A multi-sensor algorithm for activity and workflow recognition in an industrial setting
Christian Thomay, Benedikt Gollan, Michael Haslgrübler, Alois Ferscha, Josef Heftberger · 2019
In the recent revival of human labour in industry, and the subsequent push to optimally combine the strengths of man and machine in industrial processes, there is an increased need for methods allowing machines to understand and interpret the actions of their users. An important aspect of this is the understanding and evaluation of the progress of the workflows that are to be executed. Methods for this require both an appropriate choice of sensors, as well as algorithms capable of quickly and efficiently evaluating activity and workflow progress.