reynolds of aquamatix at smart homes 2013 cambridge
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Future city? CIR Smart Homes & Cleanpower 2013 www.hvm-uk.com
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$3.6bn of $100bn -‐ $400bn IFC; SWAN 2012
– but s.ll the same old pipes!
Ohio Jul 2013 London Feb 2013
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Connec.ng the water industry to an Internet of Things?
Integra.on of M2M and White Space to create smart water systems.
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1854 – the 1st big data app in water • John Snow, grandfather of drinking water
• Broad street cholera outbreak
• Iden.fied importance of primary sanita.on and link to health.
• Led to Sewerage system and wastewater networks
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New technology || New possibili.es
1851
2013 34th America’s Cup
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The world is changing rapidly...
6
SCADA -‐ Hierarchical -‐ Proprietary -‐ Bespoke
Networks -‐ Interconnected -‐ Mul.-‐vendor -‐ Standardised
• Distribu.on networks
• Supply-‐chains • Specialist Service
providers • Customers
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Integra.ng separate data resources
SCADA Real-‐.me opera.onal control and automa.on
Business Systems Enterprise asset management
People Unstructured data (knowledge assets)
Pinsent Masons: Wet Wednesday, 26 June 2013 7 Copyright © 2013 Aquama.x Limited. All
rights reserved.
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Standards – a key enabler 8 Global Standards 7 Na.onal Standards 6 Company Policy
5 Business logic Op. Rules
3 Syntax Unicode 2 Network TCP, XMPP, MQTT 1 Connec.on IP/Modbus
4 Seman.cs Meaning of data
NIST SGiP
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Applica.ons Framework
Enterprise IntegraBon
Decision-‐ support systems
S Sensors
A
Actuator Models
CommunicaBon Protocols
Performance Metrics, KPIs
VisualisaBon
GIS Customer
Real-‐Bme control
LEGACY
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Powered by Standard Apps
SaaS -‐ SCADA as a service
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WaterWorX IOT Stack
WaterWorX NoSQL Graph DB
WaterWorX TOOLS
SWIM SemanBc Interoperability Model
Apps
WaterWorX SaaS model
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Apps:
Demand curve
Energy Tariff
Pump curve
System Curve
F P
F P
Pump schedule
L
E
E
• Pumping energy management
• 3% of UK energy demand
• Lowest cost/risk scheduling • Performance benchmarking
• Demand response
• Integrated tools
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A B
C
L
D
L L
L
I Interoperable Variables
L Local Variables
Interoperability
Condi.on-‐based Maintenance
Hydraulic Model Flow & pressure sensors
Pump controllers
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Wireless Communica.ons networks • GSM – Requires medium power – Designed for high data-‐rates – Too costly for ubiquitous sensors – High frequency = poor range/penetra.on – Congested when scaling – Asynchrounous
• Whitespace (Weightless) – Ultra-‐low power, 5yr bakery – Low-‐frequency 470mHz = 2-‐5km range + good penetra.on
– Low-‐cost, 1/20th GSM cost – Scalable – 100,000 nodes
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Why IoT in water? • Improved energy efficiency • Efficient deployment of labour • Predic.ve asset health & condi.on monitoring • Extend asset life and func.on • Fewer failures = higher availability (measurable) • Improved service standards • Water quality monitoring – safety & security