Research on Application of Big Data Technology in Ecological Environment Protection

2021 ◽  
Keyword(s):  
Big Data ◽  
Ecological Environment ◽  
Environment Protection ◽  
Research On Application ◽  
Big Data Technology

scholarly journals Construction of Ecological Environment Information System Based on Big Data: A Case Study on Dongting Lake Ecological Area

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Diandi Wan ◽  
Shaohua Yin
Keyword(s):  
Information System ◽  
Big Data ◽  
Rapid Development ◽  
Dongting Lake ◽  
Ecological Environment ◽  
Ecological Problem ◽  
Collection Data ◽  
Technology Trend ◽  
Big Data Technology

With the rapid development of cloud computing, Internet of Things, and other technologies, the information technology trend led by “big data” has an impact on all fields. The application of big data technology in the field of ecological environmental protection enables accurate and comprehensive ecological information collection, data analysis, and mining, accurate ecological problem identification, and effective solution. Taking Dongting Lake Ecological Area as an example, this paper constructs an ecological environment information system based on big data and expounds its specific application in water, atmosphere, soil environment monitoring, and pollution control, aiming to provide a reference for the application of big data technology in the field of ecological environment protection in Dongting Lake Ecological Area and more effectively maintain the ecological environmental quality and safety in the area.

scholarly journals Multi-source Heterogeneous Ecological Big Data Adaptive Fusion Method Based on Symmetric Encryption

2021 ◽  
pp. 08-20
Author(s):  
Manal .. ◽  
◽  
◽  
Ahmed N. Al Al-Masri
Keyword(s):  
Sustainable Development ◽  
Economic Development ◽  
Big Data ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Ecological Environment ◽  
Symmetric Encryption ◽  
Environment Protection ◽  
Adaptive Fusion

In recent years, with the rapid development of the domestic economy, the concept of sustainable development has been paid more and more attention. Ecological environment protection is more and more important, and the ecological environment is closely related to economic development. How to measure the relationship between the two is very important. Whether it is to build ecological environment protection or to ensure sustainable development of the economy, we should take the green development concept as a guiding concept, promote ecological economic development, and study the integration of ecological data is of great significance for solving these problems. The research of this thesis studies the multi-source heterogeneous (MSH) ecological big data (BD)adaptive fusion based (FM) based on symmetric encryption. This paper sets up a comparative experiment, multi-sensor (MS) data fusion based (DFM) based on Rough set theory, MSH data fusion based on data information conversion. The method is compared with the symmetric fusion MSH BD adaptive FM proposed in this paper. The results show that the MSH DFM based on Rough set theory has the highest confidence of 0.812; the MSH DFM based on data information conversion has the highest confidence of 0.68; based on symmetric encryption MSH BD The fusion confidence of the adaptive FM is up to 0.965, and the MSH ecological BD adaptive FM based on symmetric encryption is superior.

scholarly journals Design of Intelligent Manufacturing Big Data Cloud Service Platform

2018 ◽  
Vol 153 ◽  
pp. 08005
Author(s):  
Danlin Cai ◽  
Mingyu Chen ◽  
Daxin zhu ◽  
Junjie Liu
Keyword(s):  
Big Data ◽  
Manufacturing Industry ◽  
Process Management ◽  
Cloud Service ◽  
Intelligent Manufacturing ◽  
Manufacturing Industries ◽  
Ecological Environment ◽  
Industrial Big Data ◽  
Cloud Service Platform ◽  
Big Data Technology

With the coming of the intelligent manufacturing, the technology and application of industrial big data will be popular in the future. The productivity, competitiveness and innovation of the manufacturing industries will be improved through the integrated innovation of big data technology and industries. Besides, products, production process, management, services, new form and new models will be more intellectualized. They will support the transformation and upgrading of manufacturing industry and the construction of an open, shared and collaborative ecological environment for intelligent manufacturing industry.

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