Flood Prediction using real time sensing Emergency Water Information Networks over mobile phone networks and WiFi (EWIN)
Flood Prediction using real time sensing Emergency Water Information Networks over mobile phone networks and WiFi (EWIN)
批准号:
EP/P029221/1
负责人:
Robert Edwards
金额:
$189.29万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --
中文摘要
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英文摘要
We are working on ways to monitor flooding in real time using remote water sensing over cellular phone systems. With the predicted impacts of climate change flooding will be a global problem. Minutes of advance warning are important and modern flood warning systems are critical for a country to protect its people and develop and grow its towns and cities. Flooding is the most serious of natural disasters mankind has to cope with in terms of loss of life and the long term effects of flooding have severely adverse social consequences. Unlike the UK that has a mature flood defence system, many countries have not been able to afford the technology and have poor response to flooding. However, many developing countries do now have access to modern cellular phone networks in their towns and cities. So in this project we will discover how to use mobile phone networks combined with WiFi to help countries tackle climate change.Two teams of researchers from the UK and Mexico, supported by small companies with experts in the fields of water engineering and embedded electronics have come to together to investigate how real time flood monitoring can be done over modern phone systems to provide modern water engineering infrastructure in a cost effective way to quickly make countries vulnerable to flooding more resilient to this most serious of natural disasters.To improve flood prediction several areas of research need to be addressed. Concisely, the data for real time flood prediction needs be sensed in the right place and at the right time, transmitted in harsh conditions, fused in the cloud and used to make reliable flood prediction models. our research addresses each of these areas using UK expertise in Water Engineering and Radio Communications to complement Mexican knowledge of Water Engineering, Data Networks and Enterprise.At the end of the project we will have measured parts of and modelled a complete flood prediction network for Mexico and in the process understood how water behaves before, during and after flooding. Mexico is a country of extremes with a dry season where hardly any rain falls and rainy season with volumes of water in rivers unseen in the UK. For the UK climate change is predicted to mean more dynamic and intensive large scale weather effects so there are significant benefits the United Kingdom as well as Mexico and many other countries.Combined with background research, prototyping of sensors packages and waterway modelling, our teams will be conducting a series of highly targeted field trials - small scale in the UK where rivers and lakes and relatively predictable and medium scale in Mexico where we will seek flood events to be studied in real time.Two new exciting water sensing technologies, one that uses Doppler radar and another that using similar techniques to face recognition will be used for the first time in this work to detect the water conditions prior and during a flood event. The two techniques are special because they do not need to be in the water and are therefore much harder to wash away than traditional sensors. We intend to use a portable system that can be deployed quickly in areas that may flood to give much needed advanced warning and monitor water levels during the time before the water recedes.
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Caracterización y Modelado de Redes de Telefonía Celular para la prevención de inundaciones
蜂窝电话防洪特性和模型
DOI:
--
发表时间:
2019
期刊:
影响因子:
--
作者:
[Kiomi Chavez Saishio]
通讯作者:
Kiomi Chavez Saishio
Development of flood early warning system in the hydrological system of the Colima River
科利马河水文系统洪水预警系统的开发
DOI:
--
发表时间:
2018
期刊:
影响因子:
--
作者:
[Lopez De La Cruz Jesus]
通讯作者:
Lopez De La Cruz Jesus
DISEÑO Y EVALUACION DE TECNICAS DE CALENDARIZACION APLICADOS A LOS SISTEMAS DE TRANSPORTE INTELIGENTE
智能交通系统的日历应用技术的设置和评估
DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
[GUTIERREZ A]
通讯作者:
GUTIERREZ A
A comparative evaluation of multiple machine learning approaches for short range flood level prediction
短程洪水水位预测多种机器学习方法的比较评估
DOI:
--
发表时间:
2018
期刊:
AGU Fall Meeting Abstracts
影响因子:
--
作者:
[Khouakhi A.]
通讯作者:
Khouakhi A.
Despliegue y análisis de una red LTE basada en equipo SDR y srsLTE
对 SDR 和 srsLTE 设备上的 LTE 进行分析和分析
DOI:
--
发表时间:
2020
期刊:
影响因子:
--
作者:
[Hernández-Aracil, Yoelkys]
通讯作者:
Hernández-Aracil, Yoelkys
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项目类别:Research Grant
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-
财政年份:2019
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负责人:Robert Edwards
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University of Newcastle UKRI Innovation Fellowships: BBSRC Flexible Talent Mobility Accounts
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International Workshop- Non-Target Site Based Herbicide Resistance in Grass Weeds.
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Biotransforming Phenylpropanoids derived from Biorefining: a Toolkit Approach
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Experimental and Computational Determination of Microbial Genotypes and Phenotypes
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批准号:1330800
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II-EN: Computational Enhancement of Analytical Metagenomics Systems
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A US:Indonesia workshop to explore the dimensions of biodiversity
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Biotransforming Phenylpropanoids derived from Biorefining: a Toolkit Approach
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The molecular basis of multiple herbicide resistance in grass weeds
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SPPI-NET: a Network for Synthetic Plant Products for Industry
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The biochemistry of flavone C-glycosides in cereals
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Characterisation of the unique lambda class of plant glutathione transferases
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Collaborative Research: PHANTOME: PHage ANnotation TOols and MEthods
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The molecular basis of multiple herbicide resistance in grass weeds
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The biochemistry of flavone C-glycosides in cereals
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SPPI-NET: a Network for Synthetic Plant Products for Industry
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Characterisation of the unique lambda class of plant glutathione transferases
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A Biofactory for the Production of High Impact Flavour and Fragrance Compounds
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