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dc.contributor.authorNissanka, PC
dc.contributor.authorMaduranga, MWP
dc.date.accessioned2024-03-25T09:35:20Z
dc.date.available2024-03-25T09:35:20Z
dc.date.issued2014-01-17
dc.identifier.urihttp://ir.kdu.ac.lk/handle/345/7520
dc.description.abstractLogistics in the transportation industry face ongoing difficulties, particularly in main- taining driver safety and improving operational efficiency. The frequency of accidents involving drivers who are intoxicated or fatigued is a major problem in the real world. In this study, we suggest an integrated system which includes modern technologies such as alcohol detectors, eye-tracking cameras, global positioning system, and temperature monitors. Our solution involves using smart sensors and intelligent machine learning algorithms to detect alcohol levels and spot signs of driver fatigue by analyzing their eye movements. Not only does the solution ensure compliance with safety regulations but it also allows for real-time data collection and analysis are emphasized here, making our system not just safer but more efficient for logistic operations. In the future, transportation will lean heavily on automated drones and self-driving vehicles, especially for the final parts of deliveries. These advancements mean goods will get delivered faster, accounting for less traffic, and logistics will become more eco-friendly.en_US
dc.language.isoenen_US
dc.subjectTransportation tracking systemen_US
dc.subjectGlobal positioning systemen_US
dc.subjectBlockchainen_US
dc.subjectReal time monitoringen_US
dc.subjectSustainable logisticsen_US
dc.titleTransportation Tracking System: Technologies and Applications for Logistic Firmsen_US
dc.typeArticle Abstracten_US
dc.identifier.facultyFaculty of Computingen_US
dc.identifier.journal4th Student Symposium of Faculty of Computingen_US
dc.identifier.pgnos25en_US


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