Smart city in Dananga

1. Steven Furst
FPT Information System
DATA
The ‘Lifeblood’ of digital transformation

2. Successful digital transformation in depends on successful data
management
• Digital transformation driven by smart city and digital government holds a great deal
of promise for economic growth and quality-of-life improvements in Vietnam
• Data is the lifeblood of digital transformation
• Successful digital transformation depends on effective data generation, storage,
management, and analysis
• In order to derive the expected value from smart city initiatives, we must develop our
core data capabilities
Need
graphics/images to
improve this slide

3. Smart City initiatives are a core component of Vietnam’s national digital
transformation
Chính phủ sốThành phố thông minhCông nghiệp 4.0
Được dẫn dắt bởi
Chính phủ
Được dẫn dắt bởi
sự kết hợp giữa các bên
liên quan: doanh nghiệp,
trường/viện, cộng đồng và
Chính phủ
Được dẫn dắt bởi
ngành công nghiệp và
các doanh nghiệp; kiến
tạo bởi Chính phủ
Chính phủ kiến tạo, Đổi mới 2.0, Các công nghệ CMCN 4.0
Con người thông minh
Được dẫn dắt bởi
Xã hội, cộng đồng,
người dân

4. Digital transformation in cities improves policy making, service provision
and productivity…
Key
Opportunities
for federal
government
• Forecast of citizens’ behavior and needs
• Personalization of Services
• Single identity
• Real-time feedback
• Prioritization of efforts across entities
• Reduction of process throughput times
• Improvement of financial performance
• Detection of money laundering / bribery
• Adaptive planning
• Crowd-sourcing ideas
• Accurate predictions
• Proactive policy response to emerging
issues
Improved
Policy
Making
Increased
Productivity
Better
Service
Provision
A smart sustainable city is an
innovative city that uses
information and
communication technologies
(ICTs) and other means to
improve quality of life, efficiency
of urban operation and services,
and competitiveness, while
ensuring that it meets the needs
of present and future generations
with respect to economic, social
and environmental as well as
cultural aspects
Source: ITU FG-SSC, FIS analysis Improve optics

5. …and provides opportunities across all sectors
Healthcare TransportEducation
…
Law Enforcement
• Increase clinical
treatment efficacy
• Provide patient
individualized care
• Optimize emergency
response network
• Respond faster to
epidemics
• Price drugs based on
performance
• Align road network
with economic growth
forecasts
• Minimize traffic jams
• Reduce number of
accidents
• Optimize school
network
• Allocate R&D spend
based on outcome
• Provide students
individualized
learning/coaching
• Align teachers with
population moves
• Optimize placement
of police officers
based on crime
patterns
• Identify patterns in
crime data to predict
repetitive crimes
Redraw & improve
optics

6. Use case: Smart Healthcare

7. Trung tâm điều hành
Giao thông Thông minh
Hệ thống điều khiển
Đèn tín hiệu giao thông
Thông minh
Hệ thống
Thu thập và Phân tích
Tình trạng Giao thông
Websitte
Ứng dụng
mobile
Mạng
xã hội
Chatbot
Cổng thông tin giao thông
Hệ thống
Cảnh báo Sự cố tự động
Hệ thống
Giám sát và Đảm bảo TTATGT
Hệ thống
Quản lý và Điều hành
Giao thông Công cộng
Hệ thống
Giám sát bằng RFID
ÁP DỤNG TRÍ TUỆ NHÂN TẠO
ĐỂ NÂNG CAO NĂNG LỰC QUẢN LÝ
Use Case: Smart Transportation

8. Data – The lifeblood of digital transformation
Source: McKinsey & Co., World Bank Group, Schonberger and Kenneth Cukier,
Large, diverse,
complex, longitudinal,
and/or distributed
datasets generated
from instruments,
sensors, internet
transactions, email,
video, click streams,
and/or all other digital
sources available
today and in the future
Big Data
Data in machine-readable
format that is publicly
available under an “open”
license that ensures it can
be freely used/reused/
redistributed by anyone for
any legal purpose
Open Data
“Lifeblood” - the thing that is most important to the continuing success and
existence of something else – Cambridge Dictionary
improve optics
“lifeblood” definition
should look different than
the data definitions

9. All of the tools that make a city “smart” depend on being able
to effectively manage data…
Redraw & improve

10. …and the more open, the better

11. Many city and national governments have recognized this and
built open data portals

12. Singapore's open repository stores and exposes more than 1700 datasets
from 70 agencies, with real-time API access and various formats

13. The potential benefits are clear
Source: europeandataportal.eu,

14. However… Redraw these
objects to we can
edit

15. New capabilities have to be developed over time to fully embrace the
opportunities from data
• Scalable and reliable
infrastructure required to
handle Big Data requirements
• Virtual networking and
intelligent workload
management technologies
• Entire new technology
stack and new solutions
required to enable new
data opportunities
• Reliable integration with
current environment
required
Architecture
AnalyticsData Management
Infrastructure
Data
• New Analytics capabilities
have to be built / provisioned
– Predictive Analytics
– Geospatial Analytics
– Social Analytics
– …
• Data Management will have
to become a distinct
enterprise-wide function
• Need to create and
maintain enterprise wide
data standards and policies
Enabling Capabilities

16. Differentiated analytics capabilities have to be built or acquired to
leverage data
Prescriptive
Analytics
Web/Mobile/
Social Analytics
Predictive
Analytics
Fraud and Risk
Analytics
• Using data to determine optimal zoning and infrastructure planning
• Anticipate public transportation requirements for route mapping
• Citizen Activity Analysis: Storing preferences to customize display,
tracking usage to measure web metrics
• Social Media Monitoring: Analyze citizen sentiments towards
policies and programs on social media platforms
• Forecast trends and requirements based on past and current events
• Determining probability of an event occurring and when it will occur
• Support asset management and investment requirements
• Improved Fraud Detection in payment transactions
• Predictive intelligence on banking fraudulent anomalies
Customer (Citizen)
Analytics
• Customer Driven Communications: Targeting services and
personalizing interactions based on individual behavior and life
circumstances
• Service Delivery: Multi-channel activity-based recommendations
Potential Target Platforms and Analytics Areas
• Which analytics platform gives us
the best tools? How does it add
values?
• What are the platform solution
requirements?
• Should analytics execution and
implementation be an in-house
function or can it be outsourced?
• Who are the major vendors and
how do we identify the best-in-
class solution? Three vendor
types:
– Data Provider (Access to data)
– Platform Provider (Tools)
– Service Providers
• How will the analytics platform
integrate with existing systems?
Analytics - Considerations
Architecture
Analytics
Data
Management
Infrastructure
Data

17. The infrastructure must support both smart city and digital government
requirements and designed to integrate data from all sources
Integrated Digital Government and Smart City Architecture Model
KioskOne GateEmailSMSSocial Web Portal DevicesContact Center
INTEGRATION LAYER
ESB
API Gateway
Services Gateway
Data Gateway
BPM
APPLICATIONS LAYER
User Interface/Presentation Layer
Channel Management
Health &
Social
AI
Engine &
Big Data
Analytics
INFORMATION LAYER
INFRASTRUCTURE LAYER
App Servers Storage Servers Networking
Data Integration
Platform
Firewall/SecureGateway
On Premise/Private Cloud Secure Public Cloud
AuthenticationandIdentityManagement
SecurityManagement
OperationsManagement
Education Utilities Public
Security
Environment Culture Transport Land &
Construction
SMART CITY SERVICES DELIVERY APPLICATIONS
DIGITAL GOVERNMENT SERVICES DELIVERY APPLICATIONS
BUSINESS APPLICATIONS
IoT
Integration
Hosted Managed
Services
Platform-as-a-Service
Software-as-a-Service
Cloud Data
Services
Security
Services
API
Services
Sensors
Master/
Meta Data
OperationalTransactionalUnstructured
Enterprise Data Warehouse
Architecture
Analytics
Data
Management
Infrastructure
Data

18. Architecture and processing solutions must be highly elastic and scalable
to accommodate the volume and velocity of Big Data
• Infrastructure and Technology:
– Virtualization of infrastructure through
commoditized hardware, “IaaS” options through
public and private clouds
– Virtual networking and intelligent workload
management technologies to enable scalable
‘infrastructure on demand’
– Compatibility of visualization, context, and content
aware analytics with a wide variety of presentation
and mobility devices
• Scalability and High-Performance Data Management:
– Data stream processing technologies for filtering
and capturing of high velocity information streams
through distributed processing and data file
management
– Trade-offs between in-database and in-memory
processing analytics infrastructure
• Economics:
– Appliance vs. componentized infrastructure
decisions depending on investment appetite,
speed to implement, scale of the initiative etc.
Architecture - Considerations
A
B
C
Architecture
Analytics
Data
Management
Infrastructure
Data

19. Data Management will have to become a distinct government-wide
function
• Data Management needs to define
the vision, mandate, and operating
model and organization structure for
the data program
• Operationalizing and aligning to
enterprise data strategy
• Ensures solutions are delivered using
the right business services/capabilities
• Create and maintain enterprise wide
standards and policies
• Data strategy alignment through an
effective gating process
• Assist in project prioritization and
defining roadmap to the target
operating model
Data Management - Considerations
Architecture
Analytics
Data
Management
Infrastructure
Data

20. The operating model will need to change profoundly – many key
questions will have to be answered
Governance
Processes
Organization
Skills
• How does data management weave into existing enterprise functions and sub-functions?
• How are certain business capabilities enabled and decision rights changed?
• How do existing processes have to change to accommodate the increasing impact of data?
• Responsibility and accountability?
• How to organize for the new world of big and open data?
• What is the structure of the data team?
• What are the roles for the various players in this team?
• What skills and competencies are needed?
• How do we establish clear and well-defined process & tools for how data skills
development should work?
KPIs • Which KPIs have to be adapted to reflect changes in Operating model?
Key Questions

21. Where is it all headed?
2000 to Present
Deep Impact of Big/Open Data & Advanced
Analytics
Next
Ubiquitous Data-based Decisions
Data explosion – 2.5 quintillion
bytes of data produced every day
Widespread analytics use for ticket pricing,
shopping and movie recommendations, traffic
management, etc.
Natural language processing for
analysing unstructured data – Facebook
posts, email, web pages, etc.
Server farms and low cost high speed
processing make distributed computing and
advanced analytics commercially viable
Massive talent gap – 2020 Data Science/Analytics
job listings projected to grow by nearly 364,000
listings to approximately 2,720,000
Data licensing overtakes data purchasing as the norm
(as data grows stale every few minutes)
Decline in mass marketing accelerates – all customer interaction is personal;
Individuals use analysis for everyday decisions – education, careers, health,
finance, the sharing economy
Anticipatory analytics – makes it near
impossible to crash a car (or burn dinner!)
Cloud-based analytics exchanges leads to widespread collaboration
between business, developers, data scientists, researchers, etc.
Lines blur between data science and product management and other
related roles – Clearer, deeper career paths within data science
Source: Domo.com, IBM

22. Năng lực, công nghệ, đối tác để đồng hành với TPTM
• Smart Building Solutions
• Internal best practices
• FPT iHotel solution
• FPT Telecom services to buildings/ homes
• Digital Platform for Real Estate
• Transportation Information
for citizens
• Vietnam railway online ticket
• F.iBus
• FPT.eHospital
• Healthcare 4.0 solutions
• Smart building solutions for HC
• Medical device integration
• Smart Environment
Management
• Smart Water
Management
• Smart Transportation
• FPT Telecom Services
• FPT.AI
• FPT Autonomous Car
• Blockchain based KYC
• SMAC, IoT
• Next generation security
• Smart Energy Management
• Smart Public Lighting
• Smart Building Energy
Management
• F.travel
• Smart Home
• Citizen SC mobile apps
• Sendo
• FPT Shops
• SenPay
• VNExpress
• Digital government
• Public finance solutions
• VioEdu
Countries
45
31 years
of pioneering
In Vietnam
36,000 employees
Top partners
with top global
ICT & OT players/ leaders
Optional if time allows
or just included in
printed version

23. Hệ sinh thái nền tảng số và ứng dụng FPT
DIGITAL
TRANSFORMATION
Customer Experience
Operation Excellence/
Employee Innovation
Operation Excellence
Business Models/
Products Innovation
Security Mobile Big Data/
Analytics
Cloud AI IoT Robotics AR/VR Blockchain
• FPT.eInnvoice
• Akachain Loyalty
• Omni Channel Cloud Contact Center
• FPT.eHospital
• FPT.iHotel
• FPT.eGov
• FPT.uService
• FPT.eLearning
• Helios
• FPT.eHospital
• FPT.iHotel
• FPT.eGov
• FPT.Tracebility
• FPT.E2E Visibility
• FPT.uService
• FPT.eHospital
• FPT.iHotel
• akaCare
• FPT.eGov
• FPT.eInnvoice
• FPT.eHospital
• FPT.eLearning
• FPT.iHotel
• Akachain Loyalty
HiGIO
FPT.GPUaaS
FPT.AkachainAkaBot
RPA Platform
FPT.AI
Platform
FPT.Smart
Worker
FPT.Eagle Eye MDR eMobiz
Fieldwork
FPT Play
RogoFPT DMP
Optional if time allows
or just included in
printed version

24. Thank you.
THANK YOU.
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