3. Problem recognition
• How will “smart city” build future cities?
• Technology is starting to play a key role for cities’
sustainability plans.
• This is because it is believed that new technology can
provide a robust solution that are of benefit to citizens.
• Cities aim to incorporate smart systems in their
industrial, infrastructural, educational, and social
activities.
• However, achieving this goal requires advanced support
for the development and operation of applications in a
complex environment.
• Can the platform provide an integrated infrastructure
that enables solutions for smart cities? 3
4. 4
Name Characteristics Open source
Sentilo The project began in 2012 with the Barcelona City Council and was
used to put Barcelona at the forefront of SCs .
Yes
Smart
Santander
The project is not intended to be limited solely to the city of
Santander but is intended to extend to other cities such as
Belgrade, Guildford, or Lubeck.
No
IBM IOC This is a private platform, owned by the IBM company, which is
located in different cities around the world, such as Rio de Janeiro.
No
CitySDK This aims to provide a programming structure for deploying SCs
systems, which has been tested in 8 cities in Europe.
No
Open
Cities
This is a platform that allows users to use the data stored on it in
order to be used by developers to offer services in cities.
Yes
i-SCOPE This is a platform that provides three types of services such as
optimizing energy consumption, environmental control to SCs.
No
People This is a platform that provides services for the community to use
and share those they develop, always oriented towards SCs.
Yes
IoT Open
platform
This is a platform that provides a set of libraries, technical
documentation, web services, and protocols in an open way.
Yes
Performance of existing platforms
Pablo Chamoso, et al., “Tendencies of Technologies and Platforms in Smart Cities: A State-of-the-Art Review ”, Wireless
Communications and Mobile Computing Volume 2018.
①
5. Current situation and future activities
• Smart cities are emerging as a potential solution
to tackle common problems by efficiently using
urban resources and providing quality services to
citizens.
• However, despite various advances to support
future smart cities, there is still no generally
accepted platform.
• Most existing solutions do not provide the
flexibility to share between cities.
• For this reason, it is very important to search for
various initiatives that challenge new needs.
5
6. Search for Three Aspects towards
Future Improvement
• Platform scalability
• Edge-based Platform
• Citizen centric services
Platform for infrastructure
expansion and contraction
Platform for developing and
sharing AP
Platform that hides the network
Application
8. Platform Scalability?
8
• The extensive use and development of non-open-
source software leads to interoperability issues and
limits the collaboration.
• The use of a microservices architecture to solve
these issues is the practical challenges in smart city
platforms.
• InterSCity is a microservice-based open source
smart city platform that supports collaborative, novel
smart city research, development, and deployment
initiatives.
• The microservice approach enables a flexible,
extensible, and demonstrates the scalability of this
platform.
9. • The scalability demands vary according to the
characteristics of the city, as well as those of the
deployed applications and services.
• Despite its importance, platform scalability had not
received the necessary attention in smart city
research.
• Platforms for smart cities usually implement
complex distributed architectures, requiring
considerable effort to run, configure, and test them.
• Therefore, a simulator that supports comprehensive
performance and scalability experiments on the
InterSCity platform is required, especially when
considering realistic and large-scale smart city
scenarios. 9
10. 10
By implementing a microservices architecture,
the InterSCity platform decomposes its functionalities across a
set of small, interconnected, collaborative services.
Arthur de M. Del Esposte, et al., “Design and evaluation of a scalable smart city software platform with large-scale
simulations”, Future Generation Computer Systems 93 (2019) 427–441.
②
11. 11
InterSCSimulator is an open-source, scalable simulator for large-
scale smart city scenarios.
The simulator is implemented in Erlang, a language suitable for the
development of highly parallel and distributed applications.
Arthur de M. Del Esposte, et al., “Design and evaluation of a scalable smart city software platform with large-scale
simulations”, Future Generation Computer Systems 93 (2019) 427–441.
②
12. • A mechanism to evaluate the scalability and
performance of the InterSCity platform is
established by the integration of the platform
and the InterSCSimulator.
• To achieve a more representative workload for
assessing the platform, InterSCSimulator
models is extended with real data gathered
from a large metropolis.
12
Brief Summary of InterSCity
13. • “The edge computing paradigm” through the
exploitation of the agent metaphor and a
distributed network of computing nodes
13
Edge-based Platform ?
• A platform for Smart City has to be
geographically and functionally
extensible to grow up with the physical
environment and meet the increasing
needs and demands of city users.
14. 14
iSapiens relies on two main abstractions: Virtual Objects (VOs) and Agents.
VOs are used to abstract and manage physical objects, hiding the
heterogeneity of devices and protocols.
Layers of Proposed Platform iSapiens
Franco Cicirelli, et al., “An edge-based platform for dynamic Smart City applications ”, Future Generation Computer
Systems 76 (2017) 106–118.
③
15. 15
comprehensive view of the main features
and benefits tied to iSapiens platform
Franco Cicirelli, et al., “An edge-based platform for dynamic Smart City applications ”, Future Generation Computer
Systems 76 (2017) 106–118.
③
16. Characteristics of iSapiens
• iSapiens is an agent-based platform providing
features for designing and implementing
distributed cyber physical systems and smart
environments.
• These functionalities are realized by exploiting
edge computing, internet of things and out-of-
the-edge computing services.
• Such systems are characterized by the
combined exploitation of software
components with heterogeneous physical
devices and protocols.
16
17. FogFlow: Programming of IoT Services
Over Cloud and Edges
• Smart city infrastructure is forming a large
scale Internet of Things (IoT) system.
• As such IoT system has geo-distributed nature ,
fog computing has been considered.
• However, it is a major challenge for developers
to program their IoT services to leverage
benefits of fog computing.
• FogFlow is a standard-based approach to
design and implement a new fog computing-
based framework for IoT smart city platforms.
18. 18
System architecture of FogFlow
Bin Cheng, et al., “FogFlow: Easy Programming of IoT Services Over Cloud and Edges for Smart Cities”, IEEE INTERNET
OF THINGS JOURNAL, VOL. 5, NO. 2, APRIL 2018.
④
19. Brief Summary of FogFlow
• Existing programming models focused on
batch and real-time data processing in a
cluster or cloud environment.
• FogFlow extended the traditional dataflow
programming model for enabling fog
computing.
• New methods(NGSIs) are adding the several
APIs to standard-based APIs.
• The FogFlow framework enables easy
programming of elastic IoT services.
19
20. • Smart Cities aim to improve the service they
deliver to their citizens both in terms of
economic and social impact.
20
Citizen centric services?
• IES Cities platform is enabling creative development
and easy deployment of applications which aim to
empower the citizen.
• And also, its' promoting user-centric mobile services
that exploit open data combined with user-supplied
data.
21. 21
IES Cities’ platform architecture
Unai Aguilera, et al., “Citizen-centric data services for smarter cities”, Future Generation Computer Systems 76 (2017)
234-247.
⑤
22. Characteristics of IES Cities platform
• This platform focuses on easing to developers
the creation of mobile services that leverage
on open data and user contributed data.
• This provides a solution that not only solves
data source management but also focuses on
reducing the gap between data consumer
requirements.
• This is an open platform for publishing data
accessible at different sources.
• This envisions fostering the creation of urban
services. 22
23. SOM called SmartCityWare
• SmartCityWare, the service-oriented middleware
(SOM) can help resolve some of the challenges of
developing and operating smart city services.
• The technologies to support such efforts are the
Cloud and Fog Computing.
• However, proper integration and efficient
utilization of Cloud and Fog Computing is not an
easy task.
• SmartCityWare abstracts services and components
involved in smart city applications as services
accessible model.
23
24. 24
SmartCityWare services are distributed among multiple clouds,
fogs, and IoT devices.
Each service defines a few simple interfaces to other services.
Using SOM concepts provides mechanisms to link available
services to build new services.
Nader Mohamed, et al., “SmartCityWare: A Service-Oriented Middleware for Cloud and Fog Enabled Smart City Services”,
SPECIAL SECTION ON THE NEW ERA OF SMART CITIES:.IEEE ACCESS.2017.2731382.
⑥
25. 25
The traffic light controls features monitoring devices at many locations(road
sensors, on vehicle sensors, neighboring vehicles,etc) to accurately capture
and model traffic patterns.
By using this information, it adjusts traffic lights to optimize flow.
Application Examples:Intelligent Traffic Light Control System
Nader Mohamed, et al., “SmartCityWare: A Service-Oriented Middleware for Cloud and Fog Enabled Smart City Services”,
SPECIAL SECTION ON THE NEW ERA OF SMART CITIES:.IEEE ACCESS.2017.2731382.
⑥
26. Characteristics of SmartCityWare
• Similar examples are Civitas, SOFIA, VITAL,
SmartUM, SMArc, GAMBAS, and CityHub.
• Main differences between SmartCityWare and
others is that SmartCityWare is a completely
SOM that utilizes both Cloud and Fog
Computing to provide various services for
smart cities.
• Also, main advantages of this approach is the
flexibility of extending the middleware itself
to include new and more advanced services to
support smart city. 26
27. 27
Brief Summary
InterSCity/
InterSCSimulator
Open source software
microservices architecture
scalability of the
platform
iSapiens edge computing paradigm Abstractions of VOs and Agents.
FogFlow new dataflow
programming model
easy programming of elastic
IoT services
IES Cities open platform reduce the gap between data
consumer requirements
SmartCityWare service-oriented
middleware
Integration of Cloud and Fog
Computing
Platform scalability
Edge-based Platform
Citizen centric services
28. 28
• Various attempts have emerged from ease of
programming to platform scalability.
• At present, cities of all sizes are including
Smart City proposals in their urban
sustainability programs.
• Smart city focuses on providing social
benefits, economic growth, and creating new
opportunities.
• However, there is still a big gap between
expectations and proposals.
Overview of listed proposals
29. 29
Architecture Design/
Development
Evaluation/Vali
dation/Test
Deployment to
actual system
IES Cities
Platform
++
(Open Platform)
+
(services that
leverage on open
data and user
contributed data)
++
(validate platform
taking into account the
different roles of
stakeholders)
+
(applied in four
different European
Cities)
SmartCityWare
Service
++
(abstract services
as services
accessible model)
+
(SmartCityWare
prototype was
implemented.)
+
(Utilize the flexibility
and extensibility based
on SOM architecture)
/
iSapiens
Platform
++
(Virtual Objects
(VOs) and Agents)
++
(guidelines for
design and
implementation of
smart city
applications )
+
(as a significant case
study, the design of a
real Smart Street in the
city of Cosenza (Italy) )
+
(the implementation
of a real Smart Street
in the city of Cosenza
(Italy) )
FogFlow ++
(fog computing
based framework)
+
(New methods
adding the several
APIs to standard-
based APIs)
+
(3 case studies)
/
InterSCity
Platform/InterS
CSimulator
++
(microservices
architecture, open
source)
+
(real data gathered
from metropolis)
++
(experimental results to
demonstrate the
benefits on scalability
and performance)
+
(some case studies
such as Sao Paulo)
Realization status of each project
Project Name
Stage
30. Current status of proposals
• Many of the proposals have been developed
as prototypes, and small scale adaptations are
being attempted.
• Some of them contain detailed evaluation
information, but each proposal has not yet
been fully introduced into the actual system.
• Since full-scale implementation also requires
integration with other components, many
proposals are expected to enter the
deployment stage in the future.
30
31. Summary
• There is no myth in system development.
• The emergence of numerous proposals
suggests various barriers to system
development.
• In addition, new challenges are anticipated in
the spread of systems.
• The platform is considered effective in solving
or responding to these challenges.
31