Utilizing artificial intelligence for road safety Truck tanker part faulty classification via sound detection

Muhammad Daniel Rahim, Mary Magdalene (2023) Utilizing artificial intelligence for road safety Truck tanker part faulty classification via sound detection. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Road safety is a critical concern, particularly in the transportation of hazardous materials. This study focuses on developing an innovative approach to enhance road safety by utilizing artificial intelligence (AI) techniques for the classification of faulty truck tanker parts using sound detection. The proposed methodology involves collecting sound data from truck tankers under various conditions and employing machine learning algorithms to classify the acoustic patterns associated with different types of faults. A comprehensive dataset is created by capturing sounds from diverse tanker models and fault scenarios. Through rigorous training and validation, the AI model demonstrates high accuracy in identifying specific faulty parts based on sound patterns. The model achieves an average precision rate of 90% in classifying faulty tanker parts, such as malfunctioning valves, leakage in pipelines, or structural integrity issues. The successful implementation of this AI-based system offers several benefits. It enables recorded detection and classification of faulty parts, allowing for timely maintenance and preventing potential accidents caused by equipment failures. Moreover, it reduces the dependency on manual inspections, which can be time-consuming and prone to errors. The findings of this research contribute to the growing field of AI applications in road safety and emphasize the potential of sound detection as a reliable method for fault classification in truck tankers. This study demonstrates the feasibility of integrating AI technologies into existing road safety measures, ultimately promoting safer transportation practices and mitigating risks associated with hazardous material transportation.

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