Interdisciplinary Applications of Machine Learning and Intelligent Signal Prediction for Smart and Connected Environments

Dear Colleagues,

The rapid development of artificial intelligence (AI) and machine learning (ML) is changing predictive modeling and intelligent systems in various engineering and scientific fields. Modern deep learning (DL) structures, signal classification frameworks, and facial emotion recognition (FER) systems are now essential to data-driven applications. They provide unprecedented accuracy and flexibility in complex situations.

This Special Issue aims to showcase the connections among computational intelligence, sensing technologies, and predictive analytics. It will link traditional industrial and engineering research with the latest in smart systems, the Internet of Things (IoT), and human-centered AI. Combining these technologies helps create scalable and reliable predictive methods. These improvements boost system performance, enhance decision-making, and allow for autonomous adjustments across different fields.

This Special Issue invites submissions that advance theoretical frameworks, algorithmic development, and practical applications of intelligent prediction methods. The focus is on approaches that integrate data-driven learning with domain-specific knowledge to address challenges in contemporary technological ecosystems.

The primary objectives of this Special Issue are as follows:

• Spotlighting interdisciplinary studies that integrate ML, DL, and AI for predictive modeling and intelligent control;
• Promoting novel applications in signal analysis, IoT-based sensing systems, and affective computing;
• Encouraging research that connects computational intelligence with engineering design, sustainability, and reliability;
• Supporting cross-domain methodologies for prediction, optimization, and decision support in complex systems.

Suggested topics are outlined below.

1. Machine Learning and Deep Learning for Predictive Modeling:

• Hybrid and interpretable models for system prediction and optimization;
• Transfer learning and domain adaptation in industrial applications.

2. Signal Processing and Classification for Intelligent Systems:

• Time-series forecasting and signal decomposition using AI;
• Multimodal signal fusion for performance monitoring and fault detection.

3. Facial Emotion Recognition and Affective Computing:

• Emotion-aware intelligent systems for human–machine interaction;
• Deep learning architectures for robust facial and behavioral analysis.

4. IoT and Edge Intelligence for Predictive Analytics:

• Edge and fog computing frameworks for real-time prediction;
• Distributed learning and federated intelligence for sensor networks.

The Special Issue seeks original articles, comprehensive reviews, and case studies that demonstrate methodological innovations and practical implementations of intelligent systems. Emphasis will be placed on interdisciplinary studies that combine computational intelligence with experimental data or real-world deployment. 

Dr. Maria Samarakou
Guest Editor

Dr. Eleni Tsalera
Guest Editor Assistant

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. 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.

• artificial intelligence
• predictive modeling
• deep learning
• signal classification
• facial emotion recognition
• internet of things
• intelligent systems
• affective computing