TY - GEN
T1 - Design and Development of IoT-Based Automatic Vehicle Accident Detection System
AU - Sowah, Robert A.
AU - Shahid, Mohammed
AU - Sowah, Nii Longdon
AU - Buah, Gifty
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The high demand for automobiles has also increased traffic dangers and road accidents, putting people's lives at high risk. The period between the occurrence of the accident and the arrival of emergency services to the scene is a significant antecedent of survival rates. Thus, delay in reaching the ambulance service, delay in the arrival of the ambulance and arrival at a hospital increases the victim's risk of death. With the emergence of Internet of things, it is highly desirable to have a smart monitoring and reliable system in vehicles to effectively relay information when accidents occur. This paper presents a real-time Google map and IoT-based accident tracking system, with the primary objective of assisting emergency personnel to locate the position of vehicle accidents and provide them details of the user involved in the accident for immediate assistance. The system is implemented with an accelerometer sensor, Wi-Fi module, Global Positioning System (GPS), Global System for Mobile Communication (GSM), and a mobile app for easy access and control. A microcontroller is used to control onboard sensors and continuously monitor the system. When an accident occurs, the microcontroller receives a signal from the accelerometer sensor and sends an alert message with the location and user information to a rescue team via a mobile app alert. The GSM module transmits the location of the accident and the mobile app uses Google Maps to show the location of the accident in real-time. The full functionality of the system was tested and the module successfully transmitted accident details via SMS message and the Wi-Fi module to the mobile app in less than 11 seconds after the occurrence of the accident.
AB - The high demand for automobiles has also increased traffic dangers and road accidents, putting people's lives at high risk. The period between the occurrence of the accident and the arrival of emergency services to the scene is a significant antecedent of survival rates. Thus, delay in reaching the ambulance service, delay in the arrival of the ambulance and arrival at a hospital increases the victim's risk of death. With the emergence of Internet of things, it is highly desirable to have a smart monitoring and reliable system in vehicles to effectively relay information when accidents occur. This paper presents a real-time Google map and IoT-based accident tracking system, with the primary objective of assisting emergency personnel to locate the position of vehicle accidents and provide them details of the user involved in the accident for immediate assistance. The system is implemented with an accelerometer sensor, Wi-Fi module, Global Positioning System (GPS), Global System for Mobile Communication (GSM), and a mobile app for easy access and control. A microcontroller is used to control onboard sensors and continuously monitor the system. When an accident occurs, the microcontroller receives a signal from the accelerometer sensor and sends an alert message with the location and user information to a rescue team via a mobile app alert. The GSM module transmits the location of the accident and the mobile app uses Google Maps to show the location of the accident in real-time. The full functionality of the system was tested and the module successfully transmitted accident details via SMS message and the Wi-Fi module to the mobile app in less than 11 seconds after the occurrence of the accident.
KW - alerts
KW - and notifications
KW - emergency services
KW - GSM/GPS Module
KW - hardware tracker
KW - vehicle accident detection
UR - http://www.scopus.com/inward/record.url?scp=85217834514&partnerID=8YFLogxK
U2 - 10.1109/ICAST61769.2024.10856503
DO - 10.1109/ICAST61769.2024.10856503
M3 - Conference contribution
AN - SCOPUS:85217834514
T3 - IEEE International Conference on Adaptive Science and Technology, ICAST
BT - Proceedings of the 2024 IEEE 9th International Conference on Adaptive Science and Technology, ICAST 2024
PB - IEEE Computer Society
T2 - 9th IEEE International Conference on Adaptive Science and Technology, ICAST 2024
Y2 - 24 October 2024 through 26 October 2024
ER -