University of Bahrain
Scientific Journals

Cyclist Fall Detection System via the Internet of Things (IoT)

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dc.contributor.author Kit, Tam Jun
dc.contributor.author Saruchi, Sarah Atifah
dc.contributor.author Hassan, Nurhaffizah
dc.contributor.author Izni, Nor Aziyatul
dc.date.accessioned 2023-03-02T15:57:20Z
dc.date.available 2023-03-02T15:57:20Z
dc.date.issued 2023-03-02
dc.identifier.issn 2210-142X
dc.identifier.uri https://journal.uob.edu.bh:443/handle/123456789/4790
dc.description.abstract Cycling has recently become one of the most popular activities among people worldwide. It is a practical and pollution-free way of transportation. However, it has several risks and potential impairments for users. One of the causes of an individual’s death or major injuries in an accident is a lack of first aid provision due to the emergency services that is not promptly receiving information about the event. The emergency response speed is critical for any accident. Therefore, this study developed a prototype of a cyclist fall detection system to produce immediate alerts regarding any fall incident and an accurate real-time location to the emergency contacts via smartphones. The proposed system used an ESP8266 as a microcontroller to collect and process the data from the sensors. An accelerometer sensor is also used to obtain the acceleration value to calculate the roll angle in determining the cyclist’s and bicycle’s orientation. A Global Positioning System (GPS) is installed in the proposed system to obtain the cyclist’s real-time location. The fall detection system is connected with software named BLYNK to send an emergency alert to the selected contact. As a result, the developed prototype successfully detected a fall and sent an emergency alert to specific users. Along with that, the GPS also managed to produce an accurate reading of fall’s real-time location. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.subject Cyclist, Fall Detection System, Sensors, Internet of Things en_US
dc.title Cyclist Fall Detection System via the Internet of Things (IoT) en_US
dc.type Article en_US
dc.identifier.doi http://dx.doi.org/10.12785/ijcds/130182 en
dc.contributor.authoraffiliation Faculty of Engineering, Technology & Built Environment, UCSI University, 56000 Cheras, Malaysia en_US
dc.contributor.authoraffiliation Ezlaser Enterprise, 81750 Masai, Johor, Malaysia en_US
dc.contributor.authoraffiliation Faculty of Manufacturing and Mechatronic Engineering Technology, Universiti Malaysia Pahang, 26600 Pekan, Pahang. Malaysia en_US
dc.contributor.authoraffiliation School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA, 23000 Dungun, Malaysia en_US
dc.contributor.authoraffiliation College of Computing, Informatics and Media, Centre of Foundation Studies, Universiti Teknologi MARA, Cawangan Selangor, Kampus Dengkil, 43800 Dengkil, Selangor, Malaysia en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US


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