Miniature Multi-Ion Sensor Integrated With Artificial Neural Network
计算机科学
符号
算法
人工智能
数学
算术
作者
Yuncong Chen,Zheyuan Tang,Yunjiao Zhu,Michael J. Castellano,Liang Dong
出处
期刊:IEEE Sensors Journal [Institute of Electrical and Electronics Engineers] 日期:2021-10-05卷期号:21 (22): 25606-25615被引量:10
标识
DOI:10.1109/jsen.2021.3117573
摘要
Low-cost, accurate monitoring of macronutrient ions in soils, plants, and water is highly desired to improve fertilizer management for maximum profitability and minimum negative environmental impacts. Traditional ion-selective electrodes (ISEs) suffer from interference from non-target ions. This paper reports the integration of artificial neural networks (ANNs) and a miniature sensor containing an array of three ISE-based sensing elements to improve accuracy of the sensor in detecting and quantifying target nitrate ( ${\mathrm {NO}}_{3}^{-}$ ), phosphate (H 2${\mathrm {PO}}_{4}^{-}$ ), and potassium (K + ) ions in the environment. The sensor outputs of ${\text{NO}}_{3}^{-}$ , H 2${\text{PO}}_{4}^{-}$ , and K + ion concentrations are used to train and optimize ANNs. The optimized neural networks are applied to classify and estimate concentrations of the target ions in the presence of interfering ions. The ANN-assisted array of sensing elements reduces cross-sensitivity between these elements. The present sensor is validated with measurements of ${\text{NO}}_{3}^{-}$ , $\text{H}_{2} {PO}_{4}^{-}$ , and K + ions in soil solution, plant sap, and tile drainage water from crop fields.