scholarly journals Community and Impact Based Early Warning System for Flood Risk Preparedness: The Experience of the Sirba River in Niger

2020 ◽  
Vol 12 (5) ◽  
pp. 1802 ◽  
Author(s):  
Vieri Tarchiani ◽  
Giovanni Massazza ◽  
Maurizio Rosso ◽  
Maurizio Tiepolo ◽  
Alessandro Pezzoli ◽  
...  
Keyword(s):  
Early Warning ◽  
Production Systems ◽  
Local Level ◽  
Warning System ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Top Down ◽  
Community Monitoring ◽  
Operational Decision Making ◽  
Set Up

Floods have recently become a major hazard in West Africa (WA) in terms of both their magnitude and frequency. They affect livelihoods, infrastructure and production systems, hence impacting on Sustainable Development (SD). Early Warning Systems (EWS) for floods that properly address all four EWS components, while also being community and impact-based, do not yet exist in WA. Existing systems address only the main rivers, are conceived in a top-down manner and are hazard-centered. This study on the Sirba river in Niger aims to demonstrate that an operational community and impact-based EWS for floods can be set up by leveraging the existing tools, local stakeholders and knowledge. The main finding of the study is that bridging the gap between top-down and bottom-up approaches is possible by directly connecting the available technical capabilities with the local level through a participatory approach. This allows the beneficiaries to define the rules that will develop the whole system, strengthening their ability to understand the information and take action. Moreover, the integration of hydrological forecasts and observations with the community monitoring and preparedness system provides a lead time suitable for operational decision-making at national and local levels. The study points out the need for the commitment of governments to the transboundary sharing of flood information for EWS and SD.

scholarly journals Towards Landslides Early Warning System With Fog - Edge Computing And Artificial Intelligence**

2021 ◽  
Vol 15 (02) ◽  
pp. 11-17
Author(s):  
Olivier Debauche ◽  
Meryem Elmoulat ◽  
Saïd Mahmoudi ◽  
Sidi Ahmed Mahmoudi ◽  
Adriano Guttadauria ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Large Scale ◽  
Prediction Models ◽  
Warning System ◽  
Early Warning Systems ◽  
Economic Losses ◽  
Warning Systems ◽  
Large Scale Data ◽  
Set Up

Landslides are phenomena that cause significant human and economic losses. Researchers have investigated the prediction of high landslides susceptibility with various methodologies based upon statistical and mathematical models, in addition to artificial intelligence tools. These methodologies allow to determine the areas that could present a serious risk of landslides. Monitoring these risky areas is particularly important for developing an Early Warning Systems (EWS). As matter of fact, the variety of landslides’ types make their monitoring a sophisticated task to accomplish. Indeed, each landslide area has its own specificities and potential triggering factors; therefore, there is no single device that can monitor all types of landslides. Consequently, Wireless Sensor Networks (WSN) combined with Internet of Things (IoT) allow to set up large-scale data acquisition systems. In addition, recent advances in Artificial Intelligence (AI) and Federated Learning (FL) allow to develop performant algorithms to analyze this data and predict early landslides events at edge level (on gateways). These algorithms are trained in this case at fog level on specific hardware. The novelty of the work proposed in this paper is the integration of Federated Learning based on Fog-Edge approaches to continuously improve prediction models.

Early Warning System Framework Proposal Based on Structured Analytical Techniques, SNA, and Fuzzy Expert System for Different Industries

Fuzzy Systems ◽  
2017 ◽  
pp. 202-234
Author(s):  
Goran Klepac ◽  
Robert Kopal ◽  
Leo Mrsic
Keyword(s):  
Data Mining ◽  
Expert System ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Early Warning Systems ◽  
Fuzzy Expert System ◽  
Warning Systems ◽  
Single Data ◽  
Set Up

Early warning systems are made with purpose to efficiently recognize deviant and potentially dangerous trends related to company business as early as possible and with significant relevance. There are numerous ways to set up early warning systems within company. Those solutions are often based on single data mining methods, and they rarely provide the holistic and qualitative approach needed in modern market uncertainty conditions. This chapter gives a novel concept for early warning system design within company, applicable in different industries. The core of the proposed framework is hybrid fuzzy expert system, which can contain a variety of data mining predictive models responsible for some specific areas in addition to traditional rule blocks. It can also include social network analysis metrics based on linguistic variables and incorporated within rule blocks. As part of this framework, SNA methods are also explained and introduced as a very powerful and unique tool to be used in modern early warning systems.

Early Warning System Framework Proposal Based on Structured Analytical Techniques, SNA, and Fuzzy Expert System for Different Industries

2015 ◽  
pp. 763-796 ◽  
Author(s):  
Goran Klepac ◽  
Robert Kopal ◽  
Leo Mrsic
Keyword(s):  
Data Mining ◽  
Expert System ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Early Warning Systems ◽  
Fuzzy Expert System ◽  
Warning Systems ◽  
Single Data ◽  
Set Up

Early warning systems are made with purpose to efficiently recognize deviant and potentially dangerous trends related to company business as early as possible and with significant relevance. There are numerous ways to set up early warning systems within company. Those solutions are often based on single data mining methods, and they rarely provide the holistic and qualitative approach needed in modern market uncertainty conditions. This chapter gives a novel concept for early warning system design within company, applicable in different industries. The core of the proposed framework is hybrid fuzzy expert system, which can contain a variety of data mining predictive models responsible for some specific areas in addition to traditional rule blocks. It can also include social network analysis metrics based on linguistic variables and incorporated within rule blocks. As part of this framework, SNA methods are also explained and introduced as a very powerful and unique tool to be used in modern early warning systems.

Early Warning System Framework Proposal, Based on Big Data Environment

2019 ◽  
Vol 9 (1) ◽  
pp. 35-66
Author(s):  
Goran Klepac ◽  
Robert Kopal ◽  
Leo Mrsic
Keyword(s):  
Big Data ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Data Environment ◽  
Set Up ◽  
Novel Concept ◽  
A Company

Early warning systems are made with the purpose to efficiently recognize deviant and potentially dangerous trends related to company business as early as possible. The Big Data environment gives new opportunities and new approaches in analytical processes. There are numerous ways how to set up early warning systems within a company. The Big Data environment forces companies to apply new ways of thinking and use new disposable data sources. This article gives a novel concept for an early warning system design within a company, which is applicable in different industries. The core of the proposed framework is a hybrid fuzzy expert system which can contain a variety of data mining predictive models responsible for some specific areas as addition to traditional rule blocks. It can also include social network analysis metrics based on linguistic variables and incorporated within the rule blocks. As a part of this framework, SNA methods are also explained and introduced as powerful and unique tool to be used in modern early warning systems.

scholarly journals Brief communication "Landslide Early Warning System: toolbox and general concepts"

2013 ◽  
Vol 13 (1) ◽  
pp. 85-90 ◽  
Author(s):  
E. Intrieri ◽  
G. Gigli ◽  
N. Casagli ◽  
F. Nadim
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Early Warning Systems ◽  
End Users ◽  
Flow Chart ◽  
Warning Systems ◽  
Limited Experience ◽  
Practical Guidelines ◽  
Landslide Early Warning

Abstract. We define landslide Early Warning Systems and present practical guidelines to assist end-users with limited experience in the design of landslide Early Warning Systems (EWSs). In particular, two flow chart-based tools coming from the results of the SafeLand project (7th Framework Program) have been created to make them as simple and general as possible and in compliance with a variety of landslide types and settings at single slope scale. We point out that it is not possible to cover all the real landslide early warning situations that might occur, therefore it will be necessary for end-users to adapt the procedure to local peculiarities of the locations where the landslide EWS will be operated.

scholarly journals Communication architecture of an early warning system

2010 ◽  
Vol 10 (11) ◽  
pp. 2215-2228 ◽  
Author(s):  
M. Angermann ◽  
M. Guenther ◽  
K. Wendlandt
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Satellite Communication ◽  
Warning System ◽  
Early Warning Systems ◽  
Lessons Learned ◽  
Warning Systems ◽  
Communication Architecture ◽  
Design And Implementation ◽  
Communication Links

Abstract. This article discusses aspects of communication architecture for early warning systems (EWS) in general and gives details of the specific communication architecture of an early warning system against tsunamis. While its sensors are the "eyes and ears" of a warning system and enable the system to sense physical effects, its communication links and terminals are its "nerves and mouth" which transport measurements and estimates within the system and eventually warnings towards the affected population. Designing the communication architecture of an EWS against tsunamis is particularly challenging. Its sensors are typically very heterogeneous and spread several thousand kilometers apart. They are often located in remote areas and belong to different organizations. Similarly, the geographic spread of the potentially affected population is wide. Moreover, a failure to deliver a warning has fatal consequences. Yet, the communication infrastructure is likely to be affected by the disaster itself. Based on an analysis of the criticality, vulnerability and availability of communication means, we describe the design and implementation of a communication system that employs both terrestrial and satellite communication links. We believe that many of the issues we encountered during our work in the GITEWS project (German Indonesian Tsunami Early Warning System, Rudloff et al., 2009) on the design and implementation communication architecture are also relevant for other types of warning systems. With this article, we intend to share our insights and lessons learned.

Toward a typology of weak-signal early alert systems: functional early warning systems in the post-COVID age

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jan Černý ◽  
Martin Potančok ◽  
Elias Castro Hernandez
Keyword(s):  
Peer Review ◽  
Early Warning ◽  
Warning System ◽  
Early Warning Systems ◽  
Weak Signal ◽  
Warning Systems ◽  
Weak Signals ◽  
Content Type ◽  
Human In The Loop ◽  
Early Alert Systems

PurposeThe study aims to expand on the concept of an early warning system (EWS) by introducing weak-signal detection, human-in-the-loop (HIL) verification and response tuning as integral parts of an EWS's design.Design/methodology/approachThe authors bibliographically highlight the evolution of EWS over the last 30+ years, discuss instances of EWSs in various types of organizations and industries and highlight limitations of current systems.FindingsProposed system to be used in the transforming of weak signals to early warnings and associated weak/strong responses.Originality/valueThe authors contribute to existing literature by presenting (1) novel approaches to dealing with some of the well-known issues associated with contemporary EWS and (2) an event-agnostic heuristic for dealing with weak signals.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2020-0513.

Torrent Monitoring and Early Warning Systems Development

2022 ◽  
pp. 195-216
Author(s):  
Dejan Vasović ◽  
Ratko Ristić ◽  
Muhamed Bajrić
Keyword(s):  
Emergency Management ◽  
Early Warning ◽  
Early Warning System ◽  
Catchment Area ◽  
Warning System ◽  
Modern Society ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Small Catchment ◽  
National Emergency

The level of sustainability of a modern society is associated with the ability to manage unwanted stressors from the environment, regardless of origin. Torrential floods represent a hydrological hazard whose frequency and intensity have increased in recent years, mainly due to climate changes. In order to effectively manage the risks of torrents, it is necessary to apply early warning systems, since torrential floods are formed very quickly, especially on the watercourses of a small catchment area. The early warning system is part of a comprehensive torrential flood risk management system, seen as a technical entity for the collection, transformation, and rapid distribution of data. Modern early warning systems are the successors of rudimentary methods used in the past, and they are based on ICT and mobile applications developed in relation to the requirements of end users. The chapter presents an analysis of characteristic examples of the use. The main conclusion of the chapter indicates the need to implement early warning systems in national emergency management structures.

KLR Approach as an Early Warning Indicator of Turkish Currency and Banking Crisis in 2000 and 2001

2016 ◽  
pp. 222-239
Author(s):  
Filiz Eryılmaz
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Financial Stability ◽  
Banking Crisis ◽  
Warning System ◽  
Early Warning Systems ◽  
Lessons Learned ◽  
Warning Systems ◽  
Window Approach ◽  
Global Growth

International organizations as private sector institutions started to develop Early Warning System [EWS] models aiming to anticipate whether and when individual countries can collide with a financial crisis. EWS models can be made most useful to help sustain global growth and maintain financial stability, especially in light of the lessons learned from the current and past crises. This paper proposes Early Warning Systems (EWS) for Turkish Currency and Banking Crisis in 2000 and 2001. To that end “KLR model” or “signaling window” approach developed by Kaminski, Lorezondo and Reinhart (1998) is testified in the empirical part of this research and applied to a sample of Turkey macroeconomic data for the 1998-2003 monthly periods.

scholarly journals Recognizing the Famine Early Warning Systems Network: Over 30 Years of Drought Early Warning Science Advances and Partnerships Promoting Global Food Security

2019 ◽  
Vol 100 (6) ◽  
pp. 1011-1027 ◽  
Author(s):  
Chris Funk ◽  
Shraddhanand Shukla ◽  
Wassila Mamadou Thiaw ◽  
James Rowland ◽  
Andrew Hoell ◽  
...  
Keyword(s):  
Food Security ◽  
Early Warning ◽  
Warning System ◽  
Climate Extremes ◽  
Early Warning Systems ◽  
Food Prices ◽  
Humanitarian Assistance ◽  
Warning Systems ◽  
Recent Climate ◽  
Drought Early Warning

AbstractOn a planet with a population of more than 7 billion, how do we identify the millions of drought-afflicted people who face a real threat of livelihood disruption or death without humanitarian assistance? Typically, these people are poor and heavily dependent on rainfed agriculture and livestock. Most live in Africa, Central America, or Southwest Asia. When the rains fail, incomes diminish while food prices increase, cutting off the poorest (most often women and children) from access to adequate nutrition. As seen in Ethiopia in 1984 and Somalia in 2011, food shortages can lead to famine. Yet these slow-onset disasters also provide opportunities for effective intervention, as seen in Ethiopia in 2015 and Somalia in 2017. Since 1985, the U.S. Agency for International Development’s Famine Early Warning Systems Network (FEWS NET) has been providing evidence-based guidance for effective humanitarian relief efforts. FEWS NET depends on a Drought Early Warning System (DEWS) to help understand, monitor, model, and predict food insecurity. Here we provide an overview of FEWS NET’s DEWS using examples from recent climate extremes. While drought monitoring and prediction provides just one part of FEWS NET’s monitoring system, it draws from many disciplines—remote sensing, climate prediction, agroclimatic monitoring, and hydrologic modeling. Here we describe FEWS NET’s multiagency multidisciplinary DEWS and Food Security Outlooks. This DEWS uses diagnostic analyses to guide predictions. Midseason droughts are monitored using multiple cutting-edge Earth-observing systems. Crop and hydrologic models can translate these observations into impacts. The resulting information feeds into FEWS NET reports, helping to save lives by motivating and targeting timely humanitarian assistance.

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