VISION ALGORITHM DEVELOPMENT ARTIFICIAL TO DETECT THE DROWSINESS IN DRIVERS HEAVY MACHINERY MINERS (#1048)
Read ArticleDate of Conference
July 19-21, 2023
Published In
"Leadership in Education and Innovation in Engineering in the Framework of Global Transformations: Integration and Alliances for Integral Development"
Location of Conference
Buenos Aires
Authors
Figueroa Herrera, Brenda Mariana
Sánchez Burgos, Flavio Cesar
León León, Ryan Abraham
Abstract
The main objective of this research is to develop an artificial vision algorithm that detects the drowsiness of heavy machinery mining drivers, using an artificial vision architecture with Python software, importing face detection libraries such as shape_predictor_68_face_landmarks with which it will be detected and They will identify each important point. In the input stage, the face will be detected with a camera placed in a strategic point of the vehicle and/or machine. Then the software detects and measures the required points. A threshold <0.22 was used at a time of 60 fps (1sec) to determine if the individual is blinking continuously or due to fatigue, if this is the case an alert message will be sent. In the tests carried out we obtained average positive results of 96.48%.