Evidence map›Paper›PMID 36081133›Full record

ArticleSensors (Basel, Switzerland)2022

Traffic-Aware Secured Cooperative Framework for IoT-Based Smart Monitoring in Precision Agriculture.

Ibrahim Abunadi, Amjad Rehman, Khalid Haseeb, Lorena Parra, Jaime Lloret

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
4.0field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 19 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 2 countries.

Ibrahim AbunadiCollege of Computer & Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia.ORCID 0000-0002-2546-2450
Amjad RehmanCollege of Computer & Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia.ORCID 0000-0002-0101-0329
Khalid HaseebArtificial Intelligence and Data Analytics (AIDA) Lab, CCIS Prince Sultan University, Riyadh 11586, Saudi Arabia.ORCID 0000-0001-6657-9308
Lorena ParraInstituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politenica de Valencia, 46022 Valencia, Spain.ORCID 0000-0001-9215-8734
Jaime LloretInstituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politenica de Valencia, 46022 Valencia, Spain.ORCID 0000-0002-0862-0533
Prince Sultan University · SA

Funding

Ministerio de Agricultura, Pesca y Alimentación GO TECNOGARMinisterio de Ciencia e Innovación PID2020-114467RR-C33Prince Sultan University SEED-CCIS-2022{109}
6 · The paper itself

Abstract

In recent decades, networked smart devices and cutting-edge technology have been exploited in many applications for the improvement of agriculture. The deployment of smart sensors and intelligent farming techniques supports real-time information gathering for the agriculture sector and decreases the burden on farmers. Many solutions have been presented to automate the agriculture system using IoT networks; however, the identification of redundant data traffic is one of the most significant research problems. Additionally, farmers do not obtain the information they need in time, such as data on water pressure and soil conditions. Thus, these solutions consequently reduce the production rates and increase costs for farmers. Moreover, controlling all agricultural operations in a controlled manner should also be considered in developing intelligent solutions. Therefore, this study proposes a framework for a system that combines fog computing with smart farming and effectively controls network traffic. Firstly, the proposed framework efficiently monitors redundant information and avoids the inefficient use of communication bandwidth. It also controls the number of re-transmissions in the case of malicious actions and efficiently utilizes the network's resources. Second, a trustworthy chain is built between agricultural sensors by utilizing the fog nodes to address security issues and increase reliability by preventing malicious communication. Through extensive simulation-based experiments, the proposed framework revealed an improved performance for energy efficiency, security, and network connectivity in comparison to other related works.

Indexed as

AgricultureWireless TechnologyPhysical PhenomenaReproducibility of Resultsagriculture systemfog systemgreen energyInternet of Thingssoil monitoring

Identifiers

PMID36081133
PMCPMC9460273
OpenAlexW4295084703

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.