Dr. Osman Ahmed, Ph.d. P.E. Senior Director and Head of ... · Tomorrow: Converged data using analytics create valuable knowledge and insights Meter City Business Citizens Utility

© Siemens AG 2015. All rights reserved. siemens.com

Big Data Analytics for Smart Cities IAMOT 2015, June 08-11

Cape Town- South Africa

Dr. Osman Ahmed, Ph.d. P.E. Senior Director and Head of Innovation

Building Technologies. [email protected]


Two stories: – Big Data Analytics Challenges and Opportunities:

How Target figured out a Teen girl was pregnant before her

father did- Forbes 2012.

Big data analytics for Target contributed in ravishing growth

from $44b in 2002 to $67b in 2012. But how would you handle

privacy and other pitfalls with profiling and other unintended

results?

February, 2015:

Twitter can serve as a dashboard

indicator of a community’s

psychological well being and can

predict rates of heart disease close to

what CDC can do.

Research conducted by Univ. of

Pennsylvania- 1300 counties

• Reported by NPR. www.npr.org


Big Data:


Big data analytics for Smart Cities- Background:

Scope:

• City infrastructure such as:

•Buildings, bridges, sewage, water, lighting, streets, transportation, health,

environment, sustainability

• City inspection for public health and safety

Needs:

• Monitoring

• Improve performance

• Provide better service such as security, safety

• Quick response

Constraints:

• Aging infrastructure

• Ever-expanding scope

• Shrinking budget and resources

Goal:

• Big city data analytics can find new solutions and cost-effectively


Today’s Smart City Solutions:


Today’s Smart City Solutions:

February 2015 Page 7


Megatrends

How digitalization is transforming our world

Worldwide data volume doubles every two years.

By 2020, it will have grown to 40 zettabytes – that’s

a 50-fold increase within ten years

Worldwide revenue of the IT and communications

industries reached a record €4.1 trillion in 2014.

Digitalization boosts GDP – a 10% increase in the

digitalization level of a country leads to a 0.75%

rise in per capita GDP.

Revenue from apps alone amounted to US$72 billion

in 2013 and will more than double by 2017

€4.1trillion

Worldwide revenue

in 2014

40 zettabytes

Data volume

by 2020

US$72 billion

Revenue from apps

in 2013

0.75% rise

10% increase leads to

in per capita GDP

February 2015 Page 8


Digitalization at Siemens

Leveraging technologies to deliver customer value

Digitalization

Automation

Electrification

Design & Engineering Highest productivity &

shortened time-to-market

Maintenance & Service Predictive, prescriptive &

efficient services

Operations Next level of flexibility &

resilience in operations

Security, ease-of-use,

manageable complexity

Big Data &

Analytics

Cloud

Mobile &

Collaboration

Connectivity &

Internet of Things

Leveraging key technology enablers along our entire portfolio to create next level of customer benefits.


Data Analytics opportunity for future cities

Siemens Picture of Future


Data Analytics for hopeful cities

Poverty

Misery

Hope

Future

• Dharavi, Mumbai, India.

• One of the largest slums

• Population: 1 million

• Economy: $600’- 1b

• Economy:

• Leather, Garments, Recycle

• Focus on Education

The NY Times: Dec., 2011

For internal use only. All rights reserved Page 11 July 2013 Leverage Service @ Siemens

• Optimize operation

• Performance analytics

• Efficiency based on

observation

• Apply data to Rules

Today: City Performance based on based on observed and operating data

• Sensors

• Meter

• Utility

• 3rd Party

Operating

Data

Structured program

Physics based modeling

Heuristics/ Statiscal

Today’s City Solutions:

For internal use only. All rights reserved Page 12 July 2013 Leverage Service @ Siemens

Tomorrow: Converged data using analytics create valuable knowledge and insights

Meter

City

Business Citizens

Utility

Site

3rd party

Enterprise

Plant

Sample

Modify

Model Learn

Simulate

Discover

Mine

Data Analytics

Big Volume Speed

Uncertain Variety

City Data

• Predictive Analytics

• Data create rules

• Cognitive rules

• Potential Performance

• Behavior optimization

• Business intelligence

• Identify patterns

• Hidden intelligence

• Discovery from learning

Tomorrow’s City Solutions:


Data Analytics Architecture:

• Data Source

http://www.mdpi.com/sensors/sensors-14-

09582/article_deploy/html/images/sensors-14-

09582f1-1024.png


Data Analytics Architecture- Data Source:

http://www.mdpi.com/sensors/sensors-14-

09582/article_deploy/html/images/sensors-

14-09582f1-1024.png

Merging and Synergistic Data Sources

IOT


http://3.bp.blogspot.com/-jHMYBdjkrlA/UBuQQijDyMI/AAAAAAAAATg/Y7pQqn65cx8/s1600/IOTA_MainImage.png

IOT for Smart City:

Pervasive Ubiquitous Low-cost Edge-computing Connectivity



Data Management and Integration

Data Access Layer (OBDC/JDBC……)

Data Storage Layer (SQL, OLAP….)

Data Integration Layer (Parsing…)



Statistics OR Reasoning

Diagnostics

Cognitive

Rules

Genetic

Algorithm

Neural

Network

Fuzzy

Logic

Signal

Processing

Text

Mining

Natural Language

Processing Computer Vision

Video Analytics


Data Analytics for future cities

http://www.wired.com/2013/07/the-new-horizon-for-bi-and-analytics/


Conceptual Smart and Sustainable City:

https://connectedtechnbiz.files.wordpress.com/2014/10/smart-city-concept.jpg


Data Analytics for future cities

Conceptual Smart City:

Wednesday, September 23, 2015 Restricted © Siemens AG 2013 All rights reserved. Page 21

An Overview of City Smart Service and Inspection

Data Management

Platform

IOT and Multiple Systems

Support heterogeneous

protocols

Data Analytics and Machine

Learning Platform

Classifier Clusters

Neural Network Genetic Algorithm

Decision and Deployment

Business Service

Raw Data Stream

Data Management

Platform

Data Stream Results/Output

Results/Output

Good Performers

•Continue monitoring

•Cluster and profile

•Trend patterns

•Keep learning

Poor Performers

•Apply FDD

• Apply Predictive Analytics


Big Data Analytics for Smart Cities:

http://datasmart.ash.harvard.edu/news/article/delivering-faster-results-with-food-inspection-forecasting-631

Case Study: City of Chicago. Dept. of Public Health. Restaurant Inspection

•15000 Restaurants. 36 City inspectors. Annually,15% restaurants receive violation.

•Public health hazard. Spread of food borne illnesses.

•Predict and prevent early violators

•City teams up with Allstate Insurance Analytics team- PPP project

•Tobacco & alcohol license

•Age of Restaurant

•Time since last inspection

•Location

•Garbage & sanitation complaints

•Nearby burglaries

•Three day avg. high temperature

Solution:

Machine

Learning

Platform

Predict

Violation

of

License

Results:

• Predicted earlier

• More violators

• Better utilization


Big Data Analytics for Smart City:

Case Study: City of Chicago.

•Publishes neighborhood safety index based on crime rate.

•Neighborhoods suffer because red zones are unsafe to live

Data Analytics:

•Yale University researchers

•Looked into crime rates with the victims profiles in social media

•Meta data

• NPR Radio: Shankar Vedantam: February, 2015

Results:

•Risk of facing a violent crime in red neighborhood really depends on someone’s

network of people he/she knowd and behavior

•Similar to public health crisis such as sharing a needle

•Risk is not random based on where you live but whom you know:

•Primary, secondary, or even tertiary level of connections


Big Data Analytics for Smart City:

https://www.airlouisville.com/

•A City cloud tracks usage of inhaler real-

time through sensing and mobile app.

•Data points out where usage is high and

under conditions

•Analytics help to improve air quality and

predict Asthma conditions

Louisville, Kentucky: Has one of the nation’s worst Asthma problem


Big data analytics for Smart Cities- :

Conclusions:

• Big city data analytics has significant opportunities to create new

solutions for both cities and infrastructure

•Creation of values- business, social, economic- should be the goals

•A well planned architecture needs to be implemented for the long-run

•Strategic vision is of paramount importance

•Citizens need to be inspired to participate

•Great collaboration opportunities exist for academicians, industry, and

govt. organizations.

Documents

Dr. Osman Ahmed, Ph.d. P.E. Senior Director and Head of ... · Tomorrow: Converged data using analytics create valuable knowledge and insights Meter City Business Citizens Utility