Optimal sensor placement for monitoring and controlling greenhouse internal environments

Lee, Sang-yeon; Lee, In-Bok; Yeo, Uk-Hyeon; Kim, Rack-woo; Kim, Jun-Gyu

doi:10.1016/j.biosystemseng.2019.10.005

Cited by 53 publications

(26 citation statements)

References 7 publications

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“…In general terms, the higher the level of radiation in the external environment, the greater the thermal heterogeneity generated inside the greenhouse. This type of behavior will influence the growth and development of rose plants, since it is a factor that affects phenomena such as photosynthesis and transpiration, which are relevant to the final yield of the crop in terms of both quantity and commercial quality of the final product, in the case of the rose the size and diameter of the stem, and the size, color and degree of consistency and opening of the flower head (In et al, 2016;Lee et al, 2019).…”

Section: Temperaturementioning

confidence: 99%

Experimental evaluation of the thermal and hygrometric behavior of a Colombian greenhouse used for the production of roses (Rosa spp.)

Villagrán

Bojacá²

2020

Ornam. Hortic.

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The spatial behavior of the environmental variables involved in rose production is one of the factors of greatest current interest in the Colombian ornamental sector. The aim of this work consisted in the evaluation of a passive greenhouse through an experimental approach that included the capture and recording of data through a grid of 40 sensors homogeneously distributed inside the greenhouse. The data processing was carried out through the application of geostatistical techniques that allowed to obtain contour plots for 5 levels of radiation intensity. The results of the exploratory analysis showed that the behavior of temperature, relative humidity and vapour pressure deficit are not the most suitable for rose production, mainly for the conditions of the night period where the temperature exhibited values below 12.5 °C, the relative humidity was above 90% and the vapour pressure deficit was below 0.1 kPa. On the other hand in the structural analysis the circular model of theoretical semivariogram was the one that better degree of adjustment presented in comparison with the experimental data finding that a strong spatial dependency exists for the studied variables, the prediction of the not sampled points was made by means of the method of ordinary kriging finding that horizontal gradients of temperature and relative humidity exist inside the greenhouse that increases in magnitude according to the level of radiation arriving to reach values of 6.1 °C and 30.4%.

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Section: Temperaturementioning

confidence: 99%

Experimental evaluation of the thermal and hygrometric behavior of a Colombian greenhouse used for the production of roses (Rosa spp.)

Villagrán

Bojacá²

2020

Ornam. Hortic.

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“…e modal participation variation coefficient criterion [26] is introduced to select the appropriate location of excitation points. e modal kinetic energy method [27] is introduced to select the appropriate locations of measuring points. e calculated FRFs are decomposed by SVD to extract the effective singular values according to the principle of sudden change in the number of extreme value points.…”

Section: Specific Procedures Of Model Updatingmentioning

confidence: 99%

An Improved Finite Element Model Updating Method Based on the Singular Values of Frequency Response Functions

Yin

Wang

Cao

et al. 2021

Mathematical Problems in Engineering

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Aiming at the problems that Markov chain Monte Carlo algorithm is not easy to converge, has high rejection rate, and is easy to be disturbed by the noise when the parameter dimension is high, an improved model updating method combining the singular values of frequency response functions and the beetle antennae search algorithm is proposed. Firstly, the Latin hypercube sampling is used to extract the training samples. The Hankel matrix is reconstructed using the calculated frequency response functions and is decomposed by singular value decomposition. The effective singular values are retained to represent the frequency response functions. Secondly, according to the training samples and the corresponding singular values, the support vector machine surrogate model is fitted and its accuracy is tested. Then, the posterior probability distribution of parameters is estimated by introducing the beetle antennae search algorithm on the basis of standard Metropolis–Hastings algorithm to improve the performance of Markov chains and the ergodicity of samples. The results of examples show that the Markov chains have better overall performance and the acceptance rate of candidate samples is increased after updating. Even if the Gaussian white noise is introduced into the test frequency response functions under the single and multiple working damage conditions, satisfactory updating results can also be obtained.

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“…The goal of this study was to solve the problems related to the temperature inspection and estimation of the sensor. In some recent studies related to temperature detection, aiming at the problem of regional ambient temperature detection, Lee [24] analyzed and compared the accuracy of error-and entropy-based sensor layouts in determining the best sensor location for monitoring and controlling the environment in the greenhouse. Poma [25] developed an autonomous system for remote monitoring of sea water temperature and pH to evaluate the current situation of the marine environment and predict future changes.…”

Section: Related Workmentioning

confidence: 99%

“…The objectives of the above research primarily focused on specific equipment temperature detection and regional ideal ambient temperature detection, such as in high-temperature molten pools [27] and permanent crop greenhouses [20]. A specific algorithm was applied to measure the temperature data inside the greenhouse at nine sensor positions to determine the optimal sensor location [24].…”

Section: Related Workmentioning

confidence: 99%

“…Second, biological oxidation pretreatment process equipment (oxidation tanks) are large and usually placed outdoors. Third, Lee [24] analyzed the problem of redundant information in the sensor measurement data. The smaller the amount of redundant data, the larger the amount of effective information for temperature measurement, which is directly related to the distribution of the sensor position.…”

Section: Problem Statementsmentioning

confidence: 99%

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Temperature Sequential Data Fusion Algorithm Based on Cluster Hierarchical Sensor Networks

Yang

Nan

Jin

2020

Sensors

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The process of extracting gold by biological oxidation involves oxidizing the refractory high-sulfur and high-arsenic ore with the help of bacteria to decompose the wrapping material of gold to extract the gold. Therefore, maximizing the activity of bacteria will directly affect the efficiency of gold extraction, for which it is particularly important to maintain the pulp temperature in the oxidation tank at the optimal bacteria breeding temperature. However, gold mines are generally located in mountainous areas, and the large temperature difference between day and night in winter, coupled with the influence of wind and snow, creates variations in the temperature in the oxidation tank. The traditional temperature measurement method cannot fully reflect the temperature change of the oxidation tank. As a multi-field application method, sensor information fusion can effectively address the problem of pulp temperature measurement. First, we analyzed the heat transfer principle inside the oxidation tank, and designed the cluster hierarchical sensor network according to the spatial position of each oxidation tank and the environmental interference factors. The network structure is divided into three layers; the bottom of the sensor to collect pulp temperature data shows a spiral distribution in the inner wall of the oxidation tank. Each cluster head node sensor is used as an intermediate layer to complete local measurement fusion estimation. Finally, the fusion center is taken as the upper layer to realize the global state fusion estimation. Secondly, in the data processing of the bottom temperature sensor, the traditional unscented Kalman filter (UKF) algorithm is improved and the fading memory matrix is added to improve the identification of nonlinear modeling errors. The sequential observation fusion estimator (SOFE) algorithm is embedded in the measurement update to improve the performance of local measurement fusion. Finally, in the global state fusion estimation, the sequential analysis is combined with the inverse covariance intersection, and the sequential analysis and inverse covariance intersection-global state fusion estimation (SICI-GSFE) algorithm is proposed. Through calculation and simulation, the results show that the external interference can be reduced by combining all the temperature state estimations, and the accuracy of the best global temperature state estimation is improved.

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Optimal sensor placement for monitoring and controlling greenhouse internal environments

Cited by 53 publications

References 7 publications

Experimental evaluation of the thermal and hygrometric behavior of a Colombian greenhouse used for the production of roses (Rosa spp.)

Experimental evaluation of the thermal and hygrometric behavior of a Colombian greenhouse used for the production of roses (Rosa spp.)

An Improved Finite Element Model Updating Method Based on the Singular Values of Frequency Response Functions

Temperature Sequential Data Fusion Algorithm Based on Cluster Hierarchical Sensor Networks

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