Sensor Technologies in the Age of AI: Cybersecurity Advantages and Challenges

Dear Colleagues,

Sensor technology plays a key role in systems that rely on ongoing data collection and monitoring. Sensors are widely used across the Internet of Things (IoT), healthcare, industrial automation, environmental monitoring, and autonomous systems. Recently, combining sensors with Artificial Intelligence (AI), machine learning, and edge computing has greatly expanded what these systems can do. Processing data closer to where it is collected allows for faster analysis and enables faster and better decision-making.

However, as sensor-based systems become more widespread, they also create new challenges. The constant flow of sensitive data raises the risk of cyberattacks, data tampering, and unauthorized access. These problems can affect both data privacy and system reliability. As a result, new protective measures and cybersecurity strategies are needed to find and reduce potential threats.

For this Special Issue, we invite contributions that highlight the recent advances and ongoing challenges in sensor technology, especially in secure data management and the use of Artificial Intelligence (AI). Successful submissions will explain original ideas, practical solutions, or real-world applications of intelligent sensing systems. Our aim is to support the growth of reliable and secure sensor technologies and to inspire ideas that will shape future research and innovation in this area.

The scope of this Special Issue includes, but is not limited to, the following topics:

• Novel sensor architectures and sensing mechanisms;
• Smart sensors and intelligent sensing systems;
• Low-power and energy-efficient sensor devices;
• Internet of Medical Things (IoMT) wearables;
• IoMT platforms and sensing technologies in healthcare;
• Environmental and industrial sensor applications;
• Embedded sensing platforms and edge-enabled sensors;
• Machine learning and deep learning for sensor data analysis;
• AI-based signal processing and pattern recognition;
• Intelligent data fusion from heterogeneous sensors;
• Edge AI for real-time sensing applications;
• Federated learning and distributed intelligence for sensor networks;
• Secure communication protocols for sensor networks and IoT;
• Privacy-preserving data collection and analytics;
• Cryptographic techniques for sensor data protection;
• Blockchain-based security frameworks for sensor systems;
• Trust management and authentication mechanisms in sensor networks;
• Adversarial attacks and defenses in AI-driven sensor systems.

Dr. Homero Toral-Cruz
Prof. Dr. Debiao He
Dr. Rafael Martínez Peláez
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-anonymized 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.