Search

The Application of AI Technology in the Monitoring and Treatment

Author(s)

Haorui Sun*

Affiliation(s)

Jinan Foreign Language School, Jinan, China *Corresponding Author

Abstract

Water is essential to life, and its quality and efficient utilization are critical to sustainable development. Medical wastewater, with its complex composition and high environmental risk, can severely harm ecosystems and public health if discharged untreated. Traditional monitoring and treatment approaches often suffer from low efficiency, delayed feedback, limited early warning capabilities, and potential risks of secondary pollution. This study investigates the integration of artificial intelligence (AI) technologies into medical wastewater monitoring and treatment processes. A comprehensive AI-based framework is proposed, incorporating intelligent data collection, automated analysis, AI-assisted optimization of treatment processes, and smart operation and maintenance of equipment. The results suggest that AI significantly enhances the responsiveness, accuracy, and safety of wastewater management systems. By enabling real-time monitoring, predictive control, and adaptive treatment strategies, AI offers a transformative approach to overcoming the limitations of conventional methods. This research provides a novel solution to the pressing challenges of medical wastewater treatment and contributes to the advancement of intelligent, sustainable practices in environmental protection and public health management.

Keywords

AI; Medical Wastewater; Wastewater Monitoring; Wastewater Treatment

References

[1] He Shiding, Hu Kai, Han Yuwei et al. Research progress of medical wastewater disinfection technology. Water supply and drainage, 2022, 58(S2): 277- 282. [2] Wang Lei. Status and prospect of medical wastewater treatment technology. Guangdong Chemical Industry, 2023, 50(18): 106-107+127. [3] Zhang Linlin, Kou Xinxin. Research progress of medical wastewater treatment technology. Research on industrial innovation, 2021, 12: 62-64 [4] Nagpal M, Siddique MA, Sharma K, Sharma N, Mittal A. Optimizing wastewater treatment through artificial intelligence: recent advances and future prospects. Water Sci Technol, 2024, 90(3): 731-757. [5] Hejabi, N., Saghebian, S. M., Aalami, M. T., et al. Evaluation of the effluent quality parameters of wastewater treatment plant based on uncertainty analysis and post-processing approaches (case study). Water Science and Technology, 2021, 83(7): 1633- 1648. [6] Bahrampour, C., Ihsanullah, I., Naushad, M., et al. Applications of artificial intelligence in water treatment for optimization and automation of adsorption processes: Recent advances and prospects. Chemical Engineering Journal. 2023, 427: 130011. [7] Collaborative application of artificial intelligence and activated sludge simulation software in wastewater treatment. Water purification technology, 2024, 43(10): 48-56+85. [8] Tang Baishi, Hu Yibo, Jiang Haixin. Collaborative Application of Artificial Intelligence and Activated Sludge Simulation Software in Sewage Treatment. Water Purificaton Technology, 2024, 43(10): 48-56+85.