A Brief Discussion on the Design Scheme of the University State-owned Asset Management Platform Based on the Internet of Things
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Graphical Abstract
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Abstract
This paper conducts an in-depth analysis of current state-owned asset management in higher education institutions, exploring its characteristics, current status, and informationization development. The study reveals that university asset management primarily adopts physical asset management as its foundation, emphasizing consistency between accounting records and physical inventory, while implementing an “integrated + categorized” management model. However, significant disparities in informationization levels persist, manifesting as tendencies to prioritize operations over data management, emphasize localized solutions over systematic integration, favor software development over hardware infrastructure, rely on manual control rather than intelligent systems, and focus on administration rather than service delivery.To address these challenges, the research employs structured questionnaires to investigate universities directly under the Ministry of Education, identifying critical issues in current asset management practices. Through case analysis of an IoT-based asset management system implemented in an eastern Chinese university, the paper proposes a comprehensive IoT-enabled management platform design. The architecture features: hierarchical structure design, perception layer optimization, network layer expansion, data layer enrichment, and application layer interface design.Key solutions emphasize standardized signal protocols, deployment of integrated sensing devices, flexible phased implementation, network layer technological expansion, integration of data processing tools, diversified data output, and personalized interface design. System log data mining is utilized to enhance management assistance. This research aims to elevate university state-owned asset management through IoT technologies, improve asset utilization efficiency, and provide practical references with continuous optimization pathways for institutional implementation.
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