Industrial Internet of Things (IIoT). Группа авторов

and intelligent use of devices to control various activities, from monitoring with cameras and sensors to managing spaces and of productive processes. The IoT ecosystem is a system composed of a digital space of interaction including digital tools related to data analysis and modeling, as well as digital elements that integrate and interact within it. It is through these interactions and the exchange of information that AI allows these elements to work in an integrated manner, composing an intelligence potential far superior to what each of its elements has separately. The IoT ecosystem involves different agents and processes, such as smart objects [sensors, appliances, cars (Figure 1.9), and factory automation equipment], smart modules (processors and memories), connectivity services (access to the internet or private networks that connect these devices), integrators (systems that combine applications, processes, and devices), enablers (control systems, collection, and processing of data and commands involving objects), and even providers of IoT services [45, 46].

Figure 1.9 Maintenance IoT vehicle illustration.

      Within an IoT ecosystem, applications that integrate IoT technologies with Big Data technologies are operated, enabling the collection and analysis in real time of large data sets, allowing the development of predictive models for a variety of situations, from consumer behavior to the prevention of factory failures, and optimizing activities on the most varied fronts of activity. IoT technology brings changes both in the development of more pervasive connectivity and in the increase of data processing, derived from the refinement of sensors that allow data collection in different environments. All of this is associated with some practical solution allowing for increased efficiency, reduced human intervention, or even new business models [45], still evaluating that the AI generates a layer to enhance the value generated by the analysis of the different information captured and combined; allowing the automation of the decision-making process and actions in specific situations; bringing significant benefits to the increase in the speed of processes, reduction of the error rate due to human interference, and reduction of costs per transaction, in addition to the possibility of greater absorption of insights at each interaction that feedback and “teach” the AI algorithms (Machine Learning as an example); and making this incrementally more efficient [31].

      In the digital transformation of the industry (relating the advent of the Fourth Industrial revolution), AI associates IoT with the combination of the ecosystem for data transmission between devices and the technology for analyzing this information independently, still conceptualizing the emergence of Artificial Intelligence of Things (AIoT). Considering that the IoT concept is related to the various IoT devices that collect data and create a network for transmitting critical information to administrators, on the other hand, AIoT data is processed by resources that analyze the standards providing only the information necessary for making a decision and can even make the necessary decisions without human involvement [17].

      Pondering on AI, this uses algorithms to analyze data and resources through aspects such as Machine Learning by automating processes without manual intervention, incorporating with IoT gaining connectivity and capacity for data exchange. The great advantage of the IoT concept is in the various solutions involving machine-to-machine communication, integrated into a single network, where it publish and consume information. Thus, it is through the integration of IoT, with the analysis of broad data sets (Big Data Analytics), and with the performance in ecosystems using AIoT that it is possible to exceed the limits that each of these technologies has individually, developing an advanced solution to support operational management, offering predictive maintenance, and consequently increasing control, quality, and efficiency in business operations [35].

      1.3.1 Industry 4.0 Concept

      Industry 4.0 is considered as Fourth Industrial, also characterized by the introduction of information technology in the industry, representing the total transformation of the entire ambit of industrial production through the unity of digital technology and the internet (connection) with conventional industry, deriving from IoT as a connected network, which alone has immense amounts of connections between industrial cells [1].

      IoT in Industry 4.0 is basically responsible for the integration of all devices inside and outside the industrial plant, relating the digital transformation and the function of the IIoT, together with developments in mechanics, engineering, and manufacturing [2].

      Consider that the IoT is a network of physical objects, platforms, systems, and applications with incorporated technology to communicate, feel, or interact digitally with internal and external environments. The IoT on the shop floor is related to an environment where all equipment and machines are connected in networks and providing information in a unique way; therefore, different industrial cells have different purposes, having different functions and applicabilities, but they are united under the same network. Thus, IIoT is a subcategory of IoT, which also comprises user-oriented applications, such as usable devices, machine devices, and infrastructure with integrated sensors that transmit data (collected information) via the internet and which are managed by software, technology for smart homes, and even cars autonomous [3].

      However, this industrial revolution is not yet a reality, even so, it is being motivated by three major changes in the productive industrial world related to the exponential advance of the capacity of computers, the immense amount of digitized information, and also new innovation strategies in relation to research and technology [4].

      The connections generated by IoT in the industry generate opportunities create a large circle of added value to products and services as integrated monitoring, generating data that communicate in real time through what can be considered a large unified database or even scheduled maintenance stop on the production line before this is intensified. From this generated database, automatic decisions are made through online communication between interconnected devices correlated to event monitoring. Based on the decisions taken through the global view, the production process becomes more efficient, reducing negative impacts and maximizing the value chain of a given industrial sector [5].

The benefits of IoT in Industry 4.0 for industrial plants can be understood in the following aspects related to operational efficiency and maximizing profits by introducing more flexible automation, connectivity, and production techniques. In addition, scalability, time, and cost savings help to maximize profits for industrial organizations. Pondering about the aspects that increase the operational efficiency of a plant is reducing production stops, reducing the cost of the asset cycle, improving the use of the asset, and even improving the production [46].

      Even listing the benefits of new services and business models given that IoT in Industry 4.0 allows the creation of new sources of revenue by creating new connected services. Hybrid business models allow both digital products and services to be used. In an applicable context, a vehicle manufacturer can take advantage of the raw data obtained to provide car condition service in real time as a source for preventive maintenance. This use of digital services also improves the relationship with the customer, since it allows different points of contact that generate valuable information for the customer, creating a relationship of trust and loyalty [47].

      Even the benefits related to greater knowledge for decision-making arising from the analysis of industrial data, allowing and facilitating the making of better decisions due to a more accurate view of the industry’s performance. To top it off, IIoT’s network of smart devices allows industrial organizations to connect all of their employees, data, and processes from the shop floor to executives and managers, further assisting the productivity of department leaders and decision-making [48].

      It is important to emphasize that more than facilitating decision making, Industry 4.0 aims to promote that these decisions are made automatically by intelligent techniques, toward an autonomous reaction of the machines. From the point of view of systems