Machine Learning-Based Detection of 2 Riders of E-Scooters

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dc.contributor.advisorSzilágyi, Péter
dc.contributor.authorHammoud, Walid
dc.contributor.departmentDE--Műszaki Kar
dc.date.accessioned2025-09-04T15:10:21Z
dc.date.available2025-09-04T15:10:21Z
dc.date.created2025-05-12
dc.description.abstractThe thesis is about detecting the number of people on an e-scooter using supervised machine learning. The purpose of this project is to train a model to distinguish between single-driver and double-driver on an e-scooter, this should be done through a series of measurements with different people, people with experience, and not, those of different sizes and heights. After having some graphs using an accelerometer, the gathered data is used to train the model, and then it will be trained to differentiate between the number of people in an e-scooter.
dc.description.courseMechatronical Engineeringen
dc.description.degreeMSc/MA
dc.format.extent68
dc.identifier.urihttps://hdl.handle.net/2437/397240
dc.language.isoen
dc.rights.infoHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectMachine Learning
dc.subjectE-scooter
dc.subjectGyroscope
dc.subjectAccelerometer
dc.subjectSingle Rider
dc.subjectDual Rider
dc.subject.dspaceEngineering Sciences::Electrical Engineering
dc.titleMachine Learning-Based Detection of 2 Riders of E-Scooters
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