Real-time monitoring and intelligent control for greenhouses based on wireless sensor network

Al-Aubidy, Kasim M.; Ali, Mohammad M.; Derbas, Ahmad M.; Al-Mutairi, Abdallah W.

doi:10.1109/ssd.2014.6808765

Cited by 13 publications

(4 citation statements)

References 11 publications

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“…Real-time monitoring and control of a fish farm is not an easy task due to the large number of indicators that are affected by weather and water quality change and have a great impact on fish growth. Fuzzy logic is an excellent tool for decision making due to its ability to write human rules in fuzzy linguistic terms [30]. A fuzzy controller consists of a fuzzifier, fuzzy inference engine, fuzzy rule-base, and a defuzzifier, as shown in Figure 4(a).…”

Section: Fuzzy Logic Controllersmentioning

confidence: 99%

IoT-based smart monitoring and management system for fish farming

Al-Mutairi¹,

Al-Aubidy²

2023

Bulletin EEI

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Fish farming is still controlled and managed in the traditional way where water quality and fish feeding are manually controlled. There is a need to use computer and communication technology in fish farms for remote monitoring and control. This paper deals with the design and implementation of an internet of things (IoT) based system for real-time monitoring, control and management of fish farming. The design of such a system is based on measuring different types of variables and using the information to control fish growth and increase productivity. Each fish pond is a node in a wireless sensor network. The node contains an embedded microcontroller connected to a set of sensors and actuators and a wireless communication module. Two fuzzy controllers are designed to control the water quality in the ponds as well as the environment using five sensors in each pond plus three environmental sensors. Practical results indicate the accuracy of the measurement system compared to the results obtained from commercial devices used on the farm. These results also showed that the proposed approach achieves the best performance of the real-time monitoring and control system in fish ponds.

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Section: Fuzzy Logic Controllersmentioning

confidence: 99%

IoT-based smart monitoring and management system for fish farming

Al-Mutairi¹,

Al-Aubidy²

2023

Bulletin EEI

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“…En Romania se usa energías alternativas para control de temperatura [27]. Por otro lado, el control inteligente con sensores vía inalámbrica es desarrollado por Kasim [28], que se propone realizar monitoreo y control ON-OFF en tiempo real mediante una red de sensores inalámbricos WSN, el microclima se controla con un conjunto de regla difusas Fig. 6.…”

Section: Control Automático Del Recurso Hídrico Y Variables Ambiunclassified

Sistemas automatizados para el control del recurso hídrico y variables ambientales bajo invernadero: aplicaciones y tendencias

2020

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Esta revisión se propone identificar las aplicaciones más recientes relacionadas con la automatización bajo invernadero con enfoque al uso adecuado del recurso hídrico y control de variables ambientales. La revisión hace parte del proyecto de investigación aplicada, diseño e implementación de un sistema SCADA para control del recurso hídrico y variables ambientales asociadas bajo invernadero mediante PLC. Se realiza una búsqueda detallada en revistas indexadas, nacionales e internacionales, páginas web, base de datos, y empresas relacionada al sector y se clasifica la información acorde a algunos criterios diferenciados; supervisión de variables bajo invernadero en sistemas irrigados, control automático del recurso hídrico y variables ambientales, adquisición de información para irrigación bajo invernadero, tendencias de la automatización en sistemas irrigados. A partir de la información se identifican las tecnologías recientes algunas aplicaciones, las tendencias y la necesidad de aplicarlas en el sector agrícola; como aporte para reducir el impacto de la migración de la mano de obra del campo a la ciudad.

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“…In recent years, wireless sensor networks (WSNs) have been widely applied to various fields, such as target tracking, 1 area surveillance, 2 intelligent control, 3 and so on. One of the important topics of WSNs is designing distributed filters for achieving the aforementioned missions.…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered Kalman consensus filter for sensor networks with intermittent observations

LiangYuan

LiYinya

ChenSujuan

et al. 2021

Adaptive Control & Signal

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Summary This article investigates the event‐triggered Kalman consensus filtering (ET‐KCF) problem for distributed sensor networks with intermittent observations. First, a novel ET consensus filtering structure is designed for sensor networks with intermittent observations. With the proposed consensus filtering structure, a new ET mechanism that is more efficient than the existed ones is designed to schedule transmissions of local estimates. Then, an optimal ET‐KCF in the sense of minimum mean‐square error is developed. For reducing the computational complexity of filtering algorithm, a suboptimal ET‐KCF is further proposed. Moreover, the stability of the suboptimal ET‐KCF is analyzed. Simulation results verify the validity and superiority of the proposed method.

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Real-time monitoring and intelligent control for greenhouses based on wireless sensor network

Cited by 13 publications

References 11 publications

IoT-based smart monitoring and management system for fish farming

IoT-based smart monitoring and management system for fish farming

Sistemas automatizados para el control del recurso hídrico y variables ambientales bajo invernadero: aplicaciones y tendencias

Event‐triggered Kalman consensus filter for sensor networks with intermittent observations

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