Study of Smart Black Box for Automobiles
Rohan Pawar
, Makrand Chavan , Kaustubh Rane , Mohan Kumar
Keywords — ThingSpeak Platform, Telegram, GSM Module Communication, Google Maps API, VS Code, Arduino IDE, Node MCU, ESP12E Microcontroller, MQ3 Alcohol Sensor, Vibrator Sensor, NEO6M MODULE.
Abstract — The Smart Blackbox for Automobiles is an
advanced monitoring and alerting system aimed at
improving road safety and minimizing accident risks
associated with driver fatigue, alcohol influence, or
sudden impacts. This system brings together multiple
sensors and technologies, including the MQ3 alcohol
sensor, SW420 vibration sensor, Neo-6M GPS module,
and a laptop camera using OpenCV to detect drowsiness
through eye-blink analysis. The system continuously
checks for signs of alcohol consumption, abnormal
vibrations, and driver drowsiness. If any of these risky
conditions are identified, it promptly sends alerts to a
cloud platform via ThingSpeak and notifies a designated
recipient through Telegram for quick action. The GPS
module also captures real-time location data, which
becomes crucial during emergencies or accident
scenarios. All data is uploaded to the cloud for secure
storage and later access.
This intelligent solution leverages IoT technologies for
real-time tracking and alerting, offering an affordable
and dependable method to help prevent accidents. The
inclusion of computer vision for drowsiness detection
adds a smart layer to the system, ensuring timely alerts if
the driver appears fatigued. Additionally, cloud- based
storage ensures that important data is preserved and can
be accessed later, such as for insurance purposes or
accident investigation.
In summary, the Smart Blackbox for Automobiles
presents an effective approach to enhancing vehicle
safety by targeting major accident causes. It is well-suited
for
deployment in personal cars, commercial
transportation fleets, and public transit systems.
Volume 12
Issue 4,
April-2025
Pages : a587-a591
Paper Reg. ID: TIJER_157466
Published Paper Id: TIJER2504088
Downloads: 000356
Research Area: Science and Technology
Country: Mumbai, Maharashtra, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
