Evidence map›Paper›PMID 32028736›Full record

ArticleSensors (Basel, Switzerland)2020

Advanced UAV-WSN System for Intelligent Monitoring in Precision Agriculture.

Dan Popescu, Florin Stoican, Grigore Stamatescu, Loretta Ichim, Cristian Dragana

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
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

23 citing papers in PubMed.

  1. Review
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  17. Data Gathering Techniques in WSN: A Cross-Layer View.Sensors (Basel, Switzerland) · 2022
    Review
  18. Article
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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.

Dan PopescuFaculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania.
Florin StoicanFaculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania.ORCID 0000-0002-4550-9113
Grigore StamatescuFaculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania.ORCID 0000-0002-9647-6817
Loretta IchimFaculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania.
Cristian DraganaFaculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing need for food worldwide requires the development of a high-performance, high-productivity, and sustainable agriculture, which implies the introduction of new technologies into monitoring activities related to control and decision-making. In this regard, this paper presents a hierarchical structure based on the collaboration between unmanned aerial vehicles (UAVs) and federated wireless sensor networks (WSNs) for crop monitoring in precision agriculture. The integration of UAVs with intelligent, ground WSNs, and IoT proved to be a robust and efficient solution for data collection, control, analysis, and decisions in such specialized applications. Key advantages lay in online data collection and relaying to a central monitoring point, while effectively managing network load and latency through optimized UAV trajectories and in situ data processing. Two important aspects of the collaboration were considered: designing the UAV trajectories for efficient data collection and implementing effective data processing algorithms (consensus and symbolic aggregate approximation) at the network level for the transmission of the relevant data. The experiments were carried out at a Romanian research institute where different crops and methods are developed. The results demonstrate that the collaborative UAV-WSN-IoT approach increases the performances in both precision agriculture and ecological agriculture.

Indexed as

Computer Communication NetworksCrops, AgriculturalData CollectionHumansRemote Sensing TechnologyWireless Technologydata consensusintelligent data processingInternet of Thingsprecision agriculturerelevant data extractiontrajectory planningunmanned aerial vehicleswireless sensor networks

Identifiers

PMID32028736
PMCPMC7038696

What OpenQuestion holds

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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.