Early Warning System for Landslide Risk and SHM by Means of Reinforced Optic Fiber in Lifetime Strain Analysis

2020 ◽  
Author(s):  
Renato Zona ◽  
Martina De Cristofaro ◽  
Luca Esposito ◽  
Paolo Ferla ◽  
Simone Palladino ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Strain Analysis ◽  
Warning System ◽  
Landslide Risk ◽  
Optic Fiber

scholarly journals Application of FLaIR model for early warning system in Chibo Pashyor, Kalimpong, India for rainfall-induced landslides

2017 ◽  
Author(s):  
Abhirup Dikshit ◽  
Neelima Satyam
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Risk Mitigation ◽  
Warning System ◽  
Landslide Risk ◽  
Rainfall Forecasting ◽  
Landslide Occurrence ◽  
Mobility Function ◽  
Hourly Rainfall ◽  
Rainfall Model

Abstract. The development of an early warning system for landslides due to rainfall has become an indispensable part for landslide risk mitigation. This paper explains the application of the hydrological FLaIR (Forecasting of Landslides Induced by Rainfall) model, correlating rainfall amount and landslide events. The FLaIR model comprises of two modules: RL (Rainfall-Landslide) which correlates rainfall and landslide occurrence and RF (Rainfall-Forecasting) which allows simulation of future rainfall events. The model can predetermine landslides based on identification of mobility function Y(.) which links actual rainfall and incidence of landslide occurrence. The critical value of mobility function was analyzed using 1st July 2015 event and applying it to 2016 monsoon to validate the results. These rainfall thresholds presented can be improved with intense hourly rainfall and landslide inventory data. This paper describes the details of the model and its performance for the study area.

scholarly journals Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application

2017 ◽  
Vol 17 (10) ◽  
pp. 1713-1723 ◽  
Author(s):  
Emanuele Intrieri ◽  
Federica Bardi ◽  
Riccardo Fanti ◽  
Giovanni Gigli ◽  
Francesco Fidolini ◽  
...  
Keyword(s):  
Big Data ◽  
Early Warning ◽  
Early Warning System ◽  
Risk Mitigation ◽  
Warning System ◽  
Early Warning Systems ◽  
Integrated System ◽  
Monitoring Systems ◽  
Landslide Risk ◽  
Complex Data

Abstract. A big challenge in terms or landslide risk mitigation is represented by increasing the resiliency of society exposed to the risk. Among the possible strategies with which to reach this goal, there is the implementation of early warning systems. This paper describes a procedure to improve early warning activities in areas affected by high landslide risk, such as those classified as critical infrastructures for their central role in society. This research is part of the project LEWIS (Landslides Early Warning Integrated System): An Integrated System for Landslide Monitoring, Early Warning and Risk Mitigation along Lifelines. LEWIS is composed of a susceptibility assessment methodology providing information for single points and areal monitoring systems, a data transmission network and a data collecting and processing center (DCPC), where readings from all monitoring systems and mathematical models converge and which sets the basis for warning and intervention activities. The aim of this paper is to show how logistic issues linked to advanced monitoring techniques, such as big data transfer and storing, can be dealt with compatibly with an early warning system. Therefore, we focus on the interaction between an areal monitoring tool (a ground-based interferometric radar) and the DCPC. By converting complex data into ASCII strings and through appropriate data cropping and average, and by implementing an algorithm for line-of-sight correction, we managed to reduce the data daily output without compromising the capability for performing.

Application of a dynamic terrestrial landslide early warning system in a wide high-voltage transmission line coverage area

2020 ◽  
Author(s):  
Shuhao Liu ◽  
Kunlong Yin ◽  
Yiyue Zhang ◽  
Ting Xiao ◽  
Wei Lin
Keyword(s):  
Transmission Line ◽  
High Voltage ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Landslide Risk ◽  
Coverage Area ◽  
High Voltage Transmission Line ◽  
Transmission Towers ◽  
High Voltage Transmission

<p>The power grid is one of the most important lifeline projects in modern society. However, the complex transmission network was fixed to the ground through millions of transmission towers, which were inevitably being affected by various types of geohazard. The failure of local facilities may further cause large-scale power outages, leading serious social impact and economic loss. From this perspective, this study aims to develop a territorial landslide early warning system (Te-LEWS) for the high-voltage transmission line coverage area by introducing a novel method, combining landslide inventory and susceptibility maps, rainfall thresholds and real time rainfall forecast, transmission tower vulnerability analysis and GIS-based dynamic alert system. To this objective, the power grid system consisting of over 130,000 high-voltage transmission towers and covering an area of 7 provinces in China was selected as study objective to conducted susceptibility mapping with different classification methods (information value, random forest and support vector). The rainfall threshold of each county was calculated through analyzing a 7 consecutive day rainfall data for the major historical landslide event. Instead of an ordinary landslide risk assessment practice within the transmission line coverage area, this study mainly focuses on the landslide risk over transmission towers and tries to generate an risk assessment result over a specific risk bearing element with linear distribution characteristic, in this case the electricity transmission lines. With real-time predicted rainfall value as input variable, a dynamic landslide warning system was established on a pixel basis, to identify the transmission towers that are potentially vulnerable to landslide disasters. The performance of the proposed Te-LEWS system were validated through the historical rainfall data and the landslides events from 2015-2019, to gain a comprehensive evaluation on its warning accuracy. Results suggest that the system has a high warning success rate and the false alarm was significantly reduced. In such case, the proposed To-LEWS would greatly support the grid authorities in reducing disaster risks and retrieving huge economic loss. The study shed a new light on the risk analysis method of a specific linear distributed risk bearing element towards geohazard, to demonstrate its potential over wide areas, an application to a huge area in China was shown and discussed.</p><p><strong>Keywords</strong>: Landslides; GIS; early warning system; disaster risk reduction; high-voltage transmission line</p>

MODIFIKASI ASESMEN EARLY WARNING SYSTEM UPAYA PENINGKATAN PENERAPAN KESELAMATAN PASIEN

2020 ◽  
Vol 6 (2) ◽  
pp. 112
Author(s):  
Veronika Hutabarat ◽  
Enie Novieastari ◽  
Satinah Satinah
Keyword(s):  
Action Research ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Planning Action

Salah satu faktor dalam meningkatkan penerapan keselamatan pasien adalah ketersediaan dan efektifitas prasarana dalam rumah sakit. Early warning system (EWS) merupakan prasarana dalam mendeteksi perubahan dini  kondisi pasien. Penatalaksanaan EWS masih kurang efektif karena parameter dan nilai rentang scorenya belum sesuai dengan kondisi pasien. Tujuan penulisan untuk mengidentifikasi efektifitas EWS dalam penerapan keselamatan pasien. Metode penulisan action research melalui proses diagnosa, planning action, intervensi, evaluasi dan  refleksi. Responden dalam penelitian ini adalah  perawat yang bertugas di area respirasi dan pasien dengan kasus kompleks respirasi di Rumah Sakit Pusat Rujukan Pernapasan Persahabatan Jakarta. Analisis masalah dilakukan dengan menggunakan diagram fishbone. Masalah yang muncul belum optimalnya implementasi early warning system dalam penerapan keselamatan pasien. Hasilnya 100% perawat mengatakan REWS membantu mendeteksi kondisi pasien, 97,4 % perawat mengatakan lebih efektif dan 92,3 % perawat mengatakan lebih efesien mendeteksi perubahan kondisi pasien. Modifikasi EWS menjadi REWS lebih efektif dan efesien dilakukan karena disesuaikan dengan jenis dan kekhususan Rumah Sakit dan berdampak terhadap kualitas asuhan keperawatan dalam menerapkan keselamatan pasien. Rekomendasi perlu dilakukan monitoring evaluasi terhadap implementasi t.erhadap implementasi REWS dan pengembangan aplikasi berbasis tehnologi

Development of a Pediatric Early Warning System Using Data-Driven Vital Signs

PEDIATRICS ◽  
2016 ◽  
Vol 137 (Supplement 3) ◽  
pp. 256A-256A
Author(s):  
Catherine Ross ◽  
Iliana Harrysson ◽  
Lynda Knight ◽  
Veena Goel ◽  
Sarah Poole ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Vital Signs ◽  
Warning System ◽  
Data Driven ◽  
Using Data

KAJIAN KEKUATAN SINYAL RADIO (RSSI) XBEE DALAM RANGKA PEMASANGAN LANDSLIDE EARLY WARNING SYSTEM (LEWS) DI KABUPATEN GARUT, TASIKMALAYA DAN MAJALENGKA

2019 ◽  
Vol 3 (2) ◽  
pp. 88
Author(s):  
Riski Fitriani
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Received Signal Strength Indicator ◽  
Landslide Early Warning ◽  
Point To Point

Salah satu inovasi untuk menanggulangi longsor adalah dengan melakukan pemasangan Landslide Early Warning System (LEWS). Media transmisi data dari LEWS yang dikembangkan menggunakan sinyal radio Xbee. Sehingga sebelum dilakukan pemasangan LEWS, perlu dilakukan kajian kekuatan sinyal tersebut di lokasi yang akan terpasang yaitu Garut, Tasikmalaya, dan Majalengka. Kajian dilakukan menggunakan 2 jenis Xbee yaitu Xbee Pro S2B 2,4 GHz dan Xbee Pro S5 868 MHz. Setelah dilakukan kajian, Xbee 2,4 GHz tidak dapat digunakan di lokasi pengujian Garut dan Majalengka karena jarak modul induk dan anak cukup jauh serta terlalu banyak obstacle. Topologi yang digunakan yaitu topologi pair/point to point, dengan mengukur nilai RSSI menggunakan software XCTU. Semakin kecil nilai Received Signal Strength Indicator (RSSI) dari nilai receive sensitivity Xbee maka kualitas sinyal semakin baik. Pengukuran dilakukan dengan meninggikan antena Xbee dengan beberapa variasi ketinggian untuk mendapatkan kualitas sinyal yang lebih baik. Hasilnya diperoleh beberapa rekomendasi tinggi minimal antena Xbee yang terpasang di tiap lokasi modul anak pada 3 kabupaten.

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