Knowledge Graph–Enhanced NB-IoT Architecture for Intelligent Educational Data Management and System Innovation

Abstract

This study proposes a Knowledge Graph–Enhanced NB-IoT Architecture to improve intelligent educational data management and support system innovation in learning environments. The purpose is to address limitations of traditional innovation and entrepreneurship education, which often lacks real-time contextual information and personalized guidance. The proposed approach integrates NB-IoT for distributed, real-time data acquisition with a domain-specific knowledge graph for semantic organization, correlation, and enrichment of learning resources. A multi-layer framework was designed to support data collection, knowledge representation, and intelligent recommendation processes. Experimental evaluation demonstrates that the architecture enhances the relevance of learning activities, improves resource organization, and delivers more accurate and personalized educational interventions. The results indicate that combining NB-IoT infrastructure with knowledge graph intelligence can significantly strengthen adaptive learning environments and better support the development of innovative competencies.