Lightweight Vehicle Black Box System with Automatic Emergency Assistance

In the context of increasing road traffic incidents and the demand for smarter transportation systems, the need for advanced vehicle monitoring solutions has become critical. This paper presents the design and development of an IoT-based Vehicle Black Box system that records and transmits real-time vehicular data to support accident analysis and emergency response. The proposed system integrates various sensors, including an accelerometer, GPS module, alcohol sensor, and microcontroller, to collect data such as speed, impact force, location, and driver condition. Through IoT connectivity, this information is stored in a cloud database, enabling remote access and live monitoring. In the event of an accident, the system automatically triggers an emergency alert containing the vehicle’s coordinates, significantly reducing the time taken for rescue and investigation. The system offers a scalable and cost-effective solution for both personal and commercial vehicles, with potential applications in fleet management, insurance validation, and driver behavior analysis. Its modular architecture allows easy integration with additional technologies such as predictive analytics and Vehicle-to-Everything (V2X) communication. Moreover, the secure and tamper-resistant data logging ensures the reliability and integrity of evidence in post-accident scenarios. The experimental results demonstrate the system's effectiveness in capturing critical information in real-time, making it a valuable tool in advancing road safety and intelligent transportation frameworks

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-04-12
DOI
https://doi.org/10.22214/ijraset.2025.68537
Primary Topic
IoT and GPS-based Vehicle Safety Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Lightweight Vehicle Black Box System with Automatic Emergency Assistance

K. Deeksha
International Journal for Research in Applied Science and Engineering Technology
IoT and GPS-based Vehicle Safety Systems
article

Lightweight Vehicle Black Box System with Automatic Emergency Assistance

K. Deeksha
article en

Abstract

In the context of increasing road traffic incidents and the demand for smarter transportation systems, the need for advanced vehicle monitoring solutions has become critical. This paper presents the design and development of an IoT-based Vehicle Black Box system that records and transmits real-time vehicular data to support accident analysis and emergency response. The proposed system integrates various sensors, including an accelerometer, GPS module, alcohol sensor, and microcontroller, to collect data such as speed, impact force, location, and driver condition. Through IoT connectivity, this information is stored in a cloud database, enabling remote access and live monitoring. In the event of an accident, the system automatically triggers an emergency alert containing the vehicle’s coordinates, significantly reducing the time taken for rescue and investigation. The system offers a scalable and cost-effective solution for both personal and commercial vehicles, with potential applications in fleet management, insurance validation, and driver behavior analysis. Its modular architecture allows easy integration with additional technologies such as predictive analytics and Vehicle-to-Everything (V2X) communication. Moreover, the secure and tamper-resistant data logging ensures the reliability and integrity of evidence in post-accident scenarios. The experimental results demonstrate the system's effectiveness in capturing critical information in real-time, making it a valuable tool in advancing road safety and intelligent transportation frameworks

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(4)
Openalex Percentile: Top 93%
IoT and GPS-based Vehicle Safety Systems
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Lightweight Vehicle Black Box System with Automatic Emergency Assistance — K. Deeksha · International Journal for Research in Applied Science and Engineering Technology (2025) | TGRS Research Map | TGRS