Design And Implementation Of Black Box For Automobiles Using Esp32
Journal Title: International Journal of Innovations in Science and Technology - Year 2025, Vol 7, Issue 2
Abstract
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.
Authors and Affiliations
Maaz Khan, Arbab Masood Ahmad, Waseem Sajjad, Usman Khan Khalil
Keywords
Related Articles
- EP ID EP769792
- DOI -
- Views 6
- Downloads 0
Generative AI’s Impact on Industry:Unveiling Transformative Applications, Opportunities and Challenges
With the advancement of Artificial Intelligence, a new branch of AI has emerged which is known as Generative AI. It has gained a lot of popularity in a very short time because of its human-like computational capabiliti...
A Novel Guard Zone Based Multiple Access Protocol for Autonomous D2D Cellular Communication
In today's interconnected and digitally driven era, Device-to-Device (D2D) communication has emerged as a transformative paradigm, enabling direct and efficient interactions between nearby devices with or without tradi...
Gender-Based Analysis of Employee Attrition Prediction Using Machine Learning
Employee turnover is a significant problem in organizations because it comes with productivity and cost implications. This paper focuses on predicting employee turnover using machine learning techniques that incorporat...
Recurrent Neural Network and Multi-Factor Feature Filtering for Ransomware Detection in Android Apps
The market is flooded with Android Software (apps), and at the same time that number is growing quickly, and so are the many security exploits that take advantage of such apps. The effectiveness of traditional defensiv...
Advanced Blast Algorithm for Molecular Identification, Biodegradation and Decolorization of Synthetic Melanoidins Using Fungal Species Isolated from Soil and Spent Wash
Introduction/Importance of Study: Distillery spent wash contains a high organic load as Melanoidins. It is generated due to the Millard reaction, which produces sugar and amino acids, leading to extensive water and soi...