TY - GEN
T1 - Real-Time Monitoring System for Detecting Abnormal Operation Procedures
AU - Li, Tso Ting
AU - Hsu, Chen Chien
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this paper, we propose a task monitoring system that exemplifies man-machine collaboration in a small workshop to make real-time judgments and monitor whether the operator's operation procedures comply with the pre-defined rules. The proposed system comprises an image target detection module, a hand action recognition module, and a procedure comparison module, where YOLOv4 is used to detect relevant objects in the scene, and SlowFast is used to recognize hand actions so as to create an action base to describe the corresponding relationship between the object and action. A Standard Operating Procedures (SOP) with pre-established rules is then used to compare against the action base established by the proposed system to check if the operation procedure flow of the human operator complies with the rules.
AB - In this paper, we propose a task monitoring system that exemplifies man-machine collaboration in a small workshop to make real-time judgments and monitor whether the operator's operation procedures comply with the pre-defined rules. The proposed system comprises an image target detection module, a hand action recognition module, and a procedure comparison module, where YOLOv4 is used to detect relevant objects in the scene, and SlowFast is used to recognize hand actions so as to create an action base to describe the corresponding relationship between the object and action. A Standard Operating Procedures (SOP) with pre-established rules is then used to compare against the action base established by the proposed system to check if the operation procedure flow of the human operator complies with the rules.
KW - Abnormal operation
KW - Action recognition
KW - Deep learning
KW - Object detection
KW - Smart surveillance
KW - Standard Operating Procedures.
UR - http://www.scopus.com/inward/record.url?scp=85147253711&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85147253711&partnerID=8YFLogxK
U2 - 10.1109/GCCE56475.2022.10014134
DO - 10.1109/GCCE56475.2022.10014134
M3 - Conference contribution
AN - SCOPUS:85147253711
T3 - GCCE 2022 - 2022 IEEE 11th Global Conference on Consumer Electronics
SP - 924
EP - 925
BT - GCCE 2022 - 2022 IEEE 11th Global Conference on Consumer Electronics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE Global Conference on Consumer Electronics, GCCE 2022
Y2 - 18 October 2022 through 21 October 2022
ER -