Design of a Smart Water-Saving Irrigation System for Agriculture Based on a Wireless Sensor Network for Better Crop Yield

Meeradevi,; A., Supreetha M.; Mundada, Monica R; Pooja, Jambhale

doi:10.1007/978-981-13-0212-1_11

Cited by 15 publications

(7 citation statements)

References 1 publication

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“…Structural similarity index (SSIM) mechanisms was adopted to control irrigation valves depending on zone-specific irrigation control commands. In [21] a wireless drip irrigation system was presented by deploying soil moisture sensors. An implementation of a WSN was realized for wireless managed irrigation solution and real time monitoring of soil water content.…”

Section: Wireless Sensor Networkmentioning

confidence: 99%

A Review on Various Techniques to Transform Traditional Farming to Precision Agriculture

Gill¹

2021

TURCOMAT

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The agricultural sector is of great importance to fulfill food resources need of the country. Precision Agriculture (PA) with Internet of Things and Wireless Sensor Network is a transformation from traditional farming to smart farming. Wireless sensor networks and Internet of Things are considered as drivers to develop system which can change agriculture sector from manual to automatic. Advancement in the technology have pushed the growth of precision agriculture to very large extent despite of several challenges faced in this area. System for precision agriculture relies on hardware components mainly wireless sensors which act as a source for gathering of real time data. Depending upon the real time date retrieved by sensors automation in agriculture is done by adopting decision-based system. With Precision agriculture productivity is optimized by maintaining sustaniability as crop receives what is acutual requirement on the basis of new techniques and software platforms. This review article includes Inernet of Things (IoT), Wireless Sensors, Wireless communication and challenges faced in this area.

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Section: Wireless Sensor Networkmentioning

confidence: 99%

A Review on Various Techniques to Transform Traditional Farming to Precision Agriculture

Gill¹

2021

TURCOMAT

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“…• Protocolo de comunicación: en la selección del protocolo de comunicación se encontró que autores como [20] utilizan un sistema de medición basado en Wi-fi para un modelo IoT en un entorno agrícola de adquisición y extracción de datos, mientras tanto la investigación realizada por [21] implementa Sistema Global para las Comunicaciones Móviles (GSM) en un prototipo de mediciones agroambientales; sin embargo, estos protocolos no cumplen con las necesidades del sistema de monitoreo planteado considerando que son tecnologías de difícil adquisición en sectores apartados donde se encuentran los cultivos. Finalmente, proyectos como [22] y [23], encuentran LoRaWAN como la tecnología que mejor se adapta a la agricultura de precisión por su modulación a largo alcance, baja complejidad y larga cobertura, además se basa en un sistema de nodos locales, ideal para aplicaciones en lugares remotos como campos agrícolas.…”

Section: Diseño General Del Sistema Integrado De Monitoreounclassified

Sistema integrado de monitoreo inalámbrico de variables agroambientales en un cultivo de tomate para la generación de mapas de intensidad

et al. 2021

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En este trabajo se presenta el diseño y construcción de un sistema integrado de monitoreo inalámbrico para la generación de mapas de intensidad enfocado en la agricultura de precisión empleando una metodología de cuatro etapas: análisis general, construcción, desarrollo del software y, validación y gestión de cambios. El sistema cuenta con la instrumentación para medir dióxido de carbono, temperatura, radiación ultravioleta y humedad del aire y suelo; además, implementa un sistema de posicionamiento global que permite la creación de los mapas. Los datos se envían a través del protocolo LoRaWAN a una interfaz gráfica para visualizar el comportamiento de cada variable y generar los mapas; la cual se construye bajo las necesidades particulares de un cultivo de tomate. Finalmente, se obtiene un sistema adaptable para analizar a detalle las condiciones agroambientales, facilitando la toma de decisiones del agricultor.

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“…[4]. This furtherance enables farmers to make better farm management decisions by utilizing available resources more efficiently, resulting in appropriate yields and higher income [5]. farming activity, as well as farmers' experience and ability with smart farming, in order to design an appropriate learning tools for farmers to improve farming production [6].…”

Section: Introduction (Heading 1)mentioning

confidence: 99%

Training Evaluation in a Smart Farm using Kirkpatrick Model: A Case Study of Chiang Mai

Chernbumroong

Sureephong

Suebsombut

et al. 2022

2022 Joint International Conference on Digital Arts, Media and Technology With ECTI Northern Section Conference on Electrical,

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Farmers can now use IoT to improve farm efficiency and productivity by using sensors for farm monitoring to enhance decision-making in areas such as fertilization, irrigation, climate forecast, and harvesting information. Local farmers in Chiang Mai, Thailand, on the other hand, continue to lack knowledge and experience with smart farm technology. As a result, the 'SUNSpACe' project, funded by the European Union's Erasmus+ Program, was launched to launch a training course which improve the knowledge and performance of Thai farmers. To assess the effectiveness of the training, The Kirkpatrick model was used in this study. Eight local farmers took part in the training, which was divided into two sections: mobile learning and smart farm laboratory. During the training activities, different levels of the Kirkpatrick model were conducted and tested: reaction (satisfaction test), learning (knowledge test), and behavior (performance test). The overall result demonstrated the participants' positive reaction to the outcome. The paper also discusses the limitations and suggestions for training activities.

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Design of a Smart Water-Saving Irrigation System for Agriculture Based on a Wireless Sensor Network for Better Crop Yield

Cited by 15 publications

References 1 publication

A Review on Various Techniques to Transform Traditional Farming to Precision Agriculture

A Review on Various Techniques to Transform Traditional Farming to Precision Agriculture

Sistema integrado de monitoreo inalámbrico de variables agroambientales en un cultivo de tomate para la generación de mapas de intensidad

Training Evaluation in a Smart Farm using Kirkpatrick Model: A Case Study of Chiang Mai

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