scholarly journals IoT-based Lava Flood Early Warning System with Rainfall Intensity Monitoring and Disaster Communication Technology

2021 ◽  
Vol 4 ◽  
pp. 154-166
Author(s):  
Iswanto Suwarno ◽  
Alfian Ma’arif ◽  
Nia Maharani Raharja ◽  
Adhianty Nurjanah ◽  
Jazaul Ikhsan ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Communication Systems ◽  
Warning System ◽  
Rain Gauge ◽  
Disaster Mitigation ◽  
Vibration Sensor ◽  
Decision Algorithm ◽  
Disaster Communication ◽  
Flood Detection

A lava flood disaster is a volcanic hazard that often occurs when heavy rains are happening at the top of a volcano. This flood carries volcanic material from upstream to downstream of the river, affecting populous areas located quite far from the volcano peak. Therefore, an advanced early warning system of cold lava floods is inarguably vital. This paper aims to present a reliable, remote, Early Warning System (EWS) specifically designed for lava flood detection, along with its disaster communication system. The proposed system consists of two main subsystems: lava flood detection and disaster communication systems. It utilizes a modified automatic rain gauge; a novel configured vibration sensor; Fuzzy Tree Decision algorithm; ESP microcontrollers that support IoT, and disaster communication tools (WhatsApp, SMS, radio communication). According to the experiment results, the prototype of rainfall detection using the tipping bucket rain gauge sensor can measure heavy and moderate rainfall intensities with 81.5% accuracy. Meanwhile, the prototype of earthquake vibration detection using a geophone sensor can remove noise from car vibrations with a Kalman filter and measure vibrations in high and medium intensity with an accuracy of 89.5%. Measurements from sensors are sent to the webserver. The disaster mitigation team uses data from the webserver to evacuate residents using the disaster communication method. The proposed system was successfully implemented in Mount Merapi, Indonesia, coordinated with the local Disaster Deduction Risk (DDR) forum. Doi: 10.28991/esj-2021-SP1-011 Full Text: PDF

scholarly journals Feasibility study of earthquake early warning in Tehran, Iran

2021 ◽  
Author(s):  
S. Enferadi ◽  
Z. H. Shomali ◽  
A. Niksejel
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Disaster Mitigation ◽  
Lead Times ◽  
Worst Case ◽  
Earthquake Parameters ◽  
Earthquake Early Warning System ◽  
Earthquake Scenarios

AbstractIn this study, we examine the scientific feasibility of an Earthquake Early Warning System in Tehran, Iran, by the integration of the Tehran Disaster Mitigation and Management Organization (TDMMO) accelerometric network and the PRobabilistic and Evolutionary early warning SysTem (PRESTo). To evaluate the performance of the TDMMO-PRESTo system in providing the reliable estimations of earthquake parameters and the available lead-times for The Metropolis of Tehran, two different approaches were analyzed in this work. The first approach was assessed by applying the PRESTo algorithms on waveforms from 11 moderate instrumental earthquakes that occurred in the vicinity of Tehran during the period 2009–2020. Moreover, we conducted a simulation analysis using synthetic waveforms of 10 large historical earthquakes that occurred in the vicinity of Tehran. We demonstrated that the six worst-case earthquake scenarios can be considered for The Metropolis of Tehran, which are mostly related to the historical and instrumental events that occurred in the southern, eastern, and western parts of Tehran. Our results indicate that the TDMMO-PRESTo system could provide reliable and sufficient lead-times of about 1 to 15s and maximum lead-times of about 20s for civil protection purposes in The Metropolis of Tehran.

The Utility Model of Early Warning System for Train Operation

2013 ◽  
Vol 325-326 ◽  
pp. 1249-1252
Author(s):  
Shi Yi
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Weather Conditions ◽  
Vibration Sensor ◽  
Utility Model ◽  
Photoelectric Detection ◽  
Train Operation

The utility model of early warning system for train operation detects and analysis all the information from the weather detection, photoelectric detection, vibration sensor and signal of the tracks comprehensively. It determines the position of the train by the weighted coefficients and controls the interval signal and locomotive signal accurately. This system should be barely affected by the weather conditions, the results detected by this system are reliable, and it can ensure the train operates safely.

scholarly journals RISIKO KAWASAN LONGSOR DALAM UPAYA MITIGASI BENCANA MENGGUNAKAN SISTEM INFORMASI GEOGRAFIS

Pondasi ◽  
2019 ◽  
Vol 24 (1) ◽  
pp. 67
Author(s):  
Fakhryza Nabila Hamida ◽  
Hasti Widyasamratri
Keyword(s):  
Land Use ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Disaster Risk ◽  
Risk Mapping ◽  
Disaster Mitigation ◽  
Accurate Information ◽  
Loss Of Life ◽  
Landslide Disaster

ABSTRACTIndonesia is an area prone to landslides. The occurrence of this landslide disaster can cause a large impact such as damage and loss both material and non-material. The availability of complete and accurate information in controlling land use in landslide prone areas in the development of an area becomes very important in minimizing the loss of life and losses, both physical, social and economic. This information must be disseminated to the community as an early warning system in disaster mitigation efforts. Identification of the characteristics of landslide prone areas requires a risk mapping of landslide prone areas in efforts to mitigate disasters can be done using Geographic Information Systems (GIS). The results in this study indicate the need to identify disaster risk in detail because basically, an area threatened by disaster does not necessarily mean that each community has the same level of disaster risk. Mapping can be done by clustering or by identifying each building in a vulnerable area based on the level of risk of landslides. Keywords: risk analysis, landslides, disaster mitigation, GIS ABSTRAKIndonesia merupakan wilayah yang rawan terhadap bencana longsor. Terjadinya bencana longsor ini dapat menyebabkan dampak yang besar seperti kerusakan dan kerugian baik materiil maupun non materiil. Tersedianya informasi yang lengkap dan akurat dalam pengendalian pemanfaatan lahan di kawasan rawan bencana longsor dalam pengembangan suatu wilayah menjadi hal yang sangat penting dalam meminimalisir adanya korban jiwa dan kerugian-kerugian baik fisik, sosial maupun ekonomi. Informasi tersebut harus disebarkan kepada masyarakat sebagai sistem peringatan dini dalam upaya mitigasi bencana. Identifikasi karakteristik daerah rawan longsor diperlukan sebuah pemetaan risiko kawasan rawan longsor dalam upaya mitigasi bencana dapat dilakukan menggunakan Sistem Informasi Geografis (SIG). Hasil dalam penelitian ini menunjukkan perlunya identifikasi risiko bencana secara detail karena pada dasarnya, suatu kawasan yang terancam bencana belum tentu tiap masyarakatnya mempunyai tingkat risiko bencana yang sama. Pemetaan dapat dilakukan dengan pengklusteran maupun dengan identifikasi setiap bangunan dalam kawasan rawan berdasarkan tingkat risiko terhadap bencana tanah longsor.Kata Kunci: analisis risiko, tanah longsor, mitigasi bencana, GIS

scholarly journals Internet-Based Flood Detection System (Iot) and Telegram Messenger Using Mcu Node and Water Level Sensor

2020 ◽  
Vol 4 (1) ◽  
pp. 230-235
Author(s):  
Novianda Nanda Nanda ◽  
Rizalul Akram ◽  
Liza Fitria
Keyword(s):  
Water Level ◽  
Early Warning ◽  
High Intensity ◽  
Rainy Season ◽  
Early Warning System ◽  
Detection System ◽  
Warning System ◽  
Level Sensor ◽  
Flood Detection ◽  
Internet Of Thing

During the rainy season, several regions in Indonesia experienced floods even to the capital of Indonesia also flooded. Some of the causes are the high intensity of continuous rain, clogged or non-smooth drainage, high tides to accommodate the flow of water from rivers, other causes such as forest destruction, shallow and full of garbage and other causes. Every flood disaster comes, often harming the residents who experience it. The late anticipation from the community and the absence of an early warning system or information that indicates that there will be a flood so that the community is not prepared to face floods that cause a lot of losses. Therefore it is necessary to have a detection system to provide early warning if floods will occur, this is very important to prevent material losses from flooded residents. From this problem the researchers designed an internet-based flood detection System of Things (IoT). This tool can later be controlled via a smartphone remotely and can send messages Telegram messenger to citizens if the detector detects a flood will occur.Keywords: Flooding, Smartphone, Telegram messenger, Internet of Thing (IoT).

scholarly journals Design and Implementation of Real-Time Flood Early Warning System (FEWS) Based on IoT Blynk Application

ELKHA ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 113
Author(s):  
Hasbi Nur Prasetyo Wisudawan
Keyword(s):  
Water Level ◽  
Real Time ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Disaster Risk ◽  
Disaster Mitigation ◽  
Average Temperature ◽  
Flood Warning ◽  
Flood Warning System

Disaster occurrence in Indonesia needs attention and role from all parties including the community to reduce the risks.  Disaster mitigation is one of the ways to reduce the disaster risk through awareness, capacity building, and the development of physical facilities, for example by applying disaster mitigation technology (early warning system, EWS). EWS is one of the effective methods to minimize losses due to disasters by providing warning based on certain parameters for disasters which usually occur such as floods. This research promotes a real-time IoT-based EWS flood warning system (Flood Early Warning System, FEWS) using Arduino and Blynk as well as Global System for Mobile Communication network (GSM) as the communication medium. The steps for implementing FEWS system in real locations are also discussed in this paper. Parameters such as water level, temperature, and humidity as well as rain conditions that are read by the EWS sensor can be accessed in real-time by using android based Blynk application that has been created. The result of the measurement of average temperature, humidity, and water level were 28.6 oC, 63.7 %, and 54.5 cm. Based on this analysis, the parameters indicated that the water level is in normal condition and there are no signs indicating that there will be flooding in the 30 days observation.  Based on the data collected by the sensor, FEWS can report four conditions, namely Normal, Waspada Banjir (Advisory), Siaga Banjir (Watch), and Awas Banjir (Warning) that will be sent immediately to the Blynk FEWS application user that has been created.

Special Issue on Early Warning for Natural Disaster Mitigation

2009 ◽  
Vol 4 (4) ◽  
pp. 529-529
Author(s):  
Masato Motosaka
Keyword(s):  
Research And Development ◽  
Natural Disaster ◽  
Earthquake Engineering ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Academic Community ◽  
Disaster Mitigation ◽  
Observation Data ◽  
Special Issue

Japan and many other counties face the risk of the natural disaster such as earthquakes, tsunamis, and floods. Natural disaster mitigation research and development are providing important, practical applications based on the development of the scientific technology. One major contribution is early warning system, being backed by observation and communication technology progress. Early warning research and development have been extensively studied domestically and internationally. Specifically, recent developments in earthquake engineering research and construction of seismic dense network have made it possible to issue earthquake warnings before the arrival of severe shaking. Such warnings enable emergency measures to be taken to protect lives, buildings, infrastructure, and transport from earthquake depredations. One such system went into practical use nationwide in Japan starting on October 1, 2007. Development has been conducted with cooperation of government, academic community and non-government, and private organizations. This special issue features papers on the early warning system for the natural disastermitigation covering issues ranging from natural science to social science. The recent developed earthquake early warning technology and its applications will be introduced. Besides earthquakes, the recent early warning technology for tsunami and flood are also included in this issue. The warning time available for tsunami and flood is much longer than that for earthquakes, and the contribution of numerical calculation using the real-time observation data differs with the type of disaster. Finally I would like to express my deepest gratitude for anonymous reviewers of papers in this special issue.

scholarly journals Development of Low Cost Vibration Sensor Network for Early Warning System of Landslides

2016 ◽  
Vol 89 ◽  
pp. 417-420 ◽  
Author(s):  
Somchai Biansoongnern ◽  
Boonyang Plungkang ◽  
Sriwichai Susuk
Keyword(s):  
Sensor Network ◽  
Early Warning ◽  
Early Warning System ◽  
Low Cost ◽  
Warning System ◽  
Vibration Sensor

scholarly journals Utilization of the IoT-based early warning system (EWS) for early detection of floods in Setu District, South Tangerang City

2021 ◽  
Vol 6 (8) ◽  
pp. 1414-1419
Author(s):  
Wahyu Sejati ◽  
Ning Adiasih ◽  
Tjhwa Endang Djuana
Keyword(s):  
Early Detection ◽  
Water Level ◽  
Community Service ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Ultrasonic Sensor ◽  
Detection Tool ◽  
Flood Detection

Cisadane River is the largest river whose overflow often causes flooding in several locations in South Tangerang City. One of them is located in Pesona Serpong Housing, Setu District, South Tangerang City. The Cisadane Environmental Echo Community (GEMALA) is a community that cares about the sustainability of the Cisadane River. This community service aims to improve understanding of river maintenance and socialize the IoT-based Early Warning System (EWS) tool to the GEMALA community as an early flood detection tool. The method used is to use an ultrasonic sensor HC-SR04 which will measure the water level of the river and will send a signal via the Telegram messaging application. At the end of this activity, an IoT-based Early Warning System (EWS) tool was produced that could be utilized by the GEMALA community as an early flood detection tool.

PENERAPAN ALGORITMA CLUSTERING DALAM MENGELOMPOKKAN BANYAKNYA DESA/KELURAHAN MENURUT UPAYA ANTISIPASI/ MITIGASI BENCANA ALAM MENURUT PROVINSI DENGAN K-MEANS

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Mhd Gading Sadewo ◽  
Agus Perdana Windarto ◽  
Anjar Wanto
Keyword(s):  
Natural Disaster ◽  
Early Warning ◽  
Early Warning System ◽  
Clustering Algorithm ◽  
Warning System ◽  
Volcanic Eruptions ◽  
Disaster Mitigation ◽  
Assessment Process ◽  
The Government ◽  
The Village

Natural disasters are natural events that have a large impact on the human population. Located on the Pacific Ring of Fire (an area with many tectonic activities), Indonesia must continue to face the risk of volcanic eruptions, earthquakes, floods, tsunamis. Application of Clustering Algorithm in Grouping the Number of Villages / Villages According to Anticipatory / Natural Disaster Mitigation Efforts by Province With K-Means. The source of this research data is collected based on documents that contain the number of villages / kelurahan according to natural disaster mitigation / mitigation efforts produced by the National Statistics Agency. The data used in this study is provincial data consisting of 34 provinces. There are 4 variables used, namely the Natural Disaster Early Warning System, Tsunami Early Warning System, Safety Equipment, Evacuation Line. The data will be processed by clustering in 3 clushter, namely clusther high level of anticipation / mitigation, clusters of moderate anticipation / mitigation levels and low anticipation / mitigation levels. The results obtained from the assessment process are based on the Village / Kelurahan index according to the Natural Disaster Anticipation / Mitigation Efforts with 3 provinces of high anticipation / mitigation levels, namely West Java, Central Java, East Java, 9 provinces of moderate anticipation / mitigation, and 22 other provinces including low anticipation / mitigation. This can be an input to the government, the provinces that are of greater concern to the Village / Village According to the Natural Health Disaster Mitigation / Mitigation Efforts based on the cluster that has been carried out.Keywords: Data Mining, Natural Disaster, Clustering, K-Means

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