## 1 Introduction
### IoT in Cast Manufacturing  
Using Internet of Things (IoT) technologies in cast component manufacturing improves the manufacturing process by integrating data-driven decision-making. The High-Pressure Die Casting (HPDC) process, a method used for producing automotive components, is enhanced through real-time monitoring of data acquired via IoT infrastructure. The porosity and shear bands are the identified defects in the process. To prevent this event, IoT sensors are integrated into the infrastructure. Sensors that monitor parameters like temperature and pressure during casting are employed [9]. The collected data from these sensors are analyzed to detect issues in the production cycle [10]. Integrating intelligent sensors directly into cast components during manufacturing provides information about the structural integrity of the parts. For example, thick film sensors can be incorporated into components to monitor stress and deformation in real-time, allowing manufacturers to detect potential failures before they occur [11]. This approach extends the service life of the components. Industry 4.0 infrastructure continuously monitors the process. The appearance of an event is predicted and repaired at the right time [12]. Combining IoT technologies with advanced casting techniques, such as squeeze casting, further improves the mechanical properties of the components. Combining the technologies makes them suitable for the automotive applications sector [13]. In the paper by [PERSON] [14], it is estimated that, in 2025, the Industrial Internet of Things (IIoT) will contribute trillions of dollars to the global economy. As a consequence, it will increase efficiency and reduce operational costs. By leveraging IoT, manufacturers can optimize their supply chains, improve inventory management, and increase overall operational efficiency [15]. For example, IoT devices facilitate predictive maintenance by analyzing data collected from machines to forecast failures. In this way, it reduces the downtime and maintenance costs [10; 15]. In addition, using blockchain technology in combination with IoT increases process security. Another improved factor by employing the blockchain is traceability in the manufacturing process through issues related to data integrity and supply chain vulnerabilities [16]. Integrating IoT into manufacturing processes in various configurations requires ensuring hardware and software compatibility through the employed infrastructure solution. This transformation is a key factor of Industry 4.0. It underlines the necessity of interconnected \"intelligent\" objects to facilitate data exchange. Operational coordination among different production sites is another element of Industry 4.0 presented in the paper by [PERSON] and [PERSON] (2020) [17]. The evolution of IoT infrastructure is characterized by transitioning from traditional Internet frameworks to more advanced architectures. The new proposed solution supports real-time data exchange. This facilitates the use of data-driven decision-making processes [18]. In the context of production, IoT systems are usually structured into multi-layer architectures, which include, among others, the Application, Network, and Perception layers. These modules manage the functions of IoT devices (such as sensors and actuators) that monitor and control production processes [18]. Their high level of complexity calls for specialized communication protocols designed to handle the substantial data flows generated by interconnected devices. Examples of such protocols include MQTT (Message Queuing Telemetry Transport) and CoAP (Constrained Application Protocol) [19; 20]. Security and confidentiality remain major challenges in implementing IoT in manufacturing under Industry 5.0. IIoT is exposed to cyber threats due to the extensive data exchange and the critical importance of the infrastructures involved [21].