Bike Sensor System Design for Safety and Healthy Riding

Lai, Pin-Cheng; Huang, Huihua; Sheu, Ming-Hwa.; Wu, Chien‐Wei; Le, Ji-Ting; Chen, Tzu-Hsiung

doi:10.1109/icce-china.2018.8448461

Cited by 8 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ensuring the secure operation of shared mobility systems mainly depends on monitoring the behavior of road users, especially bike and scooter riders, and minimizing the vulnerabilities they are exposed to on the road [17]. Specifically, most studies on ensuring bike/scooter rider safety focused on the use of smart helmets [18][19][20][21][22] or smart bikes [23][24][25] along with mobile applications [19,[23][24][25] or cloud-based databases [22,25].…”

Section: Literature Reviewmentioning

confidence: 99%

“…The system used a force-sensitive resistor to detect helmet wearing, an activated buzzer for helmet reminders, and an LED that flashes when the speed sensor detects exceeding speed limits. The study in [23] proposed a smart bike system that incorporated an Android application on the smartphone for data transmission through the 4G network between the app and a cloud-based real-time database and a microcontroller for communication via Bluetooth 4.0 Low Energy (BLE) between sensors and the phone. The study used ultrasonic sensors to detect nearby vehicles and an inertial measurement unit to measure acceleration and angular velocities.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Research has not only focused on mobility sharing effects on urban transportation but also on distribution techniques, route optimization, and precise demand forecasting [11][12][13][14][15][16]. Safety concerns sparked creative solutions, such as smart helmets, smart bikes, and mobile applications intended to protect road users, as these platforms have grown in popularity [17][18][19][20][21][22][23][24]. In addition, machine-learning techniques have been used to identify accidents and categorize traffic irregularities using sensor-collected data [26][27][28].…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Data-Driven Safe Deliveries: The Synergy of IoT and Machine Learning in Shared Mobility

Elwy,

Aburukba,

Al-Ali

et al. 2023

Future Internet

View full text Add to dashboard Cite

Shared mobility is one of the smart city applications in which traditional individually owned vehicles are transformed into shared and distributed ownership. Ensuring the safety of both drivers and riders is a fundamental requirement in shared mobility. This work aims to design and implement an adequate framework for shared mobility within the context of a smart city. The characteristics of shared mobility are identified, leading to the proposal of an effective solution for real-time data collection, tracking, and automated decisions focusing on safety. Driver and rider safety is considered by identifying dangerous driving behaviors and the prompt response to accidents. Furthermore, a trip log is recorded to identify the reasons behind the accident. A prototype implementation is presented to validate the proposed framework for a delivery service using motorbikes. The results demonstrate the scalability of the proposed design and the integration of the overall system to enhance the rider’s safety using machine learning techniques. The machine learning approach identifies dangerous driving behaviors with an accuracy of 91.59% using the decision tree approach when compared against the support vector machine and K-nearest neighbor approaches.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Data-Driven Safe Deliveries: The Synergy of IoT and Machine Learning in Shared Mobility

Elwy,

Aburukba,

Al-Ali

et al. 2023

Future Internet

View full text Add to dashboard Cite

show abstract

“…In particular, the Internet of Things (IoT) based on WSN is becoming popular in tracking objects applications (i.e., tracking of bicycles and portable computers). This approach allows reducing the number of cases of theft [2,3]. The conventional WSN implementation for tracking applications involves 2G/3G mobile network [4].…”

Section: Introductionmentioning

confidence: 99%

A Low-Cost Web Interface for Object Tracking Based on a Wireless Sensor Network

Carvajal

Fajardo

Páez

2021

Advanced Computing and Intelligent Technologies

View full text Add to dashboard Cite

This paper describes the design of a minimum cost web interface for object tracking applications based on open (or free) tools. Furthermore, the different blocks and parts that compose it were detailed; this paper was written as a tutorial to motivate engineers and students with basic knowledge on programming tools to integrate these web interfaces in their projects. The platform features were validated with a study case, which is based on a low-cost LoRa Network and the developed web platform. The implemented features exhibit complete functionality.

show abstract