IoT Primer: Transforming Data into Business Insights
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Given at Energy Huntsville Tues 15 Dec 15
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IoT Primer: Transforming Data into Business Insights
- 1. IoT Primer Stephen Bates seb@osisoft.com | +1 202-730-9760 http://www.linkedin.com/in/batess Energy Huntsville: Tues 15 Dec 2015 1
- 2. How complex would your business be without data?
- 3. What if you couldn’t understand your data?
- 4. The Industrial Internet of Things 4 “ The Industrial Awakening will generate $14.2 trillion of global output by 2030. ” KleinerPerkins “75 Billion Devices Will Be Connected To The Internet Of Things By 2020” MorganStanley 40% of the IoT’s total potential economic value can be unlocked only by solving interoperability challenges. ~McKinsey 2015
- 5. Citing my sources • Intelligence Business Insider • Vendor Competitive Intelligence • Gartner: Internet of Things • Verizon: Internet of Things 2015 • Cisco: Internet of Everything • Harvard Business Review • Deloitte University • Mary Meeker Internet Trends Report, Kleiner-Perkins • Mobile World Congress 2015 • O’Reilly SOLID • Interviews with trusted authoritative data sources 5
- 6. Glossary…. • Internet of Things: A network of internet-connected objects able to collect and exchange data using embedded sensors. • Internet of Things device: Any stand-alone internet- connected device that can be monitored and/or controlled from a remote location. • Internet of Things ecosystem: All the components that enable businesses, governments, and consumers to connect to their IoT devices, including remotes, dashboards, networks, gateways, analytics, data storage, and security. • Entity: Includes businesses, governments, and consumers. • Physical layer: The hardware that makes an IoT device, including sensors and networking gear. • Network layer: Responsible for transmitting the data collected by the physical layer to different devices. 6
- 7. Glossary continued… • Application layer: This includes the protocols and interfaces that devices use to identify and communicate with each other. • Remotes: Enable entities that utilize IoT devices to connect with and control them using a dashboard, such as a mobile application. They include smartphones, tablets, PCs, smartwatches, connected TVs, and nontraditional remotes. • Dashboard: Displays information about the IoT ecosystem to users and enables them to control their IoT ecosystem. It is generally housed on a remote. • Analytics: Software systems that analyze the data generated by IoT devices. The analysis can be used for a variety of scenarios, such as predictive maintenance. • Data storage: Where data from IoT devices is stored. • Networks: The internet communication layer that enables the entity to communicate with their device, and sometimes enables devices to communicate with each other. 7
- 8. Cloud, Mobility, Social, Big Data, Analytics Millennials, blah, blah, blah… 8
- 9. IoT will significantly affect every vertical •Agriculture •Connected home •Defense •Financial services •Food services •Healthcare •Hospitality •Infrastructure •Insurance •Logistics •Manufacturing •Oil, Gas, and Mining •Retail •Smart buildings •Transportation •Connected car •Utilities 9
- 10. Gartner Internet of Things Hype Cycle 10
- 11. Wearables will get the most press…. 11
- 12. 1957: 13 men delivering a computer 2017: a person may wear 13 computing devices ~ 2015 Mobile World Congress 12
- 13. Parking is a great IoT example •Parking availability IoT •Networked sensors •Mobile payments vs coin •Auto-updates boards, smartphones •Usage metrics 13 * SFO car rental 37/day. SF hotel parking 54/day.
- 14. Internet Trends for 2015 – Mary Meeker typically released end of May • Focus on findable and shareable data, generated by mobile devices and sensors • 5 platforms, photo sharing quadrupled over last year…set to rise by 600M per day from 1.2B to 1.6B • Fitness tracking: 47B steps 2013 to 2.4T in 2014 • 800M swipes per day on Tinder 14 ….As well as being uploadable and sharable, the data is findable. That means it can be mined, and "has potential to yield patterns that help solve basic [or] previously unsolvable problems, but create new challenges related to individual rights".
- 15. What can sensors measure? • Position • Occupancy and Motion • Velocity and Acceleration • Force (tactile and threshold) • Pressure (force per unit) • Flow (volume and rate) • Acoustic (digital or analog) • Humidity (absolute/relative) • Light • Radiation • Temperature • Chemical (type/concentration) • Biosensors (enzymes, acids..)
- 16. 16 Businesses -- not consumers, will be biggest adopters of the IoT
- 17. 4 Factors Propelling IoT Growth • Expanded Network Connectivity (WiFI/Cellular) • High Adoption Rates of Mobile Devices • Lower cost sensors • Large amount of corporate/government IoT investment 17
- 18. 4 Barriers to IoT Growth • Security/Trust • Privacy Concerns • Large scale implementation challenges (cost/benefit) • Technological fragmentation 18
- 19. System view Enterprise insight Individual view Group insight Real-time Decision Support Business/Operational Intelligence Operation & Bus. insight Local view $ Transform Data Information Intelligence Transform Transform 19 Transforming the Value of Data from IoT
- 20. Context is everything: scale and insight 20 Time-series data • Temperature • Pressure • Flow Process • Well drilling • Metering • Site load Asset details • Name • Model • Manufacturer Operational Context High Value Insights Require Data Context Which asset performs best? Which conditions are optimal? What are the indicators of failure? What leads to unsafe conditions? What causes quality issues?
- 21. Can you see the problem? 4:30 1766.807 1770.041 1735.584 1712.094 1748.954 1760.249 1756.513 1746.813 1751.224 4:45 1782.593 1783.582 1740.005 1713.625 1763.2 1776.202 1772.523 1762.432 1765.907 5:00 1804.619 1804.311 1753.202 1722.105 1782.787 1798.3 1796.214 1783.199 1785.155 5:15 1851.697 1851.983 1775.265 1738.878 1833.121 1848.069 1846.02 1832.959 1832.181 5:30 1891.173 1889.403 1791.779 1749.428 1874.77 1890.169 1887.194 1871.383 1867.261 5:45 1918.68 1914.849 1803.538 1749.229 1901.105 1913.318 1905.974 1891.461 1883.946 6:00 1927.751 1928.128 1797.334 1736.343 1917.293 1927.759 1919.787 1900.453 1889.87 6:15 2001.637 2003.804 1827.463 1753.16 1994.741 2006.415 1996.289 1975.221 1958.406 6:30 2054.95 2058.036 1848.321 1764.349 2050.196 2060.041 2051.025 2028.24 2008.001 6:45 2112.258 2103.88 1872.549 1778.843 2095.131 2102.328 2094.292 2072.529 2050.109 7:00 2160.629 2137.386 1888.932 1790.602 2135.888 2143.732 2138.594 2116.436 2091.379 7:15 2232.516 2211.839 1943.359 1834.518 2220.943 2225.654 2219.614 2192.266 2166.789 7:30 2267.812 2254.537 1978.218 1865.147 2270.142 2268.746 2261.528 2233.358 2211.937 7:45 2294.774 2288.251 2006.233 1889.359 2308.142 2303.487 2294.172 2266.28 2249.907 8:00 2325.94 2322.89 2040.28 1920.23 2345.282 2336.993 2324.838 2299.474 2286.259 8:15 2370.621 2371.534 2099.076 1970.189 2400.857 2389.888 2377.086 2352.518 2342.512 8:30 2398.012 2401.169 2140.396 2007.306 2437.142 2420.344 2408.794 2385.162 2377.984 8:45 2427.269 2429.596 217.261 2038.443 2468.24 2449.527 2436.273 2415.056 2409.495 9:00 2452.356 2457.249 2208.352 2074.063 2499.239 2478.301 2465.481 2444.879 2441.46 9:15 2490.627 2502.216 2255.25 2117.835 2544.785 2520.463 2509.126 2488.076 2487.573 9:30 2521.597 2540.463 2288.521 2151.365 2584.2 2557.204 2550.518 2526.244 2525.164 9:45 2551.844 2575.42 2321.138 2182.995 2621.057 2593.661 2588.434 2561.901 2560.209 10:00 2588.298 2611.475 2350.499 2213.857 2655.357 2626.772 2622.822 2596.66 2594.748 10:15 2619.03 2650.911 2388.768 2256.956 2699.702 2668.777 2666.828 2638.944 2637.933 10:30 2645.652 2678.506 2411.097 2283.247 2724.45 2695.779 2698.503 2667.695 2667.878 10:45 2668.184 2703.642 2430.173 2307.043 2749.066 2720.254 2725.196 2691.454 2693.37 11:00 2682.564 2718.079 2442.608 2324.405 2763.242 2733.837 2741.958 2709.303 2710.661 11:15 2705.387 2736.648 2461.428 2349.543 2780.964 2750.594 2762.598 2728.487 2728.311 11:30 2715.591 2742.262 2472.007 2365.656 2788.949 2764.653 2778.697 2743.69 2742.778 21
- 23. The right visualizations make information consumable 23 Operational Process Geospatial
- 24. 1% 12% 13% 15% 22% 23% 24% 25% 29% 31% 34% 46% Do Not Know Time To Market Interorganizational Collaboration Data And Physical Security Employee Satisfaction Innovativeness Revenue Growth Profitability Strategic Decisionmaking Intraorganizational Collaboration Customer Service Operational Efficiency Business Benefits of IoT? Source: Cisco, Business Intelligence
- 25. Nearly All Industries Will Benefit, But Early Adopters Are In Logistics … Source: BI Intelligence Estimates $- $40 $80 $120 $160 Professional, Scientific, And Technical Services Construction Real Estate And Rental And Leasing Mining Utilities Finance and Insurance Retail Trade Health Care And Social Assistance Wholesale Trade Information Transportation And Warehousing Manufacturing Billions Top Industries With Investments In IoT Solutions 2014E 2015E 2016E 2017E 2018E 2019E Source: Cisco, Business Intelligence
- 26. …and Manufacturing Source: SAS 2013 4% 6% 8% 13% 15% 17% 17% 17% 18% Consumer Packaged Goods Consumer Durables Metals and Mining Medical Device/Pharma/BioMed Aerospace & Defense Telecom/High Tech Consumer and/or Industrial Electronics Automotive Industrial Machinery Which Industries Are Early IoT Adopters? Source: Cisco, Business Intelligence, SAS 2013
- 27. ~1/4 Of Executives Want The IoT To Help Them Manage Plants, Property, & Equipment Source: Harvard Business Review 2014 19% 21% 22% 23% 36% Fleet Management Condition-based Monitoring Energy Data Management Security Remote Asset Management And/Or Asset Tracking Areas For IoT Business Deployment In Next 18 Months Survey Of Executives Source: Harvard Business Review 2014
- 28. Manufacturers See The IoT As A Way To Keep Factories Running Smoothly Source: SAS 2013 6% 19% 27% 30% 49% 62% Support Sales Gain Insight Into New Opportunities Deliver System Upgrades Better Understand Product Use Maintain and Repair Products Monitor Product Performances How Are Manufacturers Using IoT Sensor Data? Global Companies Source: Business Intelligence, SAS 2013
- 29. Thoughts on the IoT • Cloud Enables Big Data ….which is generated from multiple sources, humans, computers, sensors, beacons, IoT • Big Data enables Analytics ….if it is secure and the data can be trusted. • Analytics transform business and provides competitive advantage …enabling speed to the right decisions, via human or machine 29
- 30. 30
- 31. Human or machine decisions? 31
- 32. 400+ Pulp & Paper sites deployed worldwide 91% 100% of the Global Fortune Top 10 Metals & Mining companies 37 of 50 of the World’s Largest Chemical & Petro- Chemicals 9 / 10 of the Global Fortune Top 10 Pharma companies Over 1,000 of the world’s leading Power & Utilities companies 95% of the Global Fortune Top 40 Oil & Gas companies For 35 years, the world’s leading companies have trusted OSIsoft and the PI System Stephen Bates seb@osisoft.com +1 202-730-9760 Slides posted > http://www.linkedin.com/in/batess
Notas do Editor
- Complexity without data
- Cldnt read data
- Human barriers Tool barriers Technology barriers Physical barriers
- A Critical capability of an Infrastructure is adding context. With context data is truned into information that can be more readily shared and utilized for decisions. By adding context you increase the business value of the decisions that can be made You can compare assets for asset intelligence You can compare assets and processes for process intelligence You can compare processes operation intelligence across the organization With context multiple streams of similar data can be combined together for analysis. Data that might show how one asset compares to another, or how one process is better than another. If context is not there it will be difficult to interpret the data and most importantly organizations run the risk of combining data that is out of context and drawing the wrong conclusions. For instance unknowingly comparing a sensor based data stream from: An asset in a different process under different locations An asset from another manufacture
- To see the power of having the right visualization, let’s take a look at what we’ve got here. We have several readings here at 15 minute intervals for a couple data streams. But here’s the question— Can you see the problem? (pause here for 5 seconds)
- How about now? (pause 1 second) This is the same information, but now in a trend format. Now the problem is obvious and you can spot it right away, even if you’re sitting in the back of the room, and now that we are aware, we can do something about it and dive in for further analysis.
- The key take away is that the right visualization makes information consumable. This may mean that you want a quick dashboard in PI Coresight with an operational view that includes bar graphs and radial gauges. Or you might prefer a process view with PI ProcessBook so that you can view your information in a way that matches your plant floor or maybe your operators’ SCADA screens. You can see the readings as they feed into each other and visualize the information in the context of interdependencies. Or maybe a geospatial view that puts your data on a map. With this view, you can identify things like all assets in the northern area being out, or perhaps that you should send the maintenance crew out from a different shop given current traffic patterns. Putting information in the right format is key to rapid, high quality decision making.