Joicy Alwin, Jyotsna Callista, Kaviena Sharon, Paul M. Kallarackal, J. M. Asensio-Gil, Carlos Rodr´ıguez-Morcillo, Rodr´ıguez-Morcillo Garc´ıa
{"title":"iRider: Integrating Sensors and Cameras for In-depth Biomechanical Analysis of Electric Scooter","authors":"Joicy Alwin, Jyotsna Callista, Kaviena Sharon, Paul M. Kallarackal, J. M. Asensio-Gil, Carlos Rodr´ıguez-Morcillo, Rodr´ıguez-Morcillo Garc´ıa","doi":"10.1109/APSCON60364.2024.10465780","DOIUrl":null,"url":null,"abstract":"The iRider project presents an innovative initiative that seamlessly integrates sensors and cameras into electric scooters, elevating rider safety and experience through comprehensive biomechanical analysis. By incorporating an array of sensors and cameras onto electric scooters, the project acquires precise real-time data concerning scooter movements and user posture. Driven by collaborative synergy, the multidisciplinary project emphasizes objectives including biomechanical analysis, automated data collection, and versatile system design. The project holds the promise of enhancing the electric scooter riding experience and contributing to the transportation industry and academic exploration. It propels advancements in safety, sensor integration, and innovative applications within the transportation sector.","PeriodicalId":518961,"journal":{"name":"2024 IEEE Applied Sensing Conference (APSCON)","volume":"25 5","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2024 IEEE Applied Sensing Conference (APSCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSCON60364.2024.10465780","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 iRider project presents an innovative initiative that seamlessly integrates sensors and cameras into electric scooters, elevating rider safety and experience through comprehensive biomechanical analysis. By incorporating an array of sensors and cameras onto electric scooters, the project acquires precise real-time data concerning scooter movements and user posture. Driven by collaborative synergy, the multidisciplinary project emphasizes objectives including biomechanical analysis, automated data collection, and versatile system design. The project holds the promise of enhancing the electric scooter riding experience and contributing to the transportation industry and academic exploration. It propels advancements in safety, sensor integration, and innovative applications within the transportation sector.