Development of Drone-Assisted Coastal Litter Detection with AI and 5G Technology
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Abstract
This paper utilizes artificial intelligence and 5G technology to enhance the potential of drones for coastal letter detection. The research methodology is to design a mathematical model for training the computer to learn images of coastal letters such as foam boxes, plastics, bottles, and cans. By using the feature image datasets of about 2,400 pictures and providing a recurrent neural network (RNN) algorithm for a machine- learning model. We have designed wireless real-time video transmission via a 5G signal network between the drone and the display device to ensure good video quality. The results showed that it was able to detect plastic with the highest accuracy of 98.65%, 96.36% of cans, 94.21% of foam boxes, and 93.23% of bottles, respectively.
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