Abstract
In recent years, China’s aquaculture industry is booming. Aquaculture is favored by the majority of people because of its good nutritional value and sweet taste. The huge demand also makes the scale of aquaculture expanding. At present, China's aquaculture is mostly extensive management type, and there are still a lot of problems. The backward management of aquaculture water quality leads to the inability to guarantee the aquaculture quantity. Therefore, maintaining the aquaculture environment and ensuring the stable growth of aquaculture quantity are the current problems to be solved. In this paper, based on the Internet of things (IOT) technology, taking aquaculture water environment as the research object, an intelligent monitoring system (IMS) of aquaculture water environment is designed and developed. This paper studies and analyzes the overall framework of the IMS, and constructs the IMS of aquaculture water environment by realizing the software design of the monitoring system, which integrates control circuit, information collection, data transmission and mobile terminal monitoring. In this paper, the designed aquaculture water environment IMS is put into use, and the feasibility of the monitoring system is verified by analyzing the data comparison of each platform of the IMS and the sensor test data of the IMS. The experimental results show that the measurement accuracy of the sensor has a certain accuracy and fluctuates with time. At 2:00, the temperature of water environment is 22.4 ℃, the dissolved oxygen value is 8.3%, and the pH value is 9.5%; at 7:00, the temperature of water environment is 27.5 ℃ the dissolved oxygen value is 7.3%, and the pH value is 7.8%; at 12:00, the temperature of water environment is 30.5 ℃, the dissolved oxygen value is 5.7%, and the pH value is 7.1%; at 17:00, the temperature of water environment is 27.1 ℃, the dissolved oxygen value is 3.1%, and the pH value is 7.6%; at 22:00, the temperature of water environment is 27.4 ℃, the dissolved oxygen value is 8.6%, and the pH value is 8.4%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Shi, B., Victor, S., Zhao, D., et al.: A wireless sensor network-based monitoring system for freshwater fishpond aquaculture. Biosys. Eng. 17(2), 57–66 (2018)
Embug, A.J., Ibrahim, A., Hamzah, M., et al.: A review on visual water quality monitoring system in precision aquaculture. Appl. Mech. Mater. 89(2), 23–30 (2019)
Ismail, R., Shafinah, K., Latif, K.: A proposed model of fishpond water quality measurement and monitoring system based on Internet of Things (IoT). IOP Conf. Ser. Earth Environ. Sci 494(1), 012016 (10pp) (2020)
Su, B., Kelasidi, E., Frank, K., et al.: An integrated approach for monitoring structural deformation of aquaculture net cages. Ocean Eng. 219(1), 108424 (2021)
Yogev, U., Atari, A., Gross, A.: Nitrous oxide emissions from near-zero water exchange brackish recirculating aquaculture systems. Sci. Total Environ. 628–629(7), 603–610 (2018)
Calone, R.G., et al.: Improving water management in European catfish recirculating aquaculture systems through catfish-lettuce aquaponics – ScienceDirect. Sci. Total Environ. 68(7), 759–767 (2019)
Milne, J.E.: Monitoring and modelling total phosphorus contributions to a freshwater lake with cage - aquaculture. Aquac. Res. 48(1), 8463–8466 (2017)
Ma, J., Niu, X., Zhang, D., et al.: High levels of microplastic pollution in aquaculture water of fish ponds in the Pearl River Estuary of Guangzhou, China. Sci. Total Environ. 74(4), 140679 (2020)
Ye, L., Liu, G., Yao, T., et al.: Monitoring of antimicrobial resistance genes in the spotted sea bass (Lateolabrax maculatus): association with the microbiome and its environment in aquaculture ponds. Environ. Pollut. 27(6), 116714 (2021)
Shareef, Z., Reddy, S.R.N.: Deployment of sensor nodes for aquaculture in western Godavari delta: results, challenges and issues. J. Reliable Intell. Environ. 6(3), 153–167 (2020). https://doi.org/10.1007/s40860-020-00108-z
Wei, Y., Wei, Q., An, D.: Intelligent monitoring and control technologies of open sea cage culture: a review. Comput. Electron. Agric. 169(1–4), 105119 (2020)
Ayodele, A.T., Bolaji, B.O., Arowolo, M.O., et al.: Overview of sensor analysis for health monitoring - an expert system for catfish pond. IOP Conf. Ser. Mater. Sci. Eng. 1107(1), 012065 (9pp) (2021)
Acknowledgements
This article is the result of a research project funded by Jiangxi Thomson Reuters Information Technology Co., Ltd.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Yang, Y. (2022). Intelligent Monitoring System of Aquaculture Water Environment Based on Internet of Things. In: Sun, S., Hong, T., Yu, P., Zou, J. (eds) Signal and Information Processing, Networking and Computers. ICSINC 2021. Lecture Notes in Electrical Engineering, vol 895. Springer, Singapore. https://doi.org/10.1007/978-981-19-4775-9_156
Download citation
DOI: https://doi.org/10.1007/978-981-19-4775-9_156
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-4774-2
Online ISBN: 978-981-19-4775-9
eBook Packages: Computer ScienceComputer Science (R0)