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

skatraga@vbgov.com

http://www.vbgov.com

Dr. J. Derek Loftis

jdloftis@vims.edu

http://www.vims.edu/