| Details |
| Project Title | AI-Driven Adaptive Traffic Light Control System
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| Campus | Kampar campus |
| Stipend | RM2,000 per month
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| Entry Requirement | 1. Bachelor's degree in Computer Science, Engineering, or a related field, with a strong interest in AI and machine learning.
2. Proficiency in programming languages such as Python or Java.
3. Familiarity with deep learning frameworks like PyTorch or TensorFlow.
4. Strong proficiency in English, both written and spoken.
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| Job Description | 1. Literature Review: Conduct an in-depth literature review on AI applications in traffic management, focusing on adaptive and intelligent traffic signal control.
2. Data Collection & Preprocessing: Collect and preprocess data in a simulated environment to obtain traffic data, including vehicle counts, queue lengths, and traffic flow rates. Extract key traffic metrics and prepare them for model training.
3. Model Development: Design and implement an AI model to optimize traffic light timing using data generated from the traffic simulation.
4. Simulation Testing and Optimization: Test the model's effectiveness across different traffic scenarios in simulated environments, fine-tuning parameters to ensure realistic adaptability.
5. Documentation and Reporting: Analyze and document findings, contribute to academic publications, and prepare progress reports detailing improvements in traffic flow and model performance.
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| Field of study | Computer Science (Master of Science (Computer Science))
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| How to Apply | If you are interested, please contact Dr. Rahmad Sadli via email at rahmads@utar.edu.my
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