Wearable productivity measurement IoT system development
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...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
|
| Series: | MATEC Web of Conferences |
| Online Access: | https://www.matec-conferences.org/articles/matecconf/pdf/2024/18/matecconf_rapdasa2024_08003.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846125704971812864 |
|---|---|
| author | Heppell Reevan van der Merwe André |
| author_facet | Heppell Reevan van der Merwe André |
| author_sort | Heppell Reevan |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-a05a01d9f3bc4fb9bbf5441af0c42b57 |
| institution | Kabale University |
| issn | 2261-236X |
| language | English |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj-art-a05a01d9f3bc4fb9bbf5441af0c42b572024-12-13T10:05:34ZengEDP SciencesMATEC Web of Conferences2261-236X2024-01-014060800310.1051/matecconf/202440608003matecconf_rapdasa2024_08003Wearable productivity measurement IoT system developmentHeppell Reevan0van der Merwe André1Department of Industrial Engineering, University of Stellenbosch UniversityDepartment of Industrial Engineering, University of Stellenbosch UniversityThis 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.https://www.matec-conferences.org/articles/matecconf/pdf/2024/18/matecconf_rapdasa2024_08003.pdf |
| spellingShingle | Heppell Reevan van der Merwe André Wearable productivity measurement IoT system development MATEC Web of Conferences |
| title | Wearable productivity measurement IoT system development |
| title_full | Wearable productivity measurement IoT system development |
| title_fullStr | Wearable productivity measurement IoT system development |
| title_full_unstemmed | Wearable productivity measurement IoT system development |
| title_short | Wearable productivity measurement IoT system development |
| title_sort | wearable productivity measurement iot system development |
| url | https://www.matec-conferences.org/articles/matecconf/pdf/2024/18/matecconf_rapdasa2024_08003.pdf |
| work_keys_str_mv | AT heppellreevan wearableproductivitymeasurementiotsystemdevelopment AT vandermerweandre wearableproductivitymeasurementiotsystemdevelopment |