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This book chapter presents the main aspects concerning the sensor data fusion in the context of the Industrial Internet of Things Systems (IIoTS) for Industry 4.0. The industrial development based on advanced technologies such as rapid prototyping based on 3D printing (automotive, avionics, and electronics) or robotics acts as a critical enabler for rapid production with zero waste and generates new opportunities to use advanced manufacturing devices-based sensors and actuators in order to control all processes and to replace hard human work by machines. Starting from layered modular architecture of the IIoTS composed by user interface layer, software level, communication protocols, and hardware layer (cyber-physical systems, machines, sensors), we will analyze in this book chapter several aspects concerning data fusion and the possibility to use supervised and unsupervised learning algorithms in order to enable fast data analysis and classification and generate a fast response. Moreover, the Industrial Internet of Things System (IIoTS) should be designed in order to avoid security risks and to have failure tolerance. In addition, we will analyze the type of data generated in the context of Industry 4.0 and the possibilities to handle data based on methods. |
