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IOT ARCHITECTURE FOR
WATER RESOURCES SECTOR
Ashok Matta
PRESENTATION CONTENTS
•Water Resources IOT Components
•Water resources server cluster
•Real Time Flow Monitoring Data Analytics
•Web based SWMM/HEC-RAS/Flood Modeling
•IoT Platform based Advanced Decision Support
System
•Cloud Computing cost savings and Conclusion
IOT ARCHITECTURE COMPONENTS
CYBERSECURITY SOLUTION (DATA DEFENDS ITSELF)
CYBERSECURITY SOLUTION (DATA DEFENDS
CYBERSECURITYSOLUTION(DATADEFENDS
ITSELF)
CYBERSECURITYSOLUTION(DATADEFENDS
ITSELF)
Water Resources
Server Cluster
Water
Industry Cloud
Web Access
HIGH
PERFORMANC
E COMPUTING
CLUSTER
COMMUNICATION
PLATOFRM
3G,4G,5G,Internet (Wi-Fi, WiMAX and any 5G Tech)
REAL TIME
SENSOR
DATA
MAPPING
DATA
SERVERS
H/H MODEL
SCRIPT &
COMPONENT
S
MODEL
RESULT
REPOSITORIE
S
DATA
COLLECTION,
DATA QAQC,
MODELING,
REPORTING
HIGH PERFORMANCE COMPUTING
WATER RESOURCES SERVER CLUSTER
Water Resources Server
Cluster
Water Resource
Managers
Program Manager &
Consultants
State Planners
(DEP,DEQ etc.)
On-site
technicians
and Survey
Crew
EPA
Responsible
&Data driven
DATA VISUALIZATION TOOLS
SWMM,HEC-RAS ,Water
Quality Models, Watershed
Models ,Model Scripts,
Model Components
Model
Result
Repositories
All Data
Repositori
es
Researchers
LOCAL and
GLOBAL Real
Time Controls
(RTC)
REAL TIME FLOW MONITORING DATA
ANALYTICS
AUTOMATED DATA VALIDATION, OUTLIER IDENTIFICATION
AND FORECASTING
REAL TIME
SENSOR
DATA
KNOWLEDGE BASE REFERENCE
Machine Learning Techniques
help categorize the type of
scattergraph and gives
operator to confirm the field
situation
Artificial Neural
Network based
forecasting; Outlier
Identification;
Validation
Operators make sure the
sensor placement and
other logistics are in place
Good quality data saved
in databases for years
can help seasonal and
regional climatic
patterns.
The databases should
have spatial, temporal,
location data for
automated work orders
or extra survey of nearby
sites.
Automated
Discharge
Monitoring
Reports with
Engineer Review
WEB BASED H/H MODELING
COMPONENTS
PREVIOUS WORK (PCSWMM ,CHI)
Real Time Data Acquisition & Modeling
Source :
http://www.chiwater.com/Solutions/Software/RealTimeData.asp
Schematic of full-scale website architecture
Source : https://www.chijournal.org/Journals/PDF/R228-08
IOT PLATFORM BASED ADVANCED DECISION
SUPPORT SYSTEM
WATER RESOURCESThe advantages of IoT for the Water Sector
i. Real time water asset management , tracking of
rehabilitation and other activities
ii. Enhanced situational awareness of the area for forecasting
failures
iii. Sensor-driven decision analytics
iv. Wastewater treatment Process optimization
v. Optimized resource consumption (Maximum Conveyance
Utilization)
vi. Instantaneous control and response in complex autonomous
systems during inclement weather situations (Early Warning
Systems to avoid loss of life , property damage etc.)
IOT PLATFORM BASED ADVANCED DECISION SUPPORT
SYSTEM
IOT ARCHITECTURE BENEFITS
1. SMOOTH DRY WEATHER AND WET WEATHER OPERATIONS
2. BETTER MOBILIZATION AND MINIMUM DAMAGE DURIND DISASTER
SCENARIOS
3. CONSTANT IMPROVEMENT OF PROCESSES FOR OPTIMIZATION OF
RESOURCES
CYBERSECURITY SOLUTION
• Data dispersion based technology
• Data defends itself when everything fails, so its impossible to recreate the original data by
hacker
CONTACT ME FOR A DEMO.
Can you believe this ?
After energy sector the
most intruded critical
infrastructure sector is
Water and Wastewater
Systems ?
DATABASES FOR RESEARCHERS AND
CITIZEN SCIENTISTS
REAL TIME
SENSOR
DATA
Researchers and
Citizen Scientists
Researchers and the Citizen Scientists
could contribute to :
• Development of analytic solutions
based on several advanced statistical
concepts like Machine Learning,
Entropy, Boltzmann Machines etc. to
find hidden patterns in the data
• Advanced Time Series Analysis for
better understanding of the properties
non-linearity, seasonality, complexity,
cyclicity, stochasticity, fractality, chaos,
and so on.
• Development of cheaper
supercomputers for parallel processing
• Development of Algorithms for optimal
real control of water and sewer
networks
• Development of Apps for integration of
several technologies
MILLVALE FLOOD SEPTEMBER 17,2004
4:30PM
PROPERTY
DAMAGE
PUBLIC INFRASTRUCTURE
DAMAGE
CORPORATE INFRASTRUCTURE
DAMAGE
REPORTED LOSS OF LIFE IN FEW
CASES
IOT SOLUTION FOR A NATURAL DISASTER LIKE
MILLVALE FLOODING
• NO FAILURES
DUE TO
HACKED
DEVICES
• CYBERSECURI
TY SOLUTION
PROTECTS
ANY FALSE
ALARMS
CLOUD COMPUTING
Cloud Computing
1. No Maintenance and hardware problems
2. Always upto date
3. Calibration
4. Pay as you consume
5. No upgrade costs
6. Secure Data
Conclusions
There are many open source IoT platforms available which can
seamlessly integrate sensors , water utility control devices and data
analytic programs to create a robust system to protect our
infrastructure and the public from natural hazards.
For any enquiries please contact : engineermatta@gmail.com

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IoT Architecture for Water Resources Industry

  • 1. IOT ARCHITECTURE FOR WATER RESOURCES SECTOR Ashok Matta
  • 2. PRESENTATION CONTENTS •Water Resources IOT Components •Water resources server cluster •Real Time Flow Monitoring Data Analytics •Web based SWMM/HEC-RAS/Flood Modeling •IoT Platform based Advanced Decision Support System •Cloud Computing cost savings and Conclusion
  • 3. IOT ARCHITECTURE COMPONENTS CYBERSECURITY SOLUTION (DATA DEFENDS ITSELF) CYBERSECURITY SOLUTION (DATA DEFENDS CYBERSECURITYSOLUTION(DATADEFENDS ITSELF) CYBERSECURITYSOLUTION(DATADEFENDS ITSELF) Water Resources Server Cluster Water Industry Cloud Web Access HIGH PERFORMANC E COMPUTING CLUSTER COMMUNICATION PLATOFRM 3G,4G,5G,Internet (Wi-Fi, WiMAX and any 5G Tech) REAL TIME SENSOR DATA MAPPING DATA SERVERS H/H MODEL SCRIPT & COMPONENT S MODEL RESULT REPOSITORIE S DATA COLLECTION, DATA QAQC, MODELING, REPORTING HIGH PERFORMANCE COMPUTING
  • 4. WATER RESOURCES SERVER CLUSTER Water Resources Server Cluster Water Resource Managers Program Manager & Consultants State Planners (DEP,DEQ etc.) On-site technicians and Survey Crew EPA Responsible &Data driven DATA VISUALIZATION TOOLS SWMM,HEC-RAS ,Water Quality Models, Watershed Models ,Model Scripts, Model Components Model Result Repositories All Data Repositori es Researchers LOCAL and GLOBAL Real Time Controls (RTC)
  • 5. REAL TIME FLOW MONITORING DATA ANALYTICS AUTOMATED DATA VALIDATION, OUTLIER IDENTIFICATION AND FORECASTING REAL TIME SENSOR DATA KNOWLEDGE BASE REFERENCE Machine Learning Techniques help categorize the type of scattergraph and gives operator to confirm the field situation Artificial Neural Network based forecasting; Outlier Identification; Validation Operators make sure the sensor placement and other logistics are in place Good quality data saved in databases for years can help seasonal and regional climatic patterns. The databases should have spatial, temporal, location data for automated work orders or extra survey of nearby sites. Automated Discharge Monitoring Reports with Engineer Review
  • 6. WEB BASED H/H MODELING COMPONENTS PREVIOUS WORK (PCSWMM ,CHI) Real Time Data Acquisition & Modeling Source : http://www.chiwater.com/Solutions/Software/RealTimeData.asp Schematic of full-scale website architecture Source : https://www.chijournal.org/Journals/PDF/R228-08
  • 7. IOT PLATFORM BASED ADVANCED DECISION SUPPORT SYSTEM WATER RESOURCESThe advantages of IoT for the Water Sector i. Real time water asset management , tracking of rehabilitation and other activities ii. Enhanced situational awareness of the area for forecasting failures iii. Sensor-driven decision analytics iv. Wastewater treatment Process optimization v. Optimized resource consumption (Maximum Conveyance Utilization) vi. Instantaneous control and response in complex autonomous systems during inclement weather situations (Early Warning Systems to avoid loss of life , property damage etc.)
  • 8. IOT PLATFORM BASED ADVANCED DECISION SUPPORT SYSTEM IOT ARCHITECTURE BENEFITS 1. SMOOTH DRY WEATHER AND WET WEATHER OPERATIONS 2. BETTER MOBILIZATION AND MINIMUM DAMAGE DURIND DISASTER SCENARIOS 3. CONSTANT IMPROVEMENT OF PROCESSES FOR OPTIMIZATION OF RESOURCES
  • 9. CYBERSECURITY SOLUTION • Data dispersion based technology • Data defends itself when everything fails, so its impossible to recreate the original data by hacker CONTACT ME FOR A DEMO. Can you believe this ? After energy sector the most intruded critical infrastructure sector is Water and Wastewater Systems ?
  • 10. DATABASES FOR RESEARCHERS AND CITIZEN SCIENTISTS REAL TIME SENSOR DATA Researchers and Citizen Scientists Researchers and the Citizen Scientists could contribute to : • Development of analytic solutions based on several advanced statistical concepts like Machine Learning, Entropy, Boltzmann Machines etc. to find hidden patterns in the data • Advanced Time Series Analysis for better understanding of the properties non-linearity, seasonality, complexity, cyclicity, stochasticity, fractality, chaos, and so on. • Development of cheaper supercomputers for parallel processing • Development of Algorithms for optimal real control of water and sewer networks • Development of Apps for integration of several technologies
  • 11. MILLVALE FLOOD SEPTEMBER 17,2004 4:30PM PROPERTY DAMAGE PUBLIC INFRASTRUCTURE DAMAGE CORPORATE INFRASTRUCTURE DAMAGE REPORTED LOSS OF LIFE IN FEW CASES
  • 12. IOT SOLUTION FOR A NATURAL DISASTER LIKE MILLVALE FLOODING • NO FAILURES DUE TO HACKED DEVICES • CYBERSECURI TY SOLUTION PROTECTS ANY FALSE ALARMS
  • 13. CLOUD COMPUTING Cloud Computing 1. No Maintenance and hardware problems 2. Always upto date 3. Calibration 4. Pay as you consume 5. No upgrade costs 6. Secure Data Conclusions There are many open source IoT platforms available which can seamlessly integrate sensors , water utility control devices and data analytic programs to create a robust system to protect our infrastructure and the public from natural hazards. For any enquiries please contact : engineermatta@gmail.com

Notes de l'éditeur

  1. The quality of the sensor data is very crucial if it is going to be saved in repositories for further uses. There are several ways
  2. Source : Figure 1 :
  3. Source : http://ci-water.org/reports_results/allhands_oct2013/approach_FEWS.pdf