Managing Smartphone Crowdsensing Campaigns

through the OrganiCity Smart City Platform

Dimitrios Amaxilatis, Evangelos Lagoudianakis, Georgios MylonasComputer Technology Institute, “Diophantus”

Evangelos TheodoridisIntel Labs Europe

WMSC '16, Heidelberg, Germany, 13 Sep 2016

Sensing in Smart Cities

Smart City Infrastructures• Traffic• Transportation• Environment

Internet of Things• Smart Home• Fitness Trackers• Maker Movement

Why Crowdsourcing?

It is impossible to reach every corner of every neighborhood in the city

(even if you choose to do it is extremely expensive)

How it works

Why OrganiCity?

Multiple Data Services and Representation Formats used even inside a single city

OrganiCity Smart City Platform

Crowdsensing Workflow

Campaign Scenario

Code Developme

nt

Crowdsensing

CampaignData

Analysis

Campaign ScenarioCampaign Scenario

Code Developme

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Crowdsensing

CampaignData

Analysis

Define:• Sensing context

(e.g., which sensors to use)• Target Audience• Feedback from the community

Code DevelopmentCampaign Scenario

Code Developme

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Crowdsensing

CampaignData

Analysis

• Simple Mini Applications in Java/Android• 30-100 lines of code per sensing module• Based on OSGi and Ambient Dynamix• Already available sensing modules to use with

no code• Code examples available on Github

Crowdsensing CampaignCampaign Scenario

Code Developme

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Crowdsensing

CampaignData

Analysis

Campaign Parameters:• Sensing modules• Areas of interest• Time of interest• Data collection priorities

Crowdsensing Campaign

Data AnalysisCampaign Scenario

Code Developme

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Crowdsensing

CampaignData

Analysis

Near Real-Time data monitoring and analysis• Heat-maps of collected data• Temporal Distribution of data• Volunteer Distribution of data• Communication with volunteers

Future Goals

• Large Scale Campaigns• User Feedback

• De-identification• User Privacy

• Gamification• Rewarding

Thank You!Questions?