aspg-18-3051-1792025814 20261015005654 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Intelligent Systems and Internet of Things JISIoT 2769-786X 2690-6791 2024 13 2 Veena R S Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru -560082, Karnataka, Orchid - 0000-0003-1368-0634, India Seema Rani Department of Computer Science & Applications, Maharshi Dayanand University, Rohtak, Haryana, India Ch Madhava Rao Associate Professor, Dept. of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India Piyush Kumar Pareek Professor and Head Department of AIML and IPR Cell Nitte Meenakshi Institute of Technology Bengaluru , Karnataka, India Sandeep Dalal Department of Computer Science & Applications, Maharshi Dayanand University, Rohtak, Haryana, India Shweta Bansal K R Managalam University, Gurugram, Haryana-122103, India Vehicle tracking is one of computer vision's most important applications, with applications ranging from robotics and traffic monitoring to autonomous vehicle navigation and many more. Even with the significant advancements in recent research, issues like occlusion, fluctuating illumination, and fast motion still need to be addressed, calling for more investigation and creativity in this field. This study performs a thorough examination of various vehicle-tracking approaches and suggests a thorough classification scheme that divides them into four main categories: strategies that rely on features, segmentation, estimate, or learning. Two well-known methods are highlighted specifically in the estimation-based category: particle filters and Kalman filters. 2024 303 323 3051 https://creativecommons.org/licenses/by/4.0/ 10.54216/JISIoT.130224 https://americaspg.com/journal/18/article/3051 https://americaspg.com/storage/91721306829.pdf