Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Machine Learning- Based Driving Assistance System for Lane and Drowsiness Monitoring Description An account of the resource Lane line detection is a vital component when driving heavy vehicles; this concept follows the path for driving a vehicle to prevent the risk of accidentally entering another lane without the drivers knowledge, which could result in an accident. To detect the lane, use frame masking and Hough line transformation with efficient machine learning algorithms, pre-processed and trained adequately for optimum accuracy as per the provided dataset to spot the white markings on both sides of the lane. Long-distance truck drivers suffer from sleep deprivation, making driving extremely dangerous while tired and they ignore the line markings and wander into the wrong lane. This chapter proposes a portable system that does not require any sensors or interference with the vehicles wiring system; instead, a system that fits on a windshield or any surface to monitor the actions of the driver, using computer vision and feature-extracted datasets within a trained neural network model using cameras. This driver-assisted system can detect drowsiness and give an alarm to wake up the driver by identifying the Region of Interest. These predictions are made based on eye movements, and the algorithm generates a score. The higher the score, the longer the time between alarms. 2024 Taylor &amp; Francis Group, LLC. Creator An entity primarily responsible for making the resource Ramasamy S.A.G. Source A related resource from which the described resource is derived Machine Intelligence: Computer Vision and Natural Language Processing, pp. 193-208. Publisher An entity responsible for making the resource available CRC Press Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003424550-10" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003424550-10</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173415740&amp;doi=10.1201%2F9781003424550-10&amp;partnerID=40&amp;md5=18e5d624a1730fadfbe572b2c357a582" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173415740&amp;doi=10.1201%2f9781003424550-10&amp;partnerID=40&amp;md5=18e5d624a1730fadfbe572b2c357a582</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-100096031-0; 978-103220199-3 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ramasamy S.A.G., Christ University, Bangalore, India