Framework for smart city

1. Framework for Smart Cities
Prof. R V Kolhe
Assistant Professor
Department of Civil Engineering
Sanjivani College of Engineering, Kopargaon

2. IoT Use Cases in Smart City
Infrastructure
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• Smart energy grid
• Smart water grid
• Structural health
• Transportation
• Asset tracking/management

3. Structural Health Monitoring
(SHM)
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4. Many Unsafe Bridges
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• More than 700K bridges in US
• 1 in 5 is unsafe or structurally obsolete
• Only inspected once in 1-2 years
• Often takes an accident to get attention
– I-5 Skagit River Bridge (Washington, 2013)
– I-35W Mississippi River Bridge (Minnesota, 2007)

5. Why Not Real-Time Monitoring?
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• Expensive instrumentation
• Expensive cabling for data telemetry
• Expensive cabling for power supply
• Large amount of data
• >US$200,000 per site

6. Technical Aspect of SHM
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• Time domain data from many dynamic sensors
• Real-time frequency domain analysis is compute
intensive
• Transmission of data needs high bandwidth and
storage capacity
• High reliability requirement
• Model update, when needed, is very compute
intensive

7. Business Aspect of SHM
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• High organizational inertia
• Each structure is different
– System needs to be flexible
– Different sensor combinations
– Interested in different events
• Require an efficient framework
– Support customized hardware
– Customized analysis
– Up front deployment + ongoing analysis

8. What We Had Done
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• Embedded multi-sensor system
• Precision synchronization
• Rolling backup on device
• On-device data processing and compression to
reduce bandwidth requirement
• Flexible Wireless telemetry
• Could operate on harvested solar energy
• Data repository/analysis on cloud
→ Much lower cost of ownership

9. How to Value a Safe Bridge?
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Antennae
Main chassis
(Inclinometers
Accelerometers)
Much lower cost
→ Wider deployment
→ Safer public infrastructure
Temperature sensor
Water Velocity Water Level
sensor sensor

10. Need for Quantitative and
Qualitative Monitoring of Water
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• Water distribution infrastructure
• Quantitative – 30% lost through pipeline
• Qualitative – contamination
• Water quality in source water bodies
• Effective water use
• Residential, commercial, industrial,
agricultural/landscape
• Pollution detection/regulatory enforcement
• Wastewater management

11. Benefits of Water Infrastructure
Monitoring
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• 2.3 million miles of distribution system pipes in
US, most near end of lifespan
• Contamination due to biofilm growth, nitrification,
leaching, internal corrosion, scale formation, etc.
• Increasing concern over intentional sabotage

12. • Agricultural Waste Water
 Pollute source water and underground water with
pesticides and nutrients
 Infrequent monitoring/reporting is ineffective in
protecting public
• Industrial Waster Water
 Contain various industrial pollutants
 Oversight agencies can't afford the labor and
equipment to ensure compliance
• Example (Washington Post 2008-09-22)
– Maryland has 132 inspectors to cover 205,000 sites -
“not even close to adequate”
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Inability to Enforce Regulations
Without Real-Time Monitoring

13. • Citywide sensor network for water monitoring
– Infrastructure integrity
– Quality assurance
– Usage accounting
– Pollution Detection
• Different sensors on common platform
– Efficiency from sharing platform across multiple
applications
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Our Model: Smart Water Grid
Edge Sensors

14. • Sensor network management/maintenance
• Data repository
• Data analytics
– Event detection
– Event response workflow
– Cause/effect identification
• Open API
– Enable many mobile/desktop/web applications
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Our Model: Smart Water Grid
Web Services

15. Example: Water Quality Credit Trading
• Economic incentive for compliance and reuse.
• Wider adoption will require common monitoring
framework.
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Monitoring Enables Carrots and
Sticks

16. Webservices
Analytics
Event Management
API
Public/Private Networks
Water Grid
• Electrochemical
• Optical
• Submeters
• Water level
• Water velocity
Transportation
• Traffic flow
• Parking
• Access control
• Emission control
• Licensing
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Civil Structures
• Vibration
• Tilt
Energy Grid
• Submeters
Our Model: A Common Smart
Sensor Framework

17. • Challenges
 Difficult to confirm event against fluctuating
background using few parameters
• False alarms cause panic, reduce credibility
 Example: Water quality fluctuates due to operational
controls, daily and seasonal variations
• Statistical analysis
– Reduce false-positives
– Recognize known patterns
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Event Detection & Analysis

18. Incident /Event management
• Event verification protocol
• Notify first responders, officials, citizens
• How is it similar/different from previous
• Event tracking from detection through resolution
Knowledge Management
• Assess event management effectiveness
• Statistics of event type and resolution tactic/strategy
• Knowledge improves handling future events
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Work Flow

19. Citizen Access
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• Issue reporting/verification
• Smart phones are effective distributed sensors
• Turn service consumers into service providers
• Status of known issues
• Solution of past issues
• Process improvement
• Quantity benefit
• Access performance of city management

20. Conclusion
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• Technology still evolving fast
• Modular design
• Loosely-coupled components
• Integrated by open protocol
• Parts could be changed over time
• Data, data everywhere
• Mostly routine non-eventful data
• Detecting meaningful events
• Work flow to manage events
• Good API design is critical in effective use and
continued evolution of this infrastructure

21. goodXense Framework
• Built on sails.js – a real-time MVC framework
• RESTful API already familiar to web developers
• Front-end agnostic
• Smart sensors using different protocols
• Web browsers and mobile apps for human
• Supports many databases
• Extendable interface to various IoT protocols
• Under preparation for open source
• Welcome interested collaborators
info@goodxense.com
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