Artificial Intelligence in Industrial IoT Applications

Dear Colleagues,

At present, the introduction of artificial intelligence techniques into manufacturing processes has enabled significant advances in production operations. Typically, these improvements aim to refine the quality and efficiency of processes and reduce the use of resources, such as energy, raw materials, or production time and labour.

Modern industrial applications are becoming complex cyber physical systems (CPSs) that improve the performance of the manufacturing processes, leading them to achieve higher efficiency, improve quality, and reduce the use of resources. For these purposes, modern industrial applications are introducing artificial intelligence techniques which are combined with communication technologies for integrating the data acquired from diverse nodes scattered among factories.

The introduction of new concepts into production processes, such as wireless sensor networks and the Industrial Internet of Things (IIoT), is supporting the collection of updated information in production operations. In general, the use of wireless communications introduces higher flexibility and allows mobile devices to be involved. These are important benefits in industrial environments.

However, the modern industrial processes found in Industry 4.0 applications produce large amounts of data, which must be managed efficiently. This is a key issue which can be addressed through the successful introduction of artificial intelligence techniques. In this scenario, new paradigms such as the so-called edge, fog, and cloud paradigms are being introduced to create complex application architectures.

These issues are of the outmost importance in modern industrial applications; therefore, the scientific community may benefit from the presentation of use cases that show the application of both modern processing techniques and communication techniques. For that reason, we invite colleagues in the research community to disseminate their novel contributions in these fields.

Prof. Dr. Isidro Calvo
Guest Editor

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