## 7 Conclusions and Future Developments  
In the last few years, the IoT paradigm has undoubtedly influenced many fields, such as industry, agriculture, biomedicine, warehousing, construction, etc. These are just some sectors in which the IoT has significantly contributed, improving manufacturing efficiency, scheduling maintenance interventions, and safeguarding workers' health and cybersecurity. In the framework of Industry 4.0, the IoT has also enabled a more detailed and widespread control process by providing new control architectures that will allow real-time process \begin{table}
\begin{tabular}{c c c} \hline \hline
**Reference** & **Topic** & **Technological** \\ \hline [PERSON] et al. [19] & Implementation of IIoT LPWAN technologies & AM approach has high application potential in the field of smart manufacturing and is not only for the creation of intelligent objects \\ [PERSON]. [PERSON] et al. [19] & within additive manufacturing products for information collection during production and at the point of installation & AM approach has high application potential in the field of smart manufacturing and is not only for the creation of intelligent objects \\ \hline [PERSON] et al. [130] & Realization of a big data-based framework (BD-SSAM) as a decision-making tool for companies in the AM field & New framework SSAM for the product manufacturing cycle that aims to control energy consumption and quality \\ \hline [PERSON] et al. [132] & Complete monitoring of data collection to optimize the production process through AM, minimize costs, and improve product quality & A new concept of an integrated and modular intelligent production system, with full system monitoring, consumption data analysis, safer working environment, and scalable and flexible modular configuration \\ \hline [PERSON] et al. [133] & Improving the quality of realization using DT models enhanced with ML tools & The application of DT in AM is mature but still in the development phase; it is not yet standardized and requires significant investments in terms of resources and technical skills, but it allows significant improvements in production quality control with considerable adaptability \\ \hline [PERSON]. [PERSON] et al. [134] & Use of DT as a tool to optimize and improve the manufacturing phases of biomedical scaffolds & DT in the biomedical field to produce scaffolds is a technology of considerable importance as it allows the creation of increasingly ergonomic prostheses, allowing for a more optimized design \\ \hline [PERSON] et al. [135] & Decentralized monitoring of the AM process using DT & DT is a great tool for decentralizing additive manufacturing because it allows for production simulations, optimization of the manufacturing process, and real-time monitoring \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Summary of the topics covered by the references analyzed. monitoring so that no drifts could induce a reduction in product quality. It is worth noting that a fundamental aspect of IoT smart manufacturing applications is the massive presence of sensing devices directly installed in the plant to gather data, and the development of ML algorithms to process the data and detect anomalies and risk conditions. Moreover, the application of IoT strategies requires a significant flow of data, which very often contains sensitive information. For this reason, cybersecurity architectures are essential to prevent possible cyber-attacks and data theft. This paper has provided a targeted vision of the IoT paradigm in the main fields of smart manufacturing. After an accurate selection of the scientific literature based on PRISMA method, this paper has presented an overview of IoT applications in manufacturing process control, predictive maintenance, data protection, worker safety, and additive manufacturing.