A Cloud-based Architecture for the Internet of Things targeting Industrial Devices Remote Monitoring and Control

The process of acquiring, analysing and managing data obtained by sensors and actuators in industrial environments can benefit from modern Cloud-based platforms towards a complete implementation of the Industrie 4.0 concept. The analysis of huge data sets produced by these sensors (Big Data) could allow quick and accurate decision making. For example, productivity improvements can be achieved by analysing device performance and degradation for real-time feedback on configuration and optimization. This work proposes a Cloud-based architecture for Internet of Things (IoT) applications to improve the deployment of smart industrial systems based on remote monitoring and control. By using specific technologies available as a service, we demonstrate the proposed architecture on an automated electric induction motor use case. This approach includes layers for sensor network data gathering, data transformation between standard protocols, message queuing, real-time data analysis, reporting for further analysis, and real-time control. Particularly, by using the proposed architecture, we remotely monitored, controlled and processed data produced by sensors and actuators coupled to the motor. Preliminary results indicate this foundation can support predictive methods and management of automated systems in the Industrie 4.0 context.