@inproceedings{2c04e03fb11c4ac29680e2b65593ae0b,
title = "Campus safety and the internet of wearable things: Assessing student safety conditions on campus while riding a smart scooter",
abstract = "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.",
keywords = "Accident Prevention, Android, Balancing, GPS, intelligent systems, Potholes Detection, Smart sensing",
author = "Devansh Gupta and Wenyao Xu and Xiong Yu and Huang, \{Ming Chun\}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 17th IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks, BSN 2021 ; Conference date: 27-07-2021 Through 30-07-2021",
year = "2021",
month = jul,
day = "27",
doi = "10.1109/BSN51625.2021.9507033",
language = "English",
series = "2021 IEEE 17th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 IEEE 17th International Conference on Wearable and Implantable Body Sensor Networks, BSN 2021",
address = "United States",
}