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CityPulse: Real-Time IoT Stream Processing and Large-scale Data Analytics for Smart City Applications

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CityPulse– a quick snapshot

− CityPulse aims to support the integration of dynamic data

sources and context-dependent on-demand adaptations of

processing chains during run-time.

− CityPulse aims to bridge the gap between the application

technologies on the IoT and real world data streams.

− It will use Cyber-Physical and Social data and will employ

big data analytics and intelligent methods to aggregate,

interpret and extract meaningful knowledge and

perceptions from large sets of heterogeneous data streams.

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An Integrated Approach

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CityPulse Consortium

Industrial SIE (Austria,

Romania), ERIC

SME AI,

HigherEducation

UNIS, NUIG,UASO, WSU

City BR, AA

Partners:

Duration: 36 months

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The main objective in CityPulse is:

− to develop, build and test a distributed framework for the semantic discovery and processing of large-scale real-time IoT and relevant social data streams for knowledge

extraction in a city environment.

− It will prototype and demonstrate its major concepts in a city environment and evaluate the results for exploitation towards future smart city delivery and development platform and testing products.

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Processing steps and Life-cycle stages

Analytics

Toolbox

Context-aware

Decision

Support,

Visualisation

Knowledge-

based

Stream

Processing

Real-Time

Monitoring &

Testing

Accuracy &

Trust

Modelling

Semantic

Integration

On Demand

Data

Federation

Open

Reference

Data Sets

Real-Time

IoT Information

Extraction

IoT Stream

Processing

Federation of

Heterogenous

Data Streams

Design-Time Run-Time Testing

Exposure APIs

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The Key issues addressed

− Virtualisation: Semantic annotation of heterogeneous data

for automated discovery and knowledge-based processing

− Federation: On demand integration of heterogeneous

Cyber-Physical-Social sources

− Aggregation: Large-scale data analytics

− Smart Adaptation: Real-Time interpretation and data

analytics control

− User centric decision support: Context aware customized

IoT information extraction

− Reliable Information Processing: Testing and monitoring

accuracy and trust

− Smart City Applications: Application programming interface

for rapid prototyping

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Overall Structure

WP1Pr ojectManagement

CityPulse Framework

WP6 Integration & Evaluation : Smart City Applications

WP5 Real -Time IoT IntelligenceWP4

Reliable

Information

ProcessingWP3 Large-Scale IoT Stream Processing

WP2 Requirements and Smart City Framework

ConfigurationSemantic

IOT Stream

Monitoring

& Testing

WP7

DisseminationandExploitation

Contact

Payam Barnaghi, University of Surrey, UK

Email: p.barnaghi@surrey.ac.uk

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