Wearable productivity measurement IoT system development

Department of Industrial Engineering, University of Stellenbosch University, Country South Africa, e-mail address andrevdm@sun.ac.za

Abstract

This project develops a system that captures and stores acceleration and rotation data from an operator’s hand and tests said data’s compatibility with a machine-learning algorithm. Tracking the productivity of operations is a goal a follow-up project aims to achieve, and this system is a necessary part of a possible solution. An IoT system was developed and tested by presenting the data to a machine learning algorithm to ensure that an algorithm can identify certain movements from the data. The results are valid since the system itself was tested in a case study with 24 participants and performed as expected. the data that the system provides as output was presented to two machine learning algorithms and both were able to identify movements with more than 80% accuracy.