Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 7, 09 October 2023
Open
Access | Article
Research of ecological environment monitoring based on artificial intelligence
* Author to whom correspondence should be addressed.
Abstract
Traditional models of environmental supervision no longer suffice to meet the challenges of contemporary environmental governance as the tension between protecting the environment and fostering economic development grows. Given this context, ecological environment intelligent supervision has become an essential way and means to safeguard the green mountains. Comprehensive environmental regulation requires the use of cutting-edge technology like artificial intelligence, big data analytics, cloud computing, the internet of things, and online monitoring systems. Simultaneously, the internet and digital technology can enhance the quality of environmental protection decisions and the extent to which they are monitored. Artificial intelligence has the potential to improve the effectiveness of ecological environment supervision and protection, addressing issues such as a lack of human resources and an overabundance of job pressure. This paper used a literature review as its research method, studying articles in the field to learn about the current state of artificial intelligence technology in ecological environment monitoring and governance, its potential future uses, and how to best protect the planet's delicate ecosystems.
Keywords
artificial intelligence, intelligent supervision, environmental protection, economic development
References
1. Wang Jiajun. Research on the application of artificial intelligence technology in the field of ecological environment supervision [J]. Public Standardization, 2022(13):150-152.
2. Zhang Hui. Research on the integration path of artificial intelligence in ecological environment governance [J]. Leather Making and Environmental Protection Technology, 2022,3(05):176-178.
3. Li Jing, He Zhenming, Xu Jiaqi, Wang Jingjing, Chen Hao. Application of artificial intelligence in extreme weather [J]. Science and Technology Innovation, 2020, (23):59-62.
4. Dong Kuicai. The Research and application of Artificial Intelligence in Ecological monitoring of Sanjiangyuan Area [J]. Qinghai Science and Technology, 2023, 30(02):44-48.
5. Xu Ailan, Zhang Zaifeng, Sun Qiang, Zhu Yanmin, Peng Xiaoyan, Yu Xiangxiang. Construction of artificial intelligence air quality forecasting system based on deep learning [J]. China Environmental Monitoring, 2021,37(02):89-95.
6. Zhang Chen, Tang Wei, Xiao Jie, Tao Tong, Yuan Wenhua, Du Jijun, Shu Yun. Development and application of air quality prediction system based on artificial intelligence [J]. Environmental Science and Technology, 2020,43(S2):188-193.
7. Wang Lianqiang, Wu Hailong, Tao Junyi. Application of Internet of Things and Artificial Intelligence in the process of ecological water environment governance [J]. Science and Technology Innovation and Application,2020(02):160-162.
8. Wei Xiaoshu, Gao Hongjie, Chen Yuanhang, etc. Research progress of artificial intelligence technology in water pollution treatment [J]. Journal of Environmental Engineering Technology,2022,12(06):2057-2063.
Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2023 International Conference on Environmental Geoscience and Earth Ecology
- ISBN (Print)
- 978-1-83558-015-8
- ISBN (Online)
- 978-1-83558-016-5
- Published Date
- 09 October 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/7/20230120
- Copyright
- 09 October 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited