A bachelor project runned by four Chalmers students. The project focuses on the development of an AI-based tool to assist referees in badminton by accurately assessing the shuttlecock's height at the moment of service. In recent years, technological solutions such as VAR in football and Hawk-Eye in tennis have transformed decision-making processes in sports by minimizing human error. Badminton faces similar challenges, particularly with service height rules introduced by the Badminton World Federation (BWF) in 2018, which aim to ensure fair play by setting a fixed height of 1.15 meters for legal serves. However, these rules remain inconsistently applied due to reliance on subjective human judgment. This project proposes an AI-driven solution that uses video analysis and object detection techniques to address this issue. By implementing a pre-trained model, such as YOLOv8, fine-tuned for badminton-specific scenarios, the system will detect the shuttlecock's position and calculate its height with high accuracy and minimal delay. The pipeline will integrate several steps, including object detection, collision detection, and distance calculation, to provide real-time feedback on whether a serve meets the height requirement. The solution will prioritize accessibility and cost-efficiency, making it feasible for both professional and amateur use. Ethical considerations include ensuring transparency in how the model operates and maintaining trust among players, referees, and audiences. Additionally, efforts will be made to handle training data responsibly, safeguarding individual privacy. By creating a reliable and user-friendly product, this project aims to enhance fairness in badminton matches, reduce stress on referees, and contribute to the standardization of service height enforcement across all levels of the sport. The tool will also serve as an example of how AI can support decision-making in sports while preserving the integrity of the game.