Advancements in IoT and Machine Learning: Unveiling Synergies and Challenges

Dear Colleagues,

The convergence of the Internet of Things (IoT) and Machine Learning (ML) has unleashed a wave of innovation across various domains, promising transformations in how we interact with technology and perceive the world around us. This Special Issue aims to explore the latest research advancements, methodologies, applications, and challenges related to the intersection of IoT and ML, providing a comprehensive overview of the synergies and emerging trends in this rapidly evolving field.

This Special Issue aims to foster interdisciplinary discussions and collaborations among researchers, practitioners, and industry experts in the domains of IoT and Machine Learning. By compiling diverse perspectives and cutting-edge research, we strive to pave the way for innovative solutions and applications that harness the full potential of IoT and ML technologies. We look forward to receiving your contributions and advancing the state of the art in this exciting field.

This Special Issue welcomes original research contributions, review articles, and case studies that address, but are not limited to, the following topics:

• IoT-enabled Intelligent Systems:
  • Smart cities and urban infrastructure
  • Industrial IoT and Industry 4.0
  • Wearable devices and healthcare applications
  • IoT in agriculture and environmental monitoring
• Machine Learning Techniques for IoT:
  • Deep learning for sensor data analysis
  • Edge computing and distributed ML algorithms
  • Reinforcement learning in IoT applications
  • Federated learning and privacy-preserving techniques
• Security and Privacy Challenges:
  • Secure communication protocols for IoT devices
  • Privacy-preserving techniques in data collection and processing
  • Adversarial attacks and defense mechanisms in IoT systems
• Scalability and Resource Constraints:
  • Lightweight ML algorithms for resource-constrained IoT devices
  • Scalable infrastructure for handling large-scale IoT data
  • Energy-efficient computation and communication protocols
• Applications and Case Studies:
  • Predictive maintenance and fault detection
  • Intelligent transportation systems
  • Smart energy management and sustainability
  • Personalized IoT applications and user experience

Submission Guidelines:

Authors are invited to submit original, unpublished manuscripts following the Applied Sciences Journal formatting guidelines. All submissions will undergo a rigorous peer-review process to ensure the quality and relevance of the contributions.

Prof. Dr. Hani Hamdan
Dr. Jinan Charafeddine
Prof. Dr. Bang Wang
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 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.

• IoT-enabled intelligent systems
• machine learning techniques for IoT
• security and privacy