AUTOAID: An Intelligent Accident Notifier

Road accidents remain a leading cause of fatalities, injuries, and hospitalizations worldwide, primarily due to delayed emergency response and inadequate detection systems. This research paper explores advanced methods for accident detection, response facilitation, and safety enhancements to mitigate these challenges. By integrating sensor technologies, IoT systems, and real-time communication modules, the proposed solutions ensure timely alerts to emergency responders and individuals. The system employs accelerometers to detect abrupt changes in vehicle dynamics, vibration sensors to recognize collisions, and GPS-GSM modules for real-time location tracking. Alerts, including accident coordinates and timestamps, are sent via SMS or IoT-based platforms like Telegram to emergency centers. A feature allows cancellation of false alerts, optimizing response efforts. Our development has expanded the system to direct links to assistance services such as clinics, police, and fire stations. This integrated approach, supported by IoT data on distances, velocities, fuel consumption, and miles, demonstrates significant potential in saving lives and reducing accident impacts. In future, Additional functionalities could include monitoring helmet usage to mitigate head injury risks, detecting alcohol levels with MQ3 sensors, and leveraging fuel theft sensors at tank apertures. Overload risks are addressed using load cell sensors, while speed regulation can be achieved through turbine-based mechanisms emitting audible warnings at threshold velocities, A camera module may capture images post-collision, aiding in assessing accident severity.

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Publication Details

Published
2025-05-09
DOI
https://doi.org/10.1109/stcr62650.2025.11020562
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
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article

AUTOAID: An Intelligent Accident Notifier

Amit Kumar Jaiswal, Himanshu Sharma, Nikita Jha, Premprakash Motwani
Anomaly Detection Techniques and Applications
article

AUTOAID: An Intelligent Accident Notifier

Amit Kumar Jaiswal, Himanshu Sharma, Nikita Jha, Premprakash Motwani
article en

Abstract

Road accidents remain a leading cause of fatalities, injuries, and hospitalizations worldwide, primarily due to delayed emergency response and inadequate detection systems. This research paper explores advanced methods for accident detection, response facilitation, and safety enhancements to mitigate these challenges. By integrating sensor technologies, IoT systems, and real-time communication modules, the proposed solutions ensure timely alerts to emergency responders and individuals. The system employs accelerometers to detect abrupt changes in vehicle dynamics, vibration sensors to recognize collisions, and GPS-GSM modules for real-time location tracking. Alerts, including accident coordinates and timestamps, are sent via SMS or IoT-based platforms like Telegram to emergency centers. A feature allows cancellation of false alerts, optimizing response efforts. Our development has expanded the system to direct links to assistance services such as clinics, police, and fire stations. This integrated approach, supported by IoT data on distances, velocities, fuel consumption, and miles, demonstrates significant potential in saving lives and reducing accident impacts. In future, Additional functionalities could include monitoring helmet usage to mitigate head injury risks, detecting alcohol levels with MQ3 sensors, and leveraging fuel theft sensors at tank apertures. Overload risks are addressed using load cell sensors, while speed regulation can be achieved through turbine-based mechanisms emitting audible warnings at threshold velocities, A camera module may capture images post-collision, aiding in assessing accident severity.

Chandigarh University (IN)
Openalex Percentile: Top 94%
Anomaly Detection Techniques and Applications
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