Christopher Urruchi, Daniel Cervantes-Chauca, Deyby Huamanchahua
{"title":"Proposal of a Swimming Pool Drowning Detection System using Cameras and Raspberry Pi based on Machine Learning","authors":"Christopher Urruchi, Daniel Cervantes-Chauca, Deyby Huamanchahua","doi":"10.1109/RAAI56146.2022.10092956","DOIUrl":null,"url":null,"abstract":"Drowning deaths represent the third leading cause of accidental deaths worldwide. This is because traditional techniques for the supervision and care of people, especially children, in large pools are inefficient or, in some cases, nonexistent. Nowadays, this problem has become a topic of interest for several researchers who seek to propose different methods of drowning detection. This research work seeks to propose the process to be followed to develop a drowning detection system in swimming pools using cameras and Raspberry Pi based on Machine Learning. To achieve the objective, the use of the Triple Diamond design methodology was proposed. In the development of the first diamond, the information was organized in a Lotus Blossom Diagram, then the problematic situation and the main objective were described. In the development of the second diamond, a bibliometric analysis was performed, searching for information with search equations and then sorting and filtering it, and finally including it in morphological matrices. As a result, an electrical diagram of the system and a flow diagram of the algorithm based on a Support Vector Machine were proposed.","PeriodicalId":190255,"journal":{"name":"2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RAAI56146.2022.10092956","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
Drowning deaths represent the third leading cause of accidental deaths worldwide. This is because traditional techniques for the supervision and care of people, especially children, in large pools are inefficient or, in some cases, nonexistent. Nowadays, this problem has become a topic of interest for several researchers who seek to propose different methods of drowning detection. This research work seeks to propose the process to be followed to develop a drowning detection system in swimming pools using cameras and Raspberry Pi based on Machine Learning. To achieve the objective, the use of the Triple Diamond design methodology was proposed. In the development of the first diamond, the information was organized in a Lotus Blossom Diagram, then the problematic situation and the main objective were described. In the development of the second diamond, a bibliometric analysis was performed, searching for information with search equations and then sorting and filtering it, and finally including it in morphological matrices. As a result, an electrical diagram of the system and a flow diagram of the algorithm based on a Support Vector Machine were proposed.