Salvatore Distefano Politecnico di Milano – Italy [email protected] Mobile Crowdsensing, Social and Big Data as Innovation Enablers for Future.

Salvatore Distefano Politecnico di Milano – [email protected]

Mobile Crowdsensing, Social and Big Data as Innovation Enablers for Future Internet Cloud-based Architectures and Services

FIA - Athens - March 18, 2014

Mobile Crowdsensing Application

Agenda

• Introduction• Crowd-based approaches• Crowd Sensing• Mobile Crowd Sensing • MCSaaS• MCS Application

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Introduction

• 20-30 billions of devices by 2020• IoT: enhanced communication techniques• New challenges• High level solutions for managing things• New-value added applications directly involving

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• Leveraging on crowd• Data, services, ideas, contents, skills, money, … coming from

crowds• Crowdsourcing = Crowd + outsourcing• “the practice of obtaining something by contributions from a

large group of people and especially from the online community rather than from traditional employees or suppliers”

• Crowdfunding, crowdsearching, crowdsensing, open source development

• Volunteer contribution: free vs by charge

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Crowd-based approaches

• Crowdsourcing on data• Two possible ways• Direct, participatory contribution on a volunteer basis• Data are provided by sensors/sensing resources from contributors• Active, a priori, both proactive and reactive, runtime• Traffic monitoring, pothole mapping, emergency/disaster prediction, management and

recovery, VGI, …

• Indirect • DB, Web, Social Networks, Crowdsourcing/searching, data mining, feature

extraction, filtering, processing, …• Passive, a posteriori, reactive, offline• Investigation of the effect/impact of a given phenomenon on a given area, geocomputing …

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Crowdsensing

Mobile Crowdsensing• The integration of sensors

that can be used for gathering materialistic or non-materialistic information

• Involve people that both participate and use the MCS

• Geo-tagged info

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User at Front End

Web Service at Back End

The MCS Paradigm

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Participatory Sensing

Opportunistic Sensing

Users actively engage in the data collection activity.

Users manually determine how, when, what, where to sample.

Higher burdens or costs.

Can avoid phone context issues.

Takes random sample which is application defined.

Easy to gather large amount data in small time.

Can’t avoid phone context issues.

Lower burdens or costs if contextual problems are

handled.

Filtering Data by Handling Privacy Issues & Localization.

Dataset is ready for research !!!

MCS Stack

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Mobile Crowdsensing ApplicationsMonitoring common phenomenon…

•Pollution (air/noise) levels in a neighborhood.•Real-time traffic patterns.•Pot holes on roads.•Road closures and transit timings.•……

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Mobile Crowdsensing: current issues

volunteer enrolment:

• requires out-of-band campaign (social network) to get attention

• involves user-initiated activity (website download) to begin contributing

• slow and unpredictable uptake

app/service availability/reliability:

• degradation with node churn

• real-time info may translate into severe burden on resources (battery)

• privacy

• customisability

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MCS Challenges

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Localized Analytics

Resource Limitations

Privacy

Aggregate Analytics

Architecture

MCS as a service - MCSAAS

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MCSaaS: a Cloud platform for deploying MCS apps on SAaaS infrastructure

readily available infrastructure:

• a platform provider only needs booking resources for MCS, sending client-side platform code

• SAaaS will take care of (one-time) client deployment

automatic deployment:

• fire-and-forget experience for the app provider - just send a request to MCSaaS provider for resources, attaching the payload

• (SAaaS-unaware) dissemination carried out by the platform

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MCSaaS: a Cloud platform for managing MCS apps on SAaaS infrastructurechurn management(s), each at its own layer:

• transparent

• built-in, as part of the framework(s) management

real-time info:

• built-in, platform-level sharing of monitoring data

• low device-side load from infrastructure-level stats collection

• optional on-demand feature, may be disabled at will

• lower strain on constrained resources

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Mobile Crowdsensing application: PotHole Detector

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Mobile Crowdsensing application: PotHole Detector

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Q&A

THANKS!

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