Ronald Garcés | Electrical and Electronics Engineering | Research Excellence Award

Research Excellence Award

Ronald Garcés

Ronald Garcés
Affiliation Corporación WOLF S.A
Country Ecuador
Scopus ID 58072300700
Documents 1
Citations 2
h-index 1
Subject Area Electrical and Electronics Engineering
Event Scientific World Research Awards

Ronald Garcés is associated with engineering and technological research activities related to automation systems, artificial vision, and Internet of Things (IoT)-based monitoring applications. His scholarly contributions reflect emerging developments in electrical and electronics engineering, particularly in hydraulic infrastructure automation and remote measurement technologies.[1] His academic profile demonstrates participation in applied engineering research intended to improve operational efficiency and technological reliability in environmental and industrial systems.

Abstract

Ronald Garcés has contributed to the advancement of engineering applications involving artificial vision, automation, and IoT-enabled monitoring systems. His published research demonstrates interest in remote data acquisition methods for hydraulic infrastructures and automated environmental observation technologies.[2] Through collaborative engineering approaches, his work supports the modernization of remote measurement systems and contributes to practical developments within electrical and electronics engineering. The integration of intelligent monitoring solutions in hydraulic systems represents a relevant contribution to infrastructure management, operational precision, and technological sustainability within applied engineering environments.

Keywords

Artificial Vision, Internet of Things, Automation Engineering, Hydraulic Monitoring, Remote Reading Systems, Electrical Engineering

Introduction

The growing integration of intelligent automation technologies has transformed engineering practices across environmental and industrial sectors. Research involving remote sensing and IoT-based monitoring systems has become increasingly significant for operational efficiency and infrastructure analysis.[3] Ronald Garcés has participated in this evolving area through contributions connected to automated hydraulic measurement technologies and artificial vision applications.

Research Profile

The researcher’s Scopus profile identifies scholarly activity within electrical and electronics engineering. His profile includes conference-based engineering publications focused on intelligent automation and remote observation systems.[1] These contributions reflect interdisciplinary technical engagement involving automation technologies and infrastructure management systems.

Research Contributions

Ronald Garcés contributed to research concerning artificial vision and IoT solutions for automated remote reading in hydraulic weirs and limnimeter systems.[2] The study explored methods for improving monitoring precision and enabling more efficient infrastructure observation processes through integrated digital technologies.

Publications

  • “Artificial Vision and IoT for Automation of Remote Reading for Limnimeters in Hydraulic Weirs.”[2]
  • Engineering conference contributions related to intelligent monitoring and automation technologies.

Research Impact

The application of automated monitoring technologies in hydraulic systems contributes to improved data reliability and operational responsiveness. Research involving artificial vision and IoT integration has relevance for water resource management, infrastructure maintenance, and digital engineering innovation.

Award Suitability

Ronald Garcés demonstrates suitability for recognition through his involvement in applied engineering research focused on intelligent automation and infrastructure technologies. His scholarly participation within emerging engineering applications aligns with the objectives of research excellence and innovation-oriented academic awards.

Conclusion

The academic contributions of Ronald Garcés highlight ongoing engagement with technological research areas involving automation, IoT systems, and artificial vision applications. His engineering-related studies contribute to contemporary discussions surrounding intelligent monitoring systems and digital infrastructure development within applied engineering disciplines.[4]

References

  1. Elsevier. (n.d.). Scopus author details: Ronald Garcés, Author ID 58072300700. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=58072300700
  2. Garcés-Llerena, R. et al. (2022). Artificial Vision and IoT for Automation of Remote Reading for Limnimeters in Hydraulic Weirs.
    DOI:https://doi.org/10.1007/978-3-031-21438-7_34
  3. Scopus Preview. (2026). Conference publication records for Ronald Garcés-Llerena.
    https://www.scopus.com/
  4. Scientific World Research Awards. (2026). Research recognition and engineering innovation awards.

    Scientific World Research Awards


Keun Chang Kwak | Robotics and Automation | Best Researcher Award

Prof. Keun Chang Kwak | Robotics and Automation | Best Researcher Award

Professor | Chosun University | South Korea

Professor Keun-Chang Kwak is a distinguished researcher in the fields of computational intelligence, biometrics, and robotic vision systems, with extensive expertise in granular and neuro-fuzzy modeling, face and speaker recognition, knowledge extraction, behavior recognition, and auditory signal processing. He earned his Ph.D. in Electrical Engineering from Chungbuk National University, Korea, in 2002, following an MS in 1998 and a BS in 1996 from the same institution. Over his career, Prof. Kwak has held several prominent positions, including Professor at Chosun University, Korea (2007–present), Visiting Professor at California State University Fullerton, USA (2014–2015), Senior Researcher at the Intelligent Robot Research Division, Electronics and Telecommunications Research Institute (ETRI), Korea (2005–2007), and Postdoctoral Fellowships at the University of Alberta, Canada (2003–2005) and Chungbuk National University, Korea (2002–2003). He has also served as Project Manager of the AI Convergence University Project Division (2021–present) and Vice Director of the National Center of Excellence in Software at Chosun University (2018–2020), leading numerous national and international research initiatives. His research interests include computational intelligence, deep learning, speech emotion recognition, ECG-based biometrics, human-robot interaction, and knowledge extraction using fuzzy clustering. Prof. Kwak’s prolific publication record includes 138 Scopus-indexed documents, 1,667 citations, and an h-index of 21, reflecting high-impact contributions to journals such as IEEE Access, Applied Sciences, Electronics, and Sensors. He has led and mentored research teams, collaborated internationally, and contributed significantly to the robotics and AI communities. Prof. Kwak’s achievements are recognized through multiple awards, leadership roles, and professional memberships, highlighting his influence on research, education, and technology advancement. His work demonstrates exceptional innovation, academic excellence, and the potential to drive future breakthroughs in AI, robotics, and computational intelligence, making him highly deserving of the Best Researcher Award.

Profiles: Scopus | Google Scholar

Featured Publications

  1. Pedrycz, W., & Kwak, K. C. (2006). Linguistic models as a framework of user-centric system modeling. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 36(2), 187–200. [Citations: 187]

  2. Kwak, K. C., & Pedrycz, W. (2005). Face recognition using a fuzzy fisherface classifier. Pattern Recognition, 38(10), 1717–1732. [Citations: 185]

  3. Kwak, K. C., & Pedrycz, W. (2007). Face recognition using an enhanced independent component analysis approach. IEEE Transactions on Neural Networks, 18(2), 530–541. [Citations: 167]

  4. Byeon, Y. H., Pan, S. B., & Kwak, K. C. (2019). Intelligent deep models based on scalograms of electrocardiogram signals for biometrics. Sensors, 19(4), 935. [Citations: 138]

  5. Kwak, K. C., & Pedrycz, W. (2005). Face recognition: A study in information fusion using fuzzy integral. Pattern Recognition Letters, 26(6), 719–733. [Citations: 112]