Solar water desalination system based on machine learning

Ruiwu Liu

doi:10.1117/12.3004296

25 September 2023 Solar water desalination system based on machine learning

Ruiwu Liu

Proceedings Volume 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023); 1278807 (2023) https://doi.org/10.1117/12.3004296
Event: Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 2023, Kuala Lumpur, Malaysia

Abstract

In recent years, as global warming has become more severe, El Niño has swept the world, glaciers have melted, river flows have decreased, and freshwater scarcity has become increasingly frequent around the world. Moreover, the uneven distribution of freshwater resources and the lack of effective management of industrial and domestic wastewater emissions in some developing countries have strained the already scarce freshwater resources. In this study, a new water desalination system is invented to make the solar distilling process more efficient and intelligent. The system includes major components such as a water tank, outdoor solar water heaters, an advanced solar distiller, and hydraulic components such as vacuum pumps and check valves. At the same time, the project uses intelligent sensing devices such as flow meters, temperature sensors, and light intensity sensors, while the system can connect to Wi-Fi through the ESP8266 module to transmit sensor data back to Alibaba Cloud servers. What’s more, the project group uses neural network algorithms to optimize the parameters of the system, which makes the whole system learn by itself so that it can be more efficient.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ruiwu Liu "Solar water desalination system based on machine learning", Proc. SPIE 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 1278807 (25 September 2023); https://doi.org/10.1117/12.3004296

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KEYWORDS

Sunlight

Simulations

Machine learning

Sensors

Solar radiation models

Intelligence systems

Neural networks

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