1. Salvatore Distefano Politecnico di Milano – Italy salvatore.distefano@polimi.it 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

2. Agenda Introduction Crowd-based approaches Crowd Sensing Mobile Crowd Sensing MCSaaS MCS Application 2

3. 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 3

4. 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 4 Crowd-based approaches

5. Crowdsourcing "Crowdsourcing is a type of participative online activity in which an individual, an institution, a non-profit organization, or company proposes to a group of individuals of varying knowledge, heterogeneity, and number, via a flexible open call, the voluntary undertaking of a task. The undertaking of the task, of variable complexity and modularity, and in which the crowd should participate bringing their work, money, knowledge and/or experience, always entails mutual benefit. The user will receive the satisfaction of a given type of need, be it economic, social recognition, self-esteem, or the development of individual skills, while the crowdsourcer will obtain and utilize to their advantage that what the user has brought to the venture, whose form will depend on the type of activity undertaken". 5

6. 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 … 6 Crowdsensing

7. 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 7 User at Front End Web Service at Back End

8. The MCS Paradigm 8 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 !!!

9. MCS Stack 9

10. Mobile Crowdsensing Applications Monitoring common phenomenon… Pollution (air/noise) levels in a neighborhood. Real-time traffic patterns. Pot holes on roads. Road closures and transit timings. …… 10

11. 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 11

12. MCS Challenges 12 Localized Analytics Resource Limitations Privacy Aggregate Analytics Architecture

13. Mobile Crowdsensing: SAaaS possibities MCS app providers may leverage automatic management of SAaaS-enabled infrastructure: no need for targeted ads or direct interaction (app) provider-initiated involvement workflow uptake rates just limited by chosen area of interest and widespread coverage of SAaaS contributors (and by willingness to pay/barter) in typical PaaS fashion: placing a platform layer over Cloud-enabled infrastructure leaving no dependency (either explicit or strictly needed) between the two levels 13

14. MCS as a service - MCSAAS 14

15. MCSaaS - MCS as a Service 15

16. 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 16

17. MCSaaS: a Cloud platform for managing MCS apps on SAaaS infrastructure churn 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 17

18. Mobile Crowdsensing application: PotHole Detector based on two components: an Android app running on volunteer-owned mobiles a Back-End system to collect data, and also filter, analyze and mine it exploiting mobile-carrying volunteering commuters to detect and classify automatically road surface conditions combined sampling of: acceleration data from on-board motion detection sensors geospatial coordinates as provided by the GPS 18

19. Mobile Crowdsensing application: PotHole Detector enables generating a quality map of traversed roads, pinpointing any distress condition and potential presence of potholes performs uninterrupted sampling of parameteres coming from accelerometers computes changes in the sampled values for acceleration (intuitively, when bumping into a pothole on the way, or more generally going down a distressed road surface, these changes may turn out to be hefty) and marks the presence of a potentially critical condition at the corresponding geospatial coordinates info thus acquired to be stored in a centralized DB, as data source for a Web application in order to enable monitoring of roads condition the same information base could be useful for local government and competent authorities to plan carefully targeted maintenance actions and aptly arranging those according to levels of priority most business logic, data filtering and analysis routines reside inside the Web aplication, in order to keep computational duties for involved mobiles at a minimum, e.g. just essential mechanisms and filtering rules to drop false positives 19

20. Mobile Crowdsensing application: PotHole Detector 20

21. Mobile Crowdsensing application: PotHole Detector 21

22. Q&A THANKS! 22