Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{174031,
        author = {N. Satya Lokesh and K. Rajesh and V. Vinay and B. Balaji and D. Navya Narayana Kumari},
        title = {Object Detection Using IOT & Machine Learning To Avoid Accidents & Improve Driver Assistance},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {2374-2379},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174031},
        abstract = {This paper outlines the creation of a road safety system that employs IoT and Machine Learning (ML) technologies aimed at improving road safety and mitigating accidents. The system combines several hardware elements, such as an Arduino, a web camera, an ultrasonic sensor, a motor driver, DC motors, a buzzer, a 3.5mm audio jack speaker, a 12V power supply adapter, a MEMS sensor, along with GPS and GSM modules. Utilizing the YOLO (You Only Look Once) object detection algorithm, the system is capable of identifying obstacles and tracking vehicle movements in real time to prevent collisions. The Arduino manages the operations of the sensors and actuators, ensuring swift reactions to potential dangers. In case of an accident, the system utilizes GPS and GSM modules to relay accurate location details. The combination of IoT and ML technologies presents a thorough solution aimed at proactive road safety initiatives, seeking to significantly diminish the likelihood of accidents and enhance overall road safety.},
        keywords = {Arduino Uno, You Only Look Once (YOLO), Web Camera, Internet of Thing (IOT), Machine Learning (ML),},
        month = {March},
        }