Design And Implementation Of Black Box For Automobiles Using Esp 32
Keywords:
Black Box System, ESP32, Sensors, Microcontroller, Automobile, Event Data Recorder, Vehicle Safety, IoT IntegrationAbstract
A black box system in vehicles acts as an important tool that records important information to make vehicles safer, investigate accidents, and even improve the overall performance of the vehicles. This study will present the Black Box System that has been developed using ESP32 microcontrollers for cars to enhance data collection and analysis in automotive fields using technology. The Black Box System or Event Data Recorder (EDR) is an important tool in the enhancement of road safety, investigation of accidents, and evaluation of the performance of a vehicle. The system utilizes ESP32 as the main microcontroller since it is cost-effective, efficient, and can be programmed in multiple ways. It comprises several sensors and data acquisition modules to collect key parameters including speed, acceleration, geographical location, engine, and various diagnostic information about the vehicle. This paper also presents a detailed overview and integration of the system into Hardware and software parts of the automobile. A user-friendly interface facilitates data retrieval and analysis, supporting applications in fleet management, driver behavior monitoring, and accident investigations. The study focuses on the responsibility and protection of personal data, as well as ways of protecting personal data from misuse and violation of the law. Therefore, using ESP32 technology in the vehicle’s Black Box System is a great improvement towards road safety and vehicle monitoring. By ensuring data security and privacy, this system provides the users with a complete data set to support a decision-making process for self-employed drivers and other organizations.
References
A. T. Rajendran Thanikachalam, Rajendran Thavasimuthu, Godwin John J, Maria Arockia Dass J, Nithya T, “Design and Implementation of a Car’s Black Box System using Arduino,” Int. Res. J. Multidiscip. Technovation, vol. 6, no. 3, 2024, doi: 10.54392/irjmt24320.
K. M. P. Josephinshermila, S. Sharon priya, S. G. P. Ramakrishna hegde, and B. Veerasamy, “Accident detection using Automotive Smart Black-Box based Monitoring system,” Meas. Sensors, vol. 27, p. 100721, 2023, doi: https://doi.org/10.1016/j.measen.2023.100721.
A. Shinde, S., Choudhari, S., Khaladkar, A., & Randive, “Car Black Box System,” Int. Res. J. Innov. Eng. Technol., vol. 8, no. 4, pp. 194–199, 2024, doi: https://doi.org/10.47001/IRJIET/2024.804027.
S. Sethuraman and S. Santhanalakshmi, “Implementing Vehicle Black Box System by IoT based approach,” Proc. 4th Int. Conf. Trends Electron. Informatics, ICOEI 2020, pp. 390–395, Jun. 2020, doi: 10.1109/ICOEI48184.2020.9142906.
M. J. Prasad, S. Arundathi, N. Anil, H. Harshikha, and B. S. Kariyappa, “Automobile black box system for accident analysis,” 2014 Int. Conf. Adv. Electron. Comput. Commun. ICAECC 2014, Jan. 2015, doi: 10.1109/ICAECC.2014.7002430.
J. M. Hu, J. Li, and G. H. Li, “Automobile anti-theft system based on GSM and GPS module,” Proc. - 5th Int. Conf. Intell. Networks Intell. Syst. ICINIS 2012, pp. 199–201, 2012, doi: 10.1109/ICINIS.2012.86.
D. P. Raja, G. Barkavi, S. Aishwarya, K. Keerthana, and V. Vasudevan, “Alcohol Detection and Emergency Alert System using IoT,” Proc. - 2022 6th Int. Conf. Intell. Comput. Control Syst. ICICCS 2022, pp. 395–400, 2022, doi: 10.1109/ICICCS53718.2022.9788419.
M. N. Mohammed, Y. Ghanesen, S. Al-Zubaidi, M. A. M. Ali, O. Ismael Al-Sanjary, and N. S. Zamani, “Investigation on Carbon Monoxide Monitoring and Alert System for Vehicles,” Proc. - 2019 IEEE 15th Int. Colloq. Signal Process. its Appl. CSPA 2019, pp. 239–242, Apr. 2019, doi: 10.1109/CSPA.2019.8696001.
D. A. H. and F. S. J V Moniaga, S R Manalu, “Diagnostics vehicle’s condition using obd-ii and raspberry pi technology: study literature,” J. Phys. Conf. Ser., vol. 978, p. 012011, 2018, doi: 10.1088/1742-6596/978/1/012011.
R. Malekian, N. R. Moloisane, L. Nair, B. T. Maharaj, and U. A. K. Chude-Okonkwo, “Design and Implementation of a Wireless OBD II Fleet Management System,” IEEE Sens. J., vol. 17, no. 4, pp. 1154–1164, Feb. 2017, doi: 10.1109/JSEN.2016.2631542.

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