scholarly journals Development of Early Warning and Evacuation System for Multi-Density Facilities in Case of Fire

2021 ◽  
Vol 21 (6) ◽  
pp. 133-139
Author(s):  
Hyun Kang ◽  
Oh Sang Kweon
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Large Scale ◽  
Safety Management ◽  
Warning System ◽  
Management Systems ◽  
Safety Management Systems ◽  
Protection Measures ◽  
Heat Detectors ◽  
Evacuation System

Multi-density facilities with relatively large number of resident occupants and visitors can face large-scale casualties in the event of disasters such as a fire. In addition, such disasters may cause additional damage by inducing social anxiety regarding various protection measures of the buildings, such as their safety management systems. This study was aimed at developing an early warning and evacuation system to minimize casualties in multi-density facilities in case of a fire. In particular, smoke and heat detectors, which are widely used, were utilized to establish an early warning system for old multi-density facilities with relatively poor safety management systems. For the purpose of evacuation following the early warning, an online platform-based ‘Fire Safety Management’ system was established to deliver appropriate action tips to all occupants according to the four risk stages of a fire.

scholarly journals KELAYAKAN SISTEM EVAKUASI KAWASAN RAWAN BENCANA LETUSAN GUNUNG MERAPI DI KABUPATEN SLEMAN

Arsitektura ◽  
2017 ◽  
Vol 14 (1) ◽  
Author(s):  
Dicky Setya Adi W ◽  
Kusumastuti Kusumastuti ◽  
Isti Andini
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Quantitative Method ◽  
Warning System ◽  
Average Score ◽  
Qualitative And Quantitative ◽  
Meeting Point ◽  
Evacuation Route ◽  
Evacuation System

<em>Evacuation system in Mount Merapi eruption area consist of evacuation component, such early warning system, meeting point, evacuation lane, evacuation route, barrack, communication and transportation. The role of the goverment is to give services for refugees who live in scenario evacuation area. But there are some constrains, for example damaged road, evacuation lane crossover the bridge, people don’t heard the early warning system and high density of barracks. Based on those phenomenons, this research objected is to measure the feasibility of Mount Merapi evacuation system in Sleman district by using qualitative and quantitative method. The results of this research, some of evacuation systems don’t have perfect score. Early warning system has score 49%,  meeting point score 96,2%, evacuation lane 88,7%, evacuation route 100%, barracks 60,7%, transportation and communication 51,8%. From that components, the average score is 75% which means the system of evacuation in Mount Merapi Eruption Area not feasible yet.</em>

Research on the Security Monitoring and Early Warning System of Oil Depot Station

2014 ◽  
Vol 496-500 ◽  
pp. 1711-1714
Author(s):  
Shuai Wang ◽  
Ye Liu ◽  
Qing Zhong Zhou
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Safety Management ◽  
Security Analysis ◽  
Warning System ◽  
Network Services ◽  
Practical Significance ◽  
Security Monitoring ◽  
Station Safety ◽  
Monitoring And Early Warning

In order to adapt to the demand of depot station safety management work, the Security Monitoring and Early Warning System of Oil Depot Station is designed. The system has the function of network services, database, parameter and video monitoring and security analysis and early warning. Practical application shows that this system has the advantages of simple operation and powerful monitoring. It has the important practical significance to improve the level of safety management of oil depot station.

Blueprints for a Large-Scale Early Warning System

2010 ◽  
Author(s):  
Paul G. Spirakis ◽  
Vasileios Vlachos ◽  
Vassilios Karakoidas ◽  
Dimitrios Liappis ◽  
Dimitrios Kalaitzis ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Large Scale ◽  
Warning System

scholarly journals Integrated framework for early warning system in UAE

2016 ◽  
Vol 7 (4) ◽  
pp. 361-373 ◽  
Author(s):  
Abdulla Ali Alhmoudi ◽  
Zeeshan Aziz
Keyword(s):  
Natural Hazards ◽  
Early Warning ◽  
Early Warning System ◽  
Large Scale ◽  
Warning System ◽  
Essential Elements ◽  
The Other ◽  
Content Type ◽  
Integrated Framework ◽  
The Impact

Purpose The impacts and costs of natural disasters on people, properties and environment are often severe when these occur on a large scale and with no warning system in place. The lack of deployment of an early warning system (EWS), low risk and hazard knowledge and impact of natural hazard experienced by some communities in the UAE have emphasised the need for more effective EWSs. This work focuses on developing an integrated framework for EWSs for communities prone to the impact of natural hazards to reduce their vulnerability and improve emergency management arrangements in the UAE. Design/methodology/approach The essential elements of effective EWS were identified through literature review to develop an integrated framework for EWS. Semi-structured interviews and questionnaires were also used to identify and confirm hindering factors to deployment of effective EWSs in Abu Dhabi and Fujairah Emirates, while areas that require further development were also identified through this means. Findings The outcome of this research revealed that the warning for natural hazards in the UAE lacked the required elements for effective EWS, whereas the elements which are present are insufficient to mitigate the impacts of natural hazards. The information in this work emphasises the need to improve two elements, and to develop the other two essential elements of EWS in the UAE. Originality/value The outcome of this research revealed that the warning for natural hazards in the UAE lacked the required elements for effective EWS, whereas the elements which are present are insufficient to mitigate the impacts of natural hazards. The information in this work emphasises the need to improve two elements and to develop the other two essential elements of EWS in the UAE.

scholarly journals A Topology Visualization Early Warning Distribution Algorithm for Large-Scale Network Security Incidents

2013 ◽  
Vol 2013 ◽  
pp. 1-7
Author(s):  
Hui He ◽  
Guotao Fan ◽  
Jianwei Ye ◽  
Weizhe Zhang
Keyword(s):  
Network Security ◽  
Network Topology ◽  
Early Warning ◽  
Early Warning System ◽  
Large Scale ◽  
Warning System ◽  
Small Scale ◽  
Large Scale Network ◽  
Scale Network ◽  
Security Incidents

It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system’s emergency response capabilities, alleviate the cyber attacks’ damage, and strengthen the system’s counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system’s plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks’ topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology.

scholarly journals Toward a cross-border early-warning system for Central Asia

2015 ◽  
Vol 58 (1) ◽  
Author(s):  
Jacek Stankiewicz ◽  
Dino Bindi ◽  
Adrien Oth ◽  
Stefano Parolai
Keyword(s):  
Central Asia ◽  
Early Warning ◽  
Urban Areas ◽  
Early Warning System ◽  
Large Scale ◽  
Damage Control ◽  
Warning System ◽  
Earthquake Early Warning ◽  
Successful Implementation ◽  
Cross Border

<p>Rapidly expanding urban areas in Central Asia are increasingly vulnerable to seismic risk; but at present, no earthquake early warning (EEW) systems exist in the region despite their successful implementation in other earthquake-prone areas. Such systems aim to provide short (seconds to tens of seconds) warnings of impending disaster, enabling the first risk mitigation and damage control steps to be taken. This study presents the feasibility of a large scale cross-border regional system for Central Asian countries. Genetic algorithms are used to design efficient EEW networks, computing optimal station locations and trigger thresholds in recorded ground acceleration. Installation of such systems within 3 years aims to both reducing the endemic lack of strong motion data in Central Asia that is limiting the possibility of improving seismic hazard assessment, and at providing the first regional earthquake early warning system in the area.</p>

scholarly journals A Study about the 3S-based Great Ruins Monitoring and Early-warning System

2015 ◽  
Vol II-5/W3 ◽  
pp. 357-361
Author(s):  
W. Xuefeng ◽  
H. Zhongyuan ◽  
L. Gongli ◽  
Z. Li
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Large Scale ◽  
Processing System ◽  
Warning System ◽  
Monitoring Data ◽  
Software Systems ◽  
New Countryside ◽  
Monitoring Data Processing ◽  
Monitoring And Early Warning

Large-scale urbanization construction and new countryside construction, frequent natural disasters, and natural corrosion pose severe threat to the great ruins. It is not uncommon that the cultural relics are damaged and great ruins are occupied. Now the ruins monitoring mainly adopt general monitoring data processing system which can not effectively exert management, display, excavation analysis and data sharing of the relics monitoring data. Meanwhile those general software systems require layout of large number of devices or apparatuses, but they are applied to small-scope relics monitoring only. Therefore, this paper proposes a method to make use of the stereoscopic cartographic satellite technology to improve and supplement the great ruins monitoring index system and combine GIS and GPS to establish a highly automatic, real-time and intelligent great ruins monitoring and early-warning system in order to realize collection, processing, updating, spatial visualization, analysis, distribution and sharing of the monitoring data, and provide scientific and effective data for the relics protection, scientific planning, reasonable development and sustainable utilization.

scholarly journals A Mobile-Based Question-Answering and Early Warning System for Assisting Diabetes Management

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Wenxiu Xie ◽  
Ruoyao Ding ◽  
Jun Yan ◽  
Yingying Qu
Keyword(s):  
Chronic Diseases ◽  
Early Warning ◽  
Early Warning System ◽  
Large Scale ◽  
Question Answering ◽  
Diabetes Management ◽  
Health Management ◽  
Warning System ◽  
Health Condition ◽  
Increasing Demand

With increasing demand for preventive management of chronic diseases in real time by using the Internet, interest in developing a convenient device on health management and monitoring has intensified. Unlike other chronic diseases, diabetes particularly type 2 is a lifelong chronic disease and usually requires daily health management by patients themselves. This study is to develop a mobile-based diabetes question-answering (Q&A) and early warning system named Dia-AID, assisting diabetes patients and populations at high risk. The Dia-AID system consists of three modules: a large-scale multilanguage diabetes frequently asked question repository, a multimode fusion Q&A framework, and a health data management module. A list of services including risk assessment and health early warning is provided to users for health condition monitoring. Using the diabetes frequently asked question repository as data, experiments are conducted on answer ranking and answer selection aspects. Results show that two essential methods in the system outperform baseline methods on both aspects.

A downscaling model system for early warning flooding forecast

2021 ◽  
Author(s):  
Francesco Cioffi ◽  
Federico Rosario Conticello ◽  
Mario Giannini ◽  
Tommaso Lapini ◽  
Sergio Pirozzoli ◽  
...  
Keyword(s):  
Sustainable Development ◽  
Tropical Cyclone ◽  
Early Warning ◽  
Early Warning System ◽  
Large Scale ◽  
Warning System ◽  
Rainfall Threshold ◽  
Range Data ◽  
Tropical Regions ◽  
Global Circulation Models

&lt;p&gt;A&amp;#160;&amp;#160;&amp;#160;&amp;#160; recent report &amp;#8220;The Future is Now: Science for Achieving Sustainable Development&amp;#8221; Global Sustainable Development Report 2019 - SDG Summit&amp;#8217; &amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;as part of the activity of Agenda 2030 of UN, highlights the opportunity to develop Early warning system for drought, floods and other meteorological events, that by providing timely information can be used by vulnerable countries to build resilience, reduce risks and prepare more effective responses. Following the suggestion, &amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;combining outputs from Global Circulation models, remote sensing, hydraulic models and machine learning tools,&amp;#160;&amp;#160;&amp;#160;&amp;#160; &amp;#160;&amp;#160;a local scale flooding Early Warning System (EWS) is proposed for the St. Lucia island (&amp;#160;&amp;#160;&amp;#160;&amp;#160; Caribbean). The objective of the EWS is to provide forecasts of potentially dangerous flooding phenomena at different time scale: a) 0-2 hours, nowcasting; b) 24-48 hours, short range; c) 3-10 days, middle to long range. Data used to build the model are: Geopotential Height (GPH) fields at 850 hPa and Integrated Vapor Transport (IVT) fields from European Centre for Medium-range Weather Forecasts (ECMWF) - Reanalysis v5 (ERA5); Tropical Cyclone tracks from NOAA-NHC; 18 weather stations homogeneously distributed in the island; rainfall map data from the weather radar in Saint Lucia. GPH and IVT fields were defined between 110&amp;#176;W - 10&amp;#176;W and 45&amp;#176;N - 10&amp;#176;S. The EWS is constituted by an ensemble of flooding risk forecast subsystems which is potentially applicable to Atlantic tropical and extra-tropical regions. Different approaches are used for each subsystem&amp;#160;&amp;#160;&amp;#160;&amp;#160; &amp;#160;to link large scale atmospheric features to local rainfall and flooding: a) Non-homogeneous Hidden Markov and Event Synchronization models to translate IVT and GPH at 850 hPa&amp;#160; fields (from ECMWF-Set II- Atmospheric Model Ensemble) in local&amp;#160;&amp;#160;&amp;#160;&amp;#160; &amp;#160;daily rainfall amount and probability of&amp;#160; exceedance of&amp;#160; a prefixed heavy rainfall threshold; b) a physical based cyclone/rainfall&amp;#160; model to convert&amp;#160;&amp;#160;&amp;#160;&amp;#160; &amp;#160;Tropical cyclone attributes &amp;#8211; position and&amp;#160;&amp;#160;&amp;#160;&amp;#160; &amp;#160;maximum wind&amp;#160;&amp;#160;&amp;#160;&amp;#160; &amp;#160;velocity&amp;#160;&amp;#160;&amp;#160;&amp;#160; &amp;#160;&amp;#160;(provided from National Hurricane Center)- in rainfall intensity spatial distribution on the island; c) a surrogate model for a&amp;#160; fast and accurate prediction of flooding events that is obtained from a multi-layer perceptron neural network (MLPNN), which is trained on a high-fidelity dataset relying on solution of the full two-dimensional shallow water equations with direct rainfall application.&amp;#160;&amp;#160; &amp;#160;&amp;#160;&amp;#160;&amp;#160;&amp;#160;Results show an excellent ability of the models to identify the climatic configurations that determine the occurrence of extreme events and the exceeding of threshold values &amp;#8203;&amp;#8203;that generate floods. In particular, during the late hurricane season September-October-November, when is highest the probability of flood events, the EWS was able to forecast the occurrence of critical climatic configurations 86% of the times they occurred. The EWS was able to predict the exceeding of the rainfall threshold that generated floods 80% of times.&lt;/p&gt;

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