Recent Advances in Early Warning Systems for Landslide Forecasting

Wanare, Ram; Iyer, Kannan K. R.; Jayanthi, Prathyusha

doi:10.1007/978-981-16-6140-2_20

Cited by 5 publications

(1 citation statement)

References 26 publications

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“…Compared to other reviews, surveys, or papers containing literature overviews that focus on a particular type of disastrous event or a single category of hazards, such as [ 17 , 18 , 19 , 20 , 21 , 22 , 23 ], this paper takes into account multiple natural disasters highlighting the differences from one case to the other, in term of IoT architectures and systems requirements such as the required latency constraints. While some reviews, such as [ 20 , 21 ], more explicitly focused on prediction algorithms, Machine Learning prediction models and Computer Vision, or post-disaster management, the main focus of this work is on the adopted IoT solutions and their possible optimizations, including system requirements, communication protocols, data processing, and sensor network topology aspects.…”

Section: Introductionmentioning

confidence: 99%

Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review

Esposito

Palma

Belli

et al. 2022

Sensors

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Natural disasters cause enormous damage and losses every year, both economic and in terms of human lives. It is essential to develop systems to predict disasters and to generate and disseminate timely warnings. Recently, technologies such as the Internet of Things solutions have been integrated into alert systems to provide an effective method to gather environmental data and produce alerts. This work reviews the literature regarding Internet of Things solutions in the field of Early Warning for different natural disasters: floods, earthquakes, tsunamis, and landslides. The aim of the paper is to describe the adopted IoT architectures, define the constraints and the requirements of an Early Warning system, and systematically determine which are the most used solutions in the four use cases examined. This review also highlights the main gaps in literature and provides suggestions to satisfy the requirements for each use case based on the articles and solutions reviewed, particularly stressing the advantages of integrating a Fog/Edge layer in the developed IoT architectures.

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Section: Introductionmentioning

confidence: 99%

Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review

Esposito

Palma

Belli

et al. 2022

Sensors

View full text Add to dashboard Cite

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Characterising landslide susceptibility of an environmentally fragile region of the Western Ghats in Idukki district, Kerala, India, through statistical modelling and hotspot analysis

2022

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A new early warning Criterion for assessing landslide risk

Ning²,

Chicas³

et al. 2022

Nat Hazards

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A large number of engineering examples show that the displacement speed ratio(DSR) warning criterion derived from displacement as a single base information can predict the occurrence of landslides, but cannot identify the future development direction of landslides, which leads to false alarms in the warning system. In order to solve this problem, a trend speed ratio(TSR) is proposed, taking ve landslides as examples, and the research results show that when the TSR is greater than 2.0, the landslide is destroyed; when the TSR shows a decreasing trend, the landslide tends to be stabilized; and for the undamaged stepped landslide, the TSR is always less than 2.0 at the stepped acceleration in ection point of the landslide. Compared with the traditional method, the new method can identify the development direction of the landslide, and can perform a risk assessment of the stepped landslide, which provides new technical support for engineers engaged in landslide warning and prevention.

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Recent Advances in Early Warning Systems for Landslide Forecasting

Cited by 5 publications

References 26 publications

Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review

Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review

Characterising landslide susceptibility of an environmentally fragile region of the Western Ghats in Idukki district, Kerala, India, through statistical modelling and hotspot analysis

A new early warning Criterion for assessing landslide risk

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