Ken Chen
ABSTRACT
With the continuous development and wide application of big data and artificial intelligence technology, how to efficiently use and mine the whole process data of university hydropower models, perception, business and flows, and realize the transformation of informationization of hydropower management to intelligentialize and wisdom, it has become one of the main tasks in the construction of universitiy informatization under the strategy of advocating energy conservation, lowcarbon sustainable development. Combining with the actual demand of university hydropower management, managing and serving the whole process of hydropower data collection, storage, analysis, monitoring and decision-making assistance, this paper proposes the architecture of an intelligent decision-making service platform for university hydropower on big data, and sorts out the core and key technologies in the platform development process and the current mainstream development frameworks and tools to provide technical references for the realization of intelligent hydropower management and application services in universities, and promote the overall planning and step-by-step implementation of smart campuses.
- Liang J, “Research on the Application of Big Data in the Informatization of Higher Education Management Mode,” 2020 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS), 2020.Google Scholar
Cross Ref
- Zhao L, Zhang J L, Liang R B, , “Building Energy Consumption Monitoring System in the Application of Conservation-Oriented Campus,”. Applied Mechanics & Materials, pp. 209-211:1783-1787, 2012.Google ScholarCross Ref
- Yu Peng, Li Yan, “Research on University Data Governance Under the Perspective of Big Data,” Mordern Educational Tachnology, vol. 28, pp. 60-66, 2018.Google Scholar
- Yao Sheng-wu, “Design of Campus Hydropower Management Intelligent Management System Based on Integrated Platform,” Telecom Power Technology, vol. 36, pp. 41-42, 2019.Google Scholar
- Tan Wen-sheng, Wan Yuan, Pan Ping-heng. “Intelligent decision system of hydropower based on big data technology,” Mechanical & Electrical Technique of Hydropower Station, vol. 42, pp. 9-12, 2019.Google Scholar
- Youge B , Zongbi H, Xiaohui J I, “Research and Application of Intelligent Patrol-inspection Robot for Hydropower Plant based on Strong Artificial Intelligence,” Hydropower and Pumped Storage, 2019.Google Scholar
- Zhao Yangchen, “Research on the Architecture of Big Data Analysis Platform from the Perspective of Information Analysis,” Modern Information Technology, vol. 3, pp. 160-161, 2019.Google Scholar
- Tao Xue-jiao, Hu Xiao-feng, Liu Yang, “Overview of Big Data Research ,” Journal of System Simulation, vol. 25, pp. 142-146, 2013.Google Scholar
- Peng Xiaosheng, Deng Diyuan, Cheng Shijie, , “Key Technologies of Electric Power Big Data and Its Application Prospects in Smart Grid,” Proceedings of the CSEE , vol. 35, pp. 503-511, 2015.Google Scholar
- Gao Ai-yuan, Luo Ren-cai, Yu Zhi-qiang, , “State analysis method of intelligent hydropower station based on big data,” Mechanical & Electrical Technique of Hydropower Station, vol. 42, pp. 37-40. 2019.Google Scholar
- Ma Xiaodan, “Research and Application of data analysis and data mining based on electric power big data platform,” North China Electric Power University, 2016.Google Scholar
- Huang Zongbi, “Intelligent Hydropower and AI Big Data Application,” Hydropower and Pumped Storage, vol. 5, pp. 1-5, 2019.Google Scholar
Recommendations
Service-Generated Big Data and Big Data-as-a-Service: An Overview
BIGDATACONGRESS '13: Proceedings of the 2013 IEEE International Congress on Big DataWith the prevalence of service computing and cloud computing, more and more services are emerging on the Internet, generating huge volume of data, such as trace logs, QoS information, service relationship, etc. The overwhelming service-generated data ...
Responsible Big Data Analytics for E-Business Services
ICBDR '21: Proceedings of the 5th International Conference on Big Data ResearchThis paper examines responsible big data analytics for e-business services and looks at how to use responsible big data analytics to obtain responsible e-business services. It addresses why responsibility matters to big data analytics and e-business ...
The implementation of data storage and analytics platform for big data lake of electricity usage with spark
AbstractElectricity data could generate a large number of records from smart meter day by day. The traditional architecture might not properly handle the increasingly dynamic data that need flexibility. For effective storing and analytics, efficient ...
Comments