A cyber-physical intelligent agent for irrigation scheduling in horticultural crops

Jiménez, Andrés-F; Cárdenas, Pedro F.; Jiménez, Fabián; Ruiz-Canales, A.; López, Ángel L.

doi:10.1016/j.compag.2020.105777

Cited by 27 publications

(13 citation statements)

References 13 publications

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“…The water pumps are activated automatically when the soil moisture level (measured by sensor nodes in WSN) is less than a threshold value. Intelligent agent concept was used in [28] to design and implement a cyber-physical irrigation system. The physical data collected using WSN and a weather station while processing of these data is done in a central station to decide the irrigation status based on these data.…”

Section: Smart Irrigation System Based On Wsnmentioning

confidence: 99%

Review on cyber-security for optimized and smart irrigation systems

Abdulaziz

Croock

2022

TELKOMNIKA

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It is well known that the resources in agriculture are considered the most important factors for success. Therefore, numerous researchers are involved in the field of managing these resources, particularly water and consumed power. Moreover, the security side of these resources is considered, particularly the cyber-attacks. In this project, an optimized resource management method is proposed for allocating the available resources in a smart on-demand way. The proposed method is applied for dripped and sprinkler irrigation systems for managing the available water and generated power. In addition, an optimization method is utilized to obtain reliable solutions for managing the adopted resources. This method adopts a cyber security algorithm for preventing any possible attack. Wireless sensor network (WSN) is used as a reading source, in which the underlying area is covered well, since using sensors in irrigation systems is cost-effective that ensures on-demand irrigation process to save water and power resources. This network is supported by the fault tolerance method to increase availability.

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Section: Smart Irrigation System Based On Wsnmentioning

confidence: 99%

Review on cyber-security for optimized and smart irrigation systems

Abdulaziz

Croock

2022

TELKOMNIKA

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“…The data sent from the Arduino Nano to the NodeMCU is a special string that is unique to each device. Arduino Nano uses ATMega328 [16]. Arduino Nano is equipped with a 16MHz crystal, digital pins, and analog pins [17], [18].…”

Section: Fig 2 Inventory System Block Diagrammentioning

confidence: 99%

Development of Laboratory Equipment Inventory System Using Radio Frequency and Internet of Things

Wicaksono

Syahrul

Rahmatya

2021

Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika

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“…Conceptualization of Cybernetics approaches in Intelligent Systems 1,3–5 [Color figure can be viewed at wileyonlinelibrary.com]…”

Section: Introductionmentioning

confidence: 99%

Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT

Rathinam¹,

Kasinathan²,

Uma

et al. 2021

Int J of Intelligent Sys

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Detection of crop diseases is imperative for agriculture to be sustainable. Automated crop disease detection is a major issue in the current agricultural industry due to its cluttered background. Internet of Things (IoT) has gained immense interest in the past decade, as it accumulates a high level of contextual information to identify crop diseases. This study paper presents a novel method based on Taylor‐Water Wave Optimization‐based Generative Adversarial Network (Taylor‐WWO‐based GAN) to identify diseases in the agricultural industry. In this method, the IoT nodes sense the plant leaves, and the sensed data are transmitted to the Base Station (BS) using Fractional Gravitational Gray Wolf Optimization. This technique selects the optimal path for data transmission. After performing IoT routing, crop diseases are recognized at the BS. For detecting crop disease, the input image acquired from the IoT routing phase is then forwarded to the next step, that is, preprocessing, to improve the quality of the image for further processing. Then, Segmentation Network (SegNet) is adapted to segment the images, and extraction of significant features is performed using the acquired segments. The extracted features are adapted by the GAN, which is trained by Taylor‐WWO. The proposed Taylor‐WWO is newly devised by integrating the Taylor series and WWO algorithms. The proposed Taylor‐WWO‐based GAN showed improved performance with a maximum accuracy of 91.6%, maximum sensitivity of 89.3%, and maximum specificity of 92.3% in comparison with existing methods.

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A cyber-physical intelligent agent for irrigation scheduling in horticultural crops

Cited by 27 publications

References 13 publications

Review on cyber-security for optimized and smart irrigation systems

Review on cyber-security for optimized and smart irrigation systems

Development of Laboratory Equipment Inventory System Using Radio Frequency and Internet of Things

Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT

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