About the Journal

Applied Intelligent Technologies (APIT) is a peer-reviewed, open-access journal dedicated to advancing the development and practical application of intelligent technologies across diverse fields. Focusing on interdisciplinary research that bridges theory and real-world implementation, APIT publishes high-impact studies, methodological innovations, and industry-relevant case studies. The journal serves as an international platform for researchers, engineers, and industry professionals to explore cutting-edge solutions in artificial intelligence, machine learning, data analytics, and automation, emphasizing ethical, scalable, and reproducible approaches. APIT aims to foster collaboration between academia and industry, and drive technological progress with global societal impact.

APIT welcomes original contributions (such as research articles, review articles, short communications, case studies, technical briefs, software/tool descriptions, and focused perspectives) that advance the theory, development, and application of intelligent technologies. The journal addresses diverse research including but not limited to:

Research Focus:

  • Artificial Intelligence (AI) and Machine Learning (ML) algorithms for complex problem-solving.
  • Data-driven decision-making, predictive modeling, and big data analytics.
  • Intelligent systems integration (e.g., IoT, robotics, autonomous systems).
  • Human-machine interaction, explainable AI, and trust in AI systems.
  • Ethical, legal, and social implications of intelligent technology deployment.

Application Domains:

  • Healthcare: AI-driven diagnostics, personalized medicine, and medical imaging.
  • Industry 4.0: Smart manufacturing, supply chain optimization, and predictive maintenance.
  • Smart Cities: Transportation systems, energy management, and urban planning.
  • Finance: Algorithmic trading, risk analysis, and fraud detection.
  • Environment: Climate modeling, conservation technologies, and sustainable practices.

APIT adheres to rigorous peer-review standards and advocates transparency in reporting. By bridging academic inquiry and industrial practice, the journal seeks to accelerate innovation while addressing ethical, accessibility, and scalability challenges in intelligent technology ecosystems.