Journal of Intelligent Systems and Internet of Things JISIoT 2690-6791 2769-786X 10.54216/JISIoT https://www.americaspg.com/journals/show/3051 2019 2019 Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management, Bengaluru -560082, Karnataka, Orchid - 0000-0003-1368-0634, India Seema Seema Department of Computer Science & Applications, Maharshi Dayanand University, Rohtak, Haryana, India Seema Rani Associate Professor, Dept. of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India Ch Madhava Rao Professor and Head Department of AIML and IPR Cell Nitte Meenakshi Institute of Technology Bengaluru , Karnataka, India Piyush Kumar Pareek Department of Computer Science & Applications, Maharshi Dayanand University, Rohtak, Haryana, India Sandeep Dalal K R Managalam University, Gurugram, Haryana-122103, India Shweta Bansal 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 2024 303 323 10.54216/JISIoT.130224 https://www.americaspg.com/articleinfo/18/show/3051