ICT Enabled Peace Network: Case Study of Conflict Early Warning System in Kenya

2019 ◽  
pp. 127-139
Author(s):  
Arunima Mukherjee ◽  
Festus Mukoya
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System

scholarly journals Design of early warning system for nuclear preparedness case study at Serpong

2017 ◽  
Author(s):  
M. M. Farid ◽  
Prawito ◽  
I. P. Susila ◽  
A. Yuniarto
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System

ANALYSIS OF THE ACCURACY OF AN EARLY WARNING SYSTEM FOR LEARNERS AT-RISK: A CASE STUDY

2019 ◽  
Author(s):  
David Baneres ◽  
Abdulkadir Karadeniz ◽  
Ana-Elena Guerrero-Roldán ◽  
M. Elena Rodríguez-Gonzalez ◽  
Montse Serra
Keyword(s):  
At Risk ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System

scholarly journals Implementation of a Geological Disaster Monitoring and Early Warning System Based on Multi-source Spatial Data: A Case Study of Deqin County, Yunnan Province

2017 ◽  
Author(s):  
Guo-ping Chen ◽  
Jun-san Zhao ◽  
Lei Yuan ◽  
Zun-jie Ke ◽  
Miao Gu ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Laser Scanning ◽  
New Technologies ◽  
Warning System ◽  
Early Warning Systems ◽  
Geological Disaster ◽  
Monitoring And Forecasting ◽  
Monitoring And Early Warning

Abstract. New technologies, such as three-dimensional laser scanning, interferometric synthetic aperture radar (InSAR), global navigation satellite systems (GNSSs), unmanned aerial vehicles (UAVs), and the Internet of Things, will provide greater volumes of data for surveying and monitoring as well as for the development of early warning systems (EWS). This research proposes solutions for the design and implementation of a geological hazard monitoring and early warning system (GHMEWS) for landslides and debris-flow hazards based on data multi-sourced from the aforementioned technologies. We describe the complex and changeable characteristics of the GHMEWS and analyze the architecture of the system, the composition of the multi-source database, the development mode and service logic, and the methods and key technologies of the system development. To illustrate the implementation process of the GHMEWS, we selected Deqin County as the case study area due to its unique terrain and diverse types of typical landslides and debris flows. First, we discuss the system's functional requirements and the monitoring and forecasting models of the system. Second, we examine the logic relations of the overall disaster process, including pre-disaster, disaster rescue, and post-disaster reconstruction, and develop a support tool for disaster prevention, disaster reduction, and geological disaster management. Third, we describe the methods for multi-source monitoring data integration and the generation and simulation of the mechanism model of geological disasters. Finally, we construct the GHMEWS for application to the dynamic and real-time management, monitoring, and forecasting of the entire hazard process in Deqin County.

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