지능형 교통 시스템을 위한 계층적 인지 사물인터넷(CIoT) 프레임워크
Layered Cognitive Internet of Things (CIoT) Framework for Intelligent Transportation Systems
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With the growing demand for smarter, safer, and more efficient transportation systems, the integration of Cognitive Internet of Things (CIoT) into Intelligent Transportation Systems (ITS) is becoming increasingly critical. This paper proposes a layered CIoT framework that enhances decision-making, real-time data processing, and adaptive communication within Vehicular Ad Hoc Net works (VANET) and Vehicle-to-Everything (V2X) environments. By analyzing the hierarchical structure of CIoT—comprising the cognitive, network, data, and application layers—we demonstrate how CIoT can address the limitations of conventional ITS, such as lack of adaptability and intelligence. This framework supports context-aware traffic management, collision avoidance, and optimized routing through dynamic learning and reasoning capabilities. The study further presents implementation scenarios and discusses key challenges including interoperability, security, and infrastructure constraints. Ultimately, this paper aims to contribute to the development of a robust, scalable, and intelligent transportation ecosystem through the CIoT paradigm.
Abstract
With the growing demand for smarter, safer, and more efficient transportation systems, the integration of Cognitive Internet of Things (CIoT) into Intelligent Transportation Systems (ITS) is becoming increasingly critical. This paper proposes a layered CIoT framework that enhances decision-making, real-time data processing, and adaptive communication within Vehicular Ad Hoc Net works (VANET) and Vehicle-to-Everything (V2X) environments. By analyzing the hierarchical structure of CIoT—comprising the cognitive, network, data, and application layers—we demonstrate how CIoT can address the limitations of conventional ITS, such as lack of adaptability and intelligence. This framework supports context-aware traffic management, collision avoidance, and optimized routing through dynamic learning and reasoning capabilities. The study further presents implementation scenarios and discusses key challenges including interoperability, security, and infrastructure constraints. Ultimately, this paper aims to contribute to the development of a robust, scalable, and intelligent transportation ecosystem through the CIoT paradigm.