The Cricket Indoor Location System Hari Balakrishnan Bodhi Priyantha, Allen Miu, Jorge Nogueras, John Ankcorn, Kalpak Kothari, Steve Garland, Seth Teller MIT Laboratory for Computer Science

Motivation Location-awareness will be a key feature of many future mobile applications Many scenarios in pervasive computing –Active maps –Resource discovery and interaction –Way-finding & navigation –Stream redirectors Cricket focuses mainly on indoor deployment and applications

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 tells you how to get there Location by “intent”

What’s in this direction? (Viewfinder) Point-and-use UIs

How do I get to Satya’s office? How do I get to Compaq’s booth at Comdex?

Desired Functionality What space am I in? –Room 510, reception area, Compaq’s booth,… –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”

Design Goals for Cricket 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

System Components Location inference modules –Hardware, software, algorithms for space, position coordinates, orientation Programming (using) Cricket –API; language-independent “RPC” –Customized beaconing Deploying and managing a Cricket deployment –Configuration, security, data management

Cricket Architecture Beacon Listener No central beacon control or location database Passive listeners + active beacons preserves privacy Straightforward deployment and programmability No central beacon control or location database Passive listeners + active beacons preserves privacy Straightforward deployment and programmability info = “a1” info = “a2” Estimate distances to infer location

Beacons on ceiling B  NE Obtain linear distance estimates Pick nearest to infer “space” Solve for mobile’s (x, y, z) Determine  w.r.t. each beacon and deduce orientation vector Obtain linear distance estimates Pick nearest to infer “space” Solve for mobile’s (x, y, z) Determine  w.r.t. each beacon and deduce orientation vector Machinery Mobile device Cricket listener

MOREINFO Database NE Space ID INSName Aura MOTD etc. Server(Oxygen) App DB Query Centralized DB key to simple administration

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 ultra sound << 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 ultra sound << 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 t RF BRF AUS 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 t RF AUS A

t S/b r/v (max) S = size of space advertisement b = RF bit rate r = ultrasound range v = 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!

Bounding stray signal interference Envelop ultrasound by RF Interfering ultrasound causes RF signals to collide Listener does a block parity error check –The reading is discarded... Envelop ultrasound by RF Interfering ultrasound causes RF signals to collide Listener does a block parity error check –The reading is discarded... t RF AUS A RF BUS B

Preventing repeated interactions Randomize beacon transmissions: loop: pick r ~ Uniform[T 1, T 2 ]; delay(r); xmit_beacon(RF,US); Optimal choice of T 1 and T 2 can be calculated analytically –Trade-off between latency and collision probability Erroneous estimates do not repeat

Estimation Algorithm Windowed MinMode Distance (feet) Frequency A B Majority Mean (feet) 86Mode (feet) 86Actual distance (feet) BA

Orientation relative to B on horizontal plane Mobile device (parallel to horizontal plane) Beacons on ceiling  B Cricket listener with compass hardware Orientation

Trigonometry 101 d1d2 z  sin  = (d2 - d1) / sqrt (1 - z 2 /d 2 ) where d = (d1+d2)/2 Heading Beacon Idea: Use multiple ultrasonic sensors and estimate differential distances Cricket Compass 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)/ t L Beacon Estimate phase difference between ultrasonic waveforms!

Making This Idea Work d1 t 3  d2 d3 4  Estimate 2 phase differences to uniquely estimate d2-d1 Can do this when L 12 and L 23 are relatively-prime multiples of  L 12 L 23 Beacon

Beacons on ceiling at known coordinates  B Coordinate Estimation vt 1 vt 2 vt 3 vt 4 (x,y,z) Four equations, four unknowns Velocity of sound varies with temperature, humidity Can be “eliminated” (or calculated!)

Deployment: Beacon Placement Considerations Placement should allow correct inference of space –Boundaries between spaces need to be detected Placement should provide enough information for coordinate estimation –No 4 beacons on same circle on a ceiling –At least one beacon must have  < 40 degrees –sin  = (d2 - d1) / sqrt (1 - z 2 /d 2 ), so  goes as tan 

Problem: Closest Beacon May Not Reflect Correct Space I am at B Room ARoom B

Correct Beacon Placement Room ARoom B xx I am at A Position beacons to detect the boundary Multiple beacons per space are possible

System Administration Password-based authentication for configuration Currently, coordinates manually entered –Working on algorithm to deduce this from other beacons MOREINFO database centrally managed with Web front-end –Relational DBMS –Challenge: queries that don’t divulge device location, but yet are powerful

Ultrasonic sensor RF antenna Ultrasonic sensor RF module (rcv) Atmel processor ListenerBeacon RF module (xmit) RS232 i/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, smart meeting notifier,… Probably no single killer app, but a whole suite of apps that might change the way we do things

Alternative Architecture (Active Badge, Bat Systems) Networked sensor grid Location DB ID = u ID = u? Responder Problems: privacy; administration; scalability; deployment cost Problems: privacy; administration; scalability; deployment cost

Comparisons Active Badge BatRADARCricket Tracking?Yes DependsNo DeploymentCentral controller + wired IR sensors Central controller + wired RF /USsensors RF signal map; great radios Beacon placement; wireless Spatial resolution Room? (linear = few cm)Room30cm (linear 5cm) OrientationNo Yes; 3-5 degree prec. ScalabilityAll devices transmit periodically All devices must use same RF net Devices passive; distributed scheduling

Summary Cricket provides location information for mobile, pervasive computing applications –Space –Position –Orientation Flexible and programmable infrastructure Deployment and management facilities Starting to be used by other research groups