V. Akshita, R. Pushkala, R. Nivetha, S. S. Subashka
{"title":"基于支持向量机的垃圾分类系统","authors":"V. Akshita, R. Pushkala, R. Nivetha, S. S. Subashka","doi":"10.4108/EAI.16-5-2020.2303972","DOIUrl":null,"url":null,"abstract":"The garbage bins are full, half full or empty. These bins include various types of garbage ranging from metals, plastics to glasses. The collection of these dump waste are not segregated and so when the eliminating method is proposed the method is not efficient. The bio waste also gets dumped into landfills. To make the system efficient this paper proposes method to segregate system at its early stage. The system uses a Machine Learning Algorithm called Support Vector Machine (SVM) which performs image comparison in the vector form. Also, capacitive proximity sensors is used for next level of segregation which identifies type of waste either wet or dry with dielectric effect. Thus, this system collaboratively separates the waste using Machine learning and capacitance effect. The separated bio waste is converted to bio fuel for economic purposes. The plastic wastes can be given to scrap industries.","PeriodicalId":274686,"journal":{"name":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Garbage Segregation System using Support Vector Machine\",\"authors\":\"V. Akshita, R. Pushkala, R. Nivetha, S. S. Subashka\",\"doi\":\"10.4108/EAI.16-5-2020.2303972\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The garbage bins are full, half full or empty. These bins include various types of garbage ranging from metals, plastics to glasses. The collection of these dump waste are not segregated and so when the eliminating method is proposed the method is not efficient. The bio waste also gets dumped into landfills. To make the system efficient this paper proposes method to segregate system at its early stage. The system uses a Machine Learning Algorithm called Support Vector Machine (SVM) which performs image comparison in the vector form. Also, capacitive proximity sensors is used for next level of segregation which identifies type of waste either wet or dry with dielectric effect. Thus, this system collaboratively separates the waste using Machine learning and capacitance effect. The separated bio waste is converted to bio fuel for economic purposes. The plastic wastes can be given to scrap industries.\",\"PeriodicalId\":274686,\"journal\":{\"name\":\"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4108/EAI.16-5-2020.2303972\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fist International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/EAI.16-5-2020.2303972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Garbage Segregation System using Support Vector Machine
The garbage bins are full, half full or empty. These bins include various types of garbage ranging from metals, plastics to glasses. The collection of these dump waste are not segregated and so when the eliminating method is proposed the method is not efficient. The bio waste also gets dumped into landfills. To make the system efficient this paper proposes method to segregate system at its early stage. The system uses a Machine Learning Algorithm called Support Vector Machine (SVM) which performs image comparison in the vector form. Also, capacitive proximity sensors is used for next level of segregation which identifies type of waste either wet or dry with dielectric effect. Thus, this system collaboratively separates the waste using Machine learning and capacitance effect. The separated bio waste is converted to bio fuel for economic purposes. The plastic wastes can be given to scrap industries.