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Evaluation of Frameworks for MLOps and Microservices mlop和微服务框架的评估

EAI endorsed transactions on smart cities Pub Date : 2023-11-13 DOI: 10.4108/eetsc.3661

Igor Urias, Rogério Rossi

{"title":"Evaluation of Frameworks for MLOps and Microservices","authors":"Igor Urias, Rogério Rossi","doi":"10.4108/eetsc.3661","DOIUrl":"https://doi.org/10.4108/eetsc.3661","url":null,"abstract":"Information Technology involves solutions for many kinds of industries and organizations, offering conditions for solving problems of different types and complexities. Artificial Intelligence, and more specifically applications that considers Machine Learning (ML) and Software Technology are part of these solutions for solving problems, including solutions for solving problems that involve smart cities approach. In order to present frameworks that deal with the operationalization of Machine Learning and Software technology, this article is based on the study and evaluation of frameworks that involve Machine Learning Operations (MLOps) and microservices. Specifically, three frameworks that integrate ML algorithms with microservices are evaluated based on a bibliographical review in scientific journals of relevance to the area. From an exploratory analysis of these frameworks, it was possible to highlight their main objectives, their benefits, and their ability to offer solutions that favor the large-scale use of Machine Learning algorithms in problem solving. The main results are highlighted in the article through a qualitative analysis that considers six evaluation criteria, such as: capacity for sharing resources, scope of use by users, and use in a cloud environment. The results achieved are satisfactory since the work allows, through a qualitative view of the evaluated frameworks, a perspective of how the integration of MLOps and microservices has been carried out, its benefits and possible results achieved through this integration.","PeriodicalId":474370,"journal":{"name":"EAI endorsed transactions on smart cities","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136348298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Welcome to the second issue of Volume 7 of the EAI Endorsed Transactions on Smart Cities 欢迎阅读EAI《智慧城市交易报告》第七卷第二期

EAI endorsed transactions on smart cities Pub Date : 2023-10-09 DOI: 10.4108/eetsc.4106

Dario Vieira

引用次数: 0

Intelligent Aircraft Hangar Fire Detection and Location System Based on Wireless Sensor Network 基于无线传感器网络的智能机库火灾探测与定位系统

EAI endorsed transactions on smart cities Pub Date : 2023-10-05 DOI: 10.4108/eetsc.3742

Abbas Abdullahi, Mathias Usman Bonet, Ubadike Osichinaka Chiedu, Ameer Muhammed, Ubadike Obunike Arinze

{"title":"Intelligent Aircraft Hangar Fire Detection and Location System Based on Wireless Sensor Network","authors":"Abbas Abdullahi, Mathias Usman Bonet, Ubadike Osichinaka Chiedu, Ameer Muhammed, Ubadike Obunike Arinze","doi":"10.4108/eetsc.3742","DOIUrl":"https://doi.org/10.4108/eetsc.3742","url":null,"abstract":"Aircraft hangar fire detection systems are essential for protecting both the facility's assets and the contents of an aircraft. In terms of predicting a fire outbreak at an aircraft hangar, the Intelligent Aircraft Hangar Fire detection is considered as a high-performance system that is designed based on the principle of a wireless sensor network (WSN), which operates by employing three sensor nodes at different locations inside the aircraft hangar to transmit gas concentrations in the air to a base station (BS) and send the resulting data from the sensor nodes to a server for analysis and visualization of the risk level. The server uses Machine Learning (ML) techniques to analyze the acquired data along with the sample gas data and displays the report in real time. When the smoke (gas) concentration is high, the server predicts a fire outbreak by displaying a high concentration zone on the Graphic User Interface (GUI). By this, the server automatically issues a warning and identifies the potential fire location. The technology is built to protect aircraft assets, hangar buildings, and human (personnel) life. A crucial part in the early detection of fire is played by the intelligent system","PeriodicalId":474370,"journal":{"name":"EAI endorsed transactions on smart cities","volume":"301 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135481210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0