Smart City Gnosys
Smart city article details
| Title | Decision Tree Approach For Classifying E-Waste To Recycle And Reproduce |
|---|---|
| ID_Doc | 17718 |
| Authors | Dubey A.; Verma A.S. |
| Year | 2023 |
| Published | Technological Advancement in E-waste Management: Towards Smart, Sustainable, and Intelligent Systems |
| DOI | http://dx.doi.org/10.1201/9781003317050-6 |
| Abstract | Waste management, especially when we talk about plastics, is hazardous. In developing countries and in the developed world electronic waste, or e-waste, is increasing day by day. Many of us don’t even know that we are throwing out electronic items. This will create human health hazards. In India, there are many rules to overcome this problem, but we are not giving them importance. This e-waste is growing at an annual rate of 30% in the country. Hence, there is a need to choose a more imperishable approach regarding our utilization habits, which is of peculiar importance. In order to effectively dispose of refuse, it is urgent to sort all the materials into biodegradable, recyclable, and non-biodegradable substances. This will reutilize them to enrich soil and cultivation. So, to deal with these problems, machine learning-based decision trees came into existence. This approach classifies materials as reusable and reproducible, which can be again checked by the statistical method and develop a model to work efficiently. In this proposed chapter, the authors are trying to develop a highly efficient decision tree model that can work in any city/smart city to decompose efficiently e-waste and protect the environment. © 2024 selection and editorial matter, Biswajit Debnath, Abhijit Das, Potluri Anil Chowdary, and Siddhartha Bhattacharyya; individual chapters, the contributors. |
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