Recently, with the development of artificial intelligence, visual recognition, and edge intelligent computing, intelligent patrol or online monitoring technology based on visual recognition has found important applications in conventional campus security, laboratory safety monitoring, and industrial production operation and maintenance monitoring. Campus security and laboratory safety monitoring aim to protect the personal safety of students and teachers and avoid incidents such as campus bullying or laboratory safety accidents. Industrial production operation and maintenance monitoring is the identification and early warning of hidden dangers and defects in equipment or operational behaviors in industrial scenarios to avoid huge losses caused by faults and hazards. In security and production operation monitoring tasks, using manual methods for real-time detection can be labor-intensive and inefficient, and human negligence that leads to undetected dangers could occur. Therefore, based on the needs of campus security and safety or industrial production operation and maintenance monitoring, this study designs and implements an intelligent patrol system based on microservices and the operation and maintenance monitoring of industrial substations. The system does not require excessive manual participation and can automatically conduct patrols, identify dangers, and provide early warnings. Subsequently, the system adopts an advanced scheduling system that takes only 3–5 min to perform one patrol, considerably improving the efficiency of hazard detection during patrols. The system can be applied to intelligent patrols of campus and industrial substations, security, and safety.