Content Standard for Last-Mile Alert and Notification Sharing Knowledge on Disaster Warning, with a focus on Community-based Last-Mile Warning Systems.

Slides:



Advertisements
Similar presentations
Current Warning System of India Meteorological Department.
Advertisements

Use of Weather and Climate information in Climate risk management Example of ACMAD-IFRCC collaboration ACMAD by Léon Guy RAZAFINDRAKOTO.
Richard (Rick) Jones SWFDP Training Workshop on Severe Weather Forecasting Bujumbura, Burundi, Nov 11-16, 2013.
Confidential: All Rights Reserved Web-based Alerting The International Common Alerting Protocol (CAP) provides for a standardized alerting format for all.
Last-Mile Hazard Warning System in Sri Lanka: Community-based Alerting and Notification Regional Joint Conference on Disaster Relief and Management, Alexandria,
Common Alerting Protocol (CAP): The Content Standard of Alerts and Notifications in Disasters and Emergencies presented by Eliot Christian, Consultant.
1 IPAWS: The Integrated Public Alert and Warning System.
Sameera Wijerathna. Agenda The Need Uniqueness Recognition How it works The Potential.
Coastal Hazards: Tsunami & Hurricanes Week 7. Homework Questions Would you live near a coast? If so, where? What level of risk from tsunami & hurricanes.
Coastal Hazards: Tsunamis. Homework Questions Would you live in an area at risk for tsunamis? If so, where? What level of risk from tsunamis is acceptable.
1 Integrated Public Alert and Warning System (IPAWS) Overview and Commercial Mobile Alert System CMAS Introduction August 2009.
Bryan Norcross Sr. Executive Director of Weather Content Sr. Hurricane Specialist The Weather Channel Interdepartmental Hurricane Conference College Park,
Cyclone (hurricane –typhoon) sailing Very Dangerous...
Tsunamis Detection The Mission  Tsunamis Detection can help to minimize loss of life and property from future tsunamis. Mission Introduction Mechanism.
P UERTO RICO SEISMIC NETWORK Tsunami protocol for PR/VI - Caribbean and The PR Broadcast System Dr. Victor A. Huérfano CARIBBEAN DISASTER EMERGENCY RESPONSE.
Making Communities Disaster Resilient; The Sarvodaya Approach Dr.Vinya S. Ariyaratne Executive Director Sarvodaya Shramadana Movement Sri Lanka.
Use of CAP for Disease Surveillance: Real Time Biosurveillance Program Nuwan Waidyanatha LIRNEasia
Mark S. Paese United States Department of Commerce National Oceanic and Atmospheric Administration June 13, 2007 Effective All-Hazards Warning System 2007.
Tsunami Notification Procedures Brian Yanagi Manager International Tsunami Information Centre.
Two Ways to Know if a Tsunami is Coming: Natural Warnings ground shaking, a loud ocean roar, or the water receding unusually far exposing the sea floor.
Tropical Cyclone Early Warning System Vanuatu Meteorology & Geo-Hazards Department.
Foster and sustain the environmental and economic well being of the coast by linking people, information, and technology. Center Mission Coastal Hazards.
IAEA International Atomic Energy Agency EPR-Public Communications L-011 Good Practices for PIOs.
Dialog-University of Moratuwa Mobile Communications Research Laboratory Kutila Gunasekera Director, Projects.
Organizational Tabletop Exercise 1 Hurricane Scenario (Community-Based Organizations) Date | Location.
23 rd September 2008 HFA Progress Report Disaster Risk Reduction in South Asia P.G.Dhar Chakrabarti Director SAARC Disaster Management Centre New Delhi.
Community-based Hazard Warnings in Rural Sri Lanka: Performance of Alerting and Notification in a Last-Mile Relay Nuwan Waidyanatha, LIRNEasia Gordon A.
Determination of Hazard from the National Level: Sri Lanka Experience Natasha Udu-gama 25 October 2007 Dhaka, Bangladesh.
Current Technical Designs for Tsunami Warning Systems: Sri Lanka Rohan Samarajiva.
Coastal Community Resilience (CCR) initiative under the U.S. Indian Ocean Tsunami Warning System (US-IOTWS) Program Atiq Kainan Ahmed Social Scientist,
Use of ICTs in Education, Healthcare and Agriculture
Hurricanes Hurricanes  A tropical cyclone that occurs in the Atlantic.  Also a generic term for low pressure systems that develop in the tropics.
Presented by Roger Ndicu Principal Meteorologist Public Weather Service CAP Implementation Experiences in Kenya KENYA METEOROLOGICAL DEPARTMENT.
Early warning systems in disaster- risk reduction Rohan Samarajiva & Nuwan Waidyanatha IDRC-CIDA workshop 12 July 2007, Moratuwa, Sri.
Bucks County ARES – Lower Bucks American Red Cross Exercise An Integrated Training Exercise – March 12-16, 2006.
ITU-T/OASIS Workshop and Demonstration of Advances in ICT Standards for Public Warning Geneva, October 2006 International Telecommunication Union.
U.S. National Tsunami Hazard Mitigation Program 5-Year Review David Green, NOAA Tsunami Program Manager National Oceanic and Atmospheric Administration.
Flash Flood Forecasting as an Element of Multi-Hazard Warning Systems Wolfgang E. Grabs Chief, Water Resources Division WMO.
What have we learned from the tsunami? Rohan Samarajiva.
Automated Flash Flood Forecasting Systems ¿Fact or Fantasy? International Workshop on Flash Flood Forecasting San Jose, Costa Rica, March 2006 Session.
Early Warning System in Thailand by Prawit JAMPANYA Weather Forecast Bureau Thai Meteorological Department Ministry of Information and Communication Technology.
Elements of a community-based warning system* Rohan Samarajiva Presentation at Workshop on Sharing Knowledge 5 March 2008, Jakarta *
Timothy Putprush Baltimore, MD September 30, 2009 Federal Emergency Management Agency (FEMA) Integrated Public Alert and Warning System Presentation to.
Coastal Hazards: Hurricanes. Homework Questions Would you live in an area at risk for hurricanes? If so, where? What level of risk from hurricanes is.
Hurricanes In Florida Ryan Martin. Background Information More hurricanes hit Florida then any other state More hurricanes hit Florida then any other.
Evaluation of Last-Mile Hazard Warning Information & Communication Technology Hardware and Software Systems Peter Anderson Simon Fraser University Vancouver,
Effective use of telecom & electronic media in disaster-risk reduction Rohan Samarajiva Presentation at meeting convened by Ministry.
Omar Baddour Chief World Climate Data and Monitoring WMO, Geneva WMO Climate Watch System Common Alerting Protocol (CAP) Implementation.
What is a Tropical Cyclone?
Making communities disaster resilient Rohan Samarajiva Global Knowledge 3 11 December 2007, Kuala Lumpur Findings from work on preparing.
The DEWETRA platform An advanced Early Warning System.
Saving lives, changing minds. Presentation title at-a-glance info (in slide master) SEA Climate Change Training Presentation title at-a-glance.
India has multiple hazards that it must combat namely: 1.Drought 2. Floods 3.Cyclone 4.Earthquake While previous disasters form the basis of developing.
Disaster Risk Management Concepts and Applications Southern Province of Sri Lanka 1.
LESSONS LEARNT FROM THE GFCS ON DISSEMINATING CIS TO SMALLHOLDER FARMERS IN MALAWI AND TANZANIA Jeanne Coulibaly ICRAF/CGIAR "The Last Mile" workshop organized.
National Weather Service Weather Forecast Office Mobile - Pensacola Special Briefing Tropical Storm Lee Special Briefing Tropical Storm Lee 4 PM CDT Sunday.
ICTs FOR SMART SUSTAINABLE ASIA PACIFIC ITU Asia & the Pacific Regional Development Forum Sofitel Philippine Plaza Manila, Philippines June 2016.
What is Hurricane: Tropical Cyclone?  Hurricanes are severe tropical storms that form in the southern Atlantic Ocean, Caribbean Sea, Gulf of Mexico,
Hurricanes Weather. Hurricanes  The whirling tropical cyclones that occasionally have wind speeds exceeding 300 kilometers (185 miles) per hour are known.
National Weather Service Weather Forecast Office Mobile - Pensacola Special Briefing Tropical Storm Lee Special Briefing Tropical Storm Lee 1030 AM CDT.
Hazards: Take Control Weather Terms By NEMO Saint Lucia.
Evacuation Procedures City Council October 20, 2015.
National Weather Service Weather Forecast Office Mobile - Pensacola Special Briefing Tropical Storm Lee Special Briefing Tropical Storm Lee 4 PM CDT Saturday.
Regional Joint Conference on Disaster Relief and Management,
Watching the weather to protect life and property
World Meteorological Organization 2008 December 10 Geneva, Switzerland
WorldSpace Satellite Radio
A Local news at 6 p.m. on 4 October A typhoon is approaching.
DISASTER RESPONSE PLANNING IN SAMOA
DEWN Disaster and Emergency Warning Network
Presentation transcript:

Content Standard for Last-Mile Alert and Notification Sharing Knowledge on Disaster Warning, with a focus on Community-based Last-Mile Warning Systems Sarvodaya Head Quarters, Moratuwa, Sri Lanka 28th-29th Mar 2007 Nuwan Waidyanatha 12 Balcombe Place, Colombo 08, Sri Lanka Tel: +94 (0)

The general objective is to evaluate the suitability of five ICTs deployed in varied conditions for their suitability in the last mile of a national disaster warning system for Sri Lanka and possibly by extension to other developing countries. HazInfo Research Matrix for Pilot Project

Communication System under Scrutiny

Example of Input Message to the last-Mile Hazard Warning System TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST Last-Mile HazInfo Simulation. No Repeat No Real Event is Effect TROPICAL CYCLONE ADVICE NUMBER 001 Issued at 09:55 am on Monday, December 11, 2006 BY Anonymous A SEVERE CATEGORY 4 CYCLONE is now current for AMPARA and MATARA District coastal areas. At 06:00 am local time SEVERE TROPICAL CYCLONE MONTY was estimated to be 80 kilometres northeast of Ampara District and moving southwest at 10 kilometres per hour. Severe Tropical Cyclone Monty is expected to cross the coast in the vicinity of Ampara and Matara Districts during Monday. Gales with gusts to 180 kilometres per hour are likely in coastal communities in Ampara and Matara District during the day. This is to alert the residents of Ampara and Matara District about the potential of a very dangerous storm tide as the cyclone centre approaches the coast. Tides are likely to rise significantly above the normal high tide mark with very dangerous flooding, damaging waves and strong currents. Widespread heavy rain and further flooding are likely in southern parts of the Ampara and Matara Districts over the next few days. TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST TEST Last-Mile HazInfo Simulation. No Repeat No Real Event is Effect.

Example of Output Message from Hazard-Information-Hub to the Last-Mile HIH T T10:20: :00 Exercise Alert Restricted en-US Meto Cyclone Prepare Expected Severe Observed At 06:00 am local time SEVERE TROPICAL CYCLONE MONTY was estimated to be 80 kilometers northeast of Ampara District and moving southwest at 10 kilometers per hour. Severe Tropical Cyclone Monty is expected to cross the coast in the vicinity of Ampara and Matara Districts during Monday. Gales with gusts to 180 kilometers per hour are likely in coastal communities in Ampara and Matara District during the day. This is to alert the residents of Ampara and Matara District about the potential of a very dangerous storm tide as the cyclone centre approaches the coast. Tides are likely to rise significantly above the normal high tide mark with very dangerous flooding, damaging waves and strong currents. Widespread heavy rain and further flooding are likely in southern parts of the Ampara and Matara Districts over the next few days.

MTTF of Communities with Addressable Satellite Radios

Mobile Phone MTTF

CDMA 1x_RTT Fixed Phones

Remote Alarm Device MTTF

Control Village MTTF

Sigmoid Scaling Function for Language Diversity Study the Effectiveness of ICT as a Warning Technology ValueFuzzy Rule 1.00Sinhala, Tamil, & English 0.95Sinhala & Tamil 0.85Sinhala & English 0.70Sinhala Only 0.50Tamil Only 0.20English Only 0Otherwise ICT / Measure ASR RAD MP FP VSAT Language Diversity (‘si’, ‘tm’, ‘en’) Full CAP (‘XML’) Mediums (audio, text) Rating Silent-Test = {Sinhala, Tamil, & English} Live-exercises = {ENGLISH}

Sigmoid Scaling Function for Full CAP Compliance ValueRules 1.00All sub elements that are contained in the element, which includes all the qualifier and sub elements 0.95Mandatory defined in the Profile for Sri Lanka, which are the sub elements of the qualifier qualifier and elements --,,, 0.85Mandatory sub elements of the qualifier element and the sub element 0.70 only 0.50Mandatory sub elements of the element only 0Otherwise Study the Effectiveness of ICT as a Warning Technology ICT / Measure ASR RAD MP FP VSAT Language Diversity (‘si’, ‘tm’, ‘en’) Full CAP (‘XML’) Mediums (audio, text) Rating

Effectiveness of ICTs as a Warning Technology Interface HIH Monitor issued CAP Message Receiver Device and {Medium} ICT Guardian received Message elements Community Executed ERP DEWN Internet Browse sub element with en … {no size restriction} si … {no size restriction} tm … {no size restriction} MP {Text} “Warning” en A SEVERE CATEGORY 4 CYCLONE… si …{sinhala} tm … {tamil} {restricted by 130 characters} Tsunami Evacuation RAD {Text} ANNY Internet Browser (AREA) All sub elements in element and message in en only. AREA – B {Text} Alert restricted hih exercise met expected sever observed A SEVERE CATEGORY 4 CYCLONE … {restricted 250 characters} Tsunami Evacuation IPAS Internet Browser with en only … {no size restriction} Personal Computer {Text} A SEVERE CATEGORY 4 CYCLONE … {no size restriction} Not Applicable CDMA x_RTT … {no size and language restriction} CDMA2000 1x_RTT Telephones {Audio} A SEVERE CATEGORY 4 CYCLONE …{no size restriction} Tsunami Evacuation

Sigmoid Scaling Function for -- Mix of Audio and Text Communication Medium Study the Effectiveness of ICT as a Warning Technology ValueFuzzy Rule 1.00Audio and Text 0.95Audio only 0.85Text only 0Otherwise ICT / Measure AREA RAD MP FP VSAT Language Diversity (‘si’, ‘tm’, ‘en’) Full CAP (‘XML’) Medium (audio, text) Rating

Reliability and Effectiveness of the ICT Reliability is measured as the difference between the time it takes ICT Guardian to “receive” message and the time the message was “received” by the ICT Provider. Study the Reliability of ICT as a Warning Technology ICT / Measure AREA RAD MP FP VSAT Reliability Effectiveness (Complete CAP Messaging only) Rating

Discussion of the Hypothesis 1. Stage 4 & 5 Sarvodaya villages that are more organized, i.e., have a formal structure that enables coordination and direction of activities will respond more effectively to hazard warnings than less organized stage 1, 2 & 3 villages. 2. Villages that are provided training in recognizing and responding to hazards along with deployment of ICTs will respond more effectively to hazard warnings than villages that received no training. 3. Villages that have ICTs deployed for dissemination of hazard information will respond more effectively to hazard warnings than villages that have to rely on their existing channels of information for warnings. 4. ICTs that in addition to their hazard function, can also be leveraged in other areas to enrich the lives of the villages will potentially have lower downtime than ICTs that are poorly integrated into the day to day life of the beneficiaries.