Ubiquitous Devices and Applications for Disaster Prepared Smart

Ubiquitous Devices and Applications for Disaster Prepared Smart Homes and Environment Jane W. S. Liu Institute of Information Science Academia Sinica, Taiwan http: //openisdm. iis. sinica. edu. tw PNC Annual Meeting, December 11, 2013, Kyoto, Japan

i. Ga. Ds (intelligent Guards against Disasters) Making effective use of data and information http: //openisdm. iis. sinica. edu. tw PNC Annual Meeting, December 11, 2013, Kyoto, Japan

“Water, water everywhere, nor any drop to drink” from The Rime of the Ancient Mariner, by Samuel Taylor Coleridge Data, data everywhere, nor good use of them to keep us as safe as we can be in calamities

Why, What, How, Big data for Io. T? i. Ga. Ds (Intelligent Guards against Disasters)

Disaster Prediction & Detection From weather Underground From Minnesota Public Radio Org. Tsunami warning, landslide warning, debris flow monitoring systems

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

OGC Sensor Web Enablement Standards: Vision, Implementation and Applications

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

Common Alert Protocol 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 ITU-T Recommendation X 1303 (07/2007) § Automatic reports by sensor systems to analysis centers § Automatic processing by smart devices and applications

Happenings Now § i. PAWS-CAP-EAS/CMAS q CMAS § Google Now Alerts Guide for CAP-EAS implementation published by EAS industry Weekly testing in USA since December 2011

A Future Scenario Alert xmlns: … Sender: Central Weather Bureau Status: Actual Msg. Type: Alert Scope: Public Info Category: Geo Event: Earthquake Urgency: Immediate Severity: Strong Certainty: Observed Description: A strong earthquake measuring 7. 8 occurred in … Parameters: Magnitude, depth, … Areas: Polygons specifying affected areas Resources: … …

i. Ga. Ds in i. Gad OR Smart Homes (Alert. Type == Tornado) AND (Severity >= 3) AND (Outside. Air. Pressure * THRESHOLD_RATIO < Inside. Air. Pressure) and Buildings (Alert. Type == Earthquake) AND (Magnitude >= 6) i. Ga. D CAP-aware elevator controller CAP-aware entry access controller CAP-aware building management system (Alert. Type == Earthquake) AND (Magnitude>= 7. 5) OR (Alert. Type == Tornado) AND (Severity >= 4)

General Structure and Major Components Modem Alert message buffer Signature validation XML parser § Standard interfaces for processing & responding to standard-based alarms CAP Message Processor Affected areas Location filter Device location Alert type & information Resources Alert records Rule processor Activation parameters and rules Rule engine Local data Device interfaces § Standard-based alarm delivery and message exchanges as parts of DM infrastructure Configuration files Device Controller § Dependable, low-cost, customizable smart devices for enhanced disaster readiness “Cyber-physical elements of enhanced disaster prepared smart environment, ” by Liu, Chu and Shih, in IEEE Computer “Ubiquitous smart devices and applications for disaster preparedness, ” by Liao, et al, in Proceedings of UFirst, UIC 2012

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

i. Ga. Ds in i. Gad OR Smart Homes (Alert. Type == Tornado) AND (Severity >= 3) AND (Outside. Air. Pressure * THRESHOLD_RATIO < Inside. Air. Pressure) and Buildings (Alert. Type == Earthquake) AND (Magnitude >= 6) i. Ga. D CAP-aware elevator controller CAP-aware entry access controller CAP-aware building management system (Alert. Type == Earthquake) AND (Magnitude>= 7. 5) OR (Alert. Type == Tornado) AND (Severity >= 4)

BIM From “Daily life of building information modeling” by Kristin Dispenza at Buildingpedia. com, June 2010

Building Information Model Cloud Maintenance records Local sensor data Spatial and layout data i. Gad i. Ga. D Structure data

An Example of CAP-Aware Application ? xmlns version = “ 1. 0” <alert xmlns = … … <event>Earthquake</event> <urgency>Immediate</urgency> <severity>Strong</severity> <certainty>Observed</certainty> … <parameter> <value. Name>Magnitude </value. Name> <value>7. 2</value> </parameter> … <area> <circle>32. 9525 -115. 5585 0</circle> </area> …

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

Store Layouts In-Store Server Local Info Inventory & floor-plan manager Retail data capture & analysis tools LAN access points Employee device Customers’ Mobile devices

Observations § On BIM data: Data on building information modeling, store layouts, etc. are likely to become BIG with increasingly wider adoption of the BIM process worldwide q 3 – 6 D BIM data are highly structured and complex q Privacy protection is important q Current obstacles include missing international standards and interoperability and exchangeable of information in digital formats On use of BIM data by i. Ga. Ds q Small grains of data are accessed by millions of smart devices and applications concurrently q Real-time response is always required; sometimes with end-to-end delay < 1 sec. q §

IGa. Ds + Cloud + Big data = Massive Business Opportunity From “The massive M 2 M business opportunity, ” by B. Chung at Loyalty Today, February 2013.

Thank You!