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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM61058

DESINGN AND IMPLEMENTATION OF IOT ENABLED SMART VEHICLE BLACK BOX SYSTEM

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM61058

Volume:

10 |

4 |

April 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/ijsrem61058

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PD

P DHANASEKARAN

GA

G AJAY

BP

B PAVITHRA

GSP

G SRI PUBITHA

SV

S VIKRAM

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Abstract

This project presents the design and implementation of an IoT-enabled smart vehicle black box system aimed at enhancing road safety, accident analysis, and real-time monitoring. The system integrates sensors, a microcontroller, and      wireless communication modules to continuously capture critical parameters such as vehicle speed, location, acceleration, and impact force. In the event of an accident, the system automatically records and transmits essential data to a cloud platform, enabling quick access for emergency response and post-incident investigation. Additionally, features such as GPS tracking, driver behaviour monitoring, and remote data access improve vehicle security and accountability. The proposed solution offers a cost-effective, reliable, and scalable approach to modern vehicular data logging, contributing to smarter transportation systems and improved safety outcomes.

KEYWORDS

IoT Smart Vehicle System Black Box Accident Detection GPS Tracking Data Logging Real-Time Monitoring Vehicle Safety Cloud Storage Sensor Integration Emergency Alert System Telematics

Cite This Article

P DHANASEKARAN, G AJAY, B PAVITHRA, G SRI PUBITHA, S VIKRAM, "DESINGN AND IMPLEMENTATION OF IOT ENABLED SMART VEHICLE BLACK BOX SYSTEM," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, April 2026. https://doi.org/10.55041/ijsrem61058

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Publication Date

4/23/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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