Machine Learning and Signal Processing in Sensing and Sensor Applications

Dear Colleagues,

In recent decades, machine learning (ML) technologies have made it possible to collect, analyze, and interpret a large amount of sensory information. As a result, a new era of intelligent sensors is emerging that changes the ways of perceiving and understanding the world. The integration of ML algorithms with artificial intelligence (AI) technology benefits other areas such as Industry 4.0, Internet of Things, etc. leveraging these two technologies, it is possible to design sensors tailored to specific applications. To this end, signal data, such as electrical signals, vibrations, sounds, accelerometer signals, as well as any other kind of sensory data like images, numerical data, etc. need to be analyzed and processed from real-time algorithms to mine useful insights and to embed these algorithms in sensors.

This Special Issue calls for innovative work that explores new frontiers and challenges in the field of applying ML/AI technologies and algorithms for high-sample-rate sensors. It includes new ML and AI models, hybrid systems, as well as case studies or reviews of the state-of-the-art.

The topics of interest include, but are not limited to the following:

• ML algorithms in smart sensor systems
• AI models in smart sensor systems
• ML/AI‐enabled smart sensor systems
• Practical smart-sensor applications
• Practical smart-sensing systems
• Health and disease data management
• Medical image diagnosis and analysis
• Biology data analysis
• Smart visual imaging sensing systems
• Object detection and recognition
• Smart-sensors for environmental pollution management
• Smart-sensors for precision agriculture and food science
• Big data analytics for sensor data
• Intelligent real-time algorithms for sensor data
• Features for signal classification
• Feature discovery
• Applications of AI and ML in sensor domains: energy, IoT, Industry 4.0, etc.

Dr. Gianni D’Angelo
Collection Editor

Manuscript Submission Information

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