Internet of Things and Data Analytics for Smart Cities
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Payam Barnaghi
Institute for Communication Systems (ICS)
University of Surrey
Guildford, United Kingdom
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CityPulse: Large-scale data analytics for smart cities
What type of problems we expect to solve in
“smart” cities
4Source LAT Times, http://documents.latimes.com/la-2013/
Future cities: A view from 1998
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Source: http://robertluisrabello.com/denial/traffic-in-la/#gallery[default]/0/
Source: wikipedia
Smart City Data Analysis
− Analysis of thousands of traffic, pollution, weather, congestion, public transport, waste and event sensory data to provide better transport and city management.
− Converting smart meter readings to information that can help prediction and balance of power consumption in a city.
− Monitoring elderly homes, personal and public healthcare applications.
− Event and incident analysis and prediction using (near) real-time data collected by citizen and device sensors.
− Turning social media data (e.g. Tweets) related to city issues into event and sentiment analysis.
− Any many more…
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Designing for City Problems
101 Smart City Use-case Scenarios
http://www.ict-citypulse.eu/page/content/smart-city-use-cases-and-requirements
Big (IoT) Data Analytics
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Real World Data
Smart City Framework
Smart City Scenarios
Data Processing and Information Extraction
Analysis of traffic data in City of AarhusAnalysis of traffic data in City of Aarhus
University of Surrey Smart Campus data analysisUniversity of Surrey Smart Campus data analysis
Twitter data analysis for detecting city eventsTwitter data analysis for detecting city events
In Conclusion
− Combining data from Physical, Cyber and Social sources can give more complete, complementary data and contributes to better analysis and insights.
− Intelligent processing methods should be adaptable and able to handle dynamic, multi-modal, heterogeneous and noisy and incomplete data.
− Smart cities are complex social systems and no technological and data- analytics-driven solution alone can solve the problems.
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