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Internet of Things (ruSMART 2013, St. Petersburg)


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Internet of Things: The foundational infrastructure for a smarter planet …

Internet of Things: The foundational infrastructure for a smarter planet

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  • 1. IBM Institute for Business Value Rob van den Dam, Global Telecommunications Industry Lead IBV Internet of Things: The foundational infrastructure for a smarter planet 28 August 2013 © 2013 IBM Corporation
  • 2. IBM Institute for Business Value The emerging Internet of Things attracts many players 2 IBM Confidential © 2013 IBM Corporation
  • 3. IBM Institute for Business Value Smarter Planet is IBM’s #1 research focus Dublin Research Labs Almaden c  Big Data & Analytics  Storage  Nanotech Healthcare Smarter Cities Industry TSL Russia Solutions Labs(Moscow Satellite TSL) Web Services TSL China & Research Lab c Watson TSL Israel &  Semiconductors Research Lab  Systems (Haifa Satellite TSL)  Software & Services TSL Europe (La Gaude &  Big Data & TSL North America Montpellier, France) Research Lab Analytics (Austin, Texas) (Beijing) Japan  Internet of Things  Smarter Cities (Tokyo Satellite TSL) (New Delhi) TSL India (Bangalore Satellite TSL) ASEAN (Kuala Lumpur Satellite TSL) TSL LATAM Centers of Excellence 3 (Sao Paulo, Brazil Satellite TSL) Institute for Business Africa South (Johannesburg, Satellite TSL) Value Worldclass Partner Ecosystem © 2013 IBM Corporation
  • 4. IBM Institute for Business Value Internet-of-Things (IoT) provides the foundational infrastructure for a smarter planet ….  Hyper-growth of instrumented devices for sensing the world  The infrastructure to connect the devices, manage the sensor data and devices, and enable intelligence at edge and in data center  Significant growth opportunities for end-to-end infrastructure and services 50 Billion 50 40  Safety and reliability of physical infrastructure 30  Efficient asset utilization and management 20 15 Billion 10 Why IoT is needed? (SERCQ)  Reduction of energy and 7 Billion resources  Comply with regulation 2010 2015 2020  Quality of service and life Number of Connected Devices Multiple Sources: Intel, Ericsson, Gartner, etc. 4 © 2013 IBM Corporation
  • 5. IBM Institute for Business Value ..and differs from the Web on many aspects End Point IP based servers/PC/mobile devices, resource rich, human engaged on device Geo-distribution Outside data center, unmanned area Data center centric, manned Communication Pattern Uplink intensive, relative fixed access pattern, burst means important event Downlink intensive, flexible access pattern Data 10-100X volume of transactional system; numeric & multimedia; 24*7 continuous data streams; noisy sensor data Human generated content, Text, XML are popular; QoS and Reliability Stringent if managing mission critical physical infrastructure Best effort Cyber v.s. Physical 5 Not necessary IP based, heterogeneous devices, constraint resource, no human engaged Cyber & physical, influenced by physical world behavior model Cyber mainly © 2013 IBM Corporation
  • 6. IBM Institute for Business Value IBM works on a number of top challenges in Large Scale IoT systems   Sense the impossible before Higher sensitivity  Communication  Power  Sensing Distance Reliability   Scale Simulation & Data  Behavior model Testing Reverse workload pattern   Throughput Space & Time Processing Internet of Things    Resource constraint runtime Collaborative intelligence  Management Computing Automated  Intelligent  Edge Scalable Distributed Security   6 End-to-end security with insecure components and environment Resource constraint © 2013 IBM Corporation
  • 7. IBM Institute for Business Value As an example: challenges in communications include spectrum, power and inference issues Existing spectrum allocation for smart grid application in China SPECTRUM CRISIS Power 10 groups for single direction mode 15 groups for UL 15 groups for DL • Spectrum is SCARCE 150KHz • Fast grow traffic requires more spectrum 150KHz MHz Source: US FCC 223.525 …... 224.650 228.075 …... 228.750 230.525 …... 231.650 Frequency POWER • Communication is power intensive • No external power supply in certain domain RF is the BIGGEST portion of energy consumption of wireless sensors More frequent communication, more percentage, energy consumed by RF INTERFERENCE 1) Multiple Interferences • Spectrum sharing 2) Working with certain periods • Large Machinery 3) Unknown signals existed in the same band Spectrum Environment in Shanghai 7 Large machinery in mines, oil fields, etc. © 2013 IBM Corporation
  • 8. IBM Institute for Business Value These challenges are addressed by IBM’s wireless M2M Platform, based on IT-based software defined radio technology Data Center Technical Features IoT Infrastructure Management & Operation Control Center Monitoring & Control • E2E SDR technology for high flexibility Command Center Simu IoT Infrastructure Manager Communication Server SDH/SONET IoT Edge Appliance Substation • Optimized WiMAX-EXT for stable wireless communication • Optimization for spectrum and power consumption • Open IT platform for services and application injection Substation 3G/4G 3G/4G Wireless Wireless IoT Access Appliance IBM Research is leading the technology of IT-based Softwaredefined radio in the world • Collaboration with top operators, e.g. China RS232/ETH Mobile, SK Telecom • Successful demo in global industry events Feeder Terminal Unit Transmission Transformer Terminal Unit Feeder Terminal Unit Distribution Transformer Terminal Unit Consumption Tech Park Petrol/Chemical Pipe Airport © 2013 IBM Corporation 8
  • 9. IBM Institute for Business Value Four key Technologies IBM is working on are key for Internet of Things Natural Language Analytics DeepQA Data Program Cognitive Computing “SyNAPSE” Learn Big Data: Realtime Inference & Knowable Future 1,000,000X Workload Optimised Systems 1,000X Silicon Devices Nano 1 Billion Scale Transistors 1,000X 9 Exascale Software Defined Environments Nano Systems 1 Trillion Devices © 2013 IBM Corporation
  • 10. IBM Institute for Business Value Cognitive computing aims to evolve to entirely new computing architectures and programming paradigms. Current Specific questions Future Statistical analytics Rich problem scenarios Interactive dialogue Continuous learning Evidence profiles This poet wrote to a friend, “We are by September and yet my flowers are as bold as June. Amherst has gone to Eden.” Batch training 10 Statistical ranking © 2013 IBM Corporation
  • 11. IBM Institute for Business Value Cognitive computing will be central to many future applications Watson Five-in-Five Cognitive Sensing Technology: • Hearing and voice recognition • Extracting knowledge from pixels • Sniffing for healthiness • Haptic technology for retail • Healthier molecular based recipes Sensor Networks / Internet of Things Infrastructure Grids Buildings Hearing Sight Smell Taste Touch Social Business Human and knowledge capital analytics TM Metering Vehicles Billions of end points 100K+ elements,10ms latency Multiple feedback time-scales 11 © 2013 IBM Corporation
  • 12. IBM Institute for Business Value From research - to battling humans on Jeopardy! - to changing the way the world thinks, acts and operates IBM Research Project (2006 – ) Jeopardy! Grand Challenge (Feb 2011) Watson for Healthcare (Aug 2011 –) Watson for Financial Services (Mar 2012 – ) Watson Industry Solutions (2012 – ) Cross-industry Applications Expansion Commercialization Demonstration R&D 12 © 2013 IBM Corporation
  • 13. IBM Institute for Business Value Watson infrastructure comprises a platform with capabilities to address specific smarter planet areas ASK Services NLP & Machine Learning Source 13 Big Data Watson For Financial Svcs. Model Cloud Train Institution Retirement DISCOVER Services Analytics Watson for Industry Advisor Solutions Institutional Technical Knowledge Help Desk Call Center Advisor Solutions Diabetes Cardiac Oncology Utilization Advisor Solutions Watson for Client Engagement Banking Watson for Healthcare DECISION Services Mobile Workload Optimized Systems Learn © 2013 IBM Corporation
  • 14. IBM Institute for Business Value In healthcare, for example, contextual services combine many sources of data to benefit patients and providers Anne’s daughter contacts her inApp PA and requests guidance. From smart device, PA sees Anne’s diabetes, recent long flight and the local weather, determines she is seriously dehydrated, recommends IV rehydration therapy and notifies Wellness program provider. Anne, a 76 year old grandmother, becomes dizzy and faints during an outdoor event in midsummer heat and humidity Wellness program provider engages OTTER to evaluate Anne’s entire medical history. Watson MD notices a cardiac event and congestive heart failure (CHF) 10 years prior. Recommends rehydration therapy only at a cardiac care center due to risk of triggering recurrence of CHF. MD Wellness program provider authorizes fast-tracking Anne through triage directly to the cardiac care unit for rehydration therapy. Nearest cardiac care center location (given current traffic) is forwarded to Anne’s daughter’s vehicle for transport. OTTER Context Value Context Value Context Value Context Value Name Anne Chronic Illness Diabetes Medical History EMR yes Age 76 Travel 3 hrs flight today History of CHF yes Cardiac protocols authorized Location outdoors, Miami, FL Weather conditions 97 degrees, 90% humidity Last CHF episode Aug. 9, 2002 Fast-track triage authorized yes dizzy, fainting Diagnosis Dehydration Closest Cardiac Care location 201 Ridge Rd, Miami, FL Time 3:40 PM Treatment Recommended IV rehydration therapy Risk of CHF recurrence without Cardiac protocols 60% Symptoms Dedicated Traffic delay estimate 10 minutes Wellness Program Provider StayWell Health Insurance Family Support Network Cardiac Care Estimate Time of Arrival 4:30 PM Healthcare PoA Daughter, On file Treatment Location Recommended $1500 yes Nearest Urgent Care center Estimated Cost CC Staff notified Treatment Location Recommended CHF Cost Risk $100,000 Cost Averted $85,000 Estimated Cost $300 14 © 2013 IBM Corporation
  • 15. Today’s environment are making workloads (and Networks) more volatile Volatile workload characteristics result from changing business requirements Traditional Current Future C C W1 W2 W3 W4 V1 V2 V3 V4 V5 … Vn V1 R1 R2 V3 V4 V5 V5 ... …. Vn R3  Few, stable, and well known workloads  Fixed System hardware, manual scaling  Hardwired workload, minimal configuration 15 V2 Source: IBM Global Technology Outlook 2013  Workload virtualized, to cloud  Diverse workload, limited patterns  Homogeneous resource pooling  Expert configuration and mapping of workload  Rapidly changing workloads, dynamic patterns  Dynamic automatic composition of heterogeneous system  Autonomic and proactive management © 2013 IBM Corporation
  • 16. Software Defined Environments provides abstractions of workloads, services and infrastructure and an end-to-end mappings Workload Abstraction Functional and non-functional requirements that may be discovered as well as specified Resource Abstraction Semantically rich abstractions of heterogeneous resource capabilities and system components Mapping to resource Map requirements to potential system architectures. Proactively orchestrate . infrastructure and workload Continuous Optimization Autonomously construct available system architecture to optimize workload outcome Agility Consumability 16 Efficiency © 2013 IBM Corporation
  • 17. IBM Institute for Business Value Summary COGNITIVE SYSTEMS BIG DATA INTERNET OF SDE THINGS CLOUD 17 © 2013 IBM Corporation
  • 18. IBM Institute for Business Value Thank you Rob van den Dam Global Telecom Industry Leader IBM Institute for Business Value 18 © 2013 IBM Corporation