Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Big Data Analytics for the Industrial Internet of Things

7,849 views

Published on

Big Data Analytics for the Industrial Internet of Things

Published in: Internet

Big Data Analytics for the Industrial Internet of Things

  1. 1. Big Data Analytics for the Industrial Internet of Things Shyam V Nath Principal Architect SF IoT unConference Aug 16, 2014
  2. 2. Agenda • Introduction to Industrial Internet • Industry Landscape 2 • Internet of Everything • Internet of Your Things • Smarter Planet • Industrial Internet • Machine Data and Big Data Analytics • Use Cases • Wrap up
  3. 3. About Shyam • Principal Architect – Analytics • Board of Director (SIGs), 30K+ member User Group 3 (IOUG) • Started the IoT/ Industrial Internet Meetup in East Bay in June 2014, started other BI/Analytics related user groups • Worked in IBM, Deloitte, Oracle and Halliburton, prior to GE • Under grad from IIT (India), MS (Computer Science) and MBA (FAU) • Regular speaker in large events like Oracle Openworld, Collaborate, BIWA Summit on IoT, Business Analytics and Data Warehousing / Engineered Systems related topics
  4. 4. The Hype Cycle – Gartner July 2013 The 2013 Hype Cycle features Internet of Things, machine-to-machine communication services, mesh networks: sensor and activity streams. 4 http://www.gartner.com/newsroom/id/2575515
  5. 5. Preview of 2014 – Hype Cycle 5 “…the strongest advantage to early adopters and fast-followers is when the technology is still on the Hype Cycle.” https://www.gartner.com/doc/2816917?plc=ddp#a209530438
  6. 6. Hype Chart 2014 – Hot-off the Press! 6 http://www.gartner.com/newsroom/id/2819918
  7. 7. What is IoT? 7
  8. 8. Big Data and IoT 8 ERP/CRM
  9. 9. Value Creation by Industrial Internet 9
  10. 10. The value to customers is huge Connected machines and data could eliminate up to $150 billion in waste across industries 10 Industry Segment Type of savings Aviation Power Healthcare Rail Oil and Gas Estimated value over 15 years (Billion nominal US dollars) $30B $66B $63B $27B $90B Commercial Gas-fired generation System-wide Freight 1% fuel savings Exploration and development 1% fuel savings 1% reduction in system inefficiency 1% reduction in system inefficiency 1% reduction in capital expenditures Note: Illustrative examples based on potential one percent savings applied across specific global industry sectors. Source: GE estimates
  11. 11. Industrial Internet: Big Data Analytics 11 Delivering sharper insights to users Ingest massive volumes of data – with parallelization Bring analytics to data – and vice versa Elastically execute on large-scale requirements Innovative analytics models Various data sources Enterprise (operational and business) Data, Industrial Data & External Data
  12. 12. Examples from Different Domains America’s Cup: Yacht as a “Thing” embedded with sensors 12 Ref: http://medianetwork.oracle.com/video/player/3597777548001
  13. 13. Different “Views” of Aircraft - as collection of sensors 13 http://www.flightglobal.com/cutaways/civil/phenom-300/
  14. 14. Aviation and Big Data “GE expects the data collection to grow to 10 million flights and 1,500 terabytes of full flight operational data by 2015.” 14
  15. 15. 15 © General Electric Company, 2013. All Rights Reserved. Data from Jet Engine
  16. 16. 16 Wind Farms Explained Via Visuals! 1
  17. 17. More Efficient Alternative Sources of Energy Energy: Devices can adjust the speed and blade pitch of wind turbines to improve efficiency and reduce wear.
  18. 18. 18 1
  19. 19. Smarter Supply Chain • Transport refrigeration based on ambient Temperature • E.g. pre-cool the truck if driving through Arizona in summer 19
  20. 20. 20 Copyright © 2014 by United Feature Syndicate
  21. 21. HealthCare Remote monitoring of Patients, e.g. pregnant ladies with gestational diabetes in a town with no doctors. Glucose level can alter blood pressure. Monitoring of blood pressure via wearable that can be transmitted to health care monitoring facility that can route the nearest ambulance. (Uber!!!) Hospital / doctor is ready for the patient by the time patient arrives. 21 Ref: http://medianetwork.oracle.com/video/player/3597777548001
  22. 22. From Home to Hospital 22
  23. 23. Smarter Transportation Infrastructure 23
  24. 24. Smarter Grid and Homes 24 http://www.oracle.com/us/solutions/internetofthings/overview/index.html?ssSourceSiteId=ocomtr
  25. 25. Chicago turns light poles into data collectors 25 The "Array of Things" initiative by the Urban Center for Computation and Data will install data-collecting systems on eight light poles along Michigan Avenue next month, the Chicago Tribune reports. The sensors will be used to measure air quality, heat, light intensity, precipitation, sound volume, and wind. The number of people near the light poles will also be measured by tracking wireless signals from mobile devices. The light poles along Chicago's Michigan Avenue will soon do more than illuminate the city's famous street. http://www.smartplanet.com/blog/bulletin/chicago-turns-light-poles-into-data-collectors/
  26. 26. 26
  27. 27. 27
  28. 28. Other Innovations Driven by IoT A Batteryless Sensor Chip for the Internet of Things Requiring so little power means PsiKick’s chip can function even with the small amounts of power that can be scavenged without using a battery. Wentzloff and Calhoun have tested their chip design in a wearable EKG monitor that runs entirely on body heat. The device required 0.1 percent of the power consumed by a typical EKG monitor, Wentzloff says. In the future, the energy could come from a small solar panel; an antenna that collects ambient radio wave energy; a thermoelectric material that absorbs body heat; or piezoelectric devices that collect energy from movement. MIT http://www.technologyreview.com/news/529206/a-batteryless-sensor-chip-for-the-internet-of-things/ 28
  29. 29. 29 © General Electric Company, 2013. All Rights Reserved.
  30. 30. The Industrial Evolution 30 http://www.gereports.com/connected/ Electric Power Turbine data
  31. 31. 31 Cloud for efficiency and agility Going mobile: anytime/ anywhere Access End-to-end Security Predictive insights from Big Data Transition to “Brilliant machines” Cloud based Integrated Asset Management Industrial Internet computing requirements 021010308 013161090 040109010 104078050 Consistent and meaningful User experience
  32. 32. 32 Apply Batch or Real-Time Analytics to the Machine-Generated Data © General Electric Company, 2013. All Rights Reserved.
  33. 33. Architecture of Industrial Internet Analytics http://www.windriver.com/iot/use-cases/WR-IoTUseCase-AdaptiveAnalytics.pdf 33
  34. 34. Q&A Shyam Nath Shyam.Nath@GE.com Thank You!

×