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WebCall - A Rich Context Mobile Research Platform Zhigang Liu, Hawk Yin Pang, Jun Yang, Guang Yang, Peter Boda (Special thanks to August Joki) Nokia Research.

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Presentation on theme: "WebCall - A Rich Context Mobile Research Platform Zhigang Liu, Hawk Yin Pang, Jun Yang, Guang Yang, Peter Boda (Special thanks to August Joki) Nokia Research."— Presentation transcript:

1 WebCall - A Rich Context Mobile Research Platform Zhigang Liu, Hawk Yin Pang, Jun Yang, Guang Yang, Peter Boda (Special thanks to August Joki) Nokia Research Center 10/27/09

2 Outline Introduction System Architecture Features ·Viral Distribution ·Context Sharing ·Localization (Outdoor/Indoor) ·Human-Powered Q&A ·Privacy Control Lessons Learned Future Work

3 Introduction “Social network” is quite a buzzword these days. … but, one of the largest and most important social networks has long been in your pocket - i.e. the phone book or contacts. Our goal - further socialize the phone book ·Utilize sensing capabilities on modern mobile phones to share context (beyond content upload/download and status update). ·Enable easy R&D prototyping of mobile social apps for other researchers on a common platform and framework.

4 WebCall Architecture Name of “WebCall” came from past work but has since evolved. Client-server architecture on Symbian Client ·Nokia Web Run-Time (WRT): WebKit-based widget system ·HTTP server in PyS60 to serve local resources Server ·Apache HTTP server ·MySQL database ·Django framework in Python to implement service logic ·All logic is implemented on server; client needs no update when new features are added.

5 People - Places - Stories 8/28/2015 © 2008 Nokia / PPB5 STORIESPLACESPEOPLE [flickr use Savannah Grandfather]

6 Viral Distribution - Invitation Many social networks fail to grow to the “tipping point”. WebCall provides an invitation mechanism right in the contacts. ·Inviter sends invitation via SMS with embedded registration link. ·Invitee clicks on link to register and download WebCall app. ·WebCall server keeps track of inviter/invitee relations. A crucial way to bootstrap service

7 Viral Distribution - Registration Mobile-optimized registration process ·New user follows link in invitation SMS to registration page. ·Some fields are pre-populated for quick registration. ·Links are provided for easy verification and download.

8 Context Sharing WebCall users may share their contextual information with friends. Extensible - new information can be added easily. What we have so far ·Location ·Picture ·Business Card ·Calendar ·Weather (3rd party plug-in) ·Activity (3rd party) ·PEIR - Personal Environmental Impact Report (3rd party) ·Advertising (3rd party)

9 Localization - Indoor Power-controllable Bluetooth tags are deployed throughout our office. ·Tag locations are stored in DB. ·Power is controlled to achieve room-level accuracy. ·This was the quickest way for us to experiment. ·Bluetooth LP is expected to come soon.

10 Localization - Outdoor Cell-ID-based localization ·GPS is too power hungry. ·We only need coarse resolution. Several open databases are used. ·Open Cell ID ·ZoneTag ·GeoNames (for reverse geo-coding) Coarse outdoor location can be used for weather/time-zone mashups, etc.

11 Human-Powered Q&A User may post simple questions to WebCall community. Questions are routed to real people who may have the best answers. ·Match personal history and expertise with questions Multiple-choice questions make it easy to use on mobile phones.

12 Privacy Control Privacy level of each feature may be individually set. Groups may be defined to allow flexibility.

13 Lessons Learned Deployment of indoor localization is challenging ·Bluetooth range (i.e. transmission power) is difficult to fine tune Flexible/extensible database design is crucial. ·We face requests of new features throughout development. ·Database schema in constant evolvement. Mobile widget systems are still in infancy. ·Nokia WRT 1.0 lacks access to local resources. ·Latest WRT adds certain access but is still limited. User study should start early.

14 Future Work User study Research trial and scalability study Machine learning for better Human Q&A User behavior prediction

15 Video Demo


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