SISTEM BANTUAN KEMUDI KENDARAAN ALAT BERAT JARAK JAUH
DOI:
https://doi.org/10.32722/pt.v21i2.4066Abstract
Heavy equipment vehicles for transporting goods such as forklifts are often used to assist human activities. These electric-based devices use batteries as their energy storage. Technological developments, especially in the field of control and the effects of the COVID-19 pandemic, make it possible for this tool to be driven remotely. However, remote control sometimes makes it difficult for operators to respond quickly to driving. The data shows that the use of heavy equipment causes many accidents in the work environment, mainly due to human factors, especially fatigue. To overcome this, several systems were added to help reduce work accidents. One of the tools that can help the driver is a braking system with Advanced Driver Assistance Systems (ADAS). This system aims to assist the braking system, especially when the driver is negligent. Utilization of a stereo camera to recognize objects in front of the vehicle so that it can brake automatically. The economical stereo camera using the Kinect is designed for its application to indoor moving applications. Recognition and classification of objects using the Artificial Neural Network Detection method with this tool will make the system give a braking signal to the vehicle automatically. The test results show that braking can process data at a speed of less than 350 milliseconds with an average accuracy of above 90%.
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