Wireless Networks Sensors and Social Streams

Dmitry Namiot Lomonosov Moscow State Universitydnamiot@gmail.com

Manfred Sneps-Sneppe Ventspils University Collegemanfreds.sneps@gmail.com

AINA 2013

• a new approach for using wireless sensors on mobile phones for integrating data from social networks• Our model uses Wi-Fi proximity approach as a service• Any existing or even especially created Wi-Fi hot spot could be used as presence sensor that can trigger access for some content published in social networks. • An especially developed mobile application (context-aware browser) can present that information to mobile subscribers.

About

Contents

Introduction

Context and location awareness

Spot Expert (SpotEx)

Social check-ins

Conclusion

Context awareness

Modern applications adopt a context-aware perspective to manage:

a)communication among users and among systems, or between the system and the user,

b) situation-awareness, like modeling location and environment aspects (physical situation) or the current user activity (personal situation)

c) knowledge chunks: determining the set of situation-relevant information, services or behaviors

Sensors and Social Networks

• A typical example: City Sense. Collects sensor data extracted from GPS-enabled cell phones and taxi cabs in order to determine where the people are, and then deliver this information to subscribers with mobile devices. • In general, this application is designed to track important trends in the behavior of people in the city. • But: it introduces own social network. Can we merge sensors with existing networks?

Spatio-temporal streams

• Where-when-what scheme: location, time and topic. • Social stream is a collection of different spatio-temporal-thematic points. Each point has got the following attributes: location, time stamp and topic. Topic here is some content, extracted from the tweets (e.g., hashtag).

• Point = { location, time stamp, topic }• Stream = [ Point1, Point2 … ]

Proximity vs. Location

• Can we replace location with proximity?

• And proximity here is the network proximity. • In other words: use mobile user’s position relatively network nodes (e.g. Wi-Fi access points)• It could be more precise (especially for indoor)• We can use dynamic Wi-Fi access points (e.g. Hotspots on mobile phones) too.

Spot Expert (SpotEx)• It is a perfect example for network proximity as a service• What if we stop our traditional indoor positioning schema on the first stage: detection of Wi-Fi networks?

• This detection actually already provides some information about the location – just due to local nature of Wi-Fi network.

•And as the second step we add the ability to describe some rules (if-then operators, or productions) related to the Wi-Fi access points.

SpotEx

• Our rules will simply use the fact that the particularly Wi-Fi network is detected. And based on this conclusion we will open (read – make them visible) some user-defined messages to mobile terminals.

• Actually it is a typical example for the context aware computing. The visibility for user-defined text (content) depends on the network context.

• This approach uses Wi-Fi proximity

• Any Wi-Fi hot spot works here just as presence sensor.

SpotExSo, our service contains the following components:

• database (store) with productions (rules) associated with Wi-Fi networks

• rule editor. Web application (including mobile web)that lets users add (edit) rule-set, associated with some Wi-Fi network

• mobile applications, that can detect Wi-Fi networks, check the current conditions against the database and execute productions

SpotEx – use cases

The most obvious use cases:• Some shop can deliver deals/discount/coupons right to mobile terminals as soon as the user is near some predefined point of sale.

We can describe this feature as “automatic check-in” for example. Rather than directly (manually or via some API) set own presence at some place (e.g. similar to Foursquare, Facebook Places etc.) with SpotEx mobile users can pull data automaticallyand anonymously

SpotEx – use cases

• Campus admin can deliver news and special announces

• Hyper local news in Smart City projects could be tight (linked) to the public available networks and delivered information via that channel etc.

• The most interesting (by our opinion, of course) use case: Wi-Fi hot spot being opened right on the mobile phone

SpotEx – use cases

• Open Wi-Fi Access Point right in the mobile

• Add (link) proximity rules for this access point exactly

• Rules will define data chunks (info snippets) for users nearby this phone

SpotEx productions

Each rule looks like a production (if-then operator). The conditional part includes the following objects:

Wi-Fi network identity, signal strength (optionally), time of the day (optionally), client ID (MAC-address)History of visits

SpotEx productions

In other words it is a set of operators like:

IF network_SSID IS ‘mycafe’ AND time is 1pm – 2pm THEN { present the coupon for lunch }

It is like expert systemWe can use well known algorithm for the processing: Rete

Check-in

• Just a special form (record, status) in the social networks• They are always a part of the social stream• They contain location information. Either directly (latitude, longitude) or as a link to some predefined place• Based on SpotEx idea about “automatic check-in”: can we replace location with proximity here?

Social Check-in - 1

• Place is just a Wi-Fi fingerprint (Wi-Fi nodes, RSSI)

• Places are dynamical. There is no “directory” for places

• Social check-in is just a Wi-Fi fingerprint again, confirmed (signed) by some social network ID

• Social check-ins are temporal• Social check-ins could be saved outside of the

social stream (to keep privacy). E.g., they are not a part of Facebook news feed, etc.

Social Check-in -2

• In-proximity checkin example

• Saves Wi-Fi fingerprint in the external database

• Each record is signed by the user (e.g., Facebook ID)

Applications for social check-ins

• We can compare Wi-Fi fingerprints and get a list of social IDs (e.g. Facebook IDs) around

• Using social network API we can collect “local” news feed

• This system could be used as a social discovery tool: “show me, who else is here right now”. And it works not only for my existing social circle. E.g., I can see new Facebook’s members around.

Conclusion

• A new model for context-aware data discovery for A new model for context-aware data discovery for mobile users. mobile users. • This model based on the ideas of Wi-Fi and Bluetooth This model based on the ideas of Wi-Fi and Bluetooth proximity and introduces a new form of check-in proximity and introduces a new form of check-in service for social networks. service for social networks. • The proposed check-in service based on network The proposed check-in service based on network proximity rules instead of geo points and lets link proximity rules instead of geo points and lets link together wireless networks information and social together wireless networks information and social streams. streams. • Service can use existing as well as the especially Service can use existing as well as the especially created networks nodes as presence triggers for created networks nodes as presence triggers for discovering the relevant content from social networks.discovering the relevant content from social networks.

About us

International team: Russia - Latvia International team: Russia - Latvia ((Moscow – Moscow – Riga – VentspilsRiga – Ventspils). ). Big history of developing Big history of developing innovative telecom and software services, innovative telecom and software services, international contests awards international contests awards

Research areas are: Research areas are:

open API for telecom, open API for telecom, web access for telecom data, web access for telecom data, Smart Cities, Smart Cities, M2M applications, context-aware computingM2M applications, context-aware computing..