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T sensor summit-emerging iot usages & apps for trillion+ sensors-sandhi bhide-tokyo, japan-feb20-21,2014
- 1. Slide 1 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Emerging IOT Usages & Apps for Trillion+ Sensors Sandhiprakash Bhide, Strategist and Technologist, Intel Corporation Trillion Sensors Summit Japan 2014 February 20-21, 2014, Tokyo Japan
- 2. Slide 2 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 2 “We are at an inflection point in the history of Data and Computing. For the last 66 years since ENIAC, Data has always come to Computing. Not so going into the future. In the future, Compute will have to go where Data is. The future is about scaling and about distributed Intelligence. We neither have enough wireless bandwidth and spectrum to push data up from 50B Devices and 1 Trillion+ Sensors nor does it make economic sense to send senseless bits up the channel” - Sandhiprakash Bhide
- 3. Slide 3 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 3 Grand Challenges for Engineering in 21st Century Make Solar Energy Economical Provide Nuclear Fusion Energy Develop Carbon Sequestration Method Manage the Nitrogen Cycle Provide access to Clean Water Reverse Engineer the Brain Advance Health Informatics Engineer better Medicines Engineer the Tools of Scientific Discovery Restore/Improve Urban Infrastructure Advance Virtual Reality Advance Personalized Learning Prevent Nuclear Terror Secure Cyberspace/Internet Invest in Biotech/ Stem Cell Research 50B Devices 50B Devices 1T Sensors + 50B Devices and 1T+ sensors can help address these challenges
- 4. Slide 4 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 4 Clarifying Definitions: Embedded, Machine to Machine (M2M), and Internet of Things (IOT*) *Alternate names for IOT = Web 3.0, Intelligent Systems, Sensor Networks, Internet of Everything, Web of Things, Ubiquitous or Ambient Computing IOTIOT System of systems working together connected via Internet driving combinatorial analytics System of systems working together connected via Internet driving combinatorial analytics IOT System of systems working together connected via Internet driving combinatorial analytics M2MM2M Intelligent/flexible wireless or wired systems interconnected with each other for a specific app e.g. parking Intelligent/flexible wireless or wired systems interconnected with each other for a specific app e.g. parking M2M Intelligent/flexible wireless or wired systems interconnected with each other for a specific app e.g. parking EmbeddedEmbedded Computer system with a dedicated function within a larger system, often with real-time constraints Computer system with a dedicated function within a larger system, often with real-time constraints Embedded Computer system with a dedicated function within a larger system, often with real-time constraints
- 5. Slide 5 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 5 Definition Clarification Usage = How the system or product is utilized by the end-user for a particular purpose or need App: program or group of programs designed for end users Multi-vitaminTylenol Usages Technologies
- 6. Slide 6 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 6 IOT Usages & Apps: Story of OC44 Transistor
- 7. Slide 7 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 7 Types of IOT Usages Planet • Global Warming • Earthquakes • Health Epidemics • Green House gases • Glacier Monitoring • Ocean Health • Nuclear Threat Monitoring Work/Industry On-the-go • Global Warming • Earthquakes • Health Epidemics • Ecology • Infrastructure Health • Ozone Monitor • Forest Fires • Air Pollution • River Mgmt. • Smart Grid Mgmt. • Govt. Bldg. Security • Fleet Management • Healthcare Mgmt. • Actuator Mgmt. Nation • Micro-climate • Parking • Transportation • Air Pollution • Noise Pollution • Traffic Mgmt. • Waste Mgmt. • Water Mgmt. • Industrial Control • Vehicles Mgmt. • Healthcare City/ Neighborhood Family/ Home • Refrigerators • Ovens • HVAC • Water • Electricity • Health • Utilities Usage • Appliance Mgmt. • Home Security • Home Monitoring • Patient Monitoring • Smartphones Personal Management • Coffee maker • Alarm Clock • Electric Toothbrush • Smart Scale • Automobiles • Calendar Mgmt. • Transportation
- 8. Slide 8 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 8 Personal Usages Calendar Phone IOT Car Alarm Traffic Toothbrush Scale Coffee-maker
- 9. Slide 9 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 9 Home and Family Usages Home Security IOT Weather Monitor Patient Monitor HVAC Baffles Home Utilities Monitor Phones Oven/Range Refrigerator GE W D WElectricity Water Gas Window Door
- 10. Slide 10 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 10 City Usages Phones Crowd source IOT Traffic Monitor Usage Scenarios • Modes of Transportation • Macro-climate condition • Traffic Routing • Bus Route Optimization • Garbage Collection • Noise/traffic levels near Hospitals • Evaluation route Management • Monitoring of criminals Parking Waste Systems Seismic Monitor Noise MonitorTransportation Air Pollution
- 11. Slide 11 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 11 National Level Usage Forest Fire Global Warming IOT Smart Grid Sensors Usage Scenarios • Health monitoring at Airport Entry • Citizen safety: O3, rain fall, fires • Electricity usage • Infrastructure Monitoring • Monitoring rainfall, river flows, icecap melts, volcanic activity, forest fires • Cross-agency cooperation River Flow Monitor Infrastructure Health Ozone Cyber/Govt. Security Health Epidemics
- 12. Slide 12 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 12 Planet Level Usages Asteroid IOT Ocean Health Usage Scenarios • Prediction of storms, hurricanes,… • Health Epidemics • Nuclear tests and proliferation • Monitoring magnetic storms • Measurement of UV radiation Sustainable Environments Greenhouse gases Glaciers Tsunami Nuclear Control Smart Health
- 13. Slide 13 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 13 Drivers for the Growth of IOT Apps • Connected Device Growth • Real Time Data Growth (Sensors) • Growth of Verticals • Intra-vertical Traffic (M2M IOT) • Larger Storage • Larger Investments in Data networks + Technology
- 14. Slide 14 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 14 Where is growth of IOT App come from? 1. Data Manipulation 2. Security, Privacy, and Identity Protection 3. Management of IOT Devices 4. Actuator Control 5. Trend Development (Temporal Analysis) 6. New IOT Verticals 7. Integration of Verticals 8. Consumer Apps/Service 9. Analytics Critical item across the board: Analytics
- 15. Slide 15 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 15 List of Applications is endless • Smart parking • Infrastructure Health • Noise Pollution Control • Crowdsourcing information for Smartphones • Detecting pollution levels • Waste management • Smart Urban Planning • Sustainable Urban Environment • Smart Medication • Aging Population • Continuous Care • Emergency • Intelligent Commuting • Smart Product Management • Smart Meters and Metering • Home Automation • Management of renewable energy • Smart Farming • Smart Animal Farming • Handling Emergency • Health care • Smart Events • Health and Beauty Choices • Smart Food and Drink Choices • Logistics • Intelligent Shopping
- 16. Slide 16 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 16 Apps Hierarchy in the IOT Continuum Sensors Data Information Knowledge Wisdom X, Y, Z coordinates from a GPS John goes to Starbucks three/week Starbucks Near the Hotel in NY There is Starbucks at this location Node Edge Backend/Cloud E2E Security Privacy, Identity Safety Analytics
- 17. Slide 17 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 17 Sensor Data to Information Accelerometer, Audio, Video, Vibration, Seismic, Environmental, Health, CO2, O3, HC Std. Dev., Mean, Max, Min, GSR/HR* Features, Color, BW, Dynamic Range, Angle, Contours Decision Tree, GMM*, kernel Machine, Bayesian Net, Sparse Bundle Adjustment Running, Sitting, Walking, Stressed, Relaxed, Startled, Worried, Chatting, Commuting Node/Security Raw Sensor Data Feature Extraction Classification Inference Sensors Data Information Knowledge Wisdom *GMM: Gaussian Mixture Model, HR: Heart Rate, GSR: Galvanic Skin Response
- 18. Slide 18 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 18 From Information to Knowledge Sensors Data Information Knowledge Wisdom Edge Operating System Connectivity Software Complex Inferencing Engine including Contextual and Temporal Analytics and Predictive software Data Storage Dat Filtering Algorithms Security, Privacy, Identity, and Safety M2M Focus Critical item across the board: Analytics
- 19. Slide 19 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 19 From Knowledge to Wisdom Sensors Data Information Knowledge Wisdom Operating System Connectivity Software Highly Complex, combinatorial Analytics Large Mirrored Data Storage and systems Data Filtering Algorithms Security, Privacy, Identity, and Safety Backend/Cloud IOT (system of systems) Critical item across the board: Analytics
- 20. Slide 20 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 20 Conclusion • IOT App opportunity space is humongous (100M?) • The amount of data generated from 50B devices and 1T+ sensors will be massive • The data must be reduced to information at the generation node to reduce large data overload • The IOT technologies and apps must address IOT usages and deliver expected User Experience • Security, Privacy, and Identity need to be designed in from day 1
- 21. Slide 21 Sandhiprakash Bhide– Intel Corporation, TSENSOR SUMMIT, Trillion Sensors Summit, Tokyo Japan 2014 Slide 21 Thank you