Jaydevsinh Zala | Engineering | Best Researcher Award

Published on by International Popular Scientist Awards

Best Researcher Award

Jaydevsinh Zala
Parul University, India

Jaydevsinh Zala
Affiliation Parul University
Country India
Documents 2
Subject Area Engineering
Event International Popular Scientist Awards
ORCID 0009-0009-9225-7789

Jaydevsinh Zala is an engineering researcher affiliated with Parul University in India. The research record supplied for this academic recognition profile comprises two documented works addressing applied engineering and technology-oriented problems, including an artificial-intelligence-based smart-city hygiene enforcement system and an electronics prototyping workstation. The available record indicates an interdisciplinary interest in artificial intelligence, computer vision, facial recognition, electronics, and practical technology development. [1] [2]

Abstract

This academic recognition profile examines the research activities of Jaydevsinh Zala in the field of Engineering. The supplied record contains two works. The first, AI-Integrated Spitting Detection System for Smart City Hygiene Enforcement Using YOLOv11 and Facial Recognition, describes an artificial intelligence-oriented approach to smart-city hygiene enforcement using computer vision and facial recognition technologies. The work is identified as unpublished and dated 2 August 2026, with a DOI registered through ResearchGate. [1] The second work, AI Integrated Electronics Prototyping Workstation, is identified as a journal article dated 20 April 2025 and is attributed to Jaydevsinh Zala. [2]

Keywords

Jaydevsinh Zala; Engineering; Artificial Intelligence; Computer Vision; YOLOv11; Facial Recognition; Smart City Technology; Hygiene Enforcement; Electronics Prototyping; Research Innovation.

Introduction

Engineering research increasingly combines computational intelligence with physical and digital systems to address practical problems. Artificial intelligence and computer vision can support automated interpretation of visual information, while electronics prototyping environments can facilitate the development and testing of technology systems. Zala’s available research record reflects these two complementary areas, with one work focused on AI-enabled smart-city hygiene enforcement and another concerned with an integrated electronics prototyping workstation. [1] [2]

Research Profile

Jaydevsinh Zala is affiliated with Parul University and works within the broad subject area of Engineering. The supplied publication record contains two documents. One research work applies YOLOv11 and facial recognition to a proposed smart-city hygiene enforcement application, while the other concerns an AI-integrated electronics prototyping workstation. [1] [2]

Research Contributions

The documented works indicate contributions in two principal areas:

  • Application of artificial intelligence and computer vision to a proposed smart-city hygiene enforcement scenario, incorporating YOLOv11 and facial recognition technologies. [1]
  • Development-oriented work concerning an AI-integrated electronics prototyping workstation, reflecting an interest in engineering experimentation and technology prototyping. [2]

Publications

The first work identifies a specific DOI and combines machine-learning-based object detection with facial recognition for a smart-city application. [1] The second listed work addresses electronics prototyping through an AI-integrated workstation concept. [2]

Research Impact

The available information does not provide verified citation counts, h-index data, downloads, or independent measures of research influence. Therefore, quantitative scholarly impact cannot be established from the supplied record alone. The documented topics nevertheless address practical engineering applications, particularly the use of artificial intelligence and computer vision in smart-city environments and the integration of AI into electronics prototyping. [1] [2]

Award Suitability

The documented research topics are relevant to an engineering-focused academic recognition profile because they involve applied artificial intelligence, computer vision, smart-city technology, and electronics prototyping. The first work addresses an application involving automated detection and recognition, while the second focuses on an engineering workstation for electronics prototyping. [1] [2]

Conclusion

Jaydevsinh Zala’s supplied research record represents an engineering-oriented portfolio involving artificial intelligence, computer vision, smart-city applications, and electronics prototyping. Two documented works form the basis of this profile, including a 2026 work on YOLOv11 and facial recognition for smart-city hygiene enforcement and a 2025 work on an AI-integrated electronics prototyping workstation. [1] [2] Further bibliometric and independent research evidence would be required for a more comprehensive assessment of scholarly impact.

References

  1. Zala, J. (2026). AI-Integrated Spitting Detection System for Smart City Hygiene Enforcement Using YOLOv11 and Facial Recognition. Unpublished journal article.
    https://doi.org/10.13140/RG.2.2.32954.35528
  2. Zala, J. (2025). AI Integrated Electronics Prototyping Workstation. Journal article. Research record supplied for academic recognition profile.
  3. ORCID. (n.d.). ORCID record for Jaydevsinh Zala.
    https://orcid.org/0009-0009-9225-7789
  4. International Popular Scientist Awards. (n.d.). Award Website.
    https://popularscientist.com/

ABDUL SAMI | Engineering | Best Researcher Award

Published on by International Popular Scientist Awards

Mr. ABDUL SAMI | Engineering | Best Researcher Award

Lecturer Numl University Hyderabad Pakistan

Engr. Abdul Sami Shaikh is a seasoned software engineering professional with a diverse portfolio in academia, research, and freelancing. His career is marked by significant contributions to IT education, cutting-edge research, and innovative development practices. Based in Hyderabad, Sindh, Abdul Sami is driven by a passion for leveraging technology to address real-world challenges and enhance learning.

Profile

Orcid

Education 🎓

Abdul Sami Shaikh has a strong academic foundation with a Master of Engineering in Information and Communication Engineering from Harbin Engineering University, China (2013-2016), achieving an impressive 3.77 CGPA. His undergraduate degree in Computer System Engineering from Mehran University of Engineering and Technology, Jamshoro (2005-2009), laid the groundwork for his technical expertise. Earlier, he pursued Pre-Engineering at Govt. Boys Degree College, Qasimabad, Hyderabad, and completed his schooling at the Model School of Sindh University.

Experience đź’Ľ

Abdul Sami has an extensive teaching and research background, having served as a lecturer at Isra University, National University of Modern Languages (NUML), and other prestigious institutions. His professional journey includes roles such as Research Associate at Mehran UET, Program Coordinator for the National Freelance Training Program, and editorial assistant for the Mehran UET Research Journal. He also gained valuable industrial experience through internships with organizations like Sui Southern Gas Company and Microsoft.

Research Interests 🔬

His research focuses on machine learning, data visualization, deep learning, and their applications in healthcare and cybersecurity. He has explored innovative solutions in image analysis, mobile app automation for Industry 4.0, and advanced threat detection systems. Abdul Sami also delves into challenges in spatial crowdsourcing and IoT-based systems.

Awards and Recognitions 🏆

While Abdul Sami has not listed specific awards, his academic and professional milestones, coupled with his impactful publications, position him as a strong candidate for recognition in research and innovation.

Publications Top Notes: đź“š

Acoustic Propagation and Transmission Loss Analysis in Shallow Water

Automated Classification of Pneumonia from Chest X-Ray Images using EfficientNet-B0

 

Yusuf Alper KAPLAN | Engineering | Best Researcher Award

Published on by International Popular Scientist Awards

Prof. Yusuf Alper KAPLAN | Engineering | Best Researcher Award

Prof. Osmaniye Korkut Ata Unv. Turkey

Dr. Yusuf Alper Kaplan is a Professor of Energy Systems Engineering at Osmaniye Korkut Ata University in Turkey. He has a distinguished career in renewable energy, specializing in solar and wind energy modeling, estimation, and system performance. With over two decades of experience, Dr. Kaplan has contributed to advancing energy systems through innovative methodologies and predictive models.

Profile

Google scholar

Education 🎓

  • Bachelor’s in Electrical and Electronics Engineering, Gaziantep University, 2002
  • Master’s in Electrical and Electronics Engineering, Çukurova University, 2008
  • Ph.D. in Electrical and Electronics Engineering, Anadolu University, 2014

Professional Experience đź’Ľ

  • Lecturer (2004-2009) at Çukurova University
  • Research Assistant (2010-2014) at Anadolu University
  • Assistant Professor (2014-2018), Associate Professor (2018-2023), and Professor (2023-present) at Osmaniye Korkut Ata University
  • Head of Department of Energy Systems Engineering (2019-2020)
  • Director of the Continuing Education Centre (2020-present)

Research Interests 🔬

Dr. Kaplan’s research focuses on renewable energy, especially solar and wind energy systems. His work involves developing statistical and computational models for solar radiation forecasting, wind energy assessment, and performance optimization of renewable energy sources in varying environmental conditions.

Awards and Recognitions 🏆

Dr. Kaplan has been honored for his contributions to renewable energy and academic excellence. His achievements include national and international recognitions for advancements in energy system performance modeling and contributions to sustainable energy solutions.

Publications Top Notes: đź“š

Kaplan, Y. A. (2024). Forecasting of global solar radiation: A statistical approach using simulated annealing algorithm. Engineering Applications of Artificial Intelligence, 136, 109034. (Cited by 15)

Kaplan, A. G., & Kaplan, Y. A. (2024). Using of the Weibull distribution in developing global solar radiation forecasting models. Environmental Progress & Sustainable Energy. (Cited by 10)

Kaplan, Y. A. (2023). Development of backpropagation algorithm for estimating solar radiation: A case study in Turkey. Revue Roumaine des Sciences Techniques, 68(3), 313-316. (Cited by 8)