Using AI and BES/MFC to decrease the prediction time of BOD(5) measurement

利用人工智能和生物电化学系统/微生物燃料电池缩短五日生化需氧量(BOD5)测量的预测时间

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Abstract

Biochemical oxygen demand (BOD) is one of the most important water/wastewater quality parameters. BOD(5) is the amount of oxygen consumed in 5 days by microorganisms that oxidize biodegradable organic materials in an aerobic biochemical manner. The primary objective of this research is to apply microbial fuel cells (MFCs) to reduce the time requirement of BOD(5) measurements. An artificial neural network (ANN) has been created, and the predictions we obtained for BOD(5) measurements were carried out within 6-24 h with an average error of 7%. The outcomes demonstrated the viability of our AI MFC/BES BOD(5) sensor in real-life scenarios.

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