Implementation Intelligent Monitoring System based on Electricity Consumption for Telkom University Classroom
Abstract
In the use of electronic facilities are often used unintentionally, when the user leaves the room the lights, TV, and AC are still on. This can result in inefficient use of electrical energy, increased costs, to damage to electrical components or electrical short circuits. This study explains the implementation of the Intelligent Monitoring System (IMS) in the classroom of the Telkom University Landmark Tower (TULT) building. IMS is used to monitor and control classroom conditions remotely, the tool used to monitor the classroom is CCTV, while the control tool uses an IoT device, and uses a website to find out classroom conditions remotely. In this context, the author uses one of the branches of deep learning science with the YOLOv8 method and a confidence level value of 0.1 to detect the presence of humans in the classroom. The results of this test show that the use of the YOLOv8 method and a confidence level value of 0.1 in detecting humans in the classroom obtained an accuracy level of 100%, sensitivity of 100%, and specificity of 100%. So the YOLOv8 method and the confidence level value of 0.1 are used in this study.
Keywords — electronic facilities, IMS, classrooms, websites.
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