Evaluation of Intelligent Fleet Management Using Telematics Data

Abstract

The rapid digitization of transportation systems has accelerated the adoption of intelligent fleet management solutions driven by vehicle telematics data. Telematics platforms integrate sensors, global positioning systems, onboard diagnostics, and wireless communication to generate continuous streams of data related to vehicle location, driver behavior, fuel consumption, and mechanical health. This paper presents a journal-ready, long-form evaluation of intelligent fleet management systems that leverage telematics data to improve operational efficiency, safety, and sustainability. The study examines the architecture of modern telematics-based fleet management systems, data acquisition mechanisms, analytics techniques, and decision-support applications. Emphasis is placed on performance metrics such as fuel efficiency, maintenance optimization, route planning, and driver. behavior assessment. Drawing on empirical findings reported in recent literature and industry deployments, the paper evaluates the impact of telematics-driven intelligence on cost reduction and environmental performance. Challenges related to data quality, scalability, cybersecurity, and privacy are critically discussed. The paper concludes by identifying future research directions, including predictive analytics, integration with intelligent transportation systems, and the use of artificial intelligence to enable autonomous and adaptive fleet operations.