Industrial applications are customized applications with high reliability and high-cost performance. Industrial applications include process control, manufacturing automation and energy management. Process control is used in the nuclear industry, petrochemical industry, chemical industry and food industry. The application of manufacturing automation is machine numerical control and big data system. It is widely used in aviation, highway, shipping, railway, oil, and gas transportation and distribution control.

However, there is a need to consider the concept of combining artificial intelligence with distributed, high-performance hardware and adaptive algorithms in industrial systems. Local analysis of data supports the independent operation and establishes inherent data security. In industry systems, processing should be as close to the data source as possible. There are usually sensors with integrated processing that ensure low latency and improves the quality of results in the early analysis phase. To deal with a limited amount of data, it is important to combine data analysis with an understanding of industrial processes. To broaden the database, artificial intelligence methods can also be used. However, there is a need to consider the data of digital twins. The specific data can be used for training. It also requires an in-depth understanding of the process. Based on these initial considerations, key conditions for designing hardware and its infrastructure can be derived, such as selecting additional measurement variables or adaptive sampling rate of the data stream.

The aim of this Special Issue is to bring together original research and review articles discussing the application of intelligent sensing and artificial intelligence in complex modern industrial systems. Submissions considering theory, methodologies, and applications in the field of intelligent sensing, machine learning, and deep learning techniques for industrial scenarios are welcome. The target audiences are researchers and engineers who need to apply state-of-the-art and reliable sensing and artificial intelligence technologies in manufacturing industries. We welcome research from authors who are working closely with the industry using sensing and artificial intelligence (AI) technologies.

Potential topics include but are not limited to the following:

• Advances in the use of artificial intelligence for industrial automation
• Industrial Internet of Things (IIoT) for industrial applications
• Collaborative robots for industrial applications
• Data acquisition and storage for industrial AI systems
• Development of machine learning systems for industrial applications
• Sensing and/or AI systems for operating production lines, industrial equipment, warehouses, and other industrial systems
• AI-based automation of validation and verification of industrial processes
• Optimization of machine learning algorithms for complex modern industrial systems
• Artificial intelligence techniques for data security and privacy for industrial systems
• Artificial intelligence techniques for planning and decision-making for industrial automation