Paper Title
Advanced Traffic Monitoring & Speed Regulation Using Yolovxi

Abstract
Road traffic accidents caused by over-speeding remain a major concern for urban safety management, necessitating the development of intelligent, automated monitoring solutions. In this work, we present a sophisticated traffic monitoring framework that leverages the state-of-the-art object detection model YOLOv11 (You Only Look Once, version 11) for real-time vehicle detection and speed estimation. The proposed system is capable of automatically identifying over-speeding incidents and issuing prompt alerts through integrated communication application programming interfaces (APIs). Specifically, the framework enables instantaneous SMS notifications to both vehicle owners and traffic enforcement authorities, thereby facilitating timely intervention and improved compliance with traffic regulations. Our experimental evaluations demonstrate a detection accuracy of 92.3%, ensuring robust vehicle classification under varying traffic and environmental conditions. The system further achieves speed estimation within a 5% error margin, validating its reliability for precise monitoring. Designed for deployment on edge devices, the proposed solution achieves real-time performance with an average alert generation latency of 200 ms, thus confirming its feasibility for practical, large-scale applications. In addition, the system incorporates advanced image preprocessing techniques to enhance visibility during lowlight or adverse weather conditions, ensuring consistent accuracy across diverse scenarios. The modular design allows seamless integration with existing smart traffic infrastructure and supports cloud-based data analytics for historical trend analysis. The framework not only enhances road safety through rapid notification and enforcement mechanisms but also contributes to the broader vision of smart city infrastructure by enabling scalable, intelligent traffic surveillance. Keywords - YOLOv11, Vehicle Detection, Speed Estimation, Real-Time Processing, Traffic Monitoring, SMS Alerts, Computer Vision, Deep Learning, Intelligent Transportation Systems, Edge Computing, Over-Speeding Detection, Smart City Applications, Automated Alert System, Object Tracking, Road Safety, Internet of Things (IoT), Image Processing, Convolutional Neural Networks (CNNs), Traffic Surveillance, Embedded Systems.