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goodXense sensor framework for smart city
- 1. Framework for Smart Cities George Lu & YJ Yang www.goodXense.com
- 2. IoT Use Cases in Smart City Infrastructure Smart energy grid Smart water grid Structural health Transportation Asset tracking/management 2
- 4. Many Unsafe Bridges 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) 4
- 5. Why Not Real-Time Monitoring? Expensive instrumentation Expensive cabling for data telemetry Expensive cabling for power supply Large amount of data >US$200,000 per site 5
- 6. Technical Aspect of SHM 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 6
- 7. Business Aspect of SHM 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 7
- 8. What We Had Done • 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 8
- 9. How to Value a Safe Bridge? 9 Antennae Main chassis (Inclinometers Accelerometers) Water Velocity sensor Water Level sensor Much lower cost → Wider deployment → Safer public infrastructure Temperature sensor
- 10. Need for Quantitative and Qualitative Monitoring of Water • 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 10
- 11. Benefits of Water Infrastructure Monitoring • 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 11
- 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” Inability to Enforce Regulations Without Real-Time Monitoring 12
- 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 Our Model: Smart Water Grid Edge Sensors 13
- 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 Our Model: Smart Water Grid Web Services 14
- 15. Example: Water Quality Credit Trading Economic incentive for compliance and reuse. Wider adoption will require common monitoring framework. Monitoring Enables Carrots and Sticks 15
- 16. Webservices Analytics Event Management API Public/Private Networks Water Grid Electrochemical Optical Submeters Water level Water velocity Civil Structures Vibration Tilt Transportation Traffic flow Parking Access control Emission control Licensing Energy Grid Submeters Our Model: A Common Smart Sensor Framework 16
- 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 Event Detection & Analysis 17
- 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 Work Flow 18
- 19. Citizen Access • 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 19
- 20. Conclusion • 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 20
- 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 21