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Managing Smartphone
Crowdsensing Campaigns
through the OrganiCity Smart
City Platform
Dimitrios Amaxilatis, Evangelos Lagoudianakis, Georgios Mylonas
Computer Technology Institute, “Diophantus”
Evangelos Theodoridis
Intel Labs Europe
WMSC '16, Heidelberg, Germany, 13 Sep 2016
Sensing in Smart Cities
Smart City Infrastructures
• Traffic
• Transportation
• Environment
Internet ofThings
• Smart Home
• FitnessTrackers
• 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
CrowdsensingWorkflow
Campaign Scenario
Code
Development
Crowdsensing
Campaign
Data Analysis
Campaign Scenario
Campaign Scenario
Code
Development
Crowdsensing
Campaign
Data Analysis
Define:
• Sensing context
(e.g., which sensors to use)
• Target Audience
• Feedback from the community
Code Development
Campaign Scenario
Code
Development
Crowdsensing
Campaign
Data 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 Campaign
Campaign Scenario
Code
Development
Crowdsensing
Campaign
Data Analysis
Campaign Parameters:
• Sensing modules
• Areas of interest
• Time of interest
• Data collection priorities
Crowdsensing Campaign
Data Analysis
Campaign Scenario
Code
Development
Crowdsensing
Campaign
Data 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
ThankYou!
Questions?

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