Location Systems for Ubiquitous Computing

1
Location Systems for Ubiquitous Computing

• Jeffrey Hightower and Gaetano Borriello

2
Intro

• Ubiquitous computing
• a person wanting to know where he was when he did
  a particular task
• Help rescue teams
• Customize environment based on location of user
• devices have already been developed
• what they sense and how they go about achieving
  it
• physical attribute used
• size
• power usage
• type of results obtained

3
Physical Position and Symbolic Location

• Physical
• GPS - 473917 N by 1221823 W
• Symbolic
• Abstract , relative to the position of a known
  object
• Provide coarse grained location information
• Derived from Physical-positioning systems
• Linking real-time train positions to the
  reservation and ticketing database can locate a
  person on a train

4
Absolute versus Relative positioning

• Absolute location systems GPS uses a universal
  reference grid
• Two GPS receivers at the same position will show
  the same reading
• In Relative Systems, each receiver has its own
  frame of reference
• Devices that use a particular transmitter form a
  grid relative to that transmitter
• Absolute position can be transformed to a
  relative one relative to another reference
  point

5
Localized Location Computation

• Object we are interested in computes its own
  location
• Ensures privacy
• Does not require the object to transmit
  information for external systems to locate it
• Burden on the object increases so it is better
  left to the external system

6
Accuracy and Precision

• Depend on the distribution of error and the
  density of elements
• Overlapping levels of positioning systems to
  obtain fine grained location information
• Coping dynamically with failures
• Suitability for application at hand

7
Scale

• Coverage of system, the number of objects the
  system can locate per unit area per unit time
• Communication bandwidth is important
• Increasing infrastructure

8
Recognition

• Recognition of located objects to carry out some
  action, like controlling the located device over
  the internet
• Assigning unique IDs to the located objects
• Combine contextual information

9
Limitations

• GPS does not work indoors
• Interference
• Characteristics of underlying technologies

10

• Active Badge
• Active Bat
• Cricket
• RADAR
• Motionstar Magnetic Tracker
• Easy Living
• Smart Floor
• Enhanced 911

11
Active Badge

• Uses diffuse infrared technology - flooding an
  area with infra-red light
• Each badge emits signal with unique id every 10
  seconds that is received by a network of sensors
• Location is symbolic restricted area like a
  room
• Range of several meters
• Has difficulty in presence of sunlight

12
Active Bat

• Infers location based on time of flight of
  ultrasound pulse
• Each bat emits an ultrasound pulse with unique id
  to a grid of receivers
• At the same instant a controller resets the
  receiver
• Orientation is calculated by analysis
• Distance is computed from the time interval
  between the reset and receiving the pulse
• Accurate to within 3cm
• Paging
• Requires large sensor infrastructure

13
Cricket

• fixed ultrasound emitters and mobile receivers
• time gap to receive the signal is also set in the
  pulse to prevent reflected beams
• computation takes place at receiver
• decentralized architecture
• few centimeters of accuracy
• computational and power burden

14
RADAR

• Based purely in software, building on standard RF
  wireless LAN technology
• Uses signal strength and signal to noise ratio
  from wireless devices
• Employs multiple base stations with overlapping
  coverage
• Requires wireless LAN support on objects being
  tracked
• Generalization to multifloored buildings is a
  problem

15
Motionstar Magnetic Tracker

• Uses electromagnetic sensing
• Axial DC magnetic-field pulses are generated
• Position and orientation are found from by
  measuring the response on the three axes
• Less than 1mm spatial resolution and 0.1
  orientation
• Must be within 1-3 meters of transmitter
• Motion capture for animation

16
Easy Living

• System to keep track of a room's occupants and
  devices
• Uses real-time 3D cameras to provide vision
  positioning
• measures location to roughly 10 cm on the ground
  plane, and it maintains the identity of people
  based on color histograms
• Difficult to maintain accuracy
• Aimed for a home environment

17
Smart Floor

• System for identifying people based on their
  footstep force profiles
• Does not need device or tag
• 93 overall user recognition
• High cost factor

18
Enhanced 911

• Locates any phone that makes a 911 call
• reported in most instances with an accuracy of
  100 meters or less
• Can be enhanced for use by cell phone users
• Identifying areas of traffic congestion

19
Future Work

• Integrating multiple systems
• Overlapping levels off sensing
• Increases accuracy
• Ad Hoc Location sensing
• Cluster of ad hoc objects
• Relative or absolute
• Correlation of multiple measurements
• High scalability

20
Choosing a System

• Accuracy based comparison
• Representing error distributions
• Evaluation
• Density of elements
• Prototyping using a simulator
• Quake iii