Industrial Internet of Things (IIoT). Группа авторов
which is a valued characteristic, given the major obstacle related to addressing individual employee characteristics, or dynamic problems of human behavior. Through AI, it is possible to use determining complex patterns to help organizations move more quickly and respond better to the changing needs of each employee [26].
Or even, through AI, industrial systems integrate robotics powered by AI, 3D printing technologies, and human supervision, building interactive robot systems leading by AI technologies. This process not only decreases costs and increases efficiency but also generates much safer industrial environments for human workers. The dangerous elements of industrial activities are surpassed by machines [27, 28].
In simpler terms, AI technologies consist of intelligent systems or intelligent machines that mimic human intelligence to operate tasks and can improve iteratively supported on the information it collects. AI technologies manifest itself in various ways in modern contemporary society as chatbots to understand customer issues more quickly and provide more efficient responses or smart assistants to analyze critical data and information from large sets of free-text data to improve programming, or even at home, through recommendation mechanisms providing intuitive recommendations for TV programs supported on users’ viewing habits. However, AI technologies are not deliberate to replace human beings but aims to substantially improve human skills and actions, tasks, and even contributions [17, 23, 24].
AI is related to application areas that involve expert systems or systems based on knowledge, natural language comprehension/translation, intelligent systems/learning, speech comprehension/generation, automatic programming, or even image and scene analysis in real time, among many others. Therefore, it can be evaluated that the technological AI field aims to emulate human beings’ capabilities including problem-solving, understanding natural language, computer vision, and robotics, considering systems for knowledge acquisition, and even knowledge representation methodologies [15].
To obtain the full value of AI, Data Science is necessary (Figure 1.3), consisting of a multidisciplinary field that employs scientific methods to collect and extract value from data, combining skills such as statistics, probabilities, frequency of occurrence of events, observational studies, and computer science, with business knowledge to analyze data gathered from distinct sources [29, 30].
The central principle of AI technologies is to replicate, and then exceed, the processes and conduct humans perceive, notice, see, and react to the world, fueled by several forms of Machine Learning techniques that recognize patterns in data to allow prognosis and predictions. Propitiate a better comprehensive understanding of the wealth of available data, information, and predictions to automate overly complex or ordinary tasks, improving productivity and performance, automating tasks or processes that previously demand human energy, and also making sense of the data on a superhuman scale [31].
Data science makes it a priority to add technological value to business intelligence and advanced analysis as the main technology differential for companies, through the use of demographic and transactional data to foresee and predict how much certain customers and users will spend over their business relationship with a company (or even the customer’s lifetime value), price optimization supported on preferences and customer behavior, or even utilizing image recognition techniques to analyze X-ray digital images searching for signs of cancer [30].
Figure 1.3 AI and data science illustration.
Three elements are leading the development of AI technologies across all sectors, which are the computational high-performance, affordable, and even processing capacity available, assessing the abundance of computing power in the cloud technologies allowing easy access to affordable and high-performance computing power. Large volumes of data available for conduct training, given that AI, require to be trained on a lot of data available to generate the correct predictions, also relating the emergence of distinct tools for labeling data, in addition to the ease and accessibility of storing and processing structured and unstructured data, to train AI algorithms [31].
The benefits of operationalizing AI are related to the cognitive interactions of machine learning techniques with conventional business applications, methods, and processes that can greatly increase productivity and user experience, or even considering AI as a strategic method and competitive advantage related to greater efficiency in processes, doing more in less time, and increasing customer loyalty, creating customized and attractive customer (user) experiences, and predicting commercial results to generate greater profitability [23, 24, 32].
AI applications in people’s daily lives are based on an app that recognizes the content of images and allows a search by typing the name of an object or action, or streaming platforms transcribing audio and generating subtitles for videos, or in an email offering automatic responses smart; or even with regard to online translators who translate texts from signs, labels, and menus with the cell phone camera; or even pondering about streaming platforms that use AI to understand users’ preferences and recommend music and movies, respectively, still relating autonomous cars that drive alone, or even in medicine, advancing cancer studies [26].
The application of AI is present in various segments of the economy; in industry, automation is a keynote for machines that keep getting smarter. With AI, the equipment manufactures and checks the products without having to be operated by a human, that is, it performs repetitive work and has no limitations for their use. Through the GPS (Global Positioning System), the routes suggested by online applications, generally, point out the best path, considering that the AI interprets data provided automatically by other users about the traffic on the roads. Online retailers, using online store algorithms, recognize user purchasing patterns to present offers according to their preferences. Financial institutions use AI algorithms to analyze market data, manage finances, and relate to their customers [33].
Thus, the first industrial revolutions created equipment that replaced manual labor, carrying out the work of many men with greater efficiency and less cost. Currently, in several cases, through the AI employee in tasks, they have been previously seen as “intellectuals”. In any case, the important thing is that AI theater is a reality. In this regard, the understanding of its mechanisms and the understanding of the possibilities that this provides must be expanded. The concept of AI refers to the creation of machines, not necessarily with physical bodies (software that can abstract, create, deduce, and learn ideas), with the ability to think and act like human beings and aim to facilitate everyday tasks [7, 34].
1.2.2 IoT Concept
IoT in the early days corresponded to the connection via the internet in physical objects, such as a toaster, especially sensors. Over the years, the concept of connecting the physical material world with the virtual world has evolved into a technological revolution in order to connect all the objects that people use on a daily basis to the internet (Figure 1.4), describing a scenario in which several things are connected and communicate, through technologies like Wi-Fi. The result is a smarter and more responsive planet [35, 36].
Figure 1.4 Internet of Things.
Thus, IoT currently matches a series of hardware that works connected to the internet, from a smart TV to a running watch that measures heart rate and sends this data to an application. However, it is possible to interpret what part of these devices uses, even on a small scale, AI. This technological innovation connects everyday items (smart devices), or smart sensors, to the internet, making the physical