A fuzzy logic based irrigation system enhanced with wireless data logging applied to the state of Qatar

Touati, Farid; Al‐Hitmi, Mohammed; Benhmed, Kamel; Tabish, Rohan

doi:10.1016/j.compag.2013.08.018

Cited by 54 publications

(27 citation statements)

References 25 publications

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“…Qiu et al [150] established a fuzzy irrigation decision-making system using virtual instrumentation platform of sensors, test instruments, data logger, and LabVIEW. Generally, published studies use on/off controllers where the inherent complexity of irrigation process made it difficult to achieve optimal results [151]. Ali et al [152] developed temperature and humidity controller inside the greenhouse using fuzzy logic.…”

Section: Application Of Artificial Intelligence Techniques In Agriculmentioning

confidence: 99%

Monitoring and Control Systems in Agriculture Using Intelligent Sensor Techniques: A Review of the Aeroponic System

et al. 2018

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In recent years, intelligent sensor techniques have achieved significant attention in agriculture. It is applied in agriculture to plan the several activities and missions properly by utilising limited resources with minor human interference. Currently, plant cultivation using new agriculture methods is very popular among the growers. However, the aeroponics is one of the methods of modern agriculture, which is commonly practiced around the world. In the system, plant cultivates under complete control conditions in the growth chamber by providing a small mist of the nutrient solution in replacement of the soil. The nutrient mist is ejected through atomization nozzles on a periodical basis. During the plant cultivation, several steps including temperature, humidity, light intensity, water nutrient solution level, pH and EC value, CO2concentration, atomization time, and atomization interval time require proper attention for flourishing plant growth. Therefore, the object of this review study was to provide significant knowledge about early fault detection and diagnosis in aeroponics using intelligent techniques (wireless sensors). So, the farmer could monitor several paraments without using laboratory instruments, and the farmer could control the entire system remotely. Moreover, the technique also provides a wide range of information which could be essential for plant researchers and provides a greater understanding of how the key parameters of aeroponics correlate with plant growth in the system. It offers full control of the system, not by constant manual attention from the operator but to a large extent by wireless sensors. Furthermore, the adoption of the intelligent techniques in the aeroponic system could reduce the concept of the usefulness of the system due to complicated manually monitoring and controlling process.

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Section: Application Of Artificial Intelligence Techniques In Agriculmentioning

confidence: 99%

Monitoring and Control Systems in Agriculture Using Intelligent Sensor Techniques: A Review of the Aeroponic System

et al. 2018

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“…The output variable is the duration of irrigation ( D crop ) estimated to meet crop needs. As shown in Figure , triangular and trapezoidal memberships are used to define the inputs and output variables : Very Cold “VC” (0‐15°C), Cold “CO” (5‐25°C), Medium “MD” (15‐35°C), Hot “HO” (25‐45°C) and Very Hot “VH” (35‐50°C) for the inside temperature. Very Low “VL” (0‐15%), Low “LO” (0‐30%), Medium “MD” (15‐45%), High “HI” (30‐60%) and Very High “VH” (50‐60%) for the soil moisture error. Very Short “VS” (0‐2.5), Short “S” (0‐5), Medium “MD” (2.5‐7.5), Long “L” (5‐10) and Very Long “VL” (7.5‐10) for the irrigation duration. …”

Section: System Designmentioning

confidence: 99%

“…The output variable is the duration of irrigation (D crop ) estimated to meet crop needs. As shown in Figure 3, triangular and trapezoidal memberships are used to define the inputs and output variables [13,24,26]:…”

Section: Duration Flc Devicementioning

confidence: 99%

An Embedded Solar‐Powered Irrigation System Based on a Cascaded Fuzzy Logic Controller

Selmani

Outanoute

Oubehar

et al. 2019

Asian Journal of Control

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This study examines the automatization of irrigation tasks of solar photovoltaic water pumping systems (SPVWPS) in greenhouse applications. A prototype of an embedded control system has been developed for SPVWPS battery-coupled architectures. The new design aims at improving the safety of solar irrigation facility by avoiding the exhaustion of pumping resources (water and energy) while watering. The availabilities of pumping resources are introduced as new requisite inputs of a fuzzy logic-based control system (FLC) so that it can produce adequate and safe irrigation durations. The FLC design consists of two cascaded devices. The first device uses climate data to estimate durations for watering that satisfy crop needs. The second device uses actual resource levels to evaluate the pumping capacity of the SPVWPS regarding requested durations.Watering is performed whenever the pumping capacity of the system represents more than 25% of the total requirement. Test results from an experimental greenhouse prove the effectiveness of the decision-making mechanism that prevents scheduling unsuccessful watering tasks.

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“…• Fuzzy algorithms: This category includes algorithms of fuzzy decisions based on a pre-defined set of rules and Degree of Membership calculations upon sensor values (metrics) [7,8]. Fuzzy algorithms are fast and smart adaptive algorithms and may also include error control capabilities similar to the PIC algorithm.…”

Section: Irrigation Systems Algorithmsmentioning

confidence: 99%

“…All daily Errors are added to a total Error value: Error total = Σ i=1 n Error i . The n + 1 day on watering flow meter value Fv n+1 shall be set automatically as follows: Fv n+1 = K·Error n + (K/n) Error total + (Error n − Error n−1 ), where K is a statically assigned gain coefficient and n are the n days of Fv flow meter measurements [7,8,16].…”

Section: Irrigation Systems Algorithmsmentioning

confidence: 99%

Proposed Fuzzy-NN Algorithm with LoRaCommunication Protocol for Clustered Irrigation Systems

et al. 2017

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Abstract:Modern irrigation systems utilize sensors and actuators, interconnected together as a single entity. In such entities, A.I. algorithms are implemented, which are responsible for the irrigation process. In this paper, the authors present an irrigation Open Watering System (OWS) architecture that spatially clusters the irrigation process into autonomous irrigation sections. Authors' OWS implementation includes a Neuro-Fuzzy decision algorithm called FITRA, which originates from the Greek word for seed. In this paper, the FITRA algorithm is described in detail, as are experimentation results that indicate significant water conservations from the use of the FITRA algorithm. Furthermore, the authors propose a new communication protocol over LoRa radio as an alternative low-energy and long-range OWS clusters communication mechanism. The experimental scenarios confirm that the FITRA algorithm provides more efficient irrigation on clustered areas than existing non-clustered, time scheduled or threshold adaptive algorithms. This is due to the FITRA algorithm's frequent monitoring of environmental conditions, fuzzy and neural network adaptation as well as adherence to past irrigation preferences.

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A fuzzy logic based irrigation system enhanced with wireless data logging applied to the state of Qatar

Cited by 54 publications

References 25 publications

Monitoring and Control Systems in Agriculture Using Intelligent Sensor Techniques: A Review of the Aeroponic System

Monitoring and Control Systems in Agriculture Using Intelligent Sensor Techniques: A Review of the Aeroponic System

An Embedded Solar‐Powered Irrigation System Based on a Cascaded Fuzzy Logic Controller

Proposed Fuzzy-NN Algorithm with LoRaCommunication Protocol for Clustered Irrigation Systems

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