{"title":"使用计算机视觉和机器学习监控3D打印和检测故障的智能程序","authors":"Christine Li, Yujia Zhang","doi":"10.5121/csit.2023.130713","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel solution for tracking the 3D printing process using an application that provides users with real-time updates on its progress [1]. The approach involves taking pictures of the 3D printer during the printing process, which are then analyzed by an AI model trained on thousands of labeled images to detect print failures [2]. The system is implemented using a Raspberry Pi and a camera, which capture images of the 3D printer and upload them to an online database [3]. The proposed application accesses this database to keep the user informed of the printer's current state, ensuring a seamless printing experience.","PeriodicalId":42597,"journal":{"name":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","volume":"1 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Intelligent Program to Monitor 3D Printing and Detect Failures using Computer Vision and Machine Learning\",\"authors\":\"Christine Li, Yujia Zhang\",\"doi\":\"10.5121/csit.2023.130713\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a novel solution for tracking the 3D printing process using an application that provides users with real-time updates on its progress [1]. The approach involves taking pictures of the 3D printer during the printing process, which are then analyzed by an AI model trained on thousands of labeled images to detect print failures [2]. The system is implemented using a Raspberry Pi and a camera, which capture images of the 3D printer and upload them to an online database [3]. The proposed application accesses this database to keep the user informed of the printer's current state, ensuring a seamless printing experience.\",\"PeriodicalId\":42597,\"journal\":{\"name\":\"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-04-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/csit.2023.130713\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/csit.2023.130713","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
An Intelligent Program to Monitor 3D Printing and Detect Failures using Computer Vision and Machine Learning
This paper proposes a novel solution for tracking the 3D printing process using an application that provides users with real-time updates on its progress [1]. The approach involves taking pictures of the 3D printer during the printing process, which are then analyzed by an AI model trained on thousands of labeled images to detect print failures [2]. The system is implemented using a Raspberry Pi and a camera, which capture images of the 3D printer and upload them to an online database [3]. The proposed application accesses this database to keep the user informed of the printer's current state, ensuring a seamless printing experience.