This research develops and tests an innovative tool called ASLA (Automated Signal Light Brightness Adjustment) designed to automatically adjust the brightness of train signal lights based on environmental conditions such as light intensity, rain, and fog. The main purpose of this tool is to reduce the waste of electrical energy caused by using lights with constant brightness intensity all the time. An experimental method is used in this research, where tests are conducted by measuring important variables such as light intensity, current, voltage, and LED brightness. It uses sensor fusion techniques to combine data from various sensors, such as LDRs, rain sensors, and gas sensors, to obtain accurate environmental information. The test results showed that the ASLA tool successfully reduced power consumption from 2.37W to 2.24W, contributing to electricity savings. In addition, the variation of LED power decreased to less than 0.2W under certain weather conditions. This research proves that ASLA functions optimally by increasing the efficiency of electrical energy use in train signal lights.
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