DEWRS Project Proposal

DISASTER EARLY WARNING

AND RESPONSE SYSTEM

(DEWRS)

Supervisor: Dr. Mbale

Name: Raymond Muntuumo

Student Number: 200811282

Thursday, 02 August 2012

Content

Introduction

Literature review

System architecture

Methodology

Project Requirements

Conclusion

References

1

Background

Natural disasters have become frequent and

more devastating.

Early warning systems (EWS) can provide

near real-time alerts about natural disasters.

Thursday, 02 August 2012 2

DEWRS Project

Will integrate the existing emergency

response systems and the environmental

monitoring stations into a national disaster

early warning and response system.

Will provide tools to facilitate response

coordination.


Objectives

Collect data on indicators of disasters.

Predict disaster.

Disseminate warnings of impending disasters

in a timely manner.

Provide tools to assist in coordinating

response to a disaster.


Motivation

Japan earthquake

and tsunami


Floods in northern

Namibia

5

Problem Statement

No existing multi-disaster EWS in Namibia.

There is need for a mechanism to deliver

critical alerts to the threatened areas in time

for the local authorities to take action.

Such mechanism needs to be accurate, easy

to maintain and accessible to non-technical

personnel


Major Research Question

How can fuzzy case-based reasoning be used in

the development of affordable and reliable

disaster early warning systems?


Support Research Questions

How will the risk assessment and mapping be

conducted to provide information on the disaster

indicators to be monitored in the system?

In what ways can concepts of neural networks be

used to integrate systems with monitoring and

predicting capabilities to provide timely estimates of

the potential risk faced by communities?


Support Research Questions (contd.)

Which media will be used to communicate the alerts

and warnings to the threatened areas in a timely

manner?

What response coordination and mitigation tools will

be made available to the local authorities to respond

to a disaster alert?


Literature Review

Humanitarian Early Warning Service (HEWS)

Web-based warning service

inter-agency project for humanitarian early

warnings and forecasts for natural hazards.

developed by the World Food Programme (WFP)

on behalf of the IASC


Literature Review (contd.)

Information Technology for Humanitarian

Assistance, Cooperation and Action (ITHACA)

located in the Politecnico of Torino campus

partnership with the WFP

offers a web-based service

provides early impact analysis, localized aerial

surveys


Literature Review (contd.)

Global Disaster Alert and Coordination System

(GDACS)

Cooperation framework under the UN

facilitates coordination and decision-making

among bilateral responders and the affected

country

Subscription required


System Architecture


INTERNET PSTN

WIRELESS NETWORKS

CLUSTERED COMMUNICATION

SYSTEMS

BROADCAST/TV NETWORK

TRANSPORT NETWORKS

FIRE

POLICE PARAMEDICS DISASTER RELIEF UNIT

PUBLIC EDUCATION

TRANSPORT SAFETY

GOVERNMENT ADMINISTRATION

LOCAL AUTHORITIES

ALERT BROADCAST/MULTICAST CENTRAL MONITORING UNIT RESPONSE UNIT

INFORMATION EXCHANGE

DATABASE PREDICTION/EARLY

WARNING SIMULATOR

DATA PROCESSING

MET OFFICE HYDROLOGICAL SEISMIC ENVIRONMENTAL

HAZARD MONITORING

FIRE POLICE PARAMEDICS TRANSPORT

EMERGENCY DISPATCH

13

Model defining the critical indicators

Design of database – ER diagrams

Data structures design – UML diagrams

Design of neural networks

User interface design


Design Phase

Methodology

14

Design Phase (contd.)



Project Schedule

16

Project Requirements

Standard personal computer

Internet access

Oracle 11g database

Microsoft Visual Studio 2010

Artificial Intelligence programming IDE

GoldSim simulator

WebMaker or Dreamweaver

Microsoft Office 2010



Conclusion

comprehensive investigation in the

application of AI in the development of reliable

low-cost disaster early warning systems.

the creation of an EWS for Namibia.

insight into possible improvements in

applications of artificial intelligence in

developing countries.

18

References

Bates, P.D., De Roo A.P.J. (2001). A simple raster-based model for flood

inundation simulation. Journal of Hydrology, 236: 54-77.

Denis Riordan and Bjarne K Hansen (2002). A fuzzy case-based system

for weather prediction. Eng. Int. Syst. 3: 139–146, CRL Publishing Ltd

Government of Namibia (1998). National Disaster Plan.

Humanitarian Early Warning Service (HEWS), Retrieved from

http://www.hewsweb.org

Information Technology for Humanitarian Assistance, Cooperation and

Action (ITHACA). Retrieved from http://www.ithaca.polito.it


References (contd.)

Maryam Golnaraghi, Ph.D. (2011), Systematic Development of Multi-

Hazard Early Warning systems, WIS-CAP Implementation Workshop 6-

7 April 2011, World Meteorological Organization HQ.

Microsoft Research (2008). Wireless Sensor Network Provides Early

Flood Detection for Underserved Countries

Ministry of Environment and Tourism - African Adaptation Project

Namibia (2011). AAP NAM CCA Decision Makers Training.

Servaas Van Den Bosch (2011, March 29), Heaviest floods ever in

Namibia, The Namibia. Retrieved from http://www.namibian.com.na


The End

DEWRS Project Proposal

Education

early warning systems

humanitarian early warnings

global disaster alert

existing multidisaster

national disaster plan

webbased service

early impact analysis

national disasterearly