Artificial Intelligence and Big Data for Industrial Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 October 2026 | Viewed by 236
Special Issue Editors
Interests: smart sensors; fog computing; automatic identification; real-time systems; decision-making
Interests: artificial intelligence; soft computing; feature selection; fuzzy modelling; optimization; metaheuristics; computational intelligence; knowledge data discovery
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent developments in artificial intelligence have resulted in novel approaches in many fields, ranging from computer vision to machine translation. Artificial intelligence methods can bring generalization, adaptability, and flexibility to existing systems. However, many of these developments rely heavily on large volumes of data, especially deep learning approaches. Traditionally, industrial applications do not easily generate or collect enough information for these methods to succeed. Approaches and models are often based solely on simulations or data from surrogate models.
Big Data, such as high-volume sensor data collected from physical devices connected over the internet (Internet of Things), can feed AI data-hungry models. However, Big Data with excessive volume, variety and velocity hampers the applicability of AI methods, which thrive on carefully structured datasets. Nowadays, the tendency is to move from data scarcity to data overabundance. Automated data processing and analysis can be used to better handle the incoming industrial data, but more research needs to be conducted on the efficient use of noisy, streaming and weakly labelled Big Data for AI methods.
This Special Issue seeks high-quality, original research articles, reviews, and case studies that present innovative uses of artificial intelligence and big data in different industrial applications. Topics of interest include, but are not limited to, the following:
- Advancements in AI techniques that leverage Big Data: exploring new architectures, training frameworks, and validation procedures that make use of Big Data;
- Novel AI approaches to increase Big Data usability: strategies and frameworks to handle and automate large data volumes, labeling, uncertainty, missing data, etc.;
- Innovative encodings and representations of industrial problems: novel ways to represent industrial problems efficiently;
- Case studies and real-world industrial applications: detailed implementations, supporting frameworks, pain-points from real-world deployment, and impact analysis;
- Scalability, lifecycle analysis, and explainability of AI systems in industrial Big Data settings.
Dr. Miguel S. E. Martins
Dr. Susana Vieira
Guest Editors
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 250 words) can be sent to the Editorial Office for assessment.
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. Applied Sciences is an international peer-reviewed open access semimonthly 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
- artificial intelligence
- big data
- industrial applications
- data analytics
- predictive modeling
- deep learning applications
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