In the 21st century, transportation brought great convenience to people, but at the same time, automobile transportation is the major factor causing greenhouse gas emissions and climate change. Movements of the world towards green environments, there is hike in use and production of electric vehicles (energy vehicles). However, with the continuous growth in the number of energy vehicles, it is necessary for the government to provide strong support in the construction of charging piles. Real-time and effective management has become a practical problem for the relevant departments which needs to be solved. This paper uses the information research method to fuse the huge amount of heterogeneous data generated by the charging pile resultant to the new energy electric vehicle in the vehicle network and introduces cloud computing as its storage module to facilitate the storage and related expansion of the big data. This paper proposes a system scheme of heterogeneous data fusion based on cloud computing for the acquisition, storage, and fusion of heterogeneous data in the vehicle network. After testing the results, it shows that the system is stable and effective in practical application, which can meet the design requirements of the system. What is the significance of analyzing big data of charging point? Considering from the supply side, obtaining the user’s charging behaviour data is helpful to build a digital map of the charging pile of new energy vehicles, connect the service information between the vehicle enterprises and the charging pile enterprises, and provide the most comprehensive and effective real-time charging information covering the widest range of vehicles, which can solve many problems of information asymmetry in the current charging information service.

中文翻译：

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基于云存储的大数据融合在绿色交通中的应用：以医疗保健为例

进入21世纪，交通给人们带来了极大的便利，但与此同时，汽车交通是造成温室气体排放和气候变化的主要因素。世界向绿色环境发展，电动汽车（能源汽车）的使用和生产增加。但随着能源汽车保有量的不断增长，充电桩建设需要政府大力支持。实时有效的管理已成为相关部门亟待解决的现实问题。本文采用信息研究的方法，将充电桩产生的海量异构数据融合到车联网中的新能源电动汽车中，并引入云计算作为其存储模块，方便大数据的存储和相关扩展。 . 针对车联网中异构数据的采集、存储和融合，提出了一种基于云计算的异构数据融合系统方案。经测试结果表明，该系统在实际应用中稳定有效，能够满足系统的设计要求。分析充电点大数据有什么意义？从供给端考虑，