<![CDATA[The development of the Internet of Things (IoT) has transformed smart transportation systems and modern fleet management, with web technology serving as the integration platform connecting IoT devices, management systems, and users. This systematic research examines the implementation of web technology for real-time vehicle monitoring, machine learning-based route optimization, predictive maintenance, and analytics dashboards. The system architecture involves four layers: IoT (vehicle sensors), communication (MQTT, REST API, WebSocket), cloud computing (big data processing), and presentation (Progressive Web Apps, React/Vue.js). The system integrates GPS data, telemetry, fuel consumption, driving behavior, and traffic conditions for operational optimization. Research findings show operational efficiency improvements of 30-40%, maintenance cost reduction of 25%, fuel consumption decrease of 15-20%, and incident rate reduction of 35%. Challenges include data security, system interoperability, infrastructure scalability, protocol standardization, and legacy system integration. This research provides reference architecture, technology evaluation framework, best practices, and digital transformation roadmap for various organizational scales and fleet types.]]>
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