Smart city concept has a great potential improve the quality of life by use of Internet of Things paradigm. Deployment of Wireless Sensor Networks would provide huge amount of data It would present massive and unstructured data management and analysis challenges. Cloud based storage and Big Data techniques show promise to generate actionable intelligence from these data streams.

1. Smart City with Internet of Things (Sensor
networks) and Big Data
Pratibha Group of Institutes Conference , Feb 2013
Satish Phakade Pawar
Professor @ ASM’s IBMR, Chichwad
Mr.SatishPawar@gmail.com
+91-9860027825

2. The “Smart City” concept
Technology driven future vision
Urbanization is growing word wide.
6.3B + people, 60% of the population living in cities by
2050 *
Ecosystem of work, food, cloths, residence, offices,
entertainment, transport, water, energy etc.
Growth – chaos – politics and data - overwhelming.
The intelligence is sometimes digital, often analogue,
and almost inevitably human.
*(source: UN World Urbanization Perspective, the 2011 revision).

3. The “Smart City” Global Trends
 Investment in smart cities will grow from $8B to $16B by 2020
for a total of $108 billion between 2010 and 2020 (source
http://www.pikeresearch.com/research/smart-cities).
 By 2016, the IOT opportunity will be $23B, 20% of which is in
Smart Buildings (source: 2011 Executive Yun SRB, Taiwan

4. Today’s Internet of People

5. Today’s Internet of People
 made up of a core Internet of backbone routers and servers,
 massive no. of nodes in fringe including PCs, mobiles and all
other devices.
 The core Internet changes rarely and has extremely high
capacity..In 2008 it was estimated that the Internet had
approximately 1.4 billion regular users.
 The growth of the fringe is dependent on the number of
Internet users and the personal devices used by them.

6. Beyond HDTV
and e_Cinema
Service,
Software
Engineering Networked
Search
Converged and
Optical
Networks
Future Internet
Architectures
and
Technologies
Future Internet
Service
architectures
and Platforms
Internet of
Things
3D and Media
Internet
Cognitive Radio,
Spectrum
Management,
B3G..
Content aware
Nets, Net aware
Apps.
Trustworthy Networks + Trustworthy Services
Tools and technologies for Trust
Experimental Facilities + Experimentally Driven research
NETWORK SERVICES ENTREPRISES /
ORGANISATIONS
MEDIA A/V
The Future Internet
Internet
of
Things
Apps
Enter-
prise
Environ-
ments

7. Internet of Things
 Sensors and actuators embedded in physical objects—from
roadways to thermostats
 linked through networks, using the same Internet Protocol (IP)
that connects the Internet.
 All natively IP-enabled - embedded devices and networks ,
monitored and controlled through internet services.
 sensors, machines, active positioning tags, radio-frequency
identification (RFID) readers and building automation
equipment.
 The growth iwill soon exceed the rest of the Internet in size in
trillions of devices.

8. Internet of Things

9. Tomorrow’s ubiquitous world of tags, sensors
and smart systems
Info Day, Budapest, 22 January
2009

10. IoT Developments
 In 2008 the IP Smart Objects (IPSO) Alliance [IPSO] was formed
by industry leaders to promote the use of Internet protocols by
smart objects and the Internet of Things
 The Wireless Embedded Internet is a subset of the Internet of
Things;
 Wireless Embedded Internet to include resource-limited
embedded devices, often battery powered, connected by low-
power, low-bandwidth wireless networks to the Internet.
 6LoWPAN was developed to enable theWireless Embedded
Internetby simplifying IPv6 functionality, defining very compact
header formats and taking the nature of wireless networks into
account 6LoWPAN].

11. Big Data Every Where!
• Lots of data is being collected
and warehoused
– Web data, e-commerce
– purchases at department/
grocery stores
– Bank/Credit Card
transactions
– Social Network

12. How much data?
• Google processes 20 PB a day (2008)
• Wayback Machine has 3 PB + 100 TB/month (3/2009)
• Facebook has 2.5 PB of user data + 15 TB/day (4/2009)
• eBay has 6.5 PB of user data + 50 TB/day (5/2009)
• CERN’s Large Hydron Collider (LHC) generates 15 PB a
year
640K ought to be
enough for anybody.

13. Smart City & IoT Benefit to the
Citizen-
Increasing Relevant Use of the Resources with Internet to Tell Us
when and where to Save
• Internet connected sensors can control detect unnecessary use
and make adjustments.
• Irrigation systems can turn off when rain is detected,
• lights can go dim when they aren’t needed and
• leaking pipes can send a text to landlords. These improvements
help us save resources by increasing efficiency and large
amounts of money.

14. Benefit to the citizen -
• ii. Systems that save Time, Energy and Money
– public transportation
– operators and control centre to see their position in route,
ticket sales, camera. With large displays/mobile interfaces
Bus riders see real time positions and get.
• iii. Improve Quality of life and Systems that save in
emergency
– pollution concentration in each street
• IV. Smart metering to monitor the optimum usage of
energy , gas water etc.

15. Benefit to the Authorities-
• Energy management
• Water Management –
• Emergency Management
• Transport management – e,g.
• Parking -An easier parking project [3] in San Francisco city at
www.sfpark.org
• Noise and Pollution management
• Waste disposal management
• Citizen Information system
• .Waste management -Rubbish bins can send an alarm when
they are close to being full.

16. Smart City DNA – Crucial questions
• Connected devices are nothing without a service, so where is
the service?
• Where are the toll bridges in each ecosystem? physical
hardware , services, online processing or storage revenue
• Where will the intelligence in the internet of things
live? Server in the cloud? Or local device
• How many internets of things will we have?
– the vertical segmentation - e.g 1 internet of electricity -thermostats,
– 2. An internet of vehicles or transportation Google the first driverless
car San Francisco to Las Vegas. The car followed the speed limit, abided
by traffic laws, and completed its journey without any accidents. If we
have self-driving cars they will also need to connect to that will include
other cars and signals.
•

17. Smart City – Crucial questions
• How will internets of things from different equipment and
cloud providers interoperate?
• to become a part of the sensor network for ease of use.
• Cloud services are proprietary owned and operated by
individual companies.
• Interoperability and mobility may be necessary for data storage
and analysis with different cloud service providers.
• What about privacy?

18. Sensor network
• A group of specialized transducers with a communications
infrastructure intended to monitor and record conditions at
diverse locations.
• Monitored parameters temperature, humidity, pressure, wind
direction and speed, illumination intensity, vibration intensity,
sound intensity, power-line voltage, chemical concentrations,
pollutant levels and vital body functions.
• A sensor network consists of multiple detection stations called
sensor nodes, each of which is small, lightweight and portable.
Every sensor node is equipped with a transducer,
microcomputer, transceiver and power source.

19. Sensor Networks
• The transducer generates electrical signals based on sensed
physical effects and phenomena. The microcomputer processes
and stores the sensor output. The transceiver, which can be
hard-wired or wireless, receives commands from a central
computer and transmits data to that computer. The power for
each sensor node is derived from the electric utility or from a
battery.

20. Wireless Sensor Protocols Choice
• Some network protocols like 6LoWPAN,Dash7, Insteon and
WiFi, ZigBee, 6LoWPAN, EnOcean, Dash7, ONE-NET and Insteon
• trade-off between data transfer rate, speed and power
consumption..
• WiMax, WiFi (n and g) and IEEE 802.15.3a have a higher power
consumption for a higher bandwidth compared to the wireless
sensor networks and Bluetooth which were designed as low
power networks.
• Using ip was once considered impractical because these
networks are highly constrained and must operate unattended
for multiyear lifetimes on modest batteries.

21. 6LoWPAN
• 6LoWPAN is an acronym of IPv6 over Low power Wire-less
Personal Area Networks.
• This protocol is designed to be used for energy management,
home and building automation.
• operates only in the 2.4 GHz frequency range with 250 kbps
transfer rate.
• range is up to 200 meter and the maximum 100 per network..
• Extending IP to low-power, wireless personal area networks
(LoWPANs)
•

22. 6LoPAN Protocol for IoT

23. Framework of Sensor – Cloud
integration
• Cloud computing anywhere on demand services for storage,
compute and database resources.
• “software as a service” “Web 2.0” technologies .
• Wireless sensor networks (WSNs) connected to Internet would
cause explosive growth
• require cloud technologies to store, analyse , mine and derive
actionable intelligence from digital information. This
information could enable novel applications for social networks
or virtual communities, blogs,
• Our primary goal is to facilitate connecting sensors, people and
software objects to build community-centric sensing
applications where people can share and analyse real time
sensor data.
•

24. Type of Data
• Relational Data (Tables/Transaction/Legacy Data)
• Text Data (Web)
• Semi-structured Data (XML)
• Graph Data
– Social Network, Semantic Web (RDF), …
• Streaming Data
– You can only scan the data once

25. What to do with these data?
• Aggregation and Statistics
– Data warehouse and OLAP
• Indexing, Searching, and Querying
– Keyword based search
– Pattern matching (XML/RDF)
• Knowledge discovery
– Data Mining
– Statistical Modeling

26. 26
Cloud-based video content solution
and its extension to vertical industries
▪ IP-camera arrays
▪ Network routing /
infrastructure
 Datacenter HW / SW
 Console to control /
access all devices
Hosted cloud solution
▪ SW for real-time
analytics
▪ Automated alerts
▪ Advanced analytics to
identify / store
behavior patterns
IP video
camera
network and
routing
Video feed
aggregation /
centralized
storage
Real time
monitoring /
auto-alerts
Advanced
analytics and
intelligence
Distributed
video storage
and analytics
▪ Local storage (NVR)
and basic analytics
▪ Local compression
and encryption
Public safety Retail Healthcare
Transcoding and
transrating to send
alerts to multiple
devices
POS data analytics
to assess customer
shopping behavior
Medical imaging
devices and doctor
end points
Additional vertical / horizontal-specific platform capabilities
Additional motion
sensors, alarms,
RFID tags
Pattern and license
plate recognition to
identify suspicious
activities / vehicles
Customer slip / fall
notification for
liability purposes
Recording of credit
card transactions
as mandated by PCI
guidelines
Clinic decision
systems and patient
care improvement
Feasibility Study
Patent medical
records per HIPA
compliance
SOURCE: joint report by McKinsey, Cisco, IBM, Aug. 2010

27. Sensor Cloud

28. Conclusion
• Smart city concept has a great potential improve the quality of
life by use of Internet of Things paradigm.
• Deployment of Wireless Sensor Networks would provide huge
amount of data
• It would present massive and unstructured data management
and analysis challenges.
• Cloud based storage and Big Data techniques show promise to
generate actionable intelligence from these data streams.

29. Thank You
Thanks
Mr.satishpawar@gmail.com
9860027825

30. Toda of People

31. Sensor Cloud

32. Barcelona smart city development
Leading role of City Hall
• Cibernarium
• Citilab Cornella
• Municipal Police
• New incidentstools
• Intelenvironments
• 22@net
• Barc activa
• Tech park
• Urban Lab
• Strategicplan
• Kiosks
• Internal gov
• Open data
• 3D projects SMART
GOVERNA
NCE
SMART
ECONOMY
SMART
PEOPLE
SMART
LIVING
Smart city model:
Three pillars
Ubiquitous
infrastructures
Information from
sensors, open data,
and citizens
Human capital, actors,
communities
Smart city Strategy
Smart Districts:
22@Barcelona; triple
helix collaborations
Living Lab initiatives:
22@Urban Lab, Live,
Bdigital, i2Cat, Fablab,
Cornella
Infrastructure
building: traditional
and new. Integration of
ICT. From fibre optic to
Wi-Fi.
New services to
citizens: gov, quality of
life, professional
Open data: sensors,
open standard, and city
platform
SC Management
Creation of networks of
actors, organisations,
departments
Broadband network and
sensor data management
Creation of proof of
concepts for systems and
applications
Challenges
Demand for human
capital and skills
VC funding for innovation
Low global connectivity
Development of triple
helix alliances
Collaboration between
government departments

33. Thessaloniki smart city development
ICT transforming city activities and ecosystems
Broadband networks
by large companies
ADSL: 24/1 Mb
Fibre optic net: 2,5 Gb
3G-HSDPA: 42 Mb
Wireless: free
(municipal nets)
Apps and e-services:
Bottom-up initiatives
City representation
City sectors
City districts
Citizens. Aggregation /
collective content
City administration and
social services
Location-based services
City infrastructure and
utilities
City management
Planning for Smart
district
Development of wired
and wireless networks
Free Internet to users
and business.
Smart environments
based on sensors
e-services suitable for
the community of each
district
Training services for
involvement of end-users
Governance challenges:
Three gaps to address
(1) Digital skills gap - TRAINING
(2) Creativity gap – LIVING
LABS
(3) Entrepreneurship gap –
BUSINESS MODELS

34. Comparing the smart(er) city cases
Helsinki Thessaloniki Manchester Oulu Barcelona
Concept Smart City
cluster, Mobile
Intelligent Cities Urban
regeneration
City of
Innovation
Social and
urban growth
Strategies Knowledge
intensive
cluster building
Building smart
districts
Agglomeration of
Apps
Tackling skills
and divides
Pro-active
approach
Technology
Ubiquitous
Oulu
Smart
districts,
Urban Living
Lab
Drivers Strengthen the
region
ICT and
infrastructure
deployment
Economic
development
Policy and
strategies of
Oulu
Policies of city
hall; triple
helix
Challenges Human capital
base
Digital skills gaps
Creativity gap
Entrepreneurship
gap
Common
digital agenda
Adapt policy
instruments to
create
business
Enhancing
collaboration;
human capital
/ skills,
funding
Innovation
ecosystem
Public private
partnerships
Competition for
innovation
Innovation
clusters
Technology
districts
Living labs and
local action
Strong PPP
programmes,
triple helix,
urban lab
City hall
leadership;
Triple Helix
models