Christofer N. Yalung, Salah S. Al-Majeed, Cid Mathew Adolfo, J. Karam, L. Mirtskhulava
{"title":"陀螺仪探测地形角度分类","authors":"Christofer N. Yalung, Salah S. Al-Majeed, Cid Mathew Adolfo, J. Karam, L. Mirtskhulava","doi":"10.1109/EWDTS.2016.7807679","DOIUrl":null,"url":null,"abstract":"Mobile Applications (Apps) offer numerous advantages related to entertainment, communication, monitoring and sensing to name a few. In this study, a Gyroscope Explorer Apps is employed for data gathering of azimuth, pitch, and roll. The mobile phone is carried by Lego Mindstorms (EV3), in which it travels the ladder into the different angles: 4.13°, 7.77°, 10.81°, and 12.80°. The data collected was classified into eight classes: 4.13°uphill, 4.13°downhill, 7.77° uphill, 7.77° downhill, 10.81° uphill, 10.81°downhill, 12.80° uphill, 12.80° downhill. Artificial Neural Network is used to classify the angels and the orientation of the vehicle-uphill or downhill. A total of 718 data collected and divided into three sets (azimuth, pitch and roll). The number of neurons in the hidden layer is set to 10, yielding a 100% accuracy classification.","PeriodicalId":364686,"journal":{"name":"2016 IEEE East-West Design & Test Symposium (EWDTS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Gyroscope explorer terrain angles classification\",\"authors\":\"Christofer N. Yalung, Salah S. Al-Majeed, Cid Mathew Adolfo, J. Karam, L. Mirtskhulava\",\"doi\":\"10.1109/EWDTS.2016.7807679\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile Applications (Apps) offer numerous advantages related to entertainment, communication, monitoring and sensing to name a few. In this study, a Gyroscope Explorer Apps is employed for data gathering of azimuth, pitch, and roll. The mobile phone is carried by Lego Mindstorms (EV3), in which it travels the ladder into the different angles: 4.13°, 7.77°, 10.81°, and 12.80°. The data collected was classified into eight classes: 4.13°uphill, 4.13°downhill, 7.77° uphill, 7.77° downhill, 10.81° uphill, 10.81°downhill, 12.80° uphill, 12.80° downhill. Artificial Neural Network is used to classify the angels and the orientation of the vehicle-uphill or downhill. A total of 718 data collected and divided into three sets (azimuth, pitch and roll). The number of neurons in the hidden layer is set to 10, yielding a 100% accuracy classification.\",\"PeriodicalId\":364686,\"journal\":{\"name\":\"2016 IEEE East-West Design & Test Symposium (EWDTS)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE East-West Design & Test Symposium (EWDTS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EWDTS.2016.7807679\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE East-West Design & Test Symposium (EWDTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EWDTS.2016.7807679","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mobile Applications (Apps) offer numerous advantages related to entertainment, communication, monitoring and sensing to name a few. In this study, a Gyroscope Explorer Apps is employed for data gathering of azimuth, pitch, and roll. The mobile phone is carried by Lego Mindstorms (EV3), in which it travels the ladder into the different angles: 4.13°, 7.77°, 10.81°, and 12.80°. The data collected was classified into eight classes: 4.13°uphill, 4.13°downhill, 7.77° uphill, 7.77° downhill, 10.81° uphill, 10.81°downhill, 12.80° uphill, 12.80° downhill. Artificial Neural Network is used to classify the angels and the orientation of the vehicle-uphill or downhill. A total of 718 data collected and divided into three sets (azimuth, pitch and roll). The number of neurons in the hidden layer is set to 10, yielding a 100% accuracy classification.