Monitoring and Alert System for Hazardous Driving Behavior Using Internet of Vehicles Technology

The system enhances road safety by monitoring driver behavior and issuing warnings for dangerous driving, leveraging Internet of Vehicles (IoV) technology. A Raspberry Pi 3 Model B is the core of the system, processing data from various sensors, including an ultrasonic sensor for distance, ADC MCP3008 for analog-to-digital conversion, a GPS module for location tracking, and an alcohol sensor for detecting intoxication. The system also uses a USB camera for visual monitoring, Bluetooth for local communication, and GSM for long-range alerts. When risky behaviors are detected, the system provides immediate warnings through buzzers and an LCD display. Critical alerts can be sent to emergency contacts via the GSM module. The system, powered by a 12V 1A adapter, aims to reduce accidents by promoting safer driving through real-time data and IoV connectivity. The web camera captures eye movements, and the Raspberry Pi processes this data to detect drowsiness, triggering preventive actions when needed which is different from the existing methods.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/isense63713.2024.10872025
Citations
2
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
0.73
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article

Monitoring and Alert System for Hazardous Driving Behavior Using Internet of Vehicles Technology

T Madhuri, J BalaVishnu
2 citations
Fire Detection and Safety Systems
0.73
article

Monitoring and Alert System for Hazardous Driving Behavior Using Internet of Vehicles Technology

T Madhuri, J BalaVishnu
article en
2 citations

Abstract

The system enhances road safety by monitoring driver behavior and issuing warnings for dangerous driving, leveraging Internet of Vehicles (IoV) technology. A Raspberry Pi 3 Model B is the core of the system, processing data from various sensors, including an ultrasonic sensor for distance, ADC MCP3008 for analog-to-digital conversion, a GPS module for location tracking, and an alcohol sensor for detecting intoxication. The system also uses a USB camera for visual monitoring, Bluetooth for local communication, and GSM for long-range alerts. When risky behaviors are detected, the system provides immediate warnings through buzzers and an LCD display. Critical alerts can be sent to emergency contacts via the GSM module. The system, powered by a 12V 1A adapter, aims to reduce accidents by promoting safer driving through real-time data and IoV connectivity. The web camera captures eye movements, and the Raspberry Pi processes this data to detect drowsiness, triggering preventive actions when needed which is different from the existing methods.

Amrita Vishwa Vidyapeetham (IN)
Climate action
Openalex Percentile: Top 27%
Fire Detection and Safety Systems
0.73
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