Special Issues Journals

Content to be updated.

Special Issue No. 1

Special Issue “AI for Sustainable Real-World Applications”




Artificial Intelligence (AI), Intelligent Sensors, Robotics and more recently Industry 4.0 are research areas and applications aligned to benefit the research community and society in various domains. Sensors emit a tremendous amount of data (aka big data) which can be captured and analysed using different AI and Machine Learning (ML) tools and techniques. Extensive research has been developed in this area, ranging from theoretical foundations and principles, to practical applications in diverse context including medical, industry, environment, finance, education, to name just a few.


Prof Dr Dhiya Al-Jumeily OBE, UK.

Prof Dr Jamila Mustafina, Russia.

Dr Manoj Jayabalan, UK.       

The aim of this Topical Collection is allowing researchers to communicate their high-quality and original ideas by presenting and publishing innovative advances in Industry 4.0, computational intelligence and the Internet of Everything (IoE) and their applications.

This special issue explores the convergence of Industry 4.0, AI, data science, and their applications in real-world application, providing a background to problem domains, considering the progress so far, assessing the potential of such approaches, and exploring possible future directions. We aim to increase the understanding and use of AI techniques in tackling the real-world problems. We welcome contributions that deal with all aspects of the scientific foundations, theories, techniques and applications of computing, data and analytics, including, but not limited to:

  • Industry 4.0 applications in health and medicine and other social domains
  • Advances in Image and Signal Processing
  • Computational Intelligence Technology for sustainable real-world applications (Healthcare, Medicine, Education, Business, Culture, etc.)
  • Cognitive Computing and Emotional Intelligence in sustainable real-world applications
  • Computational Intelligence Technology in Data mining, Data Integration and Big Data Analysis for sustainable real-world applications
  • Predictive Models and Analytics Using Artificial Intelligence


Special Issue No. 2

International Journal of Data Science and Advanced Analytics





The International Journal of Data Science and Advanced Analytics (IJDSAA) (ISSN:
2563-4429) is an artificial intelligence (AI)-based interdisciplinary journal that was
established in 2019 by the eSystem Engineering Society (eSES), a UK-based non-
profit organisation founded in 2007.
IJDSAA serves as a platform for researchers, practitioners, and academics to share
their knowledge and advancements in the field of data science and advanced
analytics. The journal’s scope encompasses a wide range of topics and applications
in multidisciplinary and interdisciplinary fields related to AI and machine learning
The key aim of IJDSAA is to contribute to the advancement of data science and
promote the practical applications of advanced ML analytics techniques across
various disciplines bringing together interdisciplinary collaborations. The journal
welcomes submissions that explore theoretical knowledge, innovative
methodologies, statistical analysis, data mining, computational intelligence,
advanced analytics, big data analytics, predictive modelling, optimisation techniques,
and data visualisation.
The scope of IJDSAA extends to interdisciplinary research, encouraging studies that
bridge the gap between data science and other fields such as business, economics,
finance, healthcare and medicine, robotics engineering, environmental, and social

Editorial Manager:


  1. Manoj Jayabalan (PhD)ORCID logo, Liverpool John Moores University, United Kingdom.
  2. Talal Yusaf (PhD)ORCID logo, Federation University Australia, Australia.

Associate Editors:

  1. Prof. Duc Pham OBE (PhD)ORCID logo, (Fellow of the Royal Academy of Engineering), United Kingdom.
  2. Prof Hissam Tawfik (PhD)ORCID logo, University of Sharjah, UAE.
  3. Thar Baker Shamsa (PhD)ORCID logo, University of Brighton, United Kingdom.
  4. Sulaf Assi (PhD)ORCID logo, Liverpool John Moores University, United Kingdom.
  5. De-Shuang Huang (PhD)ORCID logo, Tongji University, China.
  6. Salman Rawaf (PhD)ORCID logo, Imperial College London, United Kingdom.


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