A. Ivashchenko, A. Krivosheev, Denis Sveshnikov, Nikita Svechkov, Tatiana Feschenko, Yuliya Tyshkovskaya, A. Chuvakov
{"title":"Intelligent Recognition in Automated Meters Surveying","authors":"A. Ivashchenko, A. Krivosheev, Denis Sveshnikov, Nikita Svechkov, Tatiana Feschenko, Yuliya Tyshkovskaya, A. Chuvakov","doi":"10.23919/fruct49677.2020.9211047","DOIUrl":null,"url":null,"abstract":"The paper proposes a new multi-layer solution to combine various algorithms implementing Artificial Intelligence (AI) for image recognition. Several neural networks are introduced to solve specific problems of objects identification. Additional “pre-launch matcher” is supplemented to scope out various objects and assigns them to the most corresponding AI modules. Distributed meter surveying is taken as an illustrative example of successful use. The introduced solution was implemented to process and analyze the results of electrical meters that are manually monitored by a group of patrol personnel inspectors using hand held devices. The results of development and testing show how the quality of neural network used for meter processing can be improved in practice.","PeriodicalId":149674,"journal":{"name":"2020 27th Conference of Open Innovations Association (FRUCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 27th Conference of Open Innovations Association (FRUCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/fruct49677.2020.9211047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The paper proposes a new multi-layer solution to combine various algorithms implementing Artificial Intelligence (AI) for image recognition. Several neural networks are introduced to solve specific problems of objects identification. Additional “pre-launch matcher” is supplemented to scope out various objects and assigns them to the most corresponding AI modules. Distributed meter surveying is taken as an illustrative example of successful use. The introduced solution was implemented to process and analyze the results of electrical meters that are manually monitored by a group of patrol personnel inspectors using hand held devices. The results of development and testing show how the quality of neural network used for meter processing can be improved in practice.