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Presentation: Location in ubiquitous computing

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Location in Ubiquitous Computing, …

Location in Ubiquitous Computing,
Approaches to Determining Location, Location Technologies, Location Systems Applications


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  • Inclient-basedlocationsystem, device computes it ownlocationbyusingsignalsthatcomesfromthesatelliteor a network. GPS can be given as an example. A navigation device calculatesitspositionbyusingreceivedsignalsfrom at least 4 GPS satellites.In network-basedsystems, network infrastructurewillcalculatethedevice’slocation. It is commonlyused in thebuildingstodetectwhere is thuser. The device which is carriedorwornby a person as badgesendsinfraredsignalstothedeployed sensor networks in thebuilding.In network assistedlocationsystems, both device andtheinfrastructuretakeplace in calculatingtheposition. As an example, assisted GPS can be given.The device calculatesitsownlocationbyusingagain GPS signalsandalsoadditionalinformation is takenfromthecellular network infrasturture(usually network operator) tospeedupthefindingthesatellites.Themainadvantage of theclientbasedlocationsystem is that it forbidsthetransmittingany data tooutsidefromthe device. Sotheprivacy is protected.But the as a disadvantage, our device has touseitsownprocessingandstoragecapabilities, whichcausestoshortage of thebattery life.Inothersystems, yourplace is knownfromtheinfrastructure.
  • Wewill talk aboutsixfundementalapprocahesfordeterminingthelocation of a device. Thesearelistedhere.Some of thesetechniquesrequiresoneormorereferencepointswhosepreciselocation is known in advance. Examplerefencepointsare GPS, wifiaccesspointsor a cellulartower.
  • Based on the general concepts and techniquessignaling tech-nology (e.g., IR, RF, load sensing, computer vision, or audition), line-of-sight requirements, accuracy, and cost of scaling
  • An important consideration is theperformance or accuracy of the system and its resolution (e.g., low resolution for weather forecasts and high resolution for indoor navigation).At the same time, one must consider the infrastructure requirements toevaluate the ease of deployment, cost and installation, and maintenanceburden. (simultaneously deploying, cost for ordinary home-owners vs companies)Spectral requirements (in hospitals against RF IR preferred)
  • An important consideration is theperformance or accuracy of the system and its resolution (e.g., low resolution for weather forecasts and high resolution for indoor navigation).At the same time, one must consider the infrastructure requirements toevaluate the ease of deployment, cost and installation, and maintenanceburden. (simultaneously deploying, cost for ordinary home-owners vs companies)Spectral requirements (in hospitals against RF IR preferred)
  • fully operational in 1994. started at 1973.GPS first originated for military applications, but today, GPS-based solutions permeate throughout many civilian and consumer applications, such as in-car navigation systems, marine navigation, and fleet management services.Civilian GPS has a median accuracy of 10 metersoutdoor, but areas with substantial occlusions, such as tall buildings andlarge mountains can reduce the accuracy of the system.30 healthy, 2 old satellite
  • These GPS satellites transmit data over various radio frequencies, designated as L1, L2, etc. Civilian GPS uses the L1 frequency of 1575.42 MHz inthe ultrahigh frequency band.
  • Unlike the GPS satellites, GPS receivers do not have atomic clocks andare not synchronized with the GPS satellites. therefore, a GPS receivercalculates the time difference of arrival (TDOA) using the timing slackrequired to synchronize the GPS receiver’s generation of a pseudorandomID code with those being transmitted by the satellite to determine the sig-nals’ travel time. To determine its location, the receiver applies hyperboliclateration in 3-D using the estimated TDOA values. In addition, a fourthsatellite is required to correct any synchronization errors.some factors the can degradethe quality of the GPS signal originating from the satellites:Multipath—occurs when the GPS signal is reflected off tall build-ings, thus increasing the time-of-flight of the signal.Too few satellites visible—occurs when there are major obstructions(e.g., GPS does not work well indoors or underground). Atmospheric delays—signals can slow as they pass through theatmosphere.predict and model the atmospheric delays and apply a constant correctionfactor to the received signal. !e other strategy is to increase the numberof channels in the receiver to allow for more satellite signals to be seen. Arecent system, called differential GPS, uses a collection of terrestrial beaconsto emit correction codes (using long wave radio between 285 and 325 kHz) inmultipath-prone areas. the accuracy of differential GPS has been shown tobe 1.8 meters at least 95% of the time (LaMarca and de Lara, 2008). Anotherapproach called Real-Time Kinematic GPS uses phase measurements fromexisting GPS signals to provide receivers with real-time corrections.
  • 1992The badge transmits a unique code via a pulse-width modulated IR signal tonetworked sensors/receivers deployed throughout a building. !e ActiveBadge uses 48-bit ID codes and is capable of two-way communication.
  • 1997Like push vs pullPassive betterBat vs cricketMultiple tags must coordinate their pulses so as not to interfere with each other’s time-of-flight calculations.The system supports 75 tags being tracked in a 1000 square meters space consisting of 720 receivers.
  • Given three or more measurements to the receivers, the 3-D position of the tagcan be determined using trilateration.negligible RF trip
  • Multiple tags must coordinate their pulses so as not to interfere with each other’s time-of-flight calculations.The system supports 75 tags being tracked in a 1000 square meters space consisting of 720 receivers.instrumentation to space,
  • 2000
  • at leasttwo Ubisensors
  • networking between sensors
  • 2000RADAR system implements a location service using the information obtained from an already existing 802.11 WiFi network.RADAR uses the RF signal strength [also knownas the received signal strength indicator (RSSI)] as an indicator of the dis-tance between an AP and a receiver. the major advantage of this approachis that a consumer does not have to purchase any specialized equipmentand can still benefit from a location-aware application. For example, exist-ing devices, such as WiFi-enabled mobile phones, PDAs, or laptops, can berepurposed as a receiver or tag.
  • 2000RADAR system implements a location service using the information obtained from an already existing 802.11 WiFi network.RADAR uses the RF signal strength [also knownas the received signal strength indicator (RSSI)] as an indicator of the dis-tance between an AP and a receiver. the major advantage of this approachis that a consumer does not have to purchase any specialized equipmentand can still benefit from a location-aware application. For example, exist-ing devices, such as WiFi-enabled mobile phones, PDAs, or laptops, can berepurposed as a receiver or tag.has a known median error of 5 meters and a 90 percentile resolu-tion of 15–20 meters
  • 2005Place Lab runs on commodity devices such as notebooks, PDAs, and mobile phones, and determines their position using radio beacons, such as 802.11 APs, GSM cellphone towers, and fixed Bluetooth devices that are already deployed in the environment
  • 2005Wigle.net and Worldwidewardrive.org are some examples of war driving repositoriesthat contain millions of known APs.A similar effort was also started in Japan by the Sony Computer ScienceLaboratory called PlaceEngineTM (http://www.placeengine.com/en). Place Engineprovides a mechanism for a community of users to update 802.11 beaconpositions and the ability to track the location of any WiFi-enabled device.Place Lab also inspired commercial products such as Skyhook (http://www.skyhookwireless.com/) and Navizon (http://www.navizon.com/).
  • Although this approach only infers the locationof the beacons, it has the added benefit that millions of beacon estimateshave already been determined. thus, this allows the ability to scale a loca-tion tracking system much more quickly despite the loss in accuracy. thisapproach has shown a median accuracy of 20–30 meters in large cities.
  • 2006, 2008
  • drawbacks to relying on public infrastructure or thedeployment of many beaconsPowerLine Positioning is the first example of a whole-house or whole-building indoor localization systemthat repurposes the electrical system.Depending on the location of the tag, the detected signal levelsprovide a distinctive signature, or fingerprint, resulting from the densityof electrical wiring present at the given location and the distance from theplug-in module!ese modules inject a mid-frequency (300–1600 kiloHertz), attenuated signal throughout the electricalsystem of the home. Both modules continually emit their respective signalsover the power line, and location tags equipped with specially tuned tagssense these signals in a building and relay them wirelessly to a receiver inthe building. Depending on the location of the tag, the detected signal levelsprovide a distinctive signature, or "ngerprint, resulting from the densityof electrical wiring present at the given location and the distance from theplug-in module. PowerLine Positioning is capable of providing subroom-level positioning for multiple regions of a building. !e current PLP systemhas a median error of 0.75 meters and a 90 percentile accuracy of 1 meter
  • These modules inject a mid-frequency (300–1600 kiloHertz), attenuated signal throughout the electricalsystem of the home. Both modules continually emit their respective signalsover the power line, and location tags equipped with specially tuned tagssense these signals in a building and relay them wirelessly to a receiver inthe building. Depending on the location of the tag, the detected signal levelsprovide a distinctive signature, or fingerprint, resulting from the densityof electrical wiring present at the given location and the distance from theplug-in module. PowerLine Positioning is capable of providing subroom-level positioning for multiple regions of a building. !e current PLP systemhas a median error of 0.75 meters and a 90 percentile accuracy of 1 meter
  • 1997This heel-to-toe transfer time and heel/toe GRF values canbe used to calculate a footstep signature. ActiveFloor uses these featuresfrom the footstep signatures to build a hidden Markov model in order toidentify the person. For further reading, a similar approach is also used bythe Smart Floor project (http://www.cc.gatech.edu/fce/smartfloor/).When an individual walks on the surface, the reac-tion that the load sensors produce in response to the weight and inertia of abody in contact with the *oor is called the ground reaction force (GRF) (inthis case, the person’s foot)
  • 2008Disruptionsin home air*ow caused by human movement through the house, espe-cially those caused by the blockage of doorways and thresholds, result instatic pressure changes in the HVAC air handler unit. !e system detectsand records this pressure variation using di#erential sensors mounted onthe air "lter and classi"es where certain movement events are occurring,such as an adult walking through a particular doorway or the openingand closing of a door.
  • 2000 oncameras and computer vision techniquesdistinctive textures in the pair of images to determine which points from the left cameraimage corresponds to a particular point in the right camera image.Blob detection and background subtraction techniques are used to infer the location of moving objects (usuallypeople) in the camera’s view.
  • Challenge of building and maintaining location-aware middleware and location-aware back-end services from limited existing solutions. making the informationavailable to third-party applications in a scalable and privacy-preserv-ing manner.Opportunity For instance, although the median error of GPS is 10 meters, the combined solu-tion of GPS and European’s global navigation satellite system called Galileo(as soon as it comes online) should yield a median accuracy of 1.5 meters.For example, a recent study showed that users want plausible deni-ability in a location system (Iachello et al., 2005). Another study showedthat people’s preferences for disclosing location information differs basedon many parameters, including the location of the user and the other per-son, the current user activity, and the relationship between the user andthe other person
  • Transcript

    • 1. Location in Ubiquitous Computing Fatih Özlü12.12.2012 Bilgehan Kürşad Öz
    • 2. OUTLINE 1. LOCATION TECHNOLOGIES • Introduction • Location Representation • Infrastructure&Client-Based Location Systems • Approaches to Determining Location • Error Sources in Location Systems 2. LOCATION SYSTEMS • Global Positioning System, Active Badge, Active Bat, Cricket, UbiSense, RADAR, Place Lab, PowerLine Positioning, ActiveFloor, Airbus, Tracking with12.12.2012 Cameras
    • 3. Introduction Examples Determining location Entertainment,• Specific location Navigation,• Context information Asset tracking,• Context aware Healthcare monitoring, applications Emergency response Trade-offs: accuracy, range and cost 12/12/2012
    • 4. Location Representation FORMS: • Absolute • Relative • Symbolic• Indoor Location 12/12/2012
    • 5. Infrastructure&Client-Based Location Systems THREE CLASSES of LS • LOCATION• client-based PRIVACY  Gps• network-based X  Active Badge • Battery Life• network-assisted • Processing and  aGps Store Capability 12.12.2012
    • 6. Approaches to Determining Location reference points>1• Proximity GPS satellite• Trilateration WiFi access point Cellular Tower • Time of Flight • Signal Strength Attenuation• Hyperbolic Lateration• Triangulation• Dead Reckoning 12/12/2012
    • 7. Proximity• device vs reference point • NFC in cms• closeness of a device examples • Bluetooth 10ms• more RP -> more accuracy • WiFi 100ms • Cellular phone kms 12/12/2012
    • 8. Trilateration• distance between a device • intersections of reference and a number of point circles reference points • types:  time of flight of signal  attenuation of the strength of the signal12.12.2012
    • 9. Trilateration / Time of Flight KNOWN NEEDS• Speed of Sound : • precise clock 344 meters per second in 21 C synchronization• Speed of Light : 299,792,458 meters per second • instead round trip delayEASY TO CALCULATE! X = V.t EXAMPLES:radio or light signal for light, 12.12.2012 ultrasonic pulse for sound
    • 10. Trilateration /Signal Strength Attenuation-decrease of the signal’s Challengesstrength by factor of 1/r² -signal propagation-r:distance from source medium -reflaction, diffraction,changin g direction
    • 11. Hyperbolic Lateration CALCULATION• time difference between signal arrival times to more 3 rp.
    • 12. Triangulation the angle of arrival (AOA) of signals to reference points !angle measurement errors.12.12.2012
    • 13. Dead Reckoning USES DEPENDS ON• previously known accuracy of speed and direction, location use of accelemators for• elapsed time acceleration, odometers for distance, gyroscope for• direction direction• average speed 12.12.2012
    • 14. Error Sources Sources of Errors AIM •Incorrect reference point• produce accurate coordinates location estimates •Delay in signal •Clock synchronization •Multipath •Geometry 12.12.2012
    • 15. LOCATION SYSTEMS• Based on the generalconcepts discussed• Commercial & researchsystems• Historically importantand current systems http://www.toasystems.com/• Differing characteristicsamong the solutions12.12.2012
    • 16. Characteristics Metrics for Evaluationhttp://www.army- • Scalability • Resolutiontechnology.com/features/feature121877/feature121877-1.html • Active vs. Passive • Centralization • Infrastructure http://www.pixavi.com/systems-wireless- telemetry.html 12.12.2012
    • 17. Characteristics (cont’d)Properties Concerns• Scalability • Indoor/Outdoor,• Resolution Pervasiveness• Active vs. Passive • Accuracy, Performance• Centralization • Initiating, Tag Carrying• Infrastructure • Privacy Concerns • Multiple Deployment, Cost 12.12.2012
    • 18. Global Positioning System GPS• Most popular outdoor location trackingsystem• Indoor tracking problematic  building occlusions• Started as 24 satellites http://www.nist.gov/pml/div688/grp40 /gpsarchive.cfmorbiting the Earth, Now 30 12.12.2012
    • 19. Global Positioning System (cont’d)• Satellite transmission  location and the current time At least 4  various frequencies satellite needed!• Receiver  distance to satellite calculated• Signal ID code, ephemeris data, almanac data Which Status, date, satellite? Orbital data time 12.12.2012
    • 20. Global Positioning System (cont’d)• Signals’ travel time  the time difference of arrival (TDOA)• Location Negative effect  hyperbolic lateration in 3-D Multipath,  TDOA values Atmospheri c delays• Fourth satellite is required to correct any Minimizing Errorssynchronization errors • Predicting atmospheric delays • Increase the number of channels 12.12.2012 • Correction codes
    • 21. Global Positioning System (cont’d) http://www.iranmap.com/2010/04/10/gps-signal-and-errors12.12.2012
    • 22. Active Badge Properties •Indoor, Worn density and badges placement of the sensors • Resolution • Active • central database • networked sensors deployed throughout a12.12.2012 building
    • 23. Active Badge (cont’d) Metrics • Scalability – difficult deployment • Resolution – high if well deployed • Active vs. Passive – needs active tagging • Centralization – keeps a centralized db and a lookup table • Infrastructure – low cost IR, room specific sensors12.12.2012
    • 24. Active Bat The Dark Knight RisesThe batin 2012 vs. 1997 12.12.2012
    • 25. Active Bat (cont’d) Properties • Ultrasound pulse’s travel time and location  trilateration  initiating with RF signal  Vlight > Vsound • Multiple tags must coordinate their pulses so as not to interfere with each other’s time-of-flight calculations.12.12.2012
    • 26. Active Bat (cont’d) Metrics • Scalability – more tags cause interference, activeness decreases scalability • Resolution – 90% at 3cm • Active vs. Passive – needs active tagging, if passive RF signalling independant of #tags • Centralization – central server, managing use of ultrasound bandwith, lack of12.12.2012
    • 27. Cricket Transmitter (beacon) TagRF transmitter/receiver, PropertiesUltrasonic signal • No centralized architecture!receiver, microcontroller • Tags compute their own location • Method similar to Active Bat12.12.2012
    • 28. Cricket (cont’d) Metrics • Scalability – independant of #tags • Resolution – 90% at 3cm • Active vs. Passive – passive • Centralization – decentralized, preserves privacy by local calculations • Infrastructure – no networking between beacons, difficult to deploy because of line- of-sight operation12.12.2012
    • 29. UbiSense • Ultrawideband (UWB) signal for localization • Each Ubitag incorporates a conventional RF radio (2.4 GHz) and a UWB radio (6–8 GHz).12.12.2012
    • 30. UbiSense (cont’d) • Time and Location  the time difference of arrival (TDOA)  angle of arrival (AOA)  triangulation At least two UbiSensors • Advantage of using UWB pulses is that it is easier to filter multipath signals and can endure some occlusion12.12.2012
    • 31. UbiSense (cont’d) Metrics • Scalability – dependant of #tags, separate coordination channel in favor • Resolution – 90% at 15cm • Active vs. Passive – active • Centralization – centralized • Infrastructure – physical timing cable, difficult to deploy because of line-of-sight operation12.12.2012
    • 32. Radar Properties • RF signal strength as indicator of the distance between an AP and a receiver. Makes use of 802.11 WiFi network. • Consumer does not have to purchase any specialized equipment (WiFi-enabled mobile phones, PDAs can be handled as a receiver or tag.) • Problems with multipath led researchers to use a mapping approach for localization • Receiver measures signal strength and compares it with the offline signal map • Subject to environment change12.12.2012
    • 33. Radar (cont’d) Metrics • Scalability – dependant of #tags • Resolution – 90% at 6m • Active vs. Passive – active • Centralization – decentralized • Infrastructure – reuse of existing infrastructure12.12.2012
    • 34. PlaceLab Properties • software-based indoor and outdoor localization system. • Makes use of 802.11 WiFi network. GSM towers, Bluetooth • detecting multiple unique IDs from these existing radio beacons and referring to a map of these devices So far localization similar to RADAR... • location tracking at a larger scale outdoor • Less dense calibration data, no need for an individual to populate a signal map no surveying12.12.2012
    • 35. PlaceLab War Driving • War driving is the process of driving around with a mobile device equipped with a GPS receiver and an 802.11, GSM, and/or Bluetooth radio to collect traces of wireless base stations.  time-stamped recordings containing GPS coordinates  the associated signal strength of the beacons Location • Position of the device is a weighted average of positions of the overheard beacons millions of beacon estimates already determined12.12.2012
    • 36. PlaceLab (cont’d) Metrics • Scalability – makes use of already determined estimations, still dependant on existance of tags • Resolution – 90% at 20m • Active vs. Passive – active • Centralization – no central provider, clients can determine their location privately • Infrastructure – reuse of existing infrastructure12.12.2012
    • 37. PowerLine PositioningEvery 1000m Signal generator plug-in modulesPrototype PowerLinePositioning tag 12.12.2012
    • 38. PowerLine Positioning (cont’d) Properties • drawbacks to relying on public infrastructure • indoor localization to work in nearly every building use the power line as the signaling infrastructure! • modules continually emit their respective signals over the power line, tags sense these signals in a building, relay them wirelessly to a receiver • site surveying needed12.12.2012
    • 39. PowerLine Positioning (cont’d) Metrics • Scalability – dependant of #tags • Resolution – 90% at 1m • Active vs. Passive – needs active tagging • Centralization – local or central • Infrastructure – lower deployment costs12.12.2012
    • 40. Active Floor Footstep signatureNo tags! Also by ground reactionLoad sensors force Tiles 12.12.2012
    • 41. Active Floor (cont’d) Metrics • Scalability – independant of clients, assuming only one individual on a single tile • Resolution – 91% at 1m • Active vs. Passive – passive • Centralization – central • Infrastructure – custom tiles makes deployment difficult12.12.2012
    • 42. Airbus• detecting gross • presence of ahuman movement personand room transitions • mass rather thanby sensing individualdifferential airpressure central heating, ventilation, and air conditioning (HVAC)• less obtrusivethan installingmotion detectors 12.12.2012
    • 43. Airbus (cont’d) Metrics • Scalability – scalable in the installed environment • Resolution – 88% at room level • Active vs. Passive – passive • Centralization – central, HVAC is the single monitoring point • Infrastructure – less additional infrastructure for deployment12.12.2012
    • 44. Tracking with Cameras Properties • cameras and computer vision techniques • no specialized tag and possible to leverage existing cameras • stereo camera images for locating the position, color images for inferring identities • face recognition On The Other Hand; • occlusions • dependant on the field of view of cameras, difficult coordination, small close space tracking not possible • privacy concerns12.12.2012
    • 45. Tracking with Cameras (cont’d) Metrics • Scalability – scalable, independant of #people • Resolution – 50% to 80% at 1m • Active vs. Passive – passive • Centralization – central • Infrastructure – reuse of existing infrastructure is possible12.12.2012
    • 46. Comparison of Location Systems 12.12.2012
    • 47. Summary • basic concepts of location technologies • current and historical location systems • client-based vs. network-based positioning • major sources of error • challenges and opportunities  No single location technology today that is ubiquitous, accurate, low-cost and easy to deploy.  Road to integration!12.12.2012
    • 48. Thanks For Listening12.12.2012
    • 49. Referenced from Article Location in Ubiquitous Computing Alexander Varshavsky and Shwetak Patel12.12.2012