Economic growth has always been one of the hottest topics in economic research. Behind the rapid economic growth, the economic gap between regions is gradually widening, and the internal gap will have an impact on the overall coordination of economic growth. Research on the convergence of economic development and its causes has great strategic significance for narrowing the differences in raising economy among regions. In recent years, the impact of big data on economic analysis has become more and more obvious, and this fact has attracted the attention of the academic community. Big data are a new strategic resource and a tool for assessing economic trends. Adding big data technology to the research on the convergence raise of economics can predict the law of data changes, reduce data errors, optimize research results, and provide a more scientific basis for the coordinated development of regional economies. Based on big data theory and technology, this paper uses a spatial econometric model to empirically analyze the convergence of regional economic growth and its influencing factors. The experimental results show that the research on the convergence mechanism and spatial relationship of economic growth in the context of big data can improve the accuracy of the convergence analysis of economic growth to a certain extent. Through modeling analysis, the accuracy of economic convergence is improved by 4.1%. The utilization of big data in a trend of economic development makes the analysis results more reasonable and has greater reference value.
Environmental Sensor Networks (ESNs)" are a subset of sensor networks which are specifically tuned to an environmental application. In general, there are three main subsystems in the whole infrastructure of ESNs: (1) Data acquisition subsystem; (2) Data communication subsystem; (3) Data management subsystem. Compared with two former ones, the research on data management subsystem has not been attached more importance. However, with the number of diverse sensors is increasing, integrating, sharing and visualizing the monitored data among the isolated sensor networks has become a critical problem. Thus, this paper introduces the design and implementation of data management subsystem in ESNs. The design is based on SOA (Service Oriented Architecture), for the monitored data is distributed, multiple sourced, and heterogeneous. RIA (Rich Internet Application) is the main developing mode to implement the data management subsystem. If it is combined with the whole infrastructure of ESNs efficiently, the data management subsystem can obtain more information directly, and visualize them more quickly.
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