Raising Community Awareness Through ArcGIS Mapping, IoT ...
Transcript of Raising Community Awareness Through ArcGIS Mapping, IoT ...
Raising Community Awareness
Through ArcGIS Mapping, IoT,
Analytics and Voice
Sridhar Katragadda
Systems Analyst,
City of Virginia Beach
Dr. Jon Derek LoftisAsst. Research Scientist,
VA Inst. of Marine Science
Outline
1. Project Summary
2. Hydrodynamic Modeling
3. Multi Cloud Environments
4. Data Science
5. Community Awareness
Project Summary
StormSense... A Proactive Approach to becoming a Flood-Resilient
Region...Hampton Roads
• Virginia Beach (2013) - Reviewed current implementations and research in IoT water level sensors
and high resolution flood modeling...Obtained Capital Improvement Program (CIP) funding (2016)
• Virginia Beach (Before July 2015) - 4 Sensors (NOAA), After July 2015 - 10 Sensors (USGS)
funded by Public Works were installed
• City of Newport News and Virginia Institute of Marine Science (VIMS) - Early 2016 – Won
Replicable Smart City Technologies funding from usignite/NIST
Global City Teams Challenge (GCTC) for StormSense Project. City of Virginia Beach and Norfolk
participated as a team.
• June 2017 - First Sensor Installation followed by 6 Sensors in Newport News,
10 Sensors (Pilot Project) in Virginia Beach
• Hydrodynamic Modeling and Predictive Analytics by Virginia Institute of Marine Science (VIMS)
Funding, Regional Perspective and Partnerships
Project Partners (as of November 2017):
IoT Sensor Technologies...
Measuring station shown with the ultrasonic sensor
IoT Water Level Sensors
Great Neck, Virginia Beach
Dam Neck, Virginia Beach
Leeward Marina,
Newport News
Newport News
Dorchester Lane, Virginia Beach
June 2017 - First Sensor Installation followed by 6 Sensors in Newport News,
10 Sensors (Pilot Project) in Virginia Beach...Additional 30 + sensor purchase in progress in 2018
Sensor Deployment Lessons Learned...
• Installation - Multiple options used (City, Contractor)
• Battery...Solar power issues...weather problems...snow...
• Data spikes (previous reading...)
• Data frequency adjustment (for modeling) – 6 minutes
• Sensor calibration (optimal range adjustment – Sensor range vs. settings)
• Sensor configurations (in-house and field)
Hydrodynamic Modeling
• Sensor Deployment
• Tidal Calibration (via VIMS Tidewatch)
• Model Development
• Model Release for Emergency Managers
SCOPE 2018 Workshop
• Stage 1: SensorDeployment
• Stage 2: Tidal Calibration(via Tidewatch)
• Stage 3: Model Development
• Stage 4: ModelRelease for EM’s
IoT Stream Gauge
Network
StormSense
Hydrodynamic
Forecast Model
Server StormSense
Web Portal
6-min automated
retrieval script
Observations & Predictions
stormsense.com
Hydrodynamic Modeling
• Stage 1: SensorDeployment
• Stage 2: Tidal Calibration(via Tidewatch)
• Stage 3: Model Development
• Stage 4: ModelRelease for EM’s
SCOPE 2018 Workshop
• Stage 1: SensorDeployment
• Stage 2: Tidal Calibration(via Tidewatch)
• Stage 3: Model Development
• Stage 4: ModelRelease for EM’s
Priority Site Sensor Type Power SourceData
TransmissionSensor Cost
Data Transmission
Cost
116th St. Bridge over
Salters Creek
Ultrasonic
SonarSolar/Battery Cellular Modem $2,969.00
$7.00
(Verizon 5MB plan)
Hydrodynamic Modeling
SCOPE 2018 WorkshopHydrodynamic Modeling...
• Stage 1: SensorDeployment
• Stage 2: Tidal
Calibration
(via Tidewatch)
• Stage 3: Model Development
• Stage 4: ModelRelease for EM’s
http://www.vims.edu/bayinfo/tidewatch/stations/cbbt/index.php
SCOPE 2018 Workshop
12
Central Norfolk Superposed with Sub-gridCentral Norfolk Represented by Sub-gridDowntown Norfolk and City HallCity Hall Superposed with Sub-gridCity Hall Represented by Sub-grid
Norfolk Tides
Stadium
Norfolk
City Hall
Norfolk
Scope
Arena
City of NorfolkOld Dominion University and PeninsulaODU Peninsula Superposed with Sub-gridODU Peninsula Represented by Sub-grid
Edgewater
Haven
Foreman Field
ODU
President’s
Residence
Chesterfield Heights, Grandy Park, and Broad CreekChesterfield Heights Represented by Sub-Grid
Middle Towne
Arch
Moseley Creek
Grandy Park
How the StormSense Flood
Model is built: Sensor-Driven
Predictions, Embed Lidar &
Bathymetry, Add Buildings
Hydrodynamic Modeling
• Stage 1: SensorDeployment
• Stage 2: Tidal Calibration(via Tidewatch)
• Stage 3: Model
Development
• Stage 4: ModelRelease for EM’s
SCOPE 2018 Workshop
• Water levels extracted from grid cells with
water level observations
• Perl and python scripts run in the background
to produce geotiff rasters of water level and
flood heights (water level- land elevation) for
each 6-minute interval
• Spatial outputs are prepared as .kml files and
javascript-layers for production of open layers
maps, Google Maps, and Google Earth
animations .
Hurricane Irene Storm Surge Inundation Street-Level Animation (ODU Campus)
Hydrodynamic Modeling
• Stage 1: SensorDeployment
• Stage 2: Tidal Calibration(via Tidewatch)
• Stage 3: Model Development
• Stage 4: ModelRelease for EM’s
How the StormSense Flood
Model is shared: Tidal
forecasts at sensors
• Flood maps via: AGOL
• & Google Earth
SCOPE 2018 Workshop
How the StormSense Flood
Model is shared: Tidal
forecasts at sensors
• Flood maps via: Web 3D
• Thank you to Geoff Taylor,
from ESRI (3D buildings)
Hydrodynamic Modeling
• Stage 1: SensorDeployment
• Stage 2: Tidal Calibration(via Tidewatch)
• Stage 3: Model Development
• Stage 4: ModelRelease for EM’s
http://www.vims.edu/people/loftis_jd/virginia-beach/index.php
Multi Cloud Environments
• Achieve Replicability - On-premise or Cloud?
• Multiple IoT Sensor Data Clouds (StormSense, USGS, NOAA, NWM, City
Public Works, Public Utilities Rain Gauges...)
• Aggregation to provide real-time data streams
• Multi Cloud...
- AWS (Amazon Web Services) – Provides Real-time data streams of disparate data
- ArcGIS Online for Maps and Predictive Data – AWS and VIMS Tidewatch Network
- Microsoft Power BI for Data Analytics – Provides visualization of data for citizens and
city staff
Multi Cloud Environments...AWS...
Multi Cloud Environments...ArcGIS Online...
Data Science...Analytics...
Support Citizens...
- Simplified UI to view water levels in their neighborhood
Support City Staff...
- Detailed UI for Engineers and decision-makers
Short Term (Bi-weekly) and Long Term (Monthly...Year...)
- Water levels
- Rain Gauges
- Wind Gauges
- Data outlier detection of sensor performance
- Past events review
Data Science...Analytics...
Community Awareness
• Community participation to support calibration of models
• Raising citizen awareness to water levels
- Using Real-time data
- Using Analytics
- Using Voice Assisted (Alexa, Skype, Chatbots...)
- Notification
- Mobile App
• Support FEMA’s Community Rating System (CRS) score to qualify for
lower insurance rates in the future
Community Awareness...Citizen Science...
• November 5th, 2017 – King Tide. VIMS organized
a region wide hydrodynamic model as a backdrop
for citizen volunteers to participate to validate and
improve predictive models
• 510 known participants
• 53,006 timestamped GPS max. flood extent
measurements collected
• 1,126 geotagged photographs
• Visit our presentation on Thursday at 8:30 am in
Room 26A: Crowdsourcing Hydrocorrection: How
Tidewater Virginia Caught the King Tide
Support FEMA’s CRS...Qualify for lower discounts...
Community Awareness...Voice Assisted...
• November 5th, 2017 – King Tide. VIMS organized a region wide hydrodynamic model
as a backdrop for citizen volunteers to participate to validate and improve predictive
models
Published Alexa Skill “storm sense”Participated in AWS “City on a Cloud” Innovation
Challenge and won $50,000 credits
Current Activities...Future...
• Planning to release the maps, analytics and voice applications in late July,
2018
• Working closely with ESRI on 3D/Tools views and integration of VIMS
modeling results
• Working on adding the flood levels...Minor...Moderate...Major after data
collection and observation
• Working on using AWS DeepLens Camera on Bridges to detect water-land
surface boundaries and corroborate with sensor data
• Working with AWS on Open Data, NWM integration at sensor level
• Working on notification service of water levels to Citizens
Abstract
• Raising community awareness of impending flooding conditions can be
accomplished through the recent advancements in a rich multi cloud
environment with ArcGIS being a leader in cloud-based mapping platform,
data science and hydrodynamic modeling. A glimpse of StormSense project
progress, the pathway and lessons learned to accomplish tasks through
collaborations, with replicability mindset was encouraged by
usignite/NIST’s Global Cities Teams Challenge (GCTC) that made it
possible.
Thanks for attending our presentation. I hope some
ideas that were presented here are worth taking
back with you. Your feedback is welcomed and it
may help us think of new approaches
Sridhar Katragadda
http://www.vbgov.com
Dr. J. Derek Loftis
http://www.vims.edu/