Toward ML-Based Application for Vehicles Operation Cost Management

This paper presents the design and implementation of a web-based application for managing vehicle operating costs. The application is intended to help vehicle users control and optimize the money spent on the maintenance of both a single vehicle and a group of vehicles (fleet) for the company. Moreover this application aims to collect data that will then serve as sample files that will then be used in a machine learning application. At the beginning of the work, the methodology and requirements to be met by the web application were discussed. In the following parts of the work, the implementation of the web application and tests of the application are presented. At the end of the work, proposals for further development of the application and conclusions of the work are presented. In the era of electric vehicles, such applications will play an increasingly important role, including as journey calculators (charging plans, etc., taking into account journey times, distance covered, stopping times, minimizing energy consumption, etc.), hence the role of machine learning (ML) will grow, as, for example, as a route is covered, the software will recalculate data and alternative options in real time, which can be reflected in ERP logistics and enterprise fleet management systems for sustainability.