Forecasting Vehicle Maintenance Needs and Breakdowns using Predictive Maintenance

Improving road safety has a direct impact on the lives of drivers as well as the costs incurred by companies operating commercial vehicles. One important aspect of road safety is timely and effective vehicle maintenance. By forecasting vehicle maintenance needs and predicting breakdowns before they occur, valuable insights can be provided to drivers and fleet managers ahead of time. This information allows them to make informed decisions on when to perform vehicle maintenance and avoid accidents arising from unexpected vehicle breakdowns while on the road. The goal of this project is to take advantage of Geotab’s data collected from more than 2 million connected vehicles to develop and evaluate models for forecasting vehicle maintenance needs and predicting malfunctions. The output of this project will be of value to Geotab’s customers, as well as to the wider community in understanding patterns for vehicle malfunctions and reducing accidents arising from them.

Faculty Supervisor:

Andrei Badescu

Student:

Partner:

Geotab Inc

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services; Transportation and warehousing

University:

University of Toronto

Program: