Sensor Placement Algorithm With Range Constraints for Precision Agriculture

Visalini, K.; Subathra, B.; Srinivasan, Seshadhri; Palmieri, G; Bekiroğlu, Korkut; Thiyaku, S.

doi:10.1109/maes.2019.2921177

Cited by 9 publications

(6 citation statements)

References 51 publications

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“…For sparse big data, use attribute extraction or dimensionality reduction techniques to remove redundant data. 13,14 Then, use the visualization method to transform, transform the unusable data set into a data structure through a series of differentiation solutions, and use it to present it to people through a series of operations. People can interact with the interface through a series of operations.…”

Section: Information Visualizationmentioning

confidence: 99%

(Retracted) Role of video sensors in observing visual image design in the construction of smart cities

Luo

2022

J. Electron. Imag.

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Due to the advancement of software and hardware technologies such as geographic information systems, for example, optical fiber storage, mobile network, digital camera, and high-definition network, it has promoted the establishment of a data digital management system. Network sharing, to a certain extent, makes it the smart city video sensor of today's era. It is a key component of the city's smart management system. In the context of the rapid development of the information age, I explore the role of video sensors in the visual design of smart cities. I propose three methods to analyze the theory of big data video sensors: theoretical analysis of big data video sensors, information visualization, and visual signal output, and then model the video signal output to visualize the complex multilayer network decision. Starting from the RBF neural network, I simulate a video perception prediction model system, import the data into Matlab for experimental analysis and simulation, and compare RBF and BP are based on both data predictions. RBF obviously has stronger predictive video perception. Experimental data show that the error between video perception and actual data is within 3%. It can be seen that video sensors play a key role in the construction of smart cities.

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Section: Information Visualizationmentioning

confidence: 99%

(Retracted) Role of video sensors in observing visual image design in the construction of smart cities

Luo

2022

J. Electron. Imag.

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“…Wrong placement of low energy consuming sensor nodes on farm field can defeat the promising features of wireless sensor network such as improved productivity, reduced cost, and resource optimization. A major cause of wrong sensor placement can be attributed to cost and range of each sensor [6]. Thus optimum placement of sensors in a field is a key factor to reaping the dividend of precision farming.…”

Section: Sensor Node Placementmentioning

confidence: 99%

Cost efficient internet of things based smart farm system for rural farmers: Leveraging design thinking approach

Adebayo

Emuoyibofarhe

Awofolaju

2021

Heritage and Sustainable Development

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Farmers are faced with challenges of producing enough food and the use of traditional methods seems not to keep pace with the ever-growing demand of the populace thus creating increased concern in food scarcity. Although it has been identified that smart tools will enhance the production pace needed in the Agricultural sector, unfortunately, most of these tools are designed for farmers without their inputs, thus creating tools that are not meeting demands. This study focused on a farmer-centered design, development, and deployment approach to improving farm productivity. The design thinking approach was used to identify the specific need of the farmers in selected areas, ideas were created using brainstorming sessions involving experts in the field, and prototypes were developed and deployed to evaluate the impact performance. The result shows that the proposed system improved the cost-benefit ratio of crop farming from 2.14 to 2.26. This is a 12% productivity increase.

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“…[13]briefly explains about low cost sensor usage, sustainable agricultural practices, holistic agricultural monitoring system, novel agricultural practices and emerging IOT use in the field of agriculture. In precision agriculture [14], with the help of Wireless Sensor Networks, It can help increase optimize resources and reduce cost. It describes the SPARC solution for agricultural practices.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In set A, The average fruit length of all tomato plant samples are about 3.34cm, 3.97cm, 3.80cm, 3.20cm, and 3.00cm respectively. In set B, The average height of all tomato plant [14] samples are about 3.20 cm, 3.42 cm, 4.16 cm, 3.97 cm, and 3.33cm respectively.…”

Section: Average Fruit Length (P9)mentioning

confidence: 99%

Recommender System for Nutrient Management Based on Precision Agriculture

Yogeswari,

Padmapriya

2019

IJRTE

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Agriculture is the heart of our nation and society. It is influenced by several factors and parameters such as uneven monsoon, changing climate as well as weather circumstances, rainfall and nutrient facts during the harvest. Agriculture is primarily crucial and also the main source of our livelihood. But, owed to the scarceness of nutrients in plants, the human is strained to handle many dare in everyday life. The restoration of the nutrient is essential, in this view there is need to adopt precision agriculture system which change crop related plans and regulations, whereas nutrient management is a major domain that is needed to be spotlight in the field of farming techniques. The main aim of this research is to create an idea of developing a precision based recommender system for nutrient management and the main scope of this paper to describe the initial phase of the research. The experimental study of this research work is conducted using a terrace garden. The nutrient management with respect to the horticulture crop tomato is considered as the objective. The samples are grouped as two sets namely A and B representing samples without using natural fertilizers/manures and with natural fertilizers/manures. The growth parameters are analyzed and the results are presented. The data collection phase using sensors and Arduino kit is described here. The impact of pests and the remedy taken during the period of growth is recorded. The advices from the experts given in the soil tests are considered for preparing this nutrient management system.

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Sensor Placement Algorithm With Range Constraints for Precision Agriculture

Cited by 9 publications

References 51 publications

(Retracted) Role of video sensors in observing visual image design in the construction of smart cities

(Retracted) Role of video sensors in observing visual image design in the construction of smart cities

Cost efficient internet of things based smart farm system for rural farmers: Leveraging design thinking approach

Recommender System for Nutrient Management Based on Precision Agriculture

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