Course support for Analytics in Action

1. Smart Cities
February 2019
Analytics in Action
http://DSign4.education

2. Introduction
©2016 L. SCHLENKER
Agenda
Introduction
Definitions
Infrastructure
Use Scenarios
Limits

3. • What is the “science of cities” approach?
• What are the foundations of the Quantified
City Model ?
• Why does the author argue that “big data”
methodologies are a critical component of
Smart Cities.
• How does the author build the case for
Data Science in urban transportation?
Big Data Analytics in Smart Cities
Introduction

4. Smart Cities
Technology
IoT Agenda - TechTarget
• Smart cities use information and communication
technologies (ICT) to be more intelligent and efficient in
the use of
• Smart City is not a reality but an urban development
strategy, and a mostly technology driven future vision
• Smart City is about
• how citizens are shaping the city, and
• how citizens are empowered to contribute to urban development

5. Introduction
• Process - the organization of physical and digital
resources that condition the workplace
• Platform – enriching at information is produced
and consumed
• People – modifying the frame of reference
• Practice - impacting the reality of management
Schlenker (2015)

6. Inputs
Prediction
Evaluation
Actions
Outcomes

7. •Smart Living
•Smart Building & Home
•Smart Transportation
•Smart Energy (Renewable generation &
storage, AMI,PQM,PLM,OMS)
•Smart Water Management
•Smart Waste Management(Recycling of
waste, residual management, Recovery of
waste organics & Energy)
•Smart Governance(e-governance)
Smart Cities
Technology
IoT Agenda - TechTarget
Smart Cities use data collected from
citizens, devices, and assets to supply
information which is used to manage assets
and resources efficiently.

8. • The need to handle global
environment and urbanization
problems
• The need to accommodate
changing lifestyles
• The need for a long-term approach
to developing sustainable cities
Why now?
Technology
Channel Post MEA

9. Why India?
Technology
HEALTHCARE
• The number of diabetics in India is to rise from
50million in 2010 to 100million in 2030.
• Cancer incidence in India will rise 78% by 2030
• By 2030, 25% of deaths in India will be from heart
disease.
9
Source: The Economic Times Mar 13, 2014
PROVIDING FOOD FOR EVERYBODY
 Indian population now 1.2 billion and expected population
in 2040 1.5 billion.
 Current food production 260 million tones and it are
required to be increase up to 500million tones by 2040.
 Decrease in yields predicted due to climate change up to
12%.
CLEAN WATER FOR ALL
 Climate change is going to change water availability
patters significantly over the next few decades.
 Indian has per capita water availability of only 1100
cubic metres per year; it had over 3000 cubic metres in
the 1950s.
 60% of groundwater blocks in India will be in critical
condition by 2025.
GENERATING ENERGY AT LOW COSTS
 India is world’s 4th largest Carbon Emitter.
 India’s energy production will increase by 112% by 2035,
the highest growth for any country in the world.
 India’s annual emissions are rising at about 7-8% by 2035;
India’s energy demand is expected to rise 132%.
GIVING QUALITY EDUCATION
 58% of Indian Children do not complete primary
school.
 India has a higher education enrollment ratio of just
19.4%
 India will have a shortfall of 347 million workers in the
non-agricultural work force by 2022.
MAKE OUR CITIES LIVEABLE
 Air pollution in Indian cities is among the highest in the
world, with Delhi being the most-polluted city.
 Urban waste could increase six folds over 35 years.
 Two-thirds of Indian cities are already facing water crisis.
 Violent crime is on the rise in most Indian cities.
 10% of the world’s road accidents happen in India.

10. Whose doing it?
Technology
• How smart tech is solving Thiruvananthapuram's big water
problem
• Telemedicine for mobile devices, developed by Council
Associate Partner UST Global in collaboration with
Mumbai-based Dr. Balabhai Nanavati Hospital
• Lavasais the first city in India to have adopted LIDAR
technology, which is considered a more precise system of
data capturing, making detailing of project planning and
execution more accurate

11. • Participation in decision making
• Smart Supply Chain
• Public and social services
• Transparent governance
• Life Cycle Assessment
• Environmental Accounting
• Shared service Centers
• Digital Citizenship
• Security Systems
Use Scenarios
Technology
Jatin Panchal

12.  Physical structures can be better maintained.
 Weather hazards can be better predicted and
hotspots evacuated.
 Crime can be reduced.
 Seniors and other vulnerable groups can enjoy
greater independence and safety.
 Traffic and utilities can be optimized.
Value Levers
Technology
Jenny, T., (2017), Smart City Risks And Rewar

13. • Increased risks of data breaches – movable
malware
• Vulnerabilities to invasions of privacy
• Concerns about software reliability
• The “seams”between rural and urban, and
legacy and new infrastructure components
• The “inconsistent adoption” of smart
technologies because of limited resources
• Smart city systems reduce human interaction
in order to maximize computer efficiency.
What are the risks?
Technology
Newcombe, T. (2016), Security, Privacy, Governance
Concerns About Smart City Technologies Grow

14. • 126 Data Scientist jobs in Smart Cities
• Guadalajara Ciudad Creativa Digital
• Five components of a data scientist: statistician, programmer
coach, storyteller and artist
• The problems include unemployment, housing and
transport,climate change, energy efficiency, and social care
• Key responsibilities of a data scientist include ensuring open
access to data; developing tools for data re-use; promoting the
creation of citizen-centric data models and ensuring that the
right data are used in decision-making processes.
Smart People
Technology
• De Obeso-Orendain, A., (2016?), The role of the Data Scientist within Smart Cities

15. • Each city is focusing on data that adjusts to
their most pressing needs.
• London is using traffic data to try and curb
congestion and provide solutions to ease traffic
flow around the city
• Sensors placed around the city of Singapore
can detect cleanliness, or if people are
smoking in areas that they aren’t allowed.
• In India, smart cities will be at the heart of
urban innovation in the near future
Future trends
Technology
Rossi, B. (2016), The future of smart cities

16. • Smart Cities: Solving Urban Problems Using
Technology, (video)
• De Obeso-Orendain, A., (2016?), The role of the Data
Scientist within Smart Cities
• Hamblen, M. (2015) , Just what is a smart city?
• Innovation Enterprise, (2016), 7 Uses For Analytics In
Smart Cities
• Kahn, C. (2017), What Is A 'Smart City'?
• Musa, S. (2016), Smart City Roadmap
• Pierson, L. (2017), Big Data Analytics in Smart Cities
Bibliography
Next Steps

17. • What is the organization’s business
model?
• Why does the organization focus on
data?
• How is the Data Science team
organized?
• Which data science techniques does
the organization favor ?
• What is the link between data science
and decision making?
• How does the organization use Data
Science to propel growth
Case Study Questions
Technology