Search

Zhang, N., 2019. Architecture research and design of the IoT middleware for marine logistics. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 196–199. Coconut Creek (Florida), ISSN 0749-0208. Modern marine logistics is a kind of integrated logistics. The data collected and transmitted has the characteristics of a large number, a wide variety and a high degree of heterogeneity. Based on the above characteristics, this paper presents a design scheme of internet of things (IoT) middleware, focusing on the application system and communication system structure of the marine logistics IoT middleware. The configuration middleware is used to complete the routing configuration and topology adjustment of the communication system. The hierarchical and modular design scheme is combined with the adaptive fractional interval equalization method to optimize the communication network middleware and improve the signal stability. The data sensing layer, the data and equipment control layer, and the business management layer constitute the application system of the marine logistics IoT middleware, and the functions are analyzed and designed. Finally, the effective management, state monitoring and interaction of the marine logistics are realized. [ABSTRACT FROM AUTHOR]

Zhang, N. and Zheng, K., 2020. Research and design of the architecture of the marine logistics information platform based on big data. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 628–632. Coconut Creek (Florida), ISSN 0749-0208. Using Internet of Things (IoTs) and cloud computing technologies in the era of big data to design a highly shared marine logistics information platform is the basis for realizing the information, efficiency, and intelligence of its logistics process. This research integrated big data thinking and sharing concepts into shared logistics, designed the architecture of a highly shared marine logistics information platform, and proposed an implementation method and application model for the architecture. The platform design introduces artificial intelligence and IoT technologies based on GPS, general packet radio service, and automatic identification system. The platform realizes real-time positioning and monitoring of land and sea cargo, which greatly improves the efficiency of marine logistics management. [ABSTRACT FROM AUTHOR]