# An Overview of Privacy Dimensions on the Industrial Internet of Things (IIoT)
## 3 IIoT and Privacy-Preserving Architectures  
Unlike traditional industrial systems that operate in isolation or with limited connectivity, IIoT systems enable seamless communication between devices and systems, both within a single industrial facility and across multiple sites or locations. This interconnectedness allows for the exchange of data and information, facilitating the integration of operational technology (OT) with information technology (IT) systems [12]. The IIoT leverages technologies such as cloud computing, big data analytics, machine learning, and artificial intelligence to process and derive insights from the vast amount of data generated by industrial devices and systems. These technologies enable predictive maintenance, remote monitoring, intelligent automation, and optimization of industrial processes. The applications of the IIoT are diverse and can be found in various industries, including manufacturing, energy and utilities, transportation, agriculture, healthcare, and more. Examples of IIoT implementations include smart factories, connected supply chains, remote asset management, predictive maintenance, and energy management systems. Any edge device (sensors, readers, gateways) can transfer local data to cloud systems by using any available communication system for real-time analysis. However, if they are not incorporating AI applications, their use can be considered passive, as they cannot utilize the data in real-time. AI plays a crucial role in leveraging data in real-time by enabling efficient processing, analysis, and decision-making. Also, AI empowers organizations to harness the power of real-time data by enabling efficient processing, analysis, and decision-making. By leveraging AI algorithms and techniques, organizations can extract insights, make predictions, automate processes, and provide personalized experiences in real-time, thereby gaining a competitive edge and driving innovation. It must be noted that real-time data processing focuses on the timely processing and analysis of data as it is generated, enabling organizations to make immediate decisions or take prompt actions. Intelligent automation, on the other hand, leverages AI and automation technologies to automate tasks and processes, reducing human effort and improving efficiency. Together, they can enhance operational agility, optimize decision-making, and drive intelligent actions based on real-time data. On the other hand, this closer networking of the digital world of machines creates the potential for profound changes in global industry and many areas of private and social life. Based on all this, it is necessary to present tomorrow's trends in everything related to IIoT technology applications [13]. 1. Growth of IIoT applications [14]. Manufacturing automation continues to grow, with the number of companies choosing to automate and implement the IIoT soaring to new levels due to the impact of the COVID-19 pandemic. Machine learning and robotics are two applications that increase automation. Machine learning increasingly automates manufacturing processes, so less human intervention is required, while the increasing number of human jobs being taken over by robotics results in fewer people in the workplace. Organizations need to ensure that proper security protocols are in place to safeguard data privacy and prevent unauthorized access. 2. The wireless revolution. Only some IIoT applications have access to local sockets [15]. \"Local socket\" refers to a communication endpoint or interface that allows processes running on the same device or within the same local network to communicate with each other. Local sockets in IIoT architectures can provide privacy in industrial environments by enabling secure and private communication between processes and applications running on the same device or within the same local network. By utilizing local sockets, data can be exchanged and coordinated within the confines of the device or local network, reducing the risk of unauthorized access or interception from external sources.