The development of remote monitoring system for cultivation environment of Pleurotus eryngii

Zhao, Li; Zhu, Xuejun

doi:10.1109/icinfa.2015.7279731

Cited by 7 publications

(2 citation statements)

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“…Chen et al [20] designed a remote monitoring system for the community-style growing environment of king oyster mushroom by integrating similar technologies to record all environmental factors including light intensity. Later, a study was conducted by Zhao and Zhu [21] who designed a single-chip wireless monitoring platform to monitor environmental factors simultaneously in eight mushroom farms, aiming to construct an accurate remote sensing system by eliminating problems of wiring difficulties, high-cost, and unstable data transmission.…”

Section: Remote Sensing and Data Transmissionmentioning

confidence: 99%

Research progress on indoor environment of mushroom factory

Chen¹,

Liu²,

Xiao³

et al. 2022

International Journal of Agricultural and Biological Engineering

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Mushroom factory is an emerging production mode that is relied on facility and equipment by creating a suitable, steady, and uniform growing environment to accommodate the demand of edible fungus at each stage of growth. Therefore, an optimal range of key environmental factors (temperature, humidity, light, and CO 2 concentrations) in mushroom facilities is crucial to achieving satisfactory production rates. This research aimed to provide an overview of recent progress on indoor environmental studies of mushroom cultivation facilities from three perspectives, 1) the development of environmental monitoring and controlling systems; 2) the application of computer modelling in addressing indoor environmental issues; 3) the refinement of mushroom facility design, including structure and ventilation scheme. With the aid of cutting-edge technologies, accomplishments have been made in developing smart farming systems that facilitate real-time recording of environmental parameters and automatic regulation of equipment, which helps the establishment of growth models for specific mushroom species. Computational Fluid Dynamics (CFD) modelling has been adopted by researchers to investigate indoor airflow patterns and assess the distribution of critical environmental parameters. Studies have been conducted to modify the design of mushroom facilities to improve the performance in structural stability, ventilation efficiency, and internal environmental condition. However, some existing problems still need further investigations, such as the lack of design guidelines, energy-saving strategies, and Artificial Intelligent (AI) quality control. Therefore, this overview was expected to provide constructive insights for future studies in addition to references of previous studies.

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Section: Remote Sensing and Data Transmissionmentioning

confidence: 99%

Research progress on indoor environment of mushroom factory

Chen¹,

Liu²,

Xiao³

et al. 2022

International Journal of Agricultural and Biological Engineering

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“…Though the development and application of wireless remote digital information monitoring platform provides a good technical condition for local edible fungus factory, annual production [2], due to the nonlinear, large delay and time-varying characteristics of the CO 2 concentration control system, real-time monitoring data reflected only a particular moment [3].…”

Section: Introductionmentioning

confidence: 99%

Online Prediction Control Model of CO<sub>2</sub> Concentration for <i>Pleurotus eryngii</i> in the Sporocarp Period Based on Matlab and LabVIEW

Tian

Zhang

Bai

et al. 2017

AMM

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In the industrialized cultivation process of fungi, CO2 concentration control system is a nonlinear, time-delay and time-varying system, which is difficult to establish a precise mathematical model. Considering the situation, CO2 concentration prediction model that based on neural network was built, and a fuzzy controller was proposed further based on the prediction model. Finally, matlab/labview based online forecast model was finished, and it is verified that the prediction system has higher prediction accuracy with robust character. It also provides a new approach to control key environmental factors under more favorable conditions for mushroom growth.

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Methodology for Controlling Greenhouse Microclimate Parameters and Yield Forecast Using Neural Network Technologies

Morozova

2023

Studies in Systems, Decision and Control

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The development of remote monitoring system for cultivation environment of Pleurotus eryngii

Cited by 7 publications

References 0 publications

Research progress on indoor environment of mushroom factory

Research progress on indoor environment of mushroom factory

Online Prediction Control Model of CO<sub>2</sub> Concentration for <i>Pleurotus eryngii</i> in the Sporocarp Period Based on Matlab and LabVIEW

Methodology for Controlling Greenhouse Microclimate Parameters and Yield Forecast Using Neural Network Technologies

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