校园安全和可穿戴物联网:在骑智能滑板车时评估校园学生的安全状况

Devansh Gupta, Wenyao Xu, Xiong Yu, Ming-chun Huang
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引用次数: 0

摘要

传统上,校园环境围绕着使用可持续和实用的交通工具,如自行车,但与行人和骑自行车的人相似,骑智能滑板车的学生也是脆弱的道路使用者,在道路交通事故中容易受到严重伤害。在本文中,我们创建了一个“智能安卓系统”。STEADi,用于监控智能摩托车骑手。该系统使用可穿戴式步态实验室,一种可穿戴式脚下力感应智能单元,作为主要组件之一。该系统的目的是通过提醒骑车人不可预见的情况,帮助那些刚开始在校园使用智能滑板车的学生避免受伤和事故。该系统为智能滑板车的骑行者提供了足够的路径跟踪、坑洼检测系统和人体平衡能力的数据。经过对训练数据的仔细选择,我们已经能够整合一个坑洼探测系统,该系统可以识别出有坑洼的路段。该系统基于四种不同地形的平衡测试以及与智能滑板车相关的不同骑行体验进行评估。系统测试表明,它可以成功地检测到克利夫兰地区及其周围的几个真正的坑洼,并成功地提醒骑手,包括经验不足的骑手,当他们在不同的地形上骑行时,潜在的道路相关威胁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Campus safety and the internet of wearable things: assessing student safety conditions on campus while riding a smart scooter
The campus environments have traditionally revolved around the use of sustainable and practical mobility vehicles such as bicycles, but similar to pedestrians and bicyclists, the students riding smart-scooter are also vulnerable road users and to severe injuries during road accidents. In this paper, we created a “smart android system”. STEADi, for monitoring the Smart scooter riders. The system uses a Wearable Gait Lab for, a wearable underfoot force-sensing intelligent unit, as one of the main components. The purpose of this system is to help students who are new to using smart scooters on campus to avoid injuries and accidents by alerting the rider about unforeseen conditions. The system provides adequate data for path tracking, Potholes Detection system, and human balancing ability for the Smart Scooter riders. After careful selection of training data, we have been able to integrate a pothole detector system that identifies worse road segments as having potholes. The proposed system is evaluated based on four balance tests on different terrain and with different diverse riding experiences related to the Smart Scooters. The system testing showed that it can successfully detect several real potholes in and around the Cleveland area and is successfully able to alert the riders, including the lesser experienced ones while riding on different terrains for the potential road-related threats.
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