tsensorsummit-emerging iot usages & apps for trillion+ sensors-bhide-stanford, ca, oct25-2013
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~$TSensorSummit-Emerging IOT Usages & Apps for Trillion+ Sensors-Bhide-Stanford, CA, Oct25-2013TRANSCRIPT
Slide 1
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
Emerging IOT Usages & Apps for Trillion+ SensorsSandhiprakash Bhide, Strategist and Technologist, Intel Corporation
Presentation at Stanford University, TSensor Conference
October 25, 2013
Slide 2
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
Trillian+ Sensors nor does it make economic sense to
send senseless bits up the channel”
- Sandhiprakash Bhide
Slide 3
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
Slide 4
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
Slide 5
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
Slide 5
Definition Clarification
Usage is how the system or product is utilized by
the end-user for a particular purpose or need
An application is a program or group of programs
designed for end users
Multi-vitaminTylenol
Multi-vitaminTylenol
Usages Technologies
Slide 6
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
Slide 6
IOT Usages & Apps: Story of OC44 Transistor
Slide 7
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
Slide 8
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
Slide 8
Personal Usages
Calendar
Phone
IOT
Car
Alarm
Traffic
Toothbrush
Scale
Coffee-maker
Slide 9
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
Slide 9
Home and Family Usages
HomeSecurity
IOT
Weather Monitor
Patient
Monitor
HVAC
Baffles
Home Utilities Monitor
Phones
Oven/Range Refrigerator
GE WO
DW
V
Slide 10
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
WasteSystems
Seismic
Monitor
Noise MonitorTransportation
Air Pollution
Slide 11
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
Slide 12
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
Slide 13
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
Slide 14
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
Critical item across the board: Analytics
Slide 15
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
Slide 16
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
StarbucksNear the
Hotel in NY
There is Starbucks at this location
No
de
Ed
ge B
ack
en
d/C
lou
d
E2ESecurityPrivacy, IdentitySafety
Analytics
Slide 17
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
No
de
/Se
curi
ty
Raw Sensor Data
Feature Extraction
Classification
Inference
Sensors Data
Information
Knowledge
Wisdom
*GMM: Gaussian Mixture Model, HR: Heart Rate, GSR: Galvanic Skin Response
Slide 18
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
Slide 18
From Information to Knowledge
Sensors Data
Information
Knowledge
Wisdom
Ed
ge
Operating System Connectivity Software
Complex Inferencing Engine including Contextual and Temporal Analytics and
Predictive software
Data StorageDat FilteringAlgorithms
Security, Privacy, Identity, and Safety
M2M Focus
Critical item across the board: Analytics
Slide 19
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
Ba
cke
nd
/Clo
ud
IOT (system of systems)
Critical item across the board: Analytics
Slide 20
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
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
Slide 21
Sandhiprakash Bhide – Intel Corporation, TSENSOR SUMMIT, Stanford University, October 23-25, 2013
Slide 21
Thank you