Authors : Abad, Jhon Lloyd ; Barzo, Shan Michael ; Fajardo, Jan Aron

Volume/Issue : Volume 10 - 2025, Issue 5 - May

Google Scholar : https://tinyurl.com/yzzk8h95

DOI : https://doi.org/10.38124/ijisrt/25may1106

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The rapid increasing demand in advent of technology needing to adopt to real-world instances, had led to the development of AI solutions for SEAIT in response for school uniform compliance. This study employs Machine Learning – School Uniform Detection System utilizing Incremental Process Model, an Agile Methodology that ensures systematic and adaptive presentation to system development. The system utilizes Machine Learning techniques, particularly camera vision, to accurately detect and fragment and confirm students’ uniforms in real time. By increasingly innovating and refining the model, the development process enhances system acceptability and accuracy while answering challenges such as variations in lighting, posture, and uniform designs. The study involves image pigmentations, feature extraction, and deep learning algorithms, allowing efficient uniform detection with less human intervention. The system assists school admin in enforcing school policies, reducing manual workload. Future innovations may include integrating facial recognition for customized monitoring and improving model with a more extensive dataset. Thus, this study must be implemented.

Keywords : Machine Learning, School Uniform Detection, Incremental Process Model, Computer Vision, Deep Learning, Feature Extraction, Image Processing, AI in Education, Uniform Compliance, Automated Monitoring.

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