Smart Vehicle Tracking System with Predictive Analytics and Real-Time Web Monitoring

Author(s)	Indhu V, Gokul P, Jagatheeshwaran A, Arun P, Jeeva M
Country	India
Abstract	Conventional vehicle tracking systems typically provide location updates but offer limited predictive insight, fuel analysis, and driver-behavior assessment. This paper presents a web-based Smart Vehicle Tracking System developed to improve fleet monitoring, safety, and operational efficiency. Global Positioning System (GPS) data were processed through a Python-based analytics engine to estimate estimated time of arrival (ETA), calculate fuel consumption, score driving behavior, and detect route deviations. Evaluation results indicated 90% ETA accuracy, ±8% fuel error, 88% behavior detection accuracy, and alert delivery within 5 s.
Keywords	vehicle tracking, predictive analytics, ETA estimation, behavior scoring, route deviation detection
Field	Computer Applications
Published In	Volume 7, Issue 2, March-April 2026
Published On	2026-04-10
DOI	https://doi.org/10.63363/aijfr.2026.v07i02.4798

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