Design and Implementation of Black-Box for Vehicle Safety

The increasing rate of vehicle thefts and road accidents necessitates a smart, IoT-based vehicle black box system for real-time tracking and emergency response. This system integrates GSM, GPS, and embedded automation to detect crashes, send immediate alerts, and track vehicle locations. Using sensors, wireless communication, and cloud integration, it enhances accident response time while improving vehicle security. The system comprises Arduino Uno, GSM SIM900A, GPS NEO-6M, crash sensors, and an LCD display for real-time monitoring. Upon detecting an accident, the system records vehicle parameters, geo-location, and impact severity, sending alerts to emergency contacts and authorities. Additionally, anti-theft features detect unauthorized movement and notify the vehicle owner. The system achieves high accuracy in crash detection and real-time tracking, with a response time of 5 seconds. Future improvements will focus on AI-driven analytics, predictive accident detection, and cloud-based security enhancements.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.15254823
Primary Topic
Fashion and Cultural Textiles
Type
article
Field-Weighted Citation Impact
0.00
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article

Design and Implementation of Black-Box for Vehicle Safety

Zenodo (CERN European Organization for Nuclear Research)
Fashion and Cultural Textiles
article

Design and Implementation of Black-Box for Vehicle Safety

article en

Abstract

The increasing rate of vehicle thefts and road accidents necessitates a smart, IoT-based vehicle black box system for real-time tracking and emergency response. This system integrates GSM, GPS, and embedded automation to detect crashes, send immediate alerts, and track vehicle locations. Using sensors, wireless communication, and cloud integration, it enhances accident response time while improving vehicle security. The system comprises Arduino Uno, GSM SIM900A, GPS NEO-6M, crash sensors, and an LCD display for real-time monitoring. Upon detecting an accident, the system records vehicle parameters, geo-location, and impact severity, sending alerts to emergency contacts and authorities. Additionally, anti-theft features detect unauthorized movement and notify the vehicle owner. The system achieves high accuracy in crash detection and real-time tracking, with a response time of 5 seconds. Future improvements will focus on AI-driven analytics, predictive accident detection, and cloud-based security enhancements.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 46%
Fashion and Cultural Textiles
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