Explanation of Smart City

1. Smart City in Distributed
Computing
Abdul Rehman(CSC-20S-070)

2. Content Title
Define Smart City
Benefits of Distributed Computing in Smart Cities
Distributed Technology for Smart city
Applications of Distributed Computing in Smart City Services
Need for smart city?
Smart City Challenges
Evolution of Smart City

3. Define
Smart City
The main goal of a smart city is to
optimize city functions and promote
economic growth while also improving
the quality of life for citizens by using
smart technologies and data analysis.
The value lies in how this technology is
used rather than simply how much
technology is available.

4. Continoue
A city’s smartness is determined using a set of
characteristics, including:
 An infrastructure based around technology
 Environmental initiatives
 Effective and highly functional public transportation
 Confident and progressive city plans
 People able to live and work within the city, using
its resources

6. Benefits of Distributed Computing
in Smart Cities
 Efficient resource utilization: Distributed
computing optimizes the use of computing
resources across a smart city, ensuring efficient
data processing and analysis.
 Scalability: It enables smart city services to easily
scale to handle increasing data volumes and
growing demand.
 Resilience and reliability: Distributed computing
architectures provide robustness and fault
tolerance, ensuring continuous operation of critical
services.

7. Distributed Computing
Technologies for Smart Cities
Cloud Computing:
• The cloud acts as a central hub for storing and processing
data, providing on-demand computing resources for smart
city services.
Edge Computing:
• By bringing computing capabilities closer to the edge of
the network, edge computing reduces latency and enables
real-time decision-making in smart city applications.
Fog Computing:
• Fog computing extends edge computing by providing
additional computing and storage resources at intermediate
points, enhancing data processing and analysis at the edge.

8. Applications of Distributed Computing in
Smart City Services
Transportation:
• Real-time traffic monitoring, congestion prediction, intelligent
transportation systems, and optimization of public transportation routes.
Energy Management:
• It facilitates smart grid integration, energy monitoring, load balancing, and
demand-response mechanisms, leading to efficient energy consumption and
integration of renewable energy sources.
Public Safety:
• Distributed computing allows for video surveillance, sensor networks,
emergency response systems, and predictive analytics, enhancing public safety
and disaster management capabilities

10. Need for a smart city?
Rapid urbanization:
By 2030, 60% of worlds population is expected to live in cities results in heavy
strain on energy, transportation, water, building and public spaces.
Increasing need is the being felt for smart city which are both efficient, sustainable
and Can generate economic prosperity & social well being.

11. Smart City Challenges
• Data privacy and security
• Interoperability and integration
• Digital divide and inclusivity
• Financial sustainability
• Citizen engagement and participation
• Regulatory and legal frameworks
• Scalability and sustainability

12. Evolution of Smart City
Building a smart city aims to increase the citizen’s quality of life. Using
sensors integrated with real-time monitoring systems, data is collected
from citizens and devices – then processed and analysed. The
information and knowledge collected are keys to tackling the
inefficiencies of the city administration. by IOT Sensor

13. THANK YOU