Passenger Evaluation in college bus using ML

Computer Engineering

The majority of university students commute between locations using the bus that the administration of the university provides. In order to improve the quality of bus services, analysis is needed to determine factors like the number of passengers and personal information about students or unknown individuals. This research study aims to construct a face recognition system based on student faces using convolution neural networks and the opencv environment. Additionally, it tests and validates the built system's performance for face categorization and passenger evaluation. Additionally, this system can use the Internet of Things to store passenger information in a MySQL database. This system uses the camera on a mobile phone with the assistance of the Droid Cam application, which supports libraries used for face recognition and classification, like OpenCV and face recognition, which is enhanced by the Convolution neural network model. In order to record the data in the database, this project can recognize the faces of the passengers as soon as they board the bus and identify whether they are students or unidentified individuals.

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