AI-Driven Automation for Industrial Transformation: Innovations in Smart Systems, Machine Learning and Sustainable Processes
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Manufacturing Processes and Systems".
Deadline for manuscript submissions: 10 December 2025 | Viewed by 45
Special Issue Editor
Interests: advanced control of industrial processes and mechatronic systems; intelligent sensor systems; artificial intelligence; machine learning; smart farming
Special Issue Information
Dear Colleagues,
Industries, production, and business processes are undergoing a paradigm shift toward smarter and more sustainable operations. AI-driven automation is at the forefront of this transformation, helping businesses and societies address key challenges such as skills shortages, rising energy costs, and the global environmental footprint. By integrating cutting-edge sensor systems, advanced machine learning and sustainability practices, industries can achieve improved process/product quality and productivity while minimizing environmental impact. The concept of AI-driven automation has a holistic aim, enabling production processes of the future to fully exploit the potential of their own data, combine it with AI technologies for monitoring, diagnosis and control, and make it available across the entire business through appropriate IoT infrastructures. The applications for AI-driven automation are almost limitless. They range from medical technology and industrial manufacturing to agriculture and the production of food and beverages. The AI landscape encompasses a range of technologies including computer vision, machine learning, natural language processing, and cognitive computing.
This Special Issue, "AI-Driven Automation for Industrial Transformation: Innovations in Smart Systems, Machine Learning and Sustainable Processes", invites high-quality, original research and review articles that advance methods and real-world applications of AI in automation. Contributions should address how AI technologies can drive process optimization, sustainability, and resilience in industrial and business contexts.
Topics include, but are not limited to, the following:
- Design, analysis, control, optimization, operation, planning, or scheduling of a production, medical, or transportation system using an advanced AI technology such as neural networks, deep learning, or reinforcement learning, amongst others.
- Development of novel algorithms, tools, or frameworks for AI-driven process modeling, predictive maintenance, and adaptive control.
- Novel application studies in AI-driven manufacturing, production, logistics, medical technology, precision agriculture, etc.
We encourage submissions that bridge theory and practice, demonstrate scalability, or address ethical, economic, or societal implications of AI adoption.
Prof. Dr. Mohieddine Jelali
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- smart sensors
- data engineering
- computer vision
- machine learning
- deep learning
- cognitive computing
- AI-driven modeling, monitoring, or control
- industrial IoT
- AI-based design or engineering for sustainability
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