Calibration of Conductivity Sensor using Combined Algorithm Selection and Hyperparameter Optimization: A Case Study

Nguyen, Tien-Dung; Nguyen, Thi Thanh Sang; Le, Nhat-Tan

doi:10.1109/atc.2018.8587559

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…Conforme Nguyen et al (2018), a agricultura com a aplicação da IoT, é capaz de promover benefícios na produção. Com o auxílio de sensores se faz possível em tempo real realizar a coleta de informações, a respeito de plantas, animais, temperatura do ar, localização do GPS e umidades decorrentes, no entanto a IoT no âmbito da agricultura é pouco investigada.…”

Section: Resultsunclassified

Tecnologia Da Internet Das Coisas Na Agricultura 4.0: Uma Revisão Sistemática

Ferreira,

Nascimento,

Santos

2023

GIT

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A quarta revolução industrial, denominada Indústria 4.0, traz consigo inovações tecnológicas para otimizar ou automatizar processos e recursos. Baseados em sistemas ciber físicos, onde todos os elementos e pessoas estão direta ou indiretamente conectados, tecnologias como a internet das coisas (IoT), Big Data, inteligência artificial, robótica avançada, manufatura aditiva, dentre outros, trazem uma maior integração das informações proporcionando novas possibilidades de desenvolvimentos. Uma das áreas que podem se privilegiar desse novo contexto é a de produção agrícola, principalmente voltada a alimentos, que ficou conhecida como Agricultura 4.0. Este artigo apresenta uma revisão sistemática sobre agricultura 4.0 e suas aplicações tecnológicas, tendo como objetivo investigar a aplicabilidade da tecnologia denominada internet das coisas. Autores apresentam a possibilidade de diminuição dos custos, otimização dos processos, aumento da produção e redução de desperdícios. Podemos verificar, a partir da pesquisa exposta neste trabalho, que o uso da internet das coisas se torna imprescindível na agricultura 4.0.

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Section: Resultsunclassified

Tecnologia Da Internet Das Coisas Na Agricultura 4.0: Uma Revisão Sistemática

Ferreira,

Nascimento,

Santos

2023

GIT

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“…The calibration range of the TDS sensor is up to 819 ppm. Nguyen et al (2018) shared a case study about calibrating conductivity sensors using Combined Algorithm Selection and Hyperparameter Optimization. A different model of calibration process was carried out by using the Gaussian process (Franchini et al, 2019;Ansar Jamil, Teo Sheng Ting, Zuhairiah Zainal Abidin, Maisara Othman, Mohd Helmy Abdul Wahab, Mohammad Faiz Liew Abdullah, Mariyam Jamilah Homam, Lukman Hanif Muhammad Audah and Shaharil Mohd Shah Peršić et al, 2021;Urban et al, 2015), Simple Logistic (Zheng et al, 2019) and Linear Regression (Iida et al, 2020;Koestoer et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…The recorded MAE and RMSE values are taken directly from the literature. Sec-PR provides (Goparaju et al, 2021) -27.93 0 to 400 ppm Gaussian Process (Nguyen et al, 2018) 302.681 352.2483 0 to 2000 ppm Multilayer perception (Nguyen et al, 2018) 40.6973 46.034 0 to 2000 ppm…”

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confidence: 99%

Polynomial Regression Calibration Method of Total Dissolved Solids Sensor for Hydroponic Systems

Jamil,

Sheng Ting,

Zainal Abidin

et al. 2023

JST

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Smart hydroponic systems have been introduced to allow farmers to monitor their hydroponic system conditions anywhere and anytime using Internet of Things (IoT) technology. Several sensors are installed on the system, such as Total Dissolved Solids (TDS), nutrient level, and temperature sensors. These sensors must be calibrated to ensure correct and accurate readings. Currently, calibration of a TDS sensor is only possible at one or a very small range of TDS values due to the very limited measurement range of the sensor. Because of this, we propose a TDS sensor calibration method called Sectioned-Polynomial Regression (Sec-PR). The main aim is to extend the measurement range of the TDS sensor and still provide a good accuracy of the sensor reading. Sec-PR computes the polynomial regression line that fits into the TDS sensor values. Then, it divides the regression line into several sections. Sec-PR calculates the average ratio between the polynomial regressed TDS sensor values and the TDS meter in each section. These average ratio values map the TDS sensor reading to the TDS meter. The performance of Sec-PR was determined using mathematical analysis and verified using experiments. The finding shows that Sec-PR provides a good calibration accuracy of about 91% when compared to the uncalibrated TDS sensor reading of just 78% with Mean Average Error (MAE) and Root Mean Square Error (RMSE) equal to 59.36 and 93.69 respectively. Sec-PR provides a comparable performance with Machine Learning and Multilayer Perception method.

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Assessing farmers' perception to Agriculture 4.0 technologies: A new interval‐valued spherical fuzzy sets based approach

Erdoğan

2021

Int J of Intelligent Sys

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Agriculture 4.0 is the usage of advanced technologies for ensuring sustainability and efficient use of resources in agriculture, which can be accepted one of the biggest challenges of mankind. With Agriculture 4.0 technologies, it is aimed to raise productivity, reduce waste and costs. To ensure that agriculture 4.0 technologies are adopted by farmers as soon as possible, the perspective and perception of farmers to these technologies should be analyzed firstly. For this purpose, we propose a decision-making framework to measure farmers' view of Agriculture 4.0 technologies and to perform a prioritization study based on the perception of use among these technologies. Multicriteria decision analysis is also utilized to deal with all qualitative and quantitative factors in the decision process. Within the scope of this study, interval-valued spherical fuzzy numbers are used to model the vagueness in the process in the best manner and to be able to reflect the uncertainty arising from the usage of linguistic variables in the decision process. The SWARA and MAIRCA multicriteria decision making (MCDM) methods, which have been used frequently in the literature and are applied very successfully in MCDM problems, have been firstly extended by spherical fuzzy sets (SFSs) and the advantages for these methods have been utilized within the framework of

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Calibration of Conductivity Sensor using Combined Algorithm Selection and Hyperparameter Optimization: A Case Study

Cited by 5 publications

References 19 publications

Tecnologia Da Internet Das Coisas Na Agricultura 4.0: Uma Revisão Sistemática

Tecnologia Da Internet Das Coisas Na Agricultura 4.0: Uma Revisão Sistemática

Polynomial Regression Calibration Method of Total Dissolved Solids Sensor for Hydroponic Systems

Assessing farmers' perception to Agriculture 4.0 technologies: A new interval‐valued spherical fuzzy sets based approach

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