Project Overview
As one of Cambodia’s key energy facilities, the Sihanoukville Power Plant has been actively enhancing its safety management and operational efficiency in recent years. To meet modern safety standards, the plant deployed an innovative Intelligent Patrol & Early Warning System, powered by advanced AI algorithms that significantly elevate safety performance across multiple dimensions.
Key Features
Safety Helmet Detection
High-definition cameras are installed across critical operational zones. The AI system continuously monitors whether staff members are wearing safety helmets. When a violation occurs, alerts are triggered instantly, prompting immediate correction. This feature strengthens safety awareness and greatly reduces the risk of head injuries.
Fire & Smoke Detection
Fire prevention is crucial in power plant operations. The system analyzes live video feeds to detect abnormal smoke or flames with high accuracy. Upon identifying early signs of fire, the platform automatically issues alerts to the fire response team and plant management, dramatically shortening response times and preventing major incidents.
Smoking Detection
Smoking is strictly prohibited within the plant. The AI algorithm can identify smoking behavior in restricted areas and immediately trigger alarms. This reduces fire hazards and helps maintain a healthier working environment.
Intrusion Detection
To protect restricted zones, the system includes intelligent intrusion detection. It identifies unauthorized individuals entering prohibited areas and alerts security teams in real time. The system has successfully intercepted multiple potential security threats, including unauthorized access and possible sabotage attempts.
Mobile Phone Usage Detection
Given the high-risk nature of the work environment, maintaining focus is essential. The system monitors unsafe mobile phone usage within operational areas and warns distracted workers, reducing accidents caused by lack of attention.
Project Impact
Since deployment, the intelligent patrol system has significantly strengthened safety management at the plant. Incidents caused by failure to wear helmets or smoking in restricted zones have greatly decreased.
The fire response time has dropped from several minutes to just a few seconds, substantially improving emergency handling efficiency.
Future Development
The Sihanoukville power plant plans to expand the system’s coverage and continue optimizing AI algorithms to make them more intelligent and adaptive. With the integration of machine learning and big-data analytics, the system will continuously improve its ability to identify new safety risks, helping prevent accidents and further enhance operational efficiency.
Conclusion
The Intelligent Patrol & Early Warning System at the Sihanoukville Power Plant demonstrates how AI can transform industrial safety management. This project not only elevates safety standards and operational performance at the plant but also serves as a successful model for other industrial facilities worldwide.
With ongoing technological innovation, such systems are expected to be adopted more widely, delivering both higher safety and greater efficiency across global industrial operations.