1. http://openisdm.iis.sinica.edu.tw Jane W. S. Liu ( 張韻詩 ) Institute of Information Science Academia Sinica, Taiwan Ubiquitous Devices & Applications for Disaster Prepared Smart Homes and Environment

2. Outline  Overview of OpenISDM (Open Information Systems for Disaster Management) project  iGaDs (intelligent Guards against Disasters)  Recent events and future scenarios  Examples of enabling technologies, standards, and ICT infrastructures  Cyber-physical elements of future smart living environment for better preparedness  Opportunities and challenges Examples of other on-going works on ICT for DM

3. About Our Work Response Recovery Preparedness Reconstruction Prediction and warning Scenario development Emergency SOP development Education & training Preparedness Real-time monitoring, modeling, forecasting Scenario identification/situation awareness Dependable alert/alarm/warning delivery Effective use of alarm information Prediction and warning Connectivity diagnosis and repair Information dissemination Command and control decision support Resource dispatching Response Impact assessment Restoration of telecommunication, transportation & other infrastructures Recovery Mitigation and prevention Disaster management cycle Mega disasters = Calamities for which we are unprepared: “no-notice events” by C. Dickey, Newsweek, Sept 12, 2011

4. 0% 100% 024h48h 72h Availability Impact On Power of Information “Information can save lives, livelihoods and resources.” – World Disasters Report, 2005 “Today, even mobile phones could be used as an effective medium to provide early warnings and thus save lives and property” – R. K. Pachauri, 2009 “Small advances in emergency informatics could significantly reduce deaths, accelerate damage assessment, and minimize economic downtime” – R. R. Murphy, 2010

5. Happenings Everywhere

6. SANY and OSIRIS in EU User information systems Operational services System services Sensor services Sensor Systems Generic  Display  Sensor tasking  Sensor Monitoring  Sensor man.  Proc./storage  Web mapping  Dataflow man.  Alarm service  Discovery  Access  Alert  Tasking.  Interface adaptor

7. Open SensorNet & DMIS Infrastructures in US E911 & E911-IPDM-OPEN, IPAWS, CAP

8. 中央災害應變中 心分析研判組 災害防救應用服務平台 中央災害應變中 心分析研判組 資訊綜整共享運作機制 8 交通部 中央氣象局 交通部 中央氣象局 經濟部 水利署 經濟部 水利署 行政院農委會 水保局 行政院農委會 水保局 內政部營建署 內政部消防署 交通部 公路總局 交通部 公路總局 國家災害防救 科技中心 國家災害防救 科技中心 XML, KML 地方政府 民眾，記者 XML, KML 基本圖資 監測圖資 災情資訊 設施操作 … 基本圖資 監測圖資 災情資訊 設施操作 … 基本圖資 監測圖資 中央災害應變中心 指揮官 XML KML 災情資訊 設施操作

9. Server 擴充實境 Smart phone Apps 聚落調查資料庫 保全對象 土石流 山崩地滑 避難處所 河岸侵蝕 重大災例資料庫 該地歷史災例 致災因子資料庫 調查相片

10. Common Limitations The systems cannot make good use of all information sources, including ones owned by businesses, communities, and so on The systems do not exploit synergistically information from networks of things and crowd of people The systems do not make effective use of early warnings to enhance preparedness The systems are not sufficiently agile in response to changes in disaster situation

11. A Framework for Open and Sustainable DMIS Jan-Ming Ho (IIS), Ching-Teng Hsiao (CITI), Der-Tsai Lee (IIS) and Jane W. S. Liu (IIS & CITI) Application ComponentIT Component Flow Control and Fusion of Symbiotic Information John K. Zao (NCTU), Sheng-Wei Chen (IIS) Jane W. S. Liu (IIS) & Edward T.-H. Chu (NYUST) Disaster Information System for Resilient Communities Feng-Tyan Lin (NCKU) Hsueh-Cheng Chou (NCDR) Han-Liang Lin (NCKU) Climate Extremes and Weather Disasters Data Repository Shaw-Chen Liu (RCEC); Chia Chou (RCEC) Shih-Chun Lung (RCEC) & Mong-Ming Lu (CWB) Crustal Deformation and Faulting Behavior Databases Jian-Cheng Lee (IES), Long-Chen Kuo (IES) Wen-Tzong Liang (IES) Virtual Repository Ching-Teng Hsiao (CITI), Pen-Chung Yew (U of Minn) David Hung-Chang Du (U. of Minn) Open Information Gateway Chi-Sheng Shih (NTU), Ling-Jyl Chen (IIS) Phone Lin (NTU), Kwei-Jay Lin (UCI) Ching-Ju Lin (CITI) & Wei-Ho Chung (CITI)

12. Wrapper interface Filtering and Fusion Information SourcesApplicationsOpen Information System Disaster mitigation applications Disaster warning systems Real-time C3 Sahana & other DMS Road and traffic conditions data.gov.tw datasets Weather forecast, models, imagery, sea surface temperature, etc Census and GIS data on vegetation, wildlife, geological profile, etc. Eyewitness reports, news, messages, twitter, etc. OpenSensorIS Sensor data on water levels & flow rates, soil moisture profile, land slide susceptibility; seismic activities; bridge stress, etc. Information flow control mechanisms Fusion, virtualization, & visualization services

13. Contents contributed by diverse, independent Sources Responsive, trustworthy emergency Information broker services Sources = applications/users Effective use of compute, communication and storage resources at points of service during emergencies Individualized view of a virtual data cloud and interface service for each application and user

14. TRIPS Communication infrastructure Heterogeneous And Plug-n-Play Network Store sensor data in persistent cloud Receive/report alerts Review data after disaster Publish/subscribe disaster data TRIPS Exchanger TRIPS Agent TRIPS App TRIPS Exchanger TRIPS App TRIPS Exchanger TRIPS App Points Of Services OIGY

15. Emergency Information Access Break-the-glass (BTG) extensions of authentication and authorization access control models and mechanisms TIBS (Trustworthy information brokerage service)  Proactive upload of emergency information on POS’s  Information release based on traceability and accountability Filters Scenario analysis SOPs & DSA workflows Information requirements Sources Filtered information Release and accountability causes Handle requests & enforce release policies POS

16. User Registration Policy Management Event trackers Policy DB Audit Record Identity Record Admin Audit Record Policy DB PEP PDP R RRRR P Audit Record Audit Record Helper ICC RC 3 Admin Provider Helper Policy DB PEPPIP PDP R RRRR P A Audit Record Provider Components of Information Broker Admin

17. Typical state-of- practice solution Official Sources XML ARC GIS Interfaces Custom Interfaces Other known sources Unknown Sources Including news, social media, etc. Scientific data sources CDEF CEWD Taxi & bus RT data Information access control/brokerage services VR resources and interface service tools: publishing assistant; vocabulary managers; query translators; model mapping and format conversion tools; filtering, fusion and visualization tools; crawlers, extractors, and parsers; social report validation tools, etc. LOD warehouse cloud(s) LOD repositories supporting on- demand caching Repositories with pre-cached linked- data values VR resources and LOD on points of service Interface services Virtual repository

18. Outline  Overview of OpenISDM (Open Information Systems for Disaster Management) project  iGaDs (intelligent Guards against Disasters)  Recent events and future scenarios  Examples of enabling technologies, standards, and ICT infrastructures  Cyber-physical elements of future smart living environment for better preparedness  Opportunities and challenges Examples of other on-going works on ICT

19. 05/22/2011 EF 5 Tornado, Joplin MO 162 causalities and 990 injuries Majority of causalities were home Approximately one mile wide Hit 7 minutes after first touch down

20. A Tornado Emergency Scenario...THIS IS A TORNADO EMERGENCY FOR THE WARNED AREA... AT 703 PM CDT...NATIONAL WEATHER SERVICE METEOROLOGISTS AND STORM SPOTTERS WERE TRACKING A LARGE AND EXTREMELY DANGEROUS TORNADO. THIS TORNADO WAS LOCATED 6 MILES SOUTHWEST OF SAVOY MOVING NORTHEAST AT 45 MPH. THE TORNADO WILL BE NEAR... CHAMPAIGN BY 720 PM CDT... RANTOUL BY 729 PM CDT… PAXTON BY … A TORNADO WARNING MEANS THAT A TORNADO IS OCCURRING OR IMMINENT. YOU SHOULD ACTIVATE YOUR TORNADO ACTION PLAN AND TAKE PROTECTIVE ACTION NOW. SIGNIFICANT DAMAGE HAS OCCURRED WITH THIS SIGNIFICANT TORNADO! THIS IS AN EXTREMELY DANGEROUS AND SERIOUS LIFE THREATENING SITUATION..  Sound tornado sirens  Unlock shelter doors  Turn on spot lights on shelters  Adjust traffic signals on routes to shelters  Enable outside doors in homes to open when the storm hits.

21. One of 150-200 quakes in past 25 years Buildings evacuated from NYC to DC 911 calls failed for more than an hour Traffic jams on N. VA highways Two nuclear power plants shut down 08/23/2011 5.8 quake in Virginia

22. Earthquake Detection $ 29  Affordable detectors based on that  P (primary/pressure) wave travels faster than S (secondary/shear) waves, and generate only shock  Slower S waves are destructive  Early earthquake warning systems consisting of seismic motion sensors networked with computer(s)  Issue warning based on likely strength and progression of seismic events and  Can allow warning 20 seconds or more before ground motion.

23. Earthquake Detection in Taiwan BATS: Broadband Array in Taiwan for Seismology 650 strong motion seismic stations Auto-location in seconds by taking advantage of Central Weather Bureau seismic network RF connections to TEC Data Center Capability of inverting BATS waveforms to obtain focal mechanisms for felt earthquakes in minutes Felt earthquakes 08/2011

24. Alert xmlns: … Sender: Central Weather Bureau Status: Actual MsgType: Alert Scope: Public Info Category: Geo Event: Earthquake Urgency: Immediate Severity: Strong Certainty: Observed Description: A strong earthquake measuring 6.9 occurred in … Parameters: Magnitude, depth, … Areas: Polygons specifying affected areas Resources: … … A Future Scenario

25. Standard-Based Alert Delivery Integrated Public Alert and Warning System Authenticated message senders http://www.fema.gov/emergency/ipaws/ipaws_cap_mg.pdf

26. Common Alert Protocol (CAP 1.1) ITU-T Recommendation X 1303 (07/2007) A common format that supports  Broadcast of messages of all types to all public alert systems  Message exchange between emergency information systems  Aggregation and correlation of warnings from multiple sources  End-to-end authentication and validation  Automatic reports by sensor systems to analysis centers  Automatic processing by smart devices and applications

27. ?xmlns version = “1.0” <alert xmlns = … … Earthquake Immediate Strong Observed … Magnitude 7.2 … 32.9525 -115.5585 0 … ?xmlns version = “1.0” alert xmlns = … … Earthquake Immediate Strong Observed Alert extraction Action activation rule evaluation Device interface Elevator controller Alert extraction Action activation rule evaluation Device interfaces Earthquake. Slow down, pull over Vehicle safety system iGaDsiGaDs

28. iGad CAP-aware elevator controller CAP-aware building management system CAP-aware entry access controller iGaD iGaDs in Smart Homes and Buildings (AlertType == Earthquake) AND (Magnitude>= 7.5) OR (AlertType == Tornado) AND (Severity >= 4) (AlertType == Earthquake) AND (Magnitude >= 6) OR (AlertType == Tornado) AND (Severity >= 3) AND (OutsideAirPressure * THRESHOLD_RATIO < InsideAirPressure)

29. General Structure and Major Components  Standard-based alarm delivery and message exchanges as parts of DM infrastructure  Standard interfaces for processing & responding to standard-based alarms  Dependable, low-cost, customizable smart devices for enhanced disaster readiness CAP Message Processor Alert type & information Alert records Affected areas Alert message buffer Modem Signature validation XML parser Location filter Device Controller Device interfaces Configuration files Device location Resources Local data Rule processor Rule engine Activation parameters and rules “cyber-physical elements of enhanced disaster prepared smart environment,” by Liu, Chu and Shih, to appear in IEEE Computer “Ubiquitous smart devices and applications for disaster preparedness,” by Liao, et al, Report TR-IIS-12-004

30. An Example of CAP-Aware Application ?xmlns version = “1.0” <alert xmlns = … … Earthquake Immediate Strong Observed … Magnitude 7.2 … 32.9525 -115.5585 0 …

31. Strong earthquake CAP alert … Earthquake, Stay calm, Move to Checkout counters Follow directions as indicated by either arrows to a safer place

32. Challenges  Pushing alert messages to iGaDs and people  Minimizing energy consumption for iGaDs on battery powered platforms  Creating dual (everyday and emergency) use applications  Interfaces and standards, including  With sensors, actuators, location devices and services, etc.  With information sources (e.g., BIM, store layouts, building management information system, etc.)

33. Pushing Alert Messages Happening now:  Guide for CAP-EAS implementation published by EAS industry  Weekly testing since December 2011 CMAS

34. CAP message buffer(s) Basic Info extractor From Modem Event type Scale Msg Type Certainty Urgency...... Event type LowScale Msg Type HighScale Certainty...... Configuration registers Temp Control & decision 3 8 ALU CLR Basic info registers Message screening rule processor Alert host & iGaD(s) 8 MUXMUX SEL MUXMUX ASIC CAP Message Screener

35. Challenges  Pushing alert messages to iGaDs and people  Minimizing energy consumption for iGaDs on battery powered platforms  Creating dual (everyday and emergency) use applications  Interfaces and standards, including  With sensors, actuators, location devices and services, etc.  With information sources (e.g., BIM, store layouts, building management information system, etc.)

36. Other Current Works on ICT  Technology for real-time connectivity assessment, report and repair  Models, algorithms, and tools for crowdsourcing human sensor data collection  Methods and tools for filtering and validating eyewitness reports from massive crowd  Novel disaster management applications  Methodology and scenarios for evaluation of TIBS relative to BTG approaches

37. Cases for crowdsourcing information collection as parts of SOP 2009 California wildfire Recent major disasters 2011 floods in major cities

38. Technological Support for crowdsourcing Chu, Liu and Shih, “Strategies for Crowdsourcing for Disaster Situation Information,” WIT Transactions on the Built Environment, Vol.119, 2011  Theoretical foundation of crowdsourcing human sensor data:  Models of human sensors and intelligent things  Algorithms for participant selection and tour planning  Information refinement and validation tools  Automatic crawlers and user interface for collecting and summarizing related information posted on clouds  User interfaces to let the crowd help verifying collected information  Algorithms for removal of suspect information after the crowd validation stage  Means for diverse local-based service (LBS) devices and applications to share information

39. Open GeoSMS Open GeoSMS Standard Specification, Ed by C. F. Lin, et al, OGC 09-142r1, Feb. 2010 http://maps.google.com/maps/?q= … &GeoSMS GeoSMS I am attending ESWeek 2011 at TICC in Taipei Let us meet at the conference? EJB. GeoSMS/2; NULL; NULL; Q; Where is TICC GeoSMS/2; 2520.714,N;12138.123.E; B; SMS query for location Reply with application provided location information GeoSMS/2; 2250.124.N; 12155.321.E;E; ROAD_FLOODING GeoSMS/2; 2250.124.N; 12155.321.E;E; SMOKE_VISIBLE Cross platform/system, and service standard Reports from participants Device/system/application provided location in a standard format Location accuracy adequate for now and is improving

40. 2009 Morakat typhoon  Hsiaolin village lost  Over 700 casualties  EOC was blind & deaf

41. Internet Footprint Investigation Service  Active Network Probe (ANP) proactively queries landmarks  Reactive Footprint Searcher (RFS) looks for footprints in potentially disconnected areas reported by ANP L. J. Chen, et at., “A rapid method for detecting geographically disconnected areas after disasters,” to appear in Proc. of IEEE International Conf. on Technologies for Homeland Security, Nov. 2011 Disaster Response Authorities Request for connectivity report ANP RFS List of polygons around disconnected landmarks Polygons of disconnected areas

42. Internet Mobile cellular base-station Connection Repair Last-mile mesh Gateway router  Mobile cellular base stations provide coverage for large areas temporarily.  Last-mile mesh network extends the coverage area and relays data through cellular stations to/from the Internet

43. Other Current Works on ICT  Technology for real-time connectivity assessment, report and repair  Models, algorithms, and tools for crowdsourcing human sensor data collection  Methods and tools for filtering and validating eyewitness reports from massive crowd  Novel disaster management applications  Methodology and scenarios for evaluation of TIBS relative to BTG approaches  Virtual and augment simulation environment  Intelligent active storage system  Cross-platform thin-client applications

44. VARSE Virtual Reality / Augmented Reality Simulation Environment Ben (Meng-Kai Liao) Injure (Ing-Jhe Hu) Jerry Wu (Chun-Yi Wu) Lightorz (Tzu-Liang Hsu) NeetFish (Chang Shin Yu) Red Rain (Hung-Yu Tseng)

45. Earthquake, Taichung, 1999 Fire, Changzhou, 2010 Typhoon, Hualien, 1999Tsunami, Japan, 2011 Why VARSE? How do we show students where to go during earthquakes? How do we assist citizens to escape when tsunami arrives? To travel or not to travel? How do I decide? How do we escape from fire and the panic crowd?

46. VARSE Editions VARSE Maintenance Team Public Edition Disaster Management Edition Government Edition ‥‥

47. VARSE Cloud PCLaptopTouch PC Smart Phone Feature Phone VARSE Public Edition Platforms Local Computing (with local database) Cloud Computing

48. Some of the Challenges  Agent-based models of disasters  Machine readable historical records  Interfaces and tools for incorporating data from other simulators and machine- readable historical data  Interfaces with GIS, etc.

49. Thank You!