Waste management is a certainly a very complex and difficult process especially in very large cities. It needs immense man power and also uses up other resources such as electricity and fuel. This creates a need to use a novel method with help of latest technologies. Here in this article we present a new waste classification technique using Computer Vision (CV) and deep learning (DL). To further improve waste classification ability, support machine vectors (SVM) are used. We also decompose the degradable waste with help of rapid composting. In this article we have mainly worked on segregation of municipal solid waste (MSW). For this model, we use YOLOv3 (You Only Look Once) a computer vision-based algorithm popularly used to detect objects which is developed based on Convolution Neural Networks (CNNs) which is a machine learning (ML) based tool. They are extensively used to extract features from a data especially image-oriented data. In this article we propose a waste classification technique which will be faster and more efficient. And we decompose the biodegradable waste by Berkley Method of composting (BKC)
翻译:废物管理当然是一个非常复杂和困难的过程,特别是在非常大城市。它需要巨大的人力,并且需要使用电力和燃料等其他资源。这就需要使用新颖的方法,借助最新技术。在这里,我们介绍了使用计算机视野和深层次学习(DL)的新废物分类技术。为了进一步提高废物分类能力,我们使用了支持机载媒介(SVM),我们还在快速堆肥的帮助下对可降解的废物进行分解。在本条中,我们主要致力于城市固体废物的隔离(MSW)。对于这一模型,我们使用YOLOv3(You only Look Ov3(You Ong Ov3(You Ong Ong Orth )) 一种基于计算机视野的算法,用于探测基于Convolucal Nenets(CNNs)开发的物体,这是基于机器学习(ML)的工具。它们被广泛用来从数据中提取特征,特别是图像导向的数据中提取。我们在此篇文章中建议一种更快、更高效的废物分类技术。我们用Berkley 方法解析出可生物降解的废物。我们用BKC(BKC)