Almost two thirds (63%) of Americans say it is annoying to hear ringing cell phones or cell phone chatter in public places. Ringing of cell phones is a

Almost two thirds (63%) of Americans say it is annoying to hear ringing cell phones or cell phone chatter in public places.

Ringing of cell phones is a big complaint and many times a cause of embarrassment in classrooms and meeting rooms

How about making the environment smart so that it takes care of silencing the cell phones even if the users forget!

Will save some embarrassment for sure, isn’t it?

Infrastructure for Context Driven Pervasive Computing

Applications

Presented by:

Vishakha Gupta

Advisor: Prof. Peter Steenkiste

Reader: Prof. Raj Rajkumar

Information Networking Institute

3

Agenda Goals Scenarios Requirements Concept Thesis Statement Motivation Related Work Architecture Evaluation History

Information Conclusion Limitations Future Work


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Goals

In usual applications and services user has to initiate some action in order to use the results

Smart environment for a better user experience

Focus on area based user tracking in in-building environments

Less attention has been paid to the fundamental and challenging problem of providing capability to an application in defining physical areas −Determine with high probability when the

user is in the area of interest to the application


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Scenarios

When a person enters a secure building, devices monitor his motion and warn him if he goes in a prohibited area, through a warning message passed to his cell phone

In an auditorium, where a show or some program is going to begin, everyone’s cell phone is expected to be turned off or to be in silent mode

When people are seated in the airplane, as the plane is about to take off, the cell phones and other electronic devices (if possible) could receive an interrupt indicating they should turn themselves off.

At places such as a meeting hall, a classroom, a hospital, cell phone rings may cause disturbance. At the same time, people may want to attend their calls. So the devices should be signaled to change over to the silent mode


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Requirements A method to define the regions of interest to

the application

An infrastructure to enable area based tracking for the client devices in an establishment

Need for downloading of software on a handheld or including the APIs necessary for communication in the handheld by the device manufacturers

Authenticity of the code getting downloaded and the source of the messages

No effect on the normal communication or device use

Interoperability and other challenges associated with a distributed system

Generic APIs to help accommodate new applications that are developed


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Concept

I hear: <00:14:6A:5B:95:70, -57> <00:14:6A:5B:97:70, -75> <00:14:6A:5B:98:80, -64>

You seem to be in CIC 1201. Change yourself to

silent mode


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Thesis Statement

Present an infrastructure for context-driven applications enabling them to specify area-based user tracking requirements

Ability to determine with high probability when the user is in the area of interest to the application


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Motivation Minimal change in the infrastructure.

Easy testing and deployment

No requirement to formulate a coordinate system

Flexibility to an application in defining the attributes of an area as needed

No restriction in terms of the shape of an area to be defined by the application


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Related Work

Area aware computing - relatively new concept

Research work that comes really close to the concept presented in this thesis−Area based triggers by Hermann

et. Al.−Fingerprinting using access

points as in PlaceLab project by Intel


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Related Work [2] Other related projects

−RADAR project for in-building user tracking by Microsoft Research

−AURA hybrid space model by CMU

−CRICKET project by MIT


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Terminology Zone – A physical area defined by an

application for its use. For example, the area where cell phones must be turned to silent mode like in an auditorium

Region – Any area in a building which could be a zone

Signature – Tuple consisting of <Access Point MAC, RSSI_min, RSSI_max, Weight> used by the application to define zones in WiFi signal space

Client Signature - Tuple consisting of <Access Point MAC, SSID, RSSI heard> read by a client device from its wireless interface

Region Definition or Rule – A tuple of the form <Region ID, Signature> used in defining zones


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Terminology [2] Location – A tuple of the form <X, Y, Height,

Description> defined keeping in mind a requirement of having actual Euclidean coordinates if needed anytime by the system. Currently we use the description member to make the location more meaningful wherever it is used.

Percentage Match – It’s the probability with which the client signature matches a zone definition using the algorithms described later

Message – It’s a string used as an attribute for the zone, defined by the application if it wants to convey something to the user when he is mapped to a certain zone

Action – The action that the application expects users to perform when they are in a certain zone


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Architecture

Repository

Rule Manager

ListenerSender

Server

Repository Manager

Wireless Device Reader

Sender Listener

UI Component

Client


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Architecture – Offline Zone Definition Repository

− Stores access point, zone and rule information

Repository Manager− Interface for application to provide requisite

information

Access PointAccess Point

MAC

Access Point Information

SSID

Range

Location

Additional Information

ZoneZone

ID

Zone Information

Message

Action


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Architecture – Offline Zone Definition [2]

RuleRule

Zone ID

Rule Information

Number of Access Points in Signature

RuleRule

Zone ID

Rule Information

Number of Access Points in Signature = 2

Access Point MAC Minimum Expected RSSI Maximum Expected RSSI Access Point Weight

Access Point MAC Minimum Expected RSSI Maximum Expected RSSI Access Point Weight


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Architecture – Server

Listener – Listens for client requests consisting of client signature

Rule Manager – −Uses rule and zone information

from the Repository−Uses algorithm to find a matching

zone for the current client signature

Sender – Sends the zone information to client with message and action


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Architecture – Client

Wireless Device Reader – reads wireless card information and forms client signature

Sender – sends client signature to the server for zone matching

Listener – receives zone information from server

UI Component – interacts with the user if required by the application


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Algorithmsbegin procedure find-match

Let A be the best heard access point by the client

Let L denote the client signature

Let M denote the list of zones with signatures consisting of A

loop for all the zones Z in M

store best zone(s) found

end loop

return best heard zone(s)

end procedure

find-percent-match(Z, L)


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Algorithms – Exact Match

begin procedure find-percent-match

count = number of access points in signature S used in definition of Z

loop for all access points B used in S

if (B exists in L and RSSI heard for it is within RSSI_MINA and RSSI_MAXA)

increment match

end loop

percent = match /count * 100

return percent

end procedure


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Algorithms – Deviated Matchbegin procedure find-percent-match


drop_per_deviation = 0.2



increment match

else

dMatch = (1 – (deviation in RSSI from MIN or MAX) * drop_per_deviation)

if dMatch > 0 then match += dMatch

end loop


return percent

end procedure


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Algorithms – Weighted Match





match += WeightA

end loop


return percent

end procedure


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Algorithms – Weighted Deviation Match




match += WeightA

else

dMatch = (1 – (deviation in RSSI) * drop_per_deviation)

if dMatch > 0 then match += (dMatch * WeightA)

else if (dMatch < 0) then

dMatch = exp (-WeightA * deviation in RSSI / 100); match *= dMatch

end loop


return percent

end procedure


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Evaluation – Define Zones


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Evaluation – RSSI Measurement


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Evaluation – Entering Information

Room 105 (Area: 44.6 sq.m) – can be defined as− <00:02:2D:04:68:3B,-80,-70,1.5>;

<00:60:1D:23:C5:B5,-80,-70,1.0>; <00:02:2D:51:A9:0A,-80,-70,1.5>;

Reception (Area: 38.64 sq.m) – can be defined as− <00:02:2D:04:68:3B,-80,-70,1.0>;

<00:60:1D:23:C5:B5,-80,-70,1.25>; <00:02:2D:51:A9:0A,-65,-55,2.0>;

Room 127 (Area: 8.18 sq.m) – can be defined as− <00:02:2D:04:68:3B,-60,-50,2.0>;

<00:60:1D:23:C5:B5,-75,-65,1.0>; <00:02:2D:51:A9:0A,-80,-70,1.0>;


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Evaluation – Comparison of Algorithms


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Evaluation – Comparison of Algorithms [2]


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Evaluation – Comparison of Algorithms [3]


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Evaluation - Conclusion

Deviated Match algorithm better than remaining with number of access points(N) > 3

The number of access points determined by the zone under consideration

The Weighted Deviation Match algorithm shows more consistency in accuracy − Reduces spurious results acquired

due to the exponential degradation − Example on next slide


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Evaluation – Conclusion [2]

At one point, Room 105 matched at Position 1 by Exact Match, Deviation Match and Weighted Match

The Weighted Deviation Match algorithm showed Room 127

Room 127

1

2

3

4

Client signature at 1 – <00:02:2D:51:A9:0A, -76>; <00:02:2D:04:68:3B, -43>; <00:14:1B:5A:22:90, -89>Zone definition for Room 127 – <00:02:2D:04:68:3B,-60,-50,2.0>; <00:60:1D:23:C5:B5,-75,-65,1.0>; <00:02:2D:51:A9:0A,-80,-70,1.0>;Zone definition for Room 105 – <00:02:2D:04:68:3B,-80,-70,1.5>; <00:60:1D:23:C5:B5,-80,-70,1.0>; <00:02:2D:51:A9:0A,-80,-70,1.5>;


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Evaluation - Limitations

Only defined zone is Reception

But Rooms 101, 103 and Lobby also show a match for Reception using any of the four algorithms presented


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Evaluation – Limitations [2]

Only defined zone is Room 127

But the shaded portion on the floor plan also shows a match for Room 127 using any of the four algorithms presented


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History Information

Use past area information to conclude strongly about the present position

Use bluetooth devices to conclude strongly about the present position

New term “Space” - An area that is not defined by the application but which could be of consequence in defining zones −E.g. A corridor in the building which

might be leading to a zone

Clients modified to report any nearby bluetooth devices as well as the previous area matched with a timestamp


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History – Using Space Information

Consider two applications−One has defined Zone Y−The other has defined Zone Z

At time t, the system knows that a device is in Space X (maybe by using one of the signature matching algorithms mentioned earlier)

At time t + 1, the client signature says Space X with timestamp t −Higher probability that user must be in

Zone Y for application 1 while in Zone Z for application 2

−Example follows


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History – Using Space Information [2]

Zone Y

Space X

Zone X


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History - Bluetooth

I hear: <00:14:6A:5B:95:70, -57> <00:14:6A:5B:97:70, -75>Zone A + Zone B Match

I hear: <00:14:6A:5B:95:70, -51> <00:14:6A:5B:97:70, -79>Zone A + Zone B Match

Zone A

Zone BDetermines Zone B

Determines Zone A


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History – New Algorithm


Let bDevice represent a bluetooth device

if timestamp of client signature and server do not differ by MARGIN

if bDevice heard by client and bDevice identifies Zreturn complete match

if Space S heard by client before this iteration and S leads to Z

perform signature based match percent = (weight1 * space match

percent + weight2 * signature match percent) / 2 return percent

perform match as in previous signature based cases

return percent match

end procedure


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Conclusions

Solution for area aware computing using existing infrastructure

Implemented and analyzed four algorithms for WiFi signal space matching of zones−Weighted Deviation Match

algorithm works best in general

Improvement in identifying zones using history information


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Limitations

Zone definitions in WiFi signal space−Configuration of access points−Performance at different times

of day−Varying signal strength

Bluetooth−Chances of having Bluetooth

devices installed


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Future Work Experimental evaluation of history information

Study the scalability of the system by introducing multiple clients −Account for network usage and

computation requirements on the client

Implement an end to end system involving−Download and verification of software on

multiple devices

Study the variation pattern in RSSI to define a model −Define a variable signature depending on

time of day etc. constituting an intelligent zone definition


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43

Thank You


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Implementation - Server


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Implementation - Client

Documents

Almost two thirds (63%) of Americans say it is annoying to hear ringing cell phones or cell phone chatter in public places. Ringing of cell phones is a