| Autor: |
Argel A. Bandala, Jonnel Alejandrino, Sandy Lauguico, Justin D. de Guia, Ronnie Concepcion, Elmer P. Dadios |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
2020 IEEE 8th R10 Humanitarian Technology Conference (R10-HTC). |
| DOI: |
10.1109/r10-htc49770.2020.9357030 |
| Popis: |
Crops that are cultivated in aquaponics setup highly relies on the nutrients supplied by the aqueous system through fish effluents. Continuous monitoring of essential elemental nutrients requires expensive sensors and arrays of it for full scale deployment. However, sustainable agriculture demands energy consumption reduction and cost-effectiveness. This study employed device minimization by utilizing a combination of physical water sensors, namely temperature and electrical conductivity sensors, to predict total organic carbon (TOC) and hydrogen ion (H) concentrations in pond water. Aquaphotomics through ultraviolet (UV) and visible light (Vis) wavelength sweeping from 250 to 500 nm was explored to determine the nutrient biomarkers of pond water samples that undergoes temperature perturbation from 16 to $36^{\circ}C$ with $2^{\circ}C$ increment per testing. Principal component analysis (PCA) selected the most relevant activated water bands which are 275 nm for TOC and 415 nm for H. Direct spectrophotometric TOC concentration data was passed through a Savitzky-Golay filter to smoothen the nutrient signal. Recurrent neural network (RNN) exhibited the fastest inference time of 3.5 seconds on the average with R2 of 0. S583 and 0.9686 for predicting TOC and H concentrations. Multigene symbolic regression genetic programming (MSRGP) exhibited the best R2 performances of 0.9280 and 0.9693 in predicting TOC and H concentrations by using only the temperature and electrical conductivity sensor-acquired data. This developed model is an innovative approach on measuring chemical concentrations of water using physical limnological sensors which resulted to energy consumption reduction of 50% for complete 42-day crop life cycle of lettuce. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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