The Smart PartyThe Smart Party A Personalized Location-Aware Multimedia A Personalized Location-Aware Multimedia

ExperienceExperience

The Smart PartyThe Smart Party A Personalized Location-Aware Multimedia A Personalized Location-Aware Multimedia

ExperienceExperienceKevin Eustice Nam Nguyen

V. Ramakrishna

Dr. Leonard Kleinrock Dr. Peter Reiher

Location-Driven Interactive Fiction Intelligent Museum Gallery

Access annotation, shared content from

tour group

Localize within gallery and determine objects of interest

The Panoply MiddlewareFunctions

• Secure sphere management: discovery, formation and reconfiguration• Scoping event interest and dissemination• Providing primitives for sphere collaboration• Dynamic management of policies and system state• Inter-sphere interaction and dynamic access control through negotiation• Management of a database of vouchers: electronic credentials that certify

arbitrary properties of a sphere• Provide primitives for the design of social- and location-sensitive applications

like the Smart Party

Other Supported Location-Sensitive Social Applications Our Vision

Dynamic Playlists and Music Transfers

Inference of Location Context

Device Configuration & Collaboration

Socially Aware Technology

Spheres of Influence• Automatically discovers and organizes devices into groups, or spheres, based on: social groups, physical location or proximity, task, network

• Manages: network connectivity, service discovery, location and social context

Location Sphere

Personal Sphere

Social Sphere

• Produce better user experience by making mobile consumer devices cooperate when in proximity

• Bring people together; don’t keep them apart• Leverage preferences and desires of individual users• Use groups and Panoply for organization & management

• Mobile ubiquitous environment is complex and unpredictable, requiring better tools :

• That allow simplifying generalizations, like spheres of influence

• For debugging and evaluation of complex cooperation and competition scenarios

Party guests carry mobile devices with songs and preferences

• Goal: Maximize user satisfaction through collaboration

• Criteria for music selection: song, artist, genre, album, period

Protocol• Room requests song

suggestions from users• Room makes selection;

requests song delivery• User device possessing

that song delivers it to the playback device

• Songs are cached for efficient bandwidth use

Iterative Context Refinement• Mapping observed network to party location• Trigger appropriate application that runs on guests’ mobile devices

Digital Credentials• Host provides vouchers to guests as invitations prior

to the party

Dynamic Collaboration• Negotiation between guest

device and server allows user into the party

• Deliver map of <network, rooms> to guest devices

• Switch rooms based on the map as guest moves around

• Collaborates with room servers and other devices for musical experience

Social Sphere (Team

B)

Location Sphere

(Westwood)

Social Sphere(Team A)

Customized Location and Group-Aware Experience for Individual Visitors and Tour Groups

Team-driven Non-Linear Narrative Dynamically Affected by User Actions at Designated Locations

Each Room• Maintains a dynamic playlist• Plays music that represents the collective preference of its current

occupants

Semantic Maps• Associate arbitrarily sized

semantic regions with observed wireless networks

• Semantic regions: Family, Living and Dining Rooms

Localization Scheme• A combination of scene analysis

and attenuation monitoring

• Device activates appropriate voucher based on the detected environment

• Voucher indicates which network to join

• Observed signal strengths from nearby 802.11 wireless access points are characteristic to a semantic region

Advantages of Localization Technology• Requires no deployment of custom hardware• Can distinguish semantic regions on the basis of altitude, unlike GPS

• Need to build map through observations prior to inference

Rich User Experience• Intersection of social

group and location contexts

Dynamic Interactions• Showcases different models:

cooperation, competition, even active opposition

Reconciling Guest Preferences and Selecting Songs

• Basic round-robin selection• Dynamic user voting

• Leader-based• Democratic model

Important Metrics of Success• Fairness: give everyone an equal chance to suggest a song of his choice• Satisfaction: provide better average user experience over a period of time • Occasional tradeoff required between these metrics

I’ve joined the Party!

Looks like there’s a Party going on!

I can see the Party environment!

Found a Party voucher!

VOUCHER

Delivering Map of Party Locations

LIVING ROOM

DINING ROOM

FAMILY ROOM

OUTSIDE THE PARTY ENVIRONMENT

INSIDE THE PARTY ENVIRONMENT

ROCK

JAZZ

JAZZ

JAZZ

I can’t stand the music here! The dining room is

better suited to my tastes.

ROCK

JAZZ

HIP-HOP

SONG PLAYLIST

SONG PLAYLIST

HIP-HOP

ROCK

SONG PLAYLIST

A ubicomp application to dynamically customize the music played at a party to the tastes of the party-goersA ubicomp application to dynamically customize the music played at a party to the tastes of the party-goers

This research was supported by the National Science Foundation (NSF): Grant # CNS 0427748