Evidence map›Paper›PMID 37631814›Full record

ArticleSensors (Basel, Switzerland)2023

Wireless Sensor Network-Based Rockfall and Landslide Monitoring Systems: A Review.

Mattia Ragnoli, Massimo Scarsella, Alfiero Leoni, Giuseppe Ferri, Vincenzo Stornelli

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Mattia RagnoliDepartment of Industrial and Information Engineering and Economics, University of L'Aquila, 67100 L'Aquila, Italy.ORCID 0000-0002-1536-3969
Massimo ScarsellaDepartment of Industrial and Information Engineering and Economics, University of L'Aquila, 67100 L'Aquila, Italy.ORCID 0000-0001-6305-1356
Alfiero LeoniDepartment of Industrial and Information Engineering and Economics, University of L'Aquila, 67100 L'Aquila, Italy.ORCID 0000-0002-0066-4216
Giuseppe FerriDepartment of Industrial and Information Engineering and Economics, University of L'Aquila, 67100 L'Aquila, Italy.ORCID 0000-0002-8060-9558
Vincenzo StornelliDepartment of Industrial and Information Engineering and Economics, University of L'Aquila, 67100 L'Aquila, Italy.ORCID 0000-0001-7082-9429

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rockfalls and landslide events are caused by different factors among which are included geomorphological and climatic factors and also human interaction. Therefore, the economic and social impacts can be significant and the remote monitoring of such hazards has become an essential topic in various applications. Wireless sensor networks (WSNs) are well suited for the deployment of monitoring systems, benefiting from the different technologies and topologies that are available and evolving nowadays. This review paper aims to summarize and overview the up-to-date state of the art of rockfall and landslide monitoring systems based on WSNs. The implementation and methods were analyzed for each solution, along with the system architecture and relevant hardware aspects. All the retrieved data were used to analyze the current trends and future possibilities in the field of WSN geohazard monitoring.

Indexed as

geohazardIoTlandslide monitoringrisk assessmentrockfall monitoringsensorswireless sensor network

Identifiers

PMID37631814
PMCPMC10459084

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.