Motion Detection and Prediction Using Machine Learning Algorithm

{"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}
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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.
基于机器学习算法的运动检测与预测
机器学习是人工智能的一个分支,在21世纪随着处理速度的提高和传感器的小型化,人工智能和认知技术的应用正在迅速发展。一组超声波传感器,即HCSR-04,被放置在不同的方向,在特定的一天中收集特定时间段的数据。采集的传感器值经过预处理、数据分析和可视化处理。准备好的数据现在分为测试和训练。采用logistic回归和线性回归设计预测模型,并对预测的准确性、F1评分和精度进行了检验。
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