Transportations Delay & Breakdown Predicting System
Multimedia University | Malaysia
Ugenteraan Manogaran | Larviania Somasundram
This proposed project will ease the process of booking and managing transports using the help of machine learning technology. Using the machine learning technology, it is possible to predict the delays, duration of delays and breakdowns of vehicles even before the vehicles take off for a task. Using this information, the assigned routes, drivers and busses for tasks can be modified to prevent the delays or breakdown from occurring. However, it is only applicable in certain cases such as the occurrence is due to heavy traffic, accidents between other vehicles, vehicle breakdown due to delayed servicing of the vehicle, weather or the driver’s behavior itself. Fortunately, these are the most common cases why a delay occurs. Therefore, the goal of this proposed project is to ensure a smooth process in the transportation services. The proposed project is extensible to a number of transportation services such as emergency transportation such as ambulance services, fire brigade services and police services and other services such as public busses, school busses and private transportation service companies. However, in this project, we are focusing our application on school busses as a proof of concept. The reason for this is because of the publicly available dataset and the suitability for this project.