Technological development is increasing in many areas of social and economic activity in modern society and has improved standards of living across the globe. Besides the importance of improving standards of living, current economic globalization has led to a growth in competitiveness. Furthermore, climate change has resulted in the promotion of policies that seek energy efficient systems, reduce pollution and environmental impact, and have the necessary high safety, reliability, and quality standards. In this context, it is clear the importance of ensuring the correct operation of every process, and to accomplish this, the early detection of any kind of anomaly is a critical step, especially in critical-safety and high cost processes.

However, a direct consequence of the strong development in fields such as industrial processes, social media, or medicine is growing complexity, a significant challenge in anomaly detection. Therefore, to ensure an optimum operation, the problem of supervising systems whose performance is not simple must be dealt with. To tackle the challenging task of anomaly detection, the use of virtual sensors may represent an interesting approach. Assisted by strong digitalization processes and intelligent techniques, this strategy makes use of indirect magnitude measures to determine anomalous situations in a process. This approach can be also combined with other typical anomaly detection methods, based on both unsupervised, semi-supervised, and supervised techniques.

This Special Issue offers a fascinating opportunity to explore and deliberate on the newest advances and real-world applications in virtual sensors and anomaly detection. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Virtual sensors
• Fault detection and diagnosis
• Anomaly detection
• One-class techniques
• Intelligent systems applications in industrial processes
• Systems efficiency improvement and optimisation
• Biomedical applications
• Complex sensor system modelling
• Optimisation of sensors for processes and procedures
• Intelligent systems sensor applications
• Intelligent control applications
• Sensors for smart grid and microgrid applications
• Sensors for mobility and electromobility applications
• Electronics and power electronics sensor applications