Rcup at PSA = IOT + AI for an augmented worker

Описание: In this PoC, data was gathered using smart insoles and motion sensors attached
to an operator in a live manufacturing setting. The results were quite surprising : data
scientists were able to apply machine learning algorithms to identify patterns in the datasets as co-
related to the sub activities which were performed by the operator. After data scrubbing and model
tuning, the accuracy of the results were much higher than anticipated by the team.
Processed in real time, Rcup solution could be deployed in a number of higher order use cases -
1. Health and safety
2. Operations - what if the Digital Self of the operator could be integrated with the rest of the
production line. This may enable the rest of the assembly line to move perfectly in sync with
the worker, leading to increased output for the line as a whole.
3. Quality - Co-relations can be determined between bad quality outputs and certain
movements made by the respective operators - this can lead to better and personalized
coaching to help preventing errors in tasks.