International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Vehicle Movement Detection using AI and ML

Author(s) Arjun Sansare
Country India
Abstract This master’s thesis focuses on vehicle detection and tracking. The research tries to detect vehicles in images
and videos. It deploys a dataset from Udacity in order to train the algorithms. Two machine learning algorithms.
Support Vector Machine (SVM) and Decision Tree have been developed for the detection and tracking tasks.
Python programming language have been utilized as the development language for the creation and training of
both models. These two algorithms have been developed, trained, tested, and compared to each other to specify
the weaknesses and strengths of each of them, although to present and suggest the best model among these two.
For the evaluation purpose multiple techniques are used in order to compare and identify the more accurate
model. The primary goal and target of the thesis is to develop a system in which the system should be able to
detect and track the vehicles automatically whether they are static or moving in images and videos. Efficient
management of vehicle traffic and parking is crucial for large campuses to ensure smooth operations and
enhance user experience. This problem statement addresses the need for an intelligent solution capable of
analyzing vehicle movement patterns and monitoring parking occupancy in real-time. The proposed solution
aims to analyze the frequency and timing of vehicle movements in and out of the campus, enabling the
identification of peak traffic times and movement patterns. By understanding these patterns, campus
administrators can optimize traffic flow, reduce congestion, and improve overall safety and efficiency.
Field Engineering
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-02-28
DOI https://doi.org/10.36948/ijfmr.2025.v07i01.35979
Short DOI https://doi.org/g86xb9
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