Issue |
E3S Web Conf.
Volume 328, 2021
International Conference on Science and Technology (ICST 2021)
|
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Article Number | 02003 | |
Number of page(s) | 5 | |
Section | Electrical, Intrumentation and control, Dynamic Electricity | |
DOI | https://doi.org/10.1051/e3sconf/202132802003 | |
Published online | 06 December 2021 |
Waste Collector Roboboat Using Neural Network Method Based on Tensorflow Framework
Department of Electrical Engineering, University of Trunojoyo Madura, 69162, Indonesia
Today, the waste problem has become more serious, because the waste can cause environmental pollution and bad smell pollution. The less awareness of cleanliness is the main factor, especially the less awareness of throwing waste at the right place. Based on the data of the Ministry of Environment and Forestry “Environmental Ignorance Behavior” in 2008 said that around 72 percent of Indonesian less be aware of the waste problem generally with plastic waste, this waste will flow to the sea and make pollution. This research objective is to design and accomplish previous roboboat research that still has some drawbacks. This research employs digital image processing and neural network based on the tensor flow framework method to overcome less accurate waste detection as well as autopilot navigation system. The research result shows by using 3600 dataset images, the model has the lowest loss 0.9 and 64.3% average accuracy with various samples and distance.
Key words: Waste / Roboboat / Neural Network / Tensor Flow
© The Authors, published by EDP Sciences, 2021
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