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Regular version of the site

Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
David Sogomonyan
Driver Categorization Model Based on Information from Car Sensors
Business Informatics
(Bachelor’s programme)
8
2017
The result of this work is the developed model that allows to predict the risk of an accident under certain external conditions and style of driving.

To enable the collection and storage of data has developed a special system, which included ELM327 adapter, Android smartphone and Google Spreadsheets. For the analysis of risk factors there were developed formulas for the statistical evaluation of time series.

After selecting the main methods and tools collection and further data analysis were carried out using machine learning. Testing of the system showed that the developed system is able to determine the danger of driving.

The purpose of this model is not to be a complete solution for the implementation, but to show the level of potential that machine learning and telematics have in motor insurance.

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