FUZZY MODELING IN EVALUATING THE CONSISTENCY AND EFFICIENCY OF DATA REMOTELY MONITORED BY A MULTIPARAMETRIC PROBE

Passos, Mádilo L. V.; Sousa, Alan B. O. de; Teixeira, Adunias dos S.

doi:10.1590/1809-4430-Eng.Agric.v42nepe20210128/2022

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Sumário

Scientific Paper, Special Issue: Artificial Inteligence • Eng. agríc. (Online) 42 (spe) • 2022 • https://doi.org/10.1590/1809-4430-Eng.Agric.v42nepe20210128/2022 copy

FUZZY MODELING IN EVALUATING THE CONSISTENCY AND EFFICIENCY OF DATA REMOTELY MONITORED BY A MULTIPARAMETRIC PROBE

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

The analysis of water quality for irrigation assists in solving problems with irrigation equipment, such as obstruction in localized systems, being fundamental in precision irrigation. This study aimed to develop and evaluate an affordable multiparametric probe, as well as the performance in the remote data transmission by Bluetooth classic and Wi-Fi. The probe was based on the Arduino Nano platform. The sensors consisted of a pH (potential of hydrogen) sensor, a turbidity sensor (TSW30), and a total dissolved solids sensor. Bluetooth classic (HC-06 module) and ESP8266 module (ESP-01) were implemented for wireless transmission. A fuzzy inference system was used to evaluate the performance of sending data, using the variables bit error rate (BER) and percentage efficiency (Ef). The low-cost multiparametric probe allowed the measurement of pH, turbidity, and total dissolved solids. The Wi-Fi standard (IEEE 802.11 g/b/n), via ESP8266 version 01, presented the best results of consistency and efficiency of information transmission, according to fuzzy modeling.

KEYWORDS
Arduino; Bluetooth; internet of things; artificial intelligence; Wi-Fi

Linguistic terms	Input		Linguistic terms	Output
Linguistic terms	BER	Ef	Linguistic terms	Performance
Low	[0 0 10⁻⁵ 10⁻⁵]	[0 0 50 60]	Bad	[0 0 20 20]
Medium	[10⁻⁶ 10⁻⁴ 10⁻³]	[50 70 80]	Poor	[20 30 40]
High	[10⁻⁴ 10⁻³ 1 1]	[70 80 100 100]	Fair	[30 45 60]
Universe	0.00 to 1.00	0.00 to 100,00%	Good	[45 70 80]
–	–	–	Excellent	[75 90 100 100]
–	–	–	Universe	0.00 to 100.00%

Sensor	Durbin-Watson	Breusch-Pagan	Kolmogorov-Smirnov	n
pH	0.3755^NS *, NS Significant and not significant at 5%, respectively; and TDS – Total dissolved solids.	1.1921^* *, NS Significant and not significant at 5%, respectively; and TDS – Total dissolved solids.	0.1290^* *, NS Significant and not significant at 5%, respectively; and TDS – Total dissolved solids.	50
Turbidity	0.3932^NS *, NS Significant and not significant at 5%, respectively; and TDS – Total dissolved solids.	12.3608^NS *, NS Significant and not significant at 5%, respectively; and TDS – Total dissolved solids.	0.09123^* *, NS Significant and not significant at 5%, respectively; and TDS – Total dissolved solids.	80
TDS	0.2936^NS *, NS Significant and not significant at 5%, respectively; and TDS – Total dissolved solids.	11.1543^NS *, NS Significant and not significant at 5%, respectively; and TDS – Total dissolved solids.	0.3111^NS *, NS Significant and not significant at 5%, respectively; and TDS – Total dissolved solids.	30

Method	Sensor	Equation
OLS	pH	$ŷ = - 22.7850 * x + 74.3480 *$
	Turbidity	$ŷ = - 436.3956 * x + 1811.4481 *$
	TDS	$ŷ = 604.8903 * x - 339.7890 *$
GLS	pH	$ŷ = - 14.0615 * x + 48.7629 *$
	Turbidity	$ŷ = - 396.2280 * x + 1684.3480 *$
	TDS	$ŷ = 490.0772 * x - 99 . 6983^{NS}$

Method	Sensor	RMSE	R²	r	d	c
OLS	pH	1.1750	0.9342	0.9665	0.9827	0.95
	Turbidity	56.9850	0.9401	0.9696	0.9843	0.95
	TDS	165.1435	0.8335	0.9130	0.9538	0.87

Method	Sensor	AIC	BIC
OLS	pH	162.0207	165.8447
	Turbidity	877.8761	882.6402
	TDS	395.5452	398.3476
GLS	pH	80.5616	84.3857
	Turbidity	803.3822	808.1462
	TDS	348.8896	351.6920

Test	Bluetooth classic (1 meter)
Test	BER	Ef (%)	N	Performance	Membership
01	0.00	97.50	468	Excellent	1.00
02	0.00	97.92	470	Excellent	1.00
03	0.036	98.12	471	Poor	1.00
04	0.00	97.29	467	Excellent	1.00
05	0.00411	97.71	469	Good	0.96

Test	Bluetooth classic (10 meters)
Test	BER	Ef (%)	N	Performance	Membership
01	1.00x10^-3	47.71^* * Device disconnected.	229	Poor	0.67
02	0.00	97.50	468	Excellent	1.00
03	3.26x10^-3	97.50	468	Good	0.75
04	0.00	96.87	465	Excellent	1.00
05	0.00	18.96^* * Device disconnected.	91	Good	1.00

Test	Wi-Fi (1 meter)
Test	BER	Ef (%)	N	Performance	Membership
01	0.00	95.42	458	Excellent	1.00
02	0.00	97.71	469	Excellent	1.00
03	0.00	98.12	471	Excellent	1.00
04	0.00	96.87	465	Excellent	1.00
05	0.00	97.29	467	Excellent	1.00

Test	Wi-Fi (10 meters)
Test	BER	Ef (%)	N	Performance	Membership
01	0.00	93.33	448	Excellent	1.00
02	0.00	97.50	468	Excellent	1.00
03	0.00	96.66	464	Excellent	1.00
04	0.00	96.87	465	Excellent	1.00
05	0.00	96.66	464	Excellent	1.00

Associação Brasileira de Engenharia Agrícola SBEA - Associação Brasileira de Engenharia Agrícola, Departamento de Engenharia e Ciências Exatas FCAV/UNESP, Prof. Paulo Donato Castellane, km 5, 14884.900 | Jaboticabal - SP, Tel./Fax: +55 16 3209 7619 - Jaboticabal - SP - Brazil
E-mail: revistasbea@sbea.org.br

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[1] *Corresponding author. Universidade Federal do Ceará/ Fortaleza - CE, Brasil. E-mail: madilolages@hotmail.com