfiguration are some examples of these tasks. Many industrial applications already utilise AR-based applications to solve those problems. In this work, we aim to go a little bit further beyond current possibilities that only focus on providing visual guidance. Our main goal is to add a semantic layer for existing AR-based applications, that visually validate worker¿s actions based on visual interpretation of switches, potentiometers, analog needles or buttons, among others. This semantic layer allows a new level of interaction by adding automatic interpretation of the context that affects the actions of the operator and the display of information of interest in the AR system. We propose and explain the architecture and training of the Convolutional Neural Networks (CNN) used for the semantic layer and its integration in the AR technology.
- PublicationFlipping Game Development(Institute of Electrical and Electronics Engineers, 2018) Linares Pellicer, Jordi Joan; Orta López, Jorge; Izquierdo Doménech, Juan Jesús; Instituto Universitario Mixto de Tecnología de Informática; Departamento de Sistemas Informáticos y Computación; Escuela Politécnica Superior de Alcoy; Instituto Universitario Valenciano de Investigación en Inteligencia Artificial[EN] This work describes the implementation of a flip teaching alternative in an introductory game development course, using resources from a massive open online course. The results proved to achieve better grades and higher satisfaction to previous and similar lecture-based courses