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

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• sensor technology
• smart sensors
• wireless sensor networks
• artificial intelligence
• internet of things
• internet of medical things
• wearable health devices
• edge computing
• edge AI
• intelligent sensing systems
• federated learning
• data security and privacy
• machine learning for sensors
• deep learning for sensors
• secure sensor networks
• secure data analytics
• cybersecurity in IoT
• privacy-preserving sensing
• blockchain
• cryptography