Miniature Multi-Ion Sensor Integrated With Artificial Neural Network
Miniature Multi-Ion Sensor Integrated With Artificial Neural Network
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DOI：
10.1109/jsen.2021.3117573
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发表时间：
2021-11
影响因子：
4.3
通讯作者：
Yuncong Chen;Zheyuan Tang;Yunjiao Zhu;M. Castellano;Liang Dong
中科院分区：
文献类型：
--
作者：
Yuncong Chen;Zheyuan Tang;Yunjiao Zhu;M. Castellano;Liang Dong
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 (H2 ${\mathrm {PO}}_{4}^{-}$ ), and potassium (K+) ions in the environment. The sensor outputs of ${\text{NO}}_{3}^{-}$ , H2 ${\text{PO}}_{4}^{-}$ , 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.
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 (H2 ${\mathrm {PO}}_{4}^{-}$ ), and potassium (K+) ions in the environment. The sensor outputs of ${\text{NO}}_{3}^{-}$ , H2 ${\text{PO}}_{4}^{-}$ , 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.