The study highlights that IoT and industrial automation encounter various issues, including data and service security, trust, data integrity, information privacy, scalability, interoperability, and automation domain constraints. The study combines the concepts of the raspberry pi industrial Workstation and industrial automation with IoT
In the industrial space, industrial automation plays a critical role in reducing time to market while maintaining good quality and productivity. This research describes the utilization of cloud and IoT capabilities to control devices and analyse the data generated by them
The paper proposes the integration of the internet of things (IoT) for the transformation of smart factories. The research highlights the connectivity of IoT and the distributed nature of intelligent devices. These devices, each exhibiting autonomous or semiautonomous behavior, enable higher production and better utilization of human resources by eliminating significant information gaps about real-time factory conditions. Coupled with innovative techniques like additive manufacturing, this approach facilitates the realization of an optimized advanced manufacturing floor and the vision of a lean, agile, and integrated factory of the future
The paper underlined that IoT is a crucial technology of the Fourth industrial revolution and offers a potential opportunity to establish influential services and applications for manufacturing. IoT enables smart machines to communicate with one another in order to share data and information, which is required for complex systems to make real-time choices. IoT has a favourable influence on sustainable development, particularly in terms of manufacturing dimensions
By analysing industrial IoT technology and its implementation in manufacturing workshops, this study proposes a reference design and building route for smart factories. A manufacturing workshop industrial IoT solution is provided, incorporating important technologies such as WSN and RFID. The system proves effective in monitoring production line data, as evidenced by the performance analysis in terms of real-time and quality
