This study addresses the inefficiency of logistics systems caused by data fragmentation, lack of real-time transparency, and weak integration of business processes and digital technologies. The relevance of the study is driven by the growing demand for adaptive and sustainable supply chains in the face of global challenges and increasing digitalization. The goal of the study is to develop a unified system for integrating Enterprise Architecture (EA) and Internet of Things (IoT) technologies to optimize logistics operations. The study uses a qualitative methodology based on a systematic literature review and multivariate analysis of real-world implementations, including DHL Resilience360, Continental Tires, Union Pacific Railroad, and reference architectures based on the Internet of Things. The study follows a structured sequence: literature selection, thematic analysis, case comparison, and generalization into a generalized architectural model. The results show that integrating the Internet of Things into performance management systems enhances real-time transparency, preventive maintenance efficiency, and dynamic routing, resulting in a 20-30% improvement in efficiency. A multi-level EA-IoT architecture model is proposed, combining the levels of data collection, communication, processing, and application according to the application areas of the enterprise architecture. The research results confirm that the integration of EA-IoT provides a scalable and sustainable foundation for intelligent logistics systems and addresses the existing gaps in disparate research.