SixthSenseRFID based Enterprise Intelligence

Lenin Ravindranath, Venkat Padmanabhan

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RFID Radio Frequency Identification Components

RFID Reader with Antennas Tags (Active and Passive)

Electromagnetic waves induce current Tag responds

Globally unique ID Data

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RFIDApplications

Tracking Inventory Supply Chain Authentication

Mainly an Identification Technology

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SixthSense OverviewGoal Use RFID to capture the rich interaction between

people and their surroundings

Setting Focus on Enterprise Environment People and their interesting objects are tagged

Methodology Track people and objects Infer their inter-relationship and interaction Combine with other Enterprise systems/sensors (Camera,

Presence, Calendar) Provide Useful Services

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Challenges Manual input is error prone and is best

avoided Erroneous mapping Passive Tags are fragile

RFID Passive tags are inherently unreliable Tag Orientation Environment (Metal, Water)

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Key Research Tasks Addressing Challenges

Self-configuring system/Verify manual input Person-Object Differentiation Object Ownership Inference Zone Identification Person Identification Person-Object Interaction

Reliability Multiple Tagging

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People can move on their own Objects move only when carried by a person

Co-movement based heuristic For every tag T, find co-movement tag set {T1, T2..Tn}

m – total inter-zone movement of T mi – total inter-zone movement of Ti ci – amount of co-movement exhibited by Ti with T

Declare the tag with the highest RM as person Eliminate this tags movements Repeat the algorithm till RM is positive Tags with negative RM are objects

Person-Object Differentiation

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Person Identification Find Workspace

Zone where the tag spent most of its time

Log Desktop Login/Active Events

Temporal Correlation Trace of person entering workspace zone Trace of desktop login/active events

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Person Identification

1 1

xyz@microsoft

abc@microsoft

1

12

534

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Object Interaction Identify interaction between person and

objects A person lifted an object A person turned an object

Signal Strength of tag varies Change in distance Change in orientation

Monitor the variation is Received Signal Strength from tags

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0 1.8 3.6 5.4 7.2 9 10.8

12.6

14.4

16.2

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-60

-55

-50

-45

-40

-35

-30

Object XObject YObject Z

RSSI

(dBm

)Time (s)

Interacted

Object Interaction

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Architecture RFID Monitor Enterprise Monitors

Calendar Presence Camera

Database Inference Engine

Person Differentiation Object Ownership Person Identification Object Interaction

API Lookups Callbacks

Applications Annotated Video Enhanced Calendar/IM Lost Object Alert

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Applications Lost object Finder Annotated Security Video Enhanced Calendar and IM Presence RFID based WiFi-Calibration

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Lost Object Finder Inferred object ownership Inferred workspace Raise alarm

When object misplaced and owner moving without it

Query for lost object information I had the object in the evening but not with me

right now

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Semi-Automated Image Catalog Objects Tagged Lift a object and show it before the camera Take a picture Build a catalog (Tag ID, Image)

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Annotating Videos with Events Camera – Video Feed Tagging videos with interesting RFID events

Person lifted an object Person entered workspace

Rich video database Support rich queries

Give me all videos where Person A interacted with Object B

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Enhanced Calendar/Presence Automatic Conference Room booking

If conference room not booked And bunch of people go into the conference room

Enhanced Presence Learn trajectory from one location to another

E.g. Workspace to Conference Room Trajectory Mapping Enhanced User Presence

On the way Lost