Practical Application of Artificial Intelligence Technology in Safety Management of Instrument/Electrical Laboratories in Universities

Abstract

The safety management of instrument and electrical laboratories in universities is very important. This paper focuses on the application of artificial intelligence (AI) technology in this field. Firstly, the related theories and technical foundations are expounded, covering machine learning, deep learning and sensor technology, which constitute the cornerstone of application. Then, a variety of application strategies are put forward, such as monitoring equipment and personnel by image recognition, monitoring environment and equipment status by sensors, implementing predictive maintenance by means of data analysis, and building an intelligent early warning and emergency response system to improve the efficiency of safety management in multiple dimensions. Futhermore, the challenges faced by the application are analyzed, including data quality and algorithm efficiency at the technical level, data security and privacy risks, and personnel and management problems. In view of the challenges, this paper gives corresponding solutions, including establishing data quality monitoring, optimizing algorithms, strengthening data encryption and access control, carrying out personnel training and combing management processes. The research shows that the rational use of AI technology and effective response to challenges can build a more intelligent, efficient and safe safety management system for instrument and electrical laboratories in universities, and provide a strong guarantee for the safe operation of laboratories in universities.