Open AccessSafety Supervision Method of Power Work Site Based on Computer Machine Learning and Image Recognition
Author(s) -
Jiaxuan Li,
Yiyang Liu,
Hao Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2074/1/012021
Subject(s) - electric power industry , electric power , power (physics) , work (physics) , electric power system , computer science , field (mathematics) , engineering management , sustainable development , service (business) , knowledge management , risk analysis (engineering) , manufacturing engineering , engineering , business , electrical engineering , electricity , marketing , mechanical engineering , physics , mathematics , quantum mechanics , political science , law , pure mathematics
China’s traditional power system has been unable to meet the needs of society and the development of The Times. Under the background of intelligence, it is necessary to reform the power industry and increase the application of mobile application technology in the power system, so as to realize the precise management of the power system. The application of mobile application technology in the field operation of electric power construction, based on computer machine learning and image recognition, is helpful to realize the sustainable development of electric power enterprises, improve the service level of electric power enterprises and promote the on-site safety supervision.