This document discusses how cities can become more resilient by gathering data from various systems and devices, using machine learning to develop knowledge representations, and employing reasoning algorithms to decide the best actions in response to unexpected events. The goal is for cities to respond to events effectively by coordinating public services and resources through interoperable systems informed by sophisticated event analysis.

1. The Connected
Megacity
Mobile World Congress 2013

2. THE MEGA-
URBANIZATION
› Urbanization trends
– In the year of 2050 it is estimated that 70 percent
of the world’s population will live in cities
– The highest growth will be noticed in Asia and Africa
– A high birthrate combined with an increasing
migration from the rural areas lead to the very
dynamic growth process
› Socioeconomic drivers
– Push factors include unemployment, poor housing
and infrastructure, lack of educational facilities, etc.
– Pull factors include economical opportunities,
attractive jobs, better education, modern lifestyle, etc.
– Cities are engines of economic productivity and
creativity as they bring tools and people together
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3. MEGACITIES (and almost megacities) 2025
DELHI
33 MILLIONS TOKYO
39 MILLIONS
SHANGHAI
28 MILLIONS
MEXICO CITY
MUMBAI 26 MILLIONS
27 MILLIONS
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4. DIVERSITY OF CHALLENGES
URBAN PLANNING JOBS TRANSPORTATION ENERGY WASTE
EDUCATION PUBLIC SAFETY POLLUTION HEALTH WATER
FOOD AND AGRICULTURE
GREEN ASPECTS FOOD AND AGRICULTURE URBAN DIVIDES
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5. IDEAS FOR IMPROVED
GOVERNANCE
COMPETITIVENESS ENVIRONMENT BEHAVIORAL CHANGE ICT OPPORTUNITIES
QUALITY OF LIFE SUSTAINABILITY CITIZEN DIALOGUE
Finding a balanced Awareness, understanding,
view on city growth and collaboration
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6. COMMON ICT THEMES
› The governance perspective
– Managing infrastructure and resources efficiently
– Real-time monitoring and analytics tools for dynamic
short-term action as well as holistic long-term planning
– Improved public administration with increased
transparency and efficiency through
› The citizen perspective
– Awareness of decisions and what type of behavior
that the city and the citizens benefits from
– Personal and contextual incentives for sustainable
behavioral change
– Driving collaboration and the ability to affect the city
surroundings through collective action
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7. COMMON ICT THEMES
› The technology perspective
– Bridging components supporting the understanding of
processes in other sectors to reach synergy effects
– Services having the support from the knowledge and
reasoning of an intelligent system
– Importance of data visualizations that help create
awareness about, for example, sustainability issues
› The business perspective
– Augmenting traditional products with ICT features and
services that differentiate and enhance their usage
– Enabling radically new solutions to city challenges by
building on the creativity of people and businesses
– Understanding how shifts from physical goods to the
service sector can amplify the environmental benefits
of e-services
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8. Sustainable city models
Community and business Long-term vision alignment, evaluations,
participation proactive measures, transformations,
collaboration, regulations Dynamic city operations centers
Citizen contributions, incentives and
Optimization, resource management,
rewards, responsibility, good practices,
infrastructure, public services, objects,
services, business innovation
sensors, actuators
Crowdsourcing Update
and service data reasoning Respond
Event algorithms to events
information
Knowledge and
reasoning layer
Update
Contextual and preferences Status
personal info Shared data information
Public safety Education Health Jobs
Food Energy Water
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9. Three
use cases
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10. Resilient City
From Data via learning to decision
Reinforcement
data learning knowledge reason decision
Gather data from Learning Knowledge Reasoning
representation Decide & Act
devices & systems • Machine Learning • Logic reasoning
• Find best action
• Traffic characteristics • Data Mining • Learned knowledge • Probabilistic reasoning sequence
• Mobile networks • Structure Learning • Expert knowledge • Hybrid reasoning • Decision support
• Base stations • Parameter Learning • Logic and probabilistic • Markov logic • Rule generation and
• Cell phones • Case based learning knowledge • MEBN suggestions
• Logs • Semantic models • Complex event • Explanation of decisions
• Transformation processing • Monitoring of results to
• Verification improve future decisions
• Simulation
UI, API & SDK
›It shows how the city can respond to an unexpected event in a resilient way. It also suggests how a sophisticated reasoning
around the characteristics of the event can provide knowledge to the city services about the best way of responding to it.
And how available resources (public services, people, sensors, devices, etc.) can be used in an effective way to understand
and mitigate the situation; something that require interoperability and cross-domain communication.
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11. Proactive City
› It is easy to imagine how sensors feed data into a city operations center,
and how that data is analyzed and used to optimize different public services.
› However, another interesting question is how all the gathered city data can
be used by the inhabitants, and how the data can be presented in different
contexts to create awareness and understanding.
› Something that possibly triggers a more sustainable behavior.
› This is of course done through a combination of technical enablers,
to name a few:
– Understanding data
– Decision Support
– Human Mobility Analytics
– Mode of Transport
– Context-aware ITS
– Ericsson Apps
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12. Greener City
› Cellular communications are only one part of the puzzle and the smart
grid communication architecture will be made of up many technologies
› There is no silver bullet, no one technology
› Cellular and in particular LTE is ideally placed for last-mile connectivity
in the field area network
› Experience from our Utility customers shows that the key use-cases are
– advanced metering
– grid monitoring and control
– field workforce
– distributed energy and - with a longer lead time - electric vehicles.
› It is equally important to understand network optimization for these particular
applications and this is where the features of LTE play an important role, namely
– low latency
– QoS
– high throughput
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