Design and Optimization of IoT Based Smart Irrigation System in Sri Lanka

Laksiri, H.G.C.R.; Dharmagunawardhana, H.A.C.; Wijayakulasooriya, J. V.

doi:10.1109/iciis47346.2019.9063272

Cited by 32 publications

(5 citation statements)

References 9 publications

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“…A hierarchical cluster-based network is used by the proposed joint architectural protocol to collect the distributed controllers of control systems. It includes resource allocation, clustering, and a control task participation method for wireless networks [13].…”

Section: Related Workmentioning

confidence: 99%

Development of Intelligent Monitoring and Control System for Electrostatic Precipitators in Cement Plants

DeKheel,

O. Mustafa,

Marie

2024

IRJIET

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Cement plants are crucial industrial entities that supply cement for various applications, including the construction of buildings and bridges. While these plants play a vital role in infrastructure development, they are also recognized as significant sources of environmental pollution. To mitigate air pollution, Electrostatic Precipitators (ESPs) are employed, capable of reducing air pollution by approximately 99.99%. Consequently, ESPs warrant in-depth study, and development. This project focuses on investigating, and developing a monitoring, and control system for ESPs utilizing intelligent devices. The initial step involved deriving a mathematical model based on input/output data from the critical unit, the transformer/rectifier (T/R set). The Grey Wolf Optimization algorithm was employed to determine the optimal parameters (Kp=988, Ki=37.7, Kd=88.5) for the PID controller using the MATLAB package.

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Section: Related Workmentioning

confidence: 99%

Development of Intelligent Monitoring and Control System for Electrostatic Precipitators in Cement Plants

DeKheel,

O. Mustafa,

Marie

2024

IRJIET

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“…However, the majority of the older prediction models had a large variance, which causes the machine-learning model to perform poorly. Ensemble learning, as described by Zhao et al (2018) [4], Catolino and Ferrucci [5] (2018), Joshi and Srivastava [6] (2014), and Ren et al [7] (2016), may be utilized to deal with such significant variation. By combining different learning models to predict the output of a single system, ensemble approaches improve performance.…”

Section: Goldstein Et Al (2017)mentioning

confidence: 99%

Intelligent irrigation system using ML and IoT

Manjunath¹,

Sudarshan²

2023

IJRIAS

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To realize IoT promise in commercial-scale applications, integrated Internet of Things (IoT) platforms are required. The key challenge is to make the solution flexible enough to fulfill the demands of specific applications. A platform which is IoT-based which is used for smart irrigation with a adaptable design is created so that it allows developers to quickly link IoT and machine learning (ML) components to create application solutions. The design allows for a variety of customized analytical methods for precision irrigation, allowing for the advancement of machine learning techniques. Impacts on many stakeholders may be predicted, including IoT specialists, who would benefit from easier system setup, and farmers, who will benefit from lower costs and safer crop yields. The typical irrigation procedure necessitates a large quantity of use of precious water, which results in waste of water. An intelligent irrigation system is in desperate need to decrease the wastage of water during this tiresome process. Using Machine learning (ML) and the Internet of Things (IoT),it is possible to develop an intelligent system that can accomplish this operation automatically and with minimum human intervention. An system which is enables using IoT and trained using ML is highly recommended and is suggested in this paper for optimum water consumption with minimal farmer interaction. In agriculture, IoT sensors are used to capture exact field and environmental data. The data being collected is transferred and kept in a cloud-based server that uses machine learning to evaluate the data and provide irrigation recommendations.

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“…For farmers in the agriculture industry, creating a successful IoT based intelligent irrigation system is a crucial prerequisite. An economical, weather-based intelligent irrigation system was necessary [13][14]. The first step is to create an effective drip irrigation system that can regulate the water flow to the plants according to the soil's moisture level.…”

Section: Implementationsmentioning

confidence: 99%

Enhancing Crop Growth Efficiency through IoT-enabled Smart Farming System

Jadhav,

et al. 2023

EAI Endorsed Trans IoT

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The agricultural sector is facing significant challenges in meeting the increasing demands for food production while ensuring sustainability and resource efficiency. To address these challenges, the integration of Internet of Things (IoT) technology into farming practices has gained attention as a promising solution. This research focuses on the development and implementation of an IoT-enabled smart farming system aimed at enhancing crop growth efficiency. The proposed system leverages IoT sensors and devices to monitor and collect real-time data on various parameters such as environmental conditions, soil moisture levels, and crop health. The collected data is then analyzed using advanced analytics techniques to gain valuable insights and make informed decisions regarding irrigation, fertilization, and pest control. By utilizing IoT technology, farmers can optimize their resource utilization, reduce waste, and maximize crop productivity. This research aims to investigate the potential benefits and challenges associated with implementing the IoT-enabled smart farming system. In this paper, a cutting-edge Internet of Things (IoT) technology is explored for monitoring weather and soil conditions for efficient crop development. The system was built to monitor temperature, humidity, and soil moisture using Node MCU and several linked sensors. Additionally, a Wi-Fi connection is used to send a notification through SMS to the farmer's phone about the field's environmental state. The results will help in developing strategies and guidelines for the widespread adoption of IoT-enabled smart farming practices, ultimately leading to sustainable and efficient crop production to meet the demands of a growing population.

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Design and Optimization of IoT Based Smart Irrigation System in Sri Lanka

Cited by 32 publications

References 9 publications

Development of Intelligent Monitoring and Control System for Electrostatic Precipitators in Cement Plants

Development of Intelligent Monitoring and Control System for Electrostatic Precipitators in Cement Plants

Intelligent irrigation system using ML and IoT

Enhancing Crop Growth Efficiency through IoT-enabled Smart Farming System

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