Designing efficient soil resistivity measurement technique for agricultural wireless sensor network

Parashar, Vivek; Mishra, Bharat

doi:10.1002/dac.4785

Cited by 4 publications

(2 citation statements)

References 29 publications

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“…A Mobile Ad-hoc sensor node was introduced by Li et al, [22] to comprise the sensors to collect real time environment from the agricultural land with wireless communication technology and process the data before data sharing with other nodes in the network. Wireless sensor networks in ginseng field in precision agriculture were designed by Parashar et al, [23]. According to Abdollahi et al, [24], efficient soil resistivity measurement technique using wireless sensor network (WSN) has been proposed to collect and process the data for application in the agriculture fields.…”

Section: Related Workmentioning

confidence: 99%

Accurate Range Free Location based Partial Derivative and Stochastic Feedforward Neural Network Hyperbolic-based Agriculture Sensor Network Formation

R Saravanan,

V. Sathya

2023

ARASET

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Wireless sensor networks (WSN) authorize the control of different source environmental aspects and crop states as far as precision agriculture is concerned. Nevertheless, the complicated agricultural environment brings about the WSN topology to change often and hence link association likelihood is laborious to predict. Information pertaining to agriculture is an essential distress for localization-based service in the domain of WSNs. Smooth planning and control as the most typical range-free localization method localization performance is said to be good in even distributed networks. Nevertheless, it demonstrated extremely poor accuracy under that in an urgent issue that required to be addressed. In this work a novel topology construction method called, Partial Derivative Laurent Approximation and Stochastic Feedforward Hyperbolic (PDLA-SFH) based Agriculture Sensor Network Formation is proposed. The proposed method is split into three steps. They are agriculture sensor topology construction, average hop size distance validation and position estimation. First topology construction is performed by employing Game Theory Partial Derivative Regression Coefficient-based Topology model. Second, Laurent Approximation-based Hop Size Distance validation model is designed for optimal topology formation. Finally the Stochastic Feedforward Hyperbolic-based Position Estimation is modeled. The simulation results performed in NS3 showed that the proposed localization algorithms can attain better localization performance in terms of accuracy, time and error rate in comparison with other existing methods such as basic Digital Twins and Autonomous Groups Particles Swarm Optimization (AGPSO) under distinct arbitrary network topologies.

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Section: Related Workmentioning

confidence: 99%

Accurate Range Free Location based Partial Derivative and Stochastic Feedforward Neural Network Hyperbolic-based Agriculture Sensor Network Formation

R Saravanan,

V. Sathya

2023

ARASET

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“…Furthermore, sensor nodes could monitor soil physical and biochemical attributes to increase productivity and decrease environmental footprint [144]. Sensor nodes also could measure, monitor, and integrate various soil quality parameters [145]; automate irrigation through humidity, temperature, and pH sensors [133]; and measure soil resistivity [146].…”

Section: Soil Managementmentioning

confidence: 99%

Wireless Sensor Networks in Agriculture: Insights from Bibliometric Analysis

Abdollahi

Rejeb

et al. 2021

Sustainability

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This study investigates how wireless sensor network (WSN) applications in agriculture are discussed in the current academic literature. On the basis of bibliometric techniques, 2444 publications were extracted from the Scopus database and analyzed to identify the temporal distribution of WSN research, the most productive journals, the most cited authors, the most influential studies, and the most relevant keywords. The computer program VOSviewer was used to generate the keyword co-occurrence network and partition the pertinent literature. Findings show the remarkable growth of WSN research in recent years. The most relevant journals, cited countries, and influential studies were also identified. The main results from the keyword co-occurrence clustering and the detailed analysis illustrate that WSN is a key enabler for precision agriculture. WSN research also focuses on the role of other technologies such as the Internet of Things, cloud computing, artificial intelligence, and unmanned aerial vehicles in supporting several agriculture activities, including smart irrigation and soil management. This study illuminates researchers’ and practitioners’ views of what has been researched and identifies possible opportunities for future studies. To the authors’ best knowledge, this bibliometric study represents the first attempt to map global WSN research using a comprehensive sample of documents published over nearly three decades.

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Wireless communication protocols in smart agriculture: A review on applications, challenges and future trends

Avşar

Mowla

2022

Ad Hoc Networks

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Designing efficient soil resistivity measurement technique for agricultural wireless sensor network

Cited by 4 publications

References 29 publications

Accurate Range Free Location based Partial Derivative and Stochastic Feedforward Neural Network Hyperbolic-based Agriculture Sensor Network Formation

Accurate Range Free Location based Partial Derivative and Stochastic Feedforward Neural Network Hyperbolic-based Agriculture Sensor Network Formation

Wireless Sensor Networks in Agriculture: Insights from Bibliometric Analysis

Wireless communication protocols in smart agriculture: A review on applications, challenges and future trends

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