Читать книгу Industry 4.0 Vision for the Supply of Energy and Materials - Группа авторов - Страница 69

The digital transformation to Industry 4.0 and FoF is not easily implemented, as there are diverse use cases, connectivity requirements, and multiple levels of QoS that should be considered in designing and deploying each application. Therefore, Industry 4.0 faces critical challenges that suggest future research trends for 2022 and beyond. Some major topics in this domain are:

 Development of new AI-enabled solutions: The integration of deep learning, data analysis, and artificial intelligence technologies, along with the industrial Internet, assists in offering smart monitoring and intelligent production and services.

 Implementing Edge and Fog computing: Since cloud computing systems may suffer from capacity scarcity and experience high latency, Edge- and Fog-based computing are promising solutions for low-latency and time-critical applications. In this context, a novel mobile network architecture is presented in [213], where the radio access network (RAN) relies on Fog computing to address latency issue and leads to a more reliable system.

 Cybersecurity and privacy: It is an important concern in IIoT scenarios as a heterogeneous connected environment and becomes more critical in post-Covid working trend due to worker expansion and remote working. Recent advancements in blockchain technology, wireless communication, and Edge computing offer trusted, distributed, and P2P network for failure prediction in IIoT that could improve security and intelligence of such systems [204].

Despite the fact that wireless communication is well established for some industrial use cases, heterogeneity of the connectivity landscape and its integration in the system pose critical issues in the industrial Internet. In this section, we identified some principal challenges of future wireless communication in Industry 4.0 and discuss them in the following sections.