Pervasive Location-Aware Computing

Hari Balakrishnan

Networks and Mobile Systems Group

MIT Laboratory for Computer Science

http://nms.lcs.mit.edu/

Why you should care

• Location-awareness will be a key feature of many future mobile applications

• Many scenarios in pervasive computing– Navigation– Resource discovery– Embedded applications, sensor systems– Monitoring and control applications

• The design of good location-aware computing systems cuts across many areas of CS/EE– E.g., sensors, signal processing, networking, mobility, data

management, graphics/visualization, planning, HCI, …– Most of the exciting stuff will happen in the next few years!

Computing

Input OutputProcessing

Network

Networked Computing

Processing+

communication

Processing+

communication

Processing+

communication

Processing+

communication

Networked, Context-Aware Computing

Network

Processing+

communication

Processing+

communication

Processing+

communicationProcessing

+communication

Locationinformation

Sensors

Actuators

Resourceinformation

EnvironmentalContext

Location-Aware Applications

• Human-centric– “Finding” applications

• Embedded– Sensors & actuators– Devices– Monitoring and control

• System should support both forms

This Talk

• Cricket location infrastructure• Some applications• System architecture• Challenges for the future

Cricket

• Architecture for ubiquitous location-sensing– No single location-sensing technology works

everywhere today, particularly indoors

• Integrates variety of sensory information– GPS: wide-open outdoors– Wireless access info: coarse-grained info– RF + ultrasonic trilateration: indoors and in urban

areas

• Sensor-independent location API

Desired Functionality

• What space am I in?– Room 510, reception area, seminar room,…– How do I learn more about what’s in this space?– An application-dependent notion

• What are my (x,y,z) coordinates?– “Cricket GPS”

• Which way am I pointing?– “Cricket compass”

• Goal: Linear precision of a few centimeters, angular precision of a few degrees

Design Goals

• Must determine:– Spaces: Good boundary detection is important – Position: With respect to arbitrary inertial frame– Orientation: Relative to fixed-point in frame

• Must operate well indoors• Preserve user privacy: don’t track users• Must be easy to deploy and administer• Must facilitate innovation in applications• Low energy consumption

Cricket Architecture

Beacon

Listener

Autonomous: No central beacon control or trackingPassive listeners + active beacons facilitates privacyStraightforward deployment and programmability

Autonomous: No central beacon control or trackingPassive listeners + active beacons facilitates privacyStraightforward deployment and programmability

info = “a1”

info = “a2”

Estimate distancesto infer location

Beacons onceiling

B

SPACE=NE43-510 ID=34COORD=146 272 0MOREINFO= http://cricket.lcs.mit.edu/

Obtain linear distance estimatesPick nearest to infer “space”Solve for mobile’s (x, y, z)Determine w.r.t. each beacon and deduce orientation vector

Obtain linear distance estimatesPick nearest to infer “space”Solve for mobile’s (x, y, z)Determine w.r.t. each beacon and deduce orientation vector

Machinery

Mobile deviceMobile device

Cricketlistener

• A beacon transmits an RF and an ultrasonic signal simultaneously– RF carries location data, ultrasound is a narrow

pulse

• The listener measures the time gap between the receipt of RF and ultrasonic signals– A time gap of x ms roughly corresponds to a

distance of x feet from beacon– Velocity of ultrasound << velocity of RF

• The listener measures the time gap between the receipt of RF and ultrasonic signals– A time gap of x ms roughly corresponds to a

distance of x feet from beacon– Velocity of ultrasound << velocity of RF

Determining Distance

RF data(space name)

Beacon

Listener

Ultrasound(pulse)

Multiple Beacons Cause Complications

• Beacon transmissions are uncoordinated• Ultrasonic signals reflect heavily• Ultrasonic signals are pulses (no data)

These make the correlation problem hard and can lead to incorrect distance estimates

• Beacon transmissions are uncoordinated• Ultrasonic signals reflect heavily• Ultrasonic signals are pulses (no data)

These make the correlation problem hard and can lead to incorrect distance estimates

Beacon A Beacon B

tRF B RF A US B US A

Incorrect distance

Listener

Solution

• Carrier-sense + randomized transmission– Reduce chances of concurrent beaconing

• Bounding stray signal interference– Envelop all ultrasonic signals with RF

• Listener inference algorithm– Processing distance samples to estimate location

Bounding Stray Signal Interference

• Engineer RF range to be larger than ultrasonic range– Ensures that if listener can hear ultrasound,

corresponding RF will also be heard

• Engineer RF range to be larger than ultrasonic range– Ensures that if listener can hear ultrasound,

corresponding RF will also be heard

tRF A US A

t

S/b

r/v (max)

S = size of space advertisementb = RF bit rater = ultrasound rangev = velocity of ultrasound

Bounding Stray Signal Interference

(RF transmission time) (Max. RF-US separation at the listener)

S r

b v

• No “naked” ultrasonic signal can be valid!• No “naked” ultrasonic signal can be valid!

Estimation AlgorithmWindowed MinMode

Distance(feet)

Frequency A B

5 10

5

109Majority

6.47.2Mean (feet)

86Mode (feet)

86Actual distance (feet)

BA

Orientation relative to Bon horizontal plane

Mobile device(parallel to horizontal plane)

Beacons onceiling

B

Cricket listener withcompass hardware

Orientation

Trigonometry 101

d1 d2 z

sin = (d2 - d1) / sqrt (1 - z2/d2)where d = (d1+d2)/2

Heading

Beacon

Idea: Use multiple ultrasonic sensorsand estimate differential distances

CricketCompass

Two terms need to be estimated: 1. d2 – d1 2. z/d (by estimating coordinates)

Differential Distance Estimation

• Problem: for reasonable values of parameters (d, z), (d2 - d1) must have 5mm accuracy– Well beyond all current technologies!

d2 d1

= 2(d2 – d1)/tL

Beacon

Estimate phase difference between ultrasonic waveforms!

Beacons onceiling at known

coordinates

B

Coordinate Estimation

vt1 vt2 vt3 vt4

(x,y,z)

Four equations, four unknownsVelocity of sound varies with temperature, humidity

Can be “eliminated” (or calculated!)

Beacon Placement

I am atB

Room A Room B

Totally arbitrary beacon placement won’t demarcate spaces correctly

Correct Beacon Placement

Room A Room B

x x

I am atA

• Position beacons to detect the boundary

• Multiple beacons per space are possible

System Configuration & Administration

• Password-based authentication for configuration

• Currently, coordinates manually entered• Auto-configuration algorithm being developed• MOREINFO database centrally managed with

Web front-end– Relational DBMS– Challenge: queries that don’t divulge device

location, but yet are powerful

Ultrasonicsensor

RF antenna

Ultrasonicsensor

RF module (rcv)

Atmelprocessor

Listener Beacon

RF module (xmit)

RS232i/f

Cricket v1 Prototype

Host software libraries in Java; Linux daemon (in C) for Oxygen BackPaq handhelds

Several apps…

Deployment

Some Results

• Linear distances to within 6cm precision• Spatial resolution of about 30cm• Coordinate estimation to within 6cm in each

dimension• Orientation to within 3-5 degrees when angle to some

beacon < 45 degrees• Several applications (built, or being built)

– Stream redirection, active maps, Viewfinder, Wayfinder, people-locater

– Scalable location-aware monitoring (SLAM) apps: MIT library book tracking, asset management, MIT physical plant maintenance

Where am I?(Active map)

What’s near me? Find this for me

(Resource discovery)

“Print map on a color printer,” and system sends data to nearest available free color printer and tellsyou how to get there Location by “intent”

How do I get to Jorg’s office?

Large-Scale Monitoring

Response time

Scale(# sensors)

Days/Hours Minutes Seconds

Irrigation

Physical plantRepair orders

Library usage

Power, thermalMonitoring & control

Asset tracking

Fire detectionAssisted evacuation

Cricket networkauto-configuration

HazMat responseLocal navigation

Motion detectionLeaks, floods

Lab equipmentmonitoring

Personal safetyTraffic, parking

104

105

106

107

Requirements

• Ubiquitous location-sensing• Heterogeneous sensor networking/comm. protocols• Resource discovery• Event handling• Query processing• Spatial databases• Mapping and representation• Navigation• User interfaces

Cricket beacons(Pervasive)

Fixed sensor proxy (sensor integration, pruning)

Mobile sensor proxyEvent-handling

& resource discoverynetwork

Application event handlers(Distributed)

Data stores

Tag reader

Sensors & actuators

Actions

Events

SensorProxy

Tagged books, equipment

Strawman Architecture

Summary

• Location-aware computing poses numerous interesting challenges for CS– An important component of pervasive computing– Integrating real-world information– App spectrum from HCI Embedded apps

• Cricket provides location information for mobile, pervasive computing applications– Space, position, orientation– Flexible and programmable infrastructure– Deployment and management facilities

Collaborators

• Bodhi Priyantha• Allen Miu• Ken Steele• Rafael Nogueras• Seth Teller• Steve Garland• Dorothy Curtis• Omar Aftab• Erik Demaine• Mike Stonebraker

http://nms.lcs.mit.edu/