Aims & Scope

Aims

Journal of Artificial Intelligence for Automation (JAIA) is a gold open access, peer-reviewed journal dedicated to disseminating high-quality research that advances our understanding of artificial intelligence, machine learning, intelligent optimization and their applications to automation. JAIA seeks to serve as a comprehensive platform and vital resource for researchers, practitioners, and policymakers involved in automation in such sectors as manufacturing, service, transportation, health care, and supply chains. It is published quarterly online by Scilight Press.

Scope

The journal welcomes a broad range of contributions, including original research articles, review papers, methodological papers, and brief communications that present artificial intelligence, machine learning, intelligent optimization to advance automation. Submissions should advance the state of knowledge in artificial intelligence for automation, whether through novel theories, innovative algorithms, system-level architectures, or applied solutions. Topics of interest include, but are not limited to:

  • Intelligent robots, machines, and systems–design, control, autonomy, and collaborative intelligence.
  • AI- and learning-based methods for complex systems–modeling, analysis, simulation, performance evaluation, and decision-making.
  • Optimization and resource management–AI-driven methods for resource allocation, scheduling, planning, risk management, and supply chain optimization.
  • Data-driven automation–integration of Internet of Things (IoT), big data analytics, cloud/edge computing, and knowledge-based systems in automation-intensive industries.
  • Digital transformation–digital twins, Industry 4.0/5.0, human-centered automation, and adaptive human–machine collaboration.
  • Cyber-Physical Systems (CPS) and Human-Cyber-Physical Systems (HCPS)–frameworks, architectures, and applications for intelligent, safe, and resilient automation.

The journal encourages submissions that employ cutting-edge technologies and methodologies to address pressing challenges and future opportunities in automation across sectors such as smart manufacturing, precision agriculture, intelligent logistics, sustainable transportation, and next-generation health care systems. Other emerging topics in AI for automation are welcome