{"title":"Motion Detection and Prediction Using Machine Learning\nAlgorithm","authors":"","doi":"10.46243/jst.2020.v5.i5.pp220-226","DOIUrl":null,"url":null,"abstract":"Machine learning is a branch of Artificial Intelligence which is gaining importance in the 21st century\nwith increasing processing speeds and miniaturization of sensors, the applications of Artificial Intelligence and\ncognitive technologies are growing rapidly. An array of ultrasonic sensors i.e., HCSR-04 is placed at different\ndirections, collecting data for a particularinterval of a period during a particular day. The acquired sensor values\nare subjected to pre-processing, data analytics, and visualization. The prepared data is now split into test and train.\nA prediction model is designed using logistic regression and linear regression and checked for accuracy, F1 score,\nand precision compared.","PeriodicalId":23534,"journal":{"name":"Volume 5, Issue 4","volume":"48 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 5, Issue 4","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46243/jst.2020.v5.i5.pp220-226","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
Machine learning is a branch of Artificial Intelligence which is gaining importance in the 21st century
with increasing processing speeds and miniaturization of sensors, the applications of Artificial Intelligence and
cognitive technologies are growing rapidly. An array of ultrasonic sensors i.e., HCSR-04 is placed at different
directions, collecting data for a particularinterval of a period during a particular day. The acquired sensor values
are subjected to pre-processing, data analytics, and visualization. The prepared data is now split into test and train.
A prediction model is designed using logistic regression and linear regression and checked for accuracy, F1 score,
and precision compared.