Revista Iberoamericana de Automatica e Informatica Industrial

Scope & Guideline

Advancing Automation through Open Access Research

Introduction

Delve into the academic richness of Revista Iberoamericana de Automatica e Informatica Industrial with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageSpanish
ISSN1697-7912
PublisherUNIV POLITECNICA VALENCIA, EDITORIAL UPV
Support Open AccessYes
CountrySpain
TypeJournal
Convergefrom 2007 to 2024
AbbreviationREV IBEROAM AUTOM IN / Rev. Iberoam. Autom. Inform. Ind.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressCAMINO VERA S-N, VALENCIA 46022, SPAIN

Aims and Scopes

The 'Revista Iberoamericana de Automatica e Informatica Industrial' focuses on the intersection of automation and industrial informatics, emphasizing innovative control strategies, system design, and applications of advanced technologies in various fields. The journal aims to disseminate high-quality research that contributes to the development and integration of automation systems in industrial contexts.
  1. Control Systems and Techniques:
    Research on various control strategies, including adaptive, predictive, and robust control methods tailored for complex industrial systems.
  2. Robotics and Automation:
    Development and implementation of robotic systems for a wide range of applications, including manipulation, navigation, and rehabilitation.
  3. Artificial Intelligence and Machine Learning:
    Exploration of AI and machine learning techniques applied to automation, including predictive modeling and intelligent control systems.
  4. Cyber-Physical Systems and Digital Twins:
    Research on the integration of physical processes with digital representations, focusing on applications in industries such as manufacturing, healthcare, and robotics.
  5. Energy Systems and Optimization:
    Studies on the optimization of energy consumption in industrial processes and the development of control strategies for sustainable energy systems.
  6. Real-Time Systems and Communication:
    Investigation of scheduling and communication techniques for real-time control systems, particularly in multi-agent and distributed environments.
Recent publications in the journal reveal emerging themes and trends that are shaping the future of automation and industrial informatics. These trends reflect current technological advancements and the evolving needs of industry.
  1. Integration of AI and Machine Learning:
    A significant increase in research applying machine learning techniques to improve diagnostics, control, and prediction in industrial processes and robotics.
  2. Digital Twins and Cyber-Physical Systems:
    Growing interest in digital twin technology as a means to enhance the modeling, simulation, and control of complex systems, facilitating real-time monitoring and optimization.
  3. Advanced Robotics for Rehabilitation and Healthcare:
    Emerging applications of robotics in healthcare, particularly in rehabilitation technologies, showcasing innovative designs and control strategies tailored for patient care.
  4. Energy Efficiency and Sustainability:
    A rising focus on optimizing energy consumption in industrial processes and integrating renewable energy sources into control systems, reflecting a global trend towards sustainability.
  5. Multi-Agent Systems and Distributed Control:
    Increased research on multi-agent systems, emphasizing collaborative control and communication strategies for enhanced performance in complex environments.

Declining or Waning

While the journal continues to publish diverse research, certain themes have seen a noticeable decline in recent years. This may reflect shifts in technological focus or changes in the industrial landscape.
  1. Traditional Control Theory:
    There has been a gradual decrease in papers solely focused on classical control theory approaches, as more researchers explore innovative and hybrid control strategies.
  2. Conventional Robotics Applications:
    The focus on basic robotic applications has diminished in favor of more complex, interdisciplinary approaches that integrate AI and machine learning.
  3. Static System Modeling:
    Research that relies on static models without consideration for dynamic or adaptive behaviors is becoming less frequent, reflecting a trend towards more responsive and flexible modeling techniques.
  4. Basic Automation Techniques:
    Papers focusing on traditional automation methods without incorporating modern technologies such as IoT or AI have decreased, as the field shifts towards more advanced automated solutions.
  5. Low-Level Control Systems:
    There is a waning interest in low-level control systems that do not incorporate higher-level decision-making or learning algorithms, indicating a move towards more intelligent and adaptable systems.

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