Abstract
The implementation of this project can effectively solve the problem of water shortage in urban economic development, change the single water supply pattern of Nansha District of Guangzhou drawing water from shawan waterway in the lower beijiang River and Shenzhen and Dongguan drawing water from Dongjiang river, and improve the water supply safety and emergency reserve capacity.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Information Technology;Researchers at Zhejiang University Have Reported New Data on Information Technology (data-driven Solution for Optimal Units of Smart Water Conservancy). Internet WeeklyNews (2020)
Zhang, J., Liu, J., Jin, J.: Understanding and thinking on intelligent water conservancy. J. Water Cons. Water Transp. Eng. 2019(06), 1–7 (2019)
Ge, Z.: Understanding and thinking of intelligent water conservancy construction in Shandong Province. Water Cons. Inf. 2019(05), 6–8+19 (2019)
Sheng, X., Zuo, Z.: Application research of BIM technology in intelligent water conservancy of Hunan Province. Hunan Water Cons. Hydropower 2019(05), 8–11 (2019)
Jiang, Y., Ye, Y., Zhao, H.: Research on the connotation characteristics, infrastructure and standard system of intelligent water conservancy big data. Water Cons. Inf. 2019(04), 6–19 (2019)
Zhan, Q., Zhang, C.: Network security of intelligent water conservancy overall scheme. Water Cons. Inf. 2019(04), 20–24+29 (2019)
Lu, X., Liu, S., Guo, X., Ma, Z.: Conception and thinking of intelligent water conservancy construction in Sichuan Province. Water Cons. Inf. 2019(03), 4–9 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Yang, T., Ma, J. (2021). Intelligent Water Scheme Design Based on Artificial Intelligence, Internet of Things and Big Data Technology. In: Guan, M., Na, Z. (eds) Machine Learning and Intelligent Communications. MLICOM 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 342. Springer, Cham. https://doi.org/10.1007/978-3-030-66785-6_46
Download citation
DOI: https://doi.org/10.1007/978-3-030-66785-6_46
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-66784-9
Online ISBN: 978-3-030-66785-6
eBook Packages: Computer ScienceComputer Science (R0)