Case: 1:21-cv-00699-JG Doc #: 1-2 Filed: 03/30/21 1 of 19. PageID #: 34
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`EXHIBIT B
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`

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`THAT IN A MI CORA UN MATEMATIKA MITATE
`
`US009852435B2
`
`( 12 ) United States Patent
`Wolfe
`
`( 10 ) Patent No . :
`( 45 ) Date of Patent :
`
`US 9 , 852 , 435 B2
`* Dec . 26 , 2017
`
`( * ) Notice :
`
`( 54 ) TELEMETRICS BASED LOCATION AND
`TRACKING
`( 71 ) Applicant : EMPIRE TECHNOLOGY
`DEVELOPMENT LLC , Wilmington ,
`DE ( US )
`Inventor : Andrew Wolfe , Los Gatos , CA ( US )
`( 72 )
`( 73 ) Assignee : EMPIRE TECHNOLOGY
`DEVELOPMENT LLC , Wilmington ,
`DE ( US )
`Subject to any disclaimer , the term of this
`patent is extended or adjusted under 35
`U . S . C . 154 ( b ) by 636 days .
`This patent is subject to a terminal dis
`claimer .
`( 21 ) Appl . No . : 14 / 199 , 329
`( 22 )
`Filed :
`Mar . 6 , 2014
`Prior Publication Data
`( 65 )
`US 2014 / 0188384 A1
`Jul . 3 , 2014
`Related U . S . Application Data
`( 62 ) Division of application No . 12 / 540 , 324 , filed on Aug .
`12 , 2009 , now Pat . No . 8 , 676 , 668 .
`Int . Ci .
`( 2012 . 01 )
`G06Q 30 / 00
`G060 30 / 02
`( 2012 . 01 )
`G06Q 30 / 06
`( 2012 . 01 )
`U . S . CI .
`CPC . . . . . . . . . 606Q 30 / 0202 ( 2013 . 01 ) ; G06Q 30 / 02
`( 2013 . 01 ) ; G06Q 30 / 0201 ( 2013 . 01 ) ; G06Q
`30 / 0619 ( 2013 . 01 )
`( 58 ) Field of Classification Search
`CPC . . . . . . . . . . . . GO6Q 30 / 0601 – 30 / 0643 ; G06Q 30 / 08
`See application file for complete search history .
`
`( 51 )
`
`( 52 )
`
`( 56 )
`
`References Cited
`U . S . PATENT DOCUMENTS
`6 , 885 , 936 B2
`4 / 2005 Yashio et al .
`7 , 103 , 370 B1
`9 / 2006 Creemer
`7 , 386 , 485 B1
`6 / 2008 Mussman et al .
`8 , 073 , 460 B1 . 12 / 2011 Scofield et al .
`2007 / 0260485 AL 11 / 2007 Shibata et al .
`2008 / 0004733 A1 1 / 2008 Finley et al .
`( Continued )
`
`OTHER PUBLICATIONS
`Personal Journal , “ Automotive Report : Mapping the Progress of
`Navigation Tools , ” false Sapsford , Jathon , Wall Street Journal ,
`Europe ( Brussels ) , p . 4 , ( Jul . 29 , 2005 ) .
`
`Primary Examiner — William Allen
`( 74 ) Attorney , Agent , or Firm — Moritt Hock & Hamroff
`LLP ; Steven S . Rubin , Esq .
`
`ABSTRACT
`( 57 )
`A population activity mapping method may include detect
`ing a plurality of wireless mobile devices within a geo
`graphic region . Individual wireless mobile devices may
`include a processor , a user interface , a transmitter and a
`receiver . The detecting operation may be performed by use
`of a wireless access point , a GPS satellite , and / or a base
`station , and may be performed at least two different points
`in time . Input data may be provided based upon the detecting
`operation . A distance and speed at which the mobile devices
`travel within the geographic region may be discerned depen
`dent upon the input data . The discerning operation is per
`formed by at least one processor of a computer network . A
`time and / or location at which salable output is to be made
`available and / or an amount of salable output to be made
`available may be determined dependent upon the discerning
`operation .
`
`20 Claims , 5 Drawing Sheets
`
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`detect wireless mobile devices carried by people within a
`geographic region at at least two different points in time ( 402 )
`
`provide input data based upon the detecting operation ( 404 )
`
`discern a distance and speed at which the mobile
`devices travel within the geographic region ( 406 )
`
`determine a time at which salable output is to be made
`available to the people , a location at which salable output
`is to be made available to the people , and / or an amount
`of salable output to be made available to the people ( 408 )
`
`present a result of the determining
`operation on a user interface ( 410 )
`
`400
`
`

`

`US 9 , 852 , 435 B2
`Page 2
`
`( 56 )
`
`References Cited
`U . S . PATENT DOCUMENTS
`
`2008 / 0045234 A12 / 2008 Reed
`2009 / 0125343 A1 5 / 2009 Cradick et al .
`2009 / 0171749 Al
`7 / 2009 Laruelle et al .
`2009 / 0197616 AL 8 / 2009 Lewis et al .
`2010 / 0042469 Al
`2 / 2010 Chandrasekar et al .
`2010 / 0121716 Al
`5 / 2010 Golan
`2010 / 0153174 A1 6 / 2010 Angell et al .
`2010 / 0223641 A1 9 / 2010 Hubbard
`2011 / 0022469 Al 1 / 2011 Fukui et al .
`2011 / 0035284 A1 2 / 2011 Moshfeghi
`2011 / 0066479 Al
`3 / 2011 Benson
`2011 / 0124324 A9
`5 / 2011 Friedenthal et al .
`2011 / 0276382 AL 11 / 2011 Ramchandani et al .
`
`Case: 1:21-cv-00699-JG Doc #: 1-2 Filed: 03/30/21 3 of 19. PageID #: 36
`
`

`

`U . S . Patent
`
`Dec . 26 , 2017
`
`Sheet 1 of 5
`
`US 9 , 852 , 435 B2
`
`GPS Satellite 4 ( 1144 ) ?
`Demographic And Historical Information ( 120 )
`
`GPS Satelite 3 ( 1143 )
`
`GPS Satellite 2 ( 1142 )
`
`Central Office ( 116 )
`——
`
`Mobile Device 1 ( 1121 )
`
`FIG . 1
`
`Case: 1:21-cv-00699-JG Doc #: 1-2 Filed: 03/30/21 4 of 19. PageID #: 37
`
`GPS Satellite 1 ( 1141 )
`
`100
`
`

`

`U . S . Patent
`
`Dec . 26 , 2017
`
`Sheet 2 of 5
`
`US 9 , 852 , 435 B2
`
`Demographic And Historical Information ( 120 )
`
`FIG . 2
`
`run
`
`Central Office ( 116 )
`
`Goods / Services Provider ( 118 )
`
`Data Aggregation ( 117 )
`
`200
`
`Mobile Device n ( 1120 )
`
`II
`
`Mobile Device 3 ( 1123 )
`
`Mobile Device 2 ( 1122 )
`
`Mobile Device 1 ( 1121 )
`
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`
`

`

`U . S . Patent
`
`Dec . 26 , 2017
`
`Sheet 3 of 5
`
`US 9 , 852 , 435 B2
`
`-
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`-
`
`-
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`-
`
`PORT ( S ) 1
`( 363 )
`AN
`
`
`
`OUTPUT DEVICES ( 360 )
`
`GRAPHICS PROCESSING UNIT ( 361 )
`
`AUDIO
`
`PROCESSING
`
`UNIT ( 362 )
`
`PORT
`
`( 373 )
`
`
`
`PERIPHERAL INTERFACES ( 370 )
`
`PARALLEL INTERFACE CONTROLLER ( 372 )
`SERIAL INTERFACE CONTROLLER VI ( 371 )
`
`( 382 )
`
`( 381 )
`
`COMM .
`
`COMMUNICATION DEVICES ( 380 )
`
`CONTROLLER PORT ( S )
`NETWORK
`
`INTERFACE BUS ( 342 )
`
`-
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`-
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`-
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`OTHER COMPUTING DEVICE ( S ) ( 390 )
`
`-
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`-
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`-
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`-
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`-
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`-
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`-
`
`FIG . 3
`
`—
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`—
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`—
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`
`
`- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
`
`
`PROCESSOR CORE ALU / FPU / DSP ( 313 )
`CONFIG . ( 301 ) PROCESSOR ( 310 ) BASIC
`
`UP / UC / DSP LEVEL 1 LEVEL 2 CACHE CACHE ( 311 ) ( 312 )
`
`REGISTERS ( 314 )
`
`. . . . . . . - - -
`
`-
`
`MEMORY BUS ( 330 )
`
`MEMORY CONTROLLER ( 315 )
`
`. . . . .
`
`BUSI
`
`( 340 ) 1
`
`
`
`STORAGE INTERFACE BUS ( 341 )
`
`( E . G . , HDD )
`
`-
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`-
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`-
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`-
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`-
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`-
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`-
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`INTERFACE
`REMOVABLE
`REMOVABLE
`
`_
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`_
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`_
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`_
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`_
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`APPLICATION ( 322 )
`
`
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`i SYSTEM MEMORY ( 320 )
`
`
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`PROGRAM DATA ( 324 )
`
`
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`HISTORICAL DATA ( 325 )
`
`AGGREGATION ALGORITHM ( 323 )
`
`Case: 1:21-cv-00699-JG Doc #: 1-2 Filed: 03/30/21 6 of 19. PageID #: 39
`| - - - - - - - - - -
`
`
`
`| COMPUTING DEVICE ( 300 )
`
`ROM / RAM OPERATING SYSTEM ( 321 )
`
`84
`Til
`
`NON
`STORAGE DEVICES ( 350 )
`
`
`| ( E . G . , CD / DVD ) STORAGE ( 352 ) CONTROLLER
`STORAGE ( 351 )
`
`=
`
`=
`
`=
`
`-
`
`-
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`-
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`—
`
`—
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`—
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`-
`
`

`

`U . S . Patent
`
`Dec . 26 , 2017
`
`Sheet 4 of 5
`
`US 9 , 852 , 435 B2
`
`detect wireless mobile devices carried by people within a
`geographic region at at least two different points in time ( 402 )
`
`provide input data based upon the detecting operation ( 404 )
`
`discern a distance and speed at which the mobile
`devices travel within the geographic region ( 406 )
`
`determine a time at which salable output is to be made
`available to the people , a location at which salable output
`is to be made available to the people , and / or an amount
`of salable output to be made available to the people ( 408 )
`
`Case: 1:21-cv-00699-JG Doc #: 1-2 Filed: 03/30/21 7 of 19. PageID #: 40
`
`present a result of the determining
`operation on a user interface ( 410 )
`
`400
`
`FIG . 4
`
`

`

`U . S . Patent
`
`Dec . 26 , 2017
`
`Sheet 5 of 5
`
`US 9 , 852 , 435 B2
`
`- - - Mobile 11 Device 2 ( 1122 ) 1
`
`-
`
`-
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`-
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`-
`
`L
`
`Mobile Device 2 ( 1122 )
`Central Office ( 116 )
`
`-
`
`,
`
`-
`
`-
`
`Mobile | Device 11 ( 1121 ) |
`
`Geographic Area ( 522 )
`
`Mobile Device 1 ( 1121 )
`
`Case: 1:21-cv-00699-JG Doc #: 1-2 Filed: 03/30/21 8 of 19. PageID #: 41
`
`FIG . 5
`
`500
`
`Mobile Device 3 ( 1123 )
`| Mobile 1 H Device 31 ( 1123 ) - - - -
`
`1
`
`Mobile Device 4 ! ( 1124 ) L - - -
`Mobile Device 4 ( 1124 )
`
`

`

`US 9 , 852 , 435 B2
`
`that the aspects of the present disclosure , as generally
`TELEMETRICS BASED LOCATION AND
`described herein , and illustrated in the Figures , may be
`TRACKING
`arranged , substituted , combined , and designed in a wide
`variety of different configurations , all of which are explicitly
`CROSS - REFERENCE TO RELATED
`5 contemplated and make part of this disclosure .
`APPLICATION
`This disclosure is drawn , inter alia , to methods and
`systems related to telemetrics - based location and / or tracking
`This application is a divisional application under 35
`technology . An example embodiment may relate to deter
`U . S . C . $ 121 that claims priority under 35 U . S . C . $ 120 to
`mining the locations of wireless devices ( e . g . , cell phones ) ,
`U . S . application Ser . No . 12 / 540 . 324 . filed on Aug . 12 . 2009 .
`now U . S . Pat . No . 8 , 676 , 668 . The disclosure of U . S . appli - 10 and this information may be used in conjunction with
`population density maps , population activity maps , and / or
`cation Ser . No . 12 / 540 , 324 is hereby incorporated by refer
`transaction likelihood maps , in order to match - up clients
`ence in its entirety .
`and / or vendors .
`BACKGROUND
`This disclosure may include methods and systems for
`15 providing details of where crowds of people are located ,
`how the crowds are changing , where they are moving to ,
`Providing goods and / or services to a group of people at a
`when they are transitioning from one activity to another ,
`particular time and place presents numerous logistical prob -
`and / or what activity they are transitioning to . Because the
`lems . A particular problem that arises is that some customers
`people in the crowd may want or need to purchase a
`demand prompt service or otherwise a sales opportunity may
`be lost . A large number of businesses and other agencies 20 provider ' s goods or services , it may be valuable to the
`provide goods and services that are valuable to consumers
`provider to know such information about the crowd .
`only when they can be provided at a proper time and place .
`There are many example applications of the present
`Moreover , these goods and services may call for some
`disclosure which may enable goods and services to be
`advance planning immediately prior to providing the goods
`provided in a better and / or more responsive fashion by
`or services to such customers . This may be a particular 25 virtue of having determined and / or reported a crowd ' s
`problem when dealing with crowds , e . g . , when large num -
`location , pattern of movement , and / or activity level . In one
`example , a taxi service may be informed of when and how
`bers of potential customers demand prompt service at a
`many passengers will be arriving , are arriving , and / or have
`given time , and if no such service is provided , then oppor
`arrived at an airport , bus station or train station so that the
`tunities to be a service provider may be lost .
`30 taxi service may dispatch an appropriate number of taxis at
`an appropriate time to the airport , bus station or train station .
`BRIEF DESCRIPTION OF THE SEVERAL
`VIEWS OF THE DRAWING
`The taxi service may be informed of how many passengers
`are arriving , how many passengers are exiting the airport ,
`The foregoing and other features of the present disclosure
`bus station or train station as opposed to making connec
`will become more fully apparent from the following descrip - 35 tions , and / or which exits the passengers are using . In addi
`tion and appended claims , taken in conjunction with the
`tion , the taxi service may be informed of when and how
`accompanying drawings . Understanding that these drawings
`many passengers have arrived at baggage claim areas . The
`depict only several embodiments in accordance with the
`earlier and more accurately such crowd information can be
`disclosure and , therefore , are not to be considered limiting of
`predicted and / or provided , the greater the number of taxi
`its scope , the disclosure will be described with additional 40 fares that may be received with less time waiting on the part
`specificity and detail through use of the accompanying
`of the taxi drivers .
`drawings .
`In another example , outdoor food vendors may be
`informed of when exactly crowds begin to leave theaters or
`In the drawings :
`FIG . 1 is a block diagram of an example arrangement for
`when office workers begin leaving for lunch . Being armed
`determining and / or collecting the location of a mobile 45 with such information , the food vendors may be better able
`to prepare and provide appropriate amounts of food at
`device ;
`FIG . 2 is a block diagram of an example telemetrics - based
`appropriate times .
`In another example , a police force may be informed of the
`location and / or tracking arrangement ;
`FIG . 3 is a block diagram illustrating an example com -
`distribution of people around a city and / or changes in
`puting device that may be arranged for telemetrics - based 50 activity levels in specific locations around a city . Based on
`this information , the police force may better position its
`location and / or tracking ;
`FIG . 4 is a flow chart showing the operation of an example
`patrol officers to locations around the city where the officers
`may be needed .
`population activity mapping method ; and
`FIG . 5 is a diagram of a map , all arranged in accordance
`In another example , a city government may be informed
`with at least some embodiments of the present disclosure . 55 of the number of attendees at a city - sponsored event . Thus ,
`the city government may gauge the level of the citizen ' s
`DETAILED DESCRIPTION
`interest in the event .
`In yet another example , an ambulance service may be
`In the following detailed description , reference is made to
`informed of the locations of people , and consequently their
`the accompanying drawings , which form a part hereof . In 60 vehicles , on the roadways . The ambulance service may use
`the drawings , similar symbols typically identify similar
`this information to create a traffic congestion model in order
`components , unless context dictates otherwise . The illustra -
`to determine the best , most uncongested , and / or quickest
`tive embodiments described in the detailed description ,
`route for an ambulance to take to the location of an emer
`drawings , and claims are not meant to be limiting . Other
`gency , and / or from the location of the emergency to a
`embodiments may be utilized , and other changes may be 65 hospital .
`made , without departing from the spirit or scope of the
`The present disclosure contemplates that a modern popu
`subject matter presented here . It will be readily understood
`lation of consumers may include a substantial and relatively
`
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`

`

`US 9 , 852 , 435 B2
`
`of the mobile device and transmit the location to the central
`predictable percentage of people who possess a mobile
`office . For example , the iPhone 3G
`from Apple Computer
`phone or other wireless device that may be in contact with
`can determine its approximate location using either GPS or
`a network , such as a wide area network . The disclosure may
`a combination of proximate wireless access points .
`provide techniques that may be used to determine and / or
`FIG . 2 is a block diagram of an example telemetrics - based
`report the locations of each of these terminal devices . These 5
`location and / or tracking arrangement 200 including mobile
`techniques may include GPS - based location determination
`device 112 , and central office 116 , which were described
`techniques and / or Wi - Fi - based or cell - tower - based location
`above with regard to FIG . 1 , as well as other mobile devices
`determination techniques , which may involve triangulation .
`112 , 112 , . . . , 112 , ( where n is any number ) , a goods
`Once the individual location data is gathered , aggregation
`algorithms may be used to create a model of the distribution 10 and / or services provider 118 , and a memory device 120
`of the locations of the mobile device users . Population
`storing demographic and historical information . Each of the
`estimation models may be used to determine or estimate size
`n number of mobile devices 112 , 1122 , 1123 , . . . , 112 , may
`and location of crowds based on this aggregated informa
`determine its location via communication with GPS satel
`tion . Demographic information about each of the users may
`lites and / or cell phone towers , and then wirelessly transmit
`be collected , and this demographic information may be used 15 its identity and its location to central office 116 .
`to derive or estimate characteristics of the crowds , such as
`Central office 116 may store the received mobile device
`locations in memory device 120 . In one embodiment
`the number of men or women in a certain age group .
`The changing locations of the mobile device users may
`memory device 120 may store mobile device locations on a
`continue to be monitored , and the motion of individual
`first in first out basis such that only the most recent locations
`terminals may be aggregated to estimate the movement of a 20 are stored . In another embodiment , historical location data
`that is over a few hours old may be compressed to store only
`crowd or to estimate changes in activity levels . Alterna
`lar
`representative location data and / or sampled location data .
`tively , the flow of terminals from one geographic cell or area
`For example , memory device 120 may store one to three
`to another may be used to estimate motion or activity .
`Instead of tracking the changing locations of individual
`locations that each mobile device spent the most time at
`terminals , changes in the terminal locations as a group , 25 during each day in the past .
`regardless of their individual identities or individual
`Central office 116 may also store demographic informa
`motions , may be monitored . Thus , " snapshots ” of the group
`tion related to each of the people who carry mobile devices
`locations may be taken at periodic time intervals without
`112 . Central office 116 may receive such demographic
`information from mobile device carrier companies that bill
`regard to the identities of the individual terminals .
`Regardless of whether the aggregated information relates 30 the people who carry mobile devices 112 for their use of the
`wireless network . Alternatively , or in addition , central office
`to individual terminals or only to a group of the terminals as
`a whole , the aggregated information may be provided to
`116 may receive such demographic information directly
`providers of goods and / or services . The aggregated infor -
`from the owners of mobile devices 112 and / or from third
`mation may be provided directly to providers of goods
`parties .
`and / or services in an unfiltered state . Alternatively , there 35
`Central office 116 may be communicatively coupled to a
`may be applied an analysis protocol that may determine
`data aggregation module 117 . Central office 116 may store
`which information is of interest to which provider . Thus ,
`and run aggregation algorithms on the new location data
`each provider may receive only the filtered information in
`from mobile devices 112 and / or on the demographic and
`which he is interested or is willing to purchase . The pro -
`historical data from memory device 120 . The output of the
`viders of goods and / or services may then use the filtered or 40 aggregation algorithms may include a model of the distri
`unfiltered information to decide the location , timing and / or
`bution of the locations of mobile devices 112 . This model
`may be used by central office 116 to estimate the size and / or
`quantity of goods and services to provide .
`FIG . 1 is a block diagram of an example arrangement 100
`location of crowds including the users of mobile devices
`112 . The demographic information retrieved from memory
`for determining and / or collecting the location of a mobile
`device , which is arranged in accordance with at least some 45 device 120 may be used to derive and / or estimate charac
`embodiments of the present disclosure . The example
`teristics of the crowds represented by mobile devices 112 ,
`arrangement 100 includes a mobile device 112 , which a user
`such as the number of men or women broken down by age
`may carry with him or on his person . Mobile device 112
`groups , monetary income levels , and / or where the people
`may be a cell phone and / or another form of wireless device
`live ( which may be used as a proxy for where they are
`which may include a radio receiver , radio transmitter , pro - 50 going ) .
`cessor and / or user interface . Mobile device 112 may
`Central office 116 may transmit the crowd information ,
`include a built - in GPS receiver and may be in communica
`which may include the crowd ' s demographics , number of
`tion with satellites 1141 , 114 , 1142 and 1144 . Mobile device
`people , locations , and / or patterns of movement , to goods
`may determine its global geographic coordinates via com -
`and / or services provider 118 . Provider 118 may then esti
`munication with the satellites in conjunction with trilatera - 55 mate the demands of the crowd for the provider ' s goods
`tion and / or other techniques . Mobile device 112 , may then
`and / or services , including quantities and / or times , based at
`wirelessly communicate its location to a central office 116 or
`least in part on the received crowd information . Hence ,
`other centralized depository of mobile device location infor
`provider 118 may prepare to supply a level or number of
`mation . Central office 116 may be communicatively coupled
`goods and / or services that corresponds to , or is appropriate
`to a memory device 120 which may store mobile device 60 for , the anticipated demands of the crowd .
`Many central offices may be provided , and individual
`locations .
`In another embodiment in which the mobile device is not
`central offices 116 may be associated with certain respective
`GPS - equipped , the mobile device may communicate with
`geographic areas . In one embodiment , each geographic area
`cell phone towers to determine its approximate global loca -
`may measure about a square mile , which may correspond to
`tion and transmit the location to the central office . It is also 65 an area that the crowd is expected , during the next one to two
`possible for one or more of the cell phone towers or the
`hours , to traverse on foot , and / or to purchase goods and / or
`wireless service provider company to determine the location
`services within . Central office 116 may filter the crowd
`
`Case: 1:21-cv-00699-JG Doc #: 1-2 Filed: 03/30/21 10 of 19. PageID #: 43
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`

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`US 9 , 852 , 435 B2
`
`people carrying a mobile device 112 , may realistically
`information on a geographic basis , and thus use , or transmit
`qualify as a potential client and / or customer for every
`to provider 118 , only the crowd information that is of
`product and / or service . The pool of people in the region may
`interest to provider 118 . For example , central office 116 may
`be filtered based upon the time - of - day , day of the week ,
`transmit to provider 118 information only about mobile
`devices 112 that are within a half - mile radius of provider 5 calendar date , historical information , and / or demographic
`information to identify people who have above a threshold
`118 .
`In one embodiment , central office 116 may be in com
`level of likelihood of purchasing the particular goods and / or
`services of a provider 118 . In one embodiment , the popu
`munication with only mobile devices 112 that are within the
`geographic area with which central office 116 is associated .
`lation of interest may be estimated by accessing stored
`In another embodiment , mobile devices 112 may be in
`10 demographic and / and historical information about each
`communication with their corresponding wireless service
`detected client . For example , central office 116 may retrieve
`carriers , and the carriers may determine the locations of
`demographic and / and historical information about mobile
`mobile devices 112 . Each of the wireless service carriers
`devices 112 from memory device 120 . The historical infor
`may then send to each central office 116 only information
`mation may include a number of times , and / or a frequency
`about mobile devices 112 that are within the geographic area 15 with which , a particular mobile device 112 has visited
`with which that particular central office 116 is associated .
`provider 118 .
`In another embodiment , central office 116 may include a
`Estimating the population of interest may also involve
`wireless access point in a retail store , library , and / or other
`filtering and / or weighting detected potential clients accord
`public place . Mobile devices 112 may connect with the
`ing to search criteria . For example , the detected population
`wireless access point only within a range of about one 20 of mobile device 112 users may be broken down by the sex ,
`hundred meters , and thus the locations of the individual
`age , income level , and / or place of residence of the users .
`mobile devices 112 may not need to be specified with any
`Estimating the population of interest may further involve
`greater precision . However , in this embodiment , central
`applying an estimation function to predict the actual poten
`office 116 may still receive demographic information from a
`tial customer base . This function may depend on : detected
`wireless carrier or other source about the mobile devices that 25 client locations ; client demographic and historical informa
`tion ; source of client location data ; and / or the day of week
`are in communication with the wireless access point .
`Static Population Density Map
`and time - of - day . For example , a formula or lookup table
`may be used to estimate an expected level of sales for
`In one embodiment contemplated by the present disclo -
`sure , a static population density map may be provided . A first
`individuals detected within the region . Variables in the
`operation of this process may include determining the loca - 30 formula / lookup table may include the current location of the
`tions of individual accessible phones and / or data terminal
`person , his demographic and / or historical location informa
`customers . For example , mobile devices 112 within the
`tion , how reliable the source of the client location data is ,
`geographic area of a central office 116 , and / or the wireless
`and / or the day of the week , time - of - day , and / or season of the
`carriers of such mobile devices , may report the exact loca -
`year . The formula / lookup table may be based on and / or
`tions of the mobile devices within the geographic area to
`35 derived from historical sales data , which data may relate to
`central office 116 .
`any of the variables and / or parameters used in the formula .
`As alluded to above , determining the location of each
`In one example , a taxi company may have derived a
`accessible phone and / or data terminal customer may possi -
`formula based on historical data for the likelihood that an
`bly involve aggregating data from multiple sources . For
`individual at an airport will hail a cab . According to the
`example , data from the wireless service carriers , cell phone 40 formula , the likelihood may be estimated as the sum total of
`towers , third parties connected to the wireless service car -
`four parameters that depend on the above - described vari
`riers or cell phone towers , and / or from the mobile devices
`ables . For instance , the first parameter may be 0 . 02 if the
`themselves may be collected and integrated together by
`person is at a gate area of the airport , and 0 . 07 if the person
`is at a baggage claim area . The second parameter may be
`central office 116 .
`Another operation of the static population density map 45 0 . 03 if the person lives in the state , and 0 . 08 if he does not .
`process may involve assigning the detected mobile device
`The third parameter may be 0 . 06 if the user location data was
`locations to geographic regions . For example , each central
`received from a wireless service provider , and 0 . 03 if
`office 116 may be associated with one or more respective
`received from a less reliable third party . The fourth param
`geographic regions , such as an area in which potential
`eter may be 0 . 05 on a weekday , and 0 . 03 on a weekend .
`common customers and / or clients of retailers within the 50 Thus , for a person currently at the gate area ( 0 . 02 ) , who lives
`geographic region may be congregated . However , it is to be
`in the state ( 0 . 03 ) , whose information was received from a
`understood that one central computer system may be
`third party ( 0 . 03 ) , and for a weekday ( 0 . 05 ) , the formula may
`arranged to create the maps and the associated data struc -
`indicate a probability of 0 . 13 , or 13 percent , that the person
`tures for many or all of the regions . Such a central computer
`will attempt to hail a cab . By summing the estimated
`system may be communicatively coupled to each of a
`55 probabilities for individuals determined to be in the region
`plurality of central office ' s 116 . In one embodiment , the
`( e . g . , airport ) , the taxi company may estimate the number of
`geographic region may be a set rectangular area within a
`taxi cabs that may be needed at the airport . Thus , for
`city , such as a one mile by one mile square . In other
`example , if 1 , 000 people are determined to be at the airport ,
`embodiments , the geographic region may be defined at least
`and individuals have , on average , a 13 % likelihood of
`in part by barriers to travel ( e . g . , foot travel ) , such as a river , 60 hailing a cab , then it may be estimated that 130 taxi cabs
`highway , lake , private property , fence , and / or difficult ter -
`may be needed at the airport during some period of time . A
`rain , for example . Thus , central office 116 may determine in
`message related to the estimated sales level may be trans
`which of the geographic regions that each mobile device 112
`mitted to a user interface associated with the taxi company ,
`is disposed .
`such as a printer , display monitor , wireless mobile device ,
`Yet another operation of the static population density map 65 and / or email account , for example .
`process may involve estimating the population of interest for
`further operation of the static population density map
`individual regions . For example , not all people , and not all
`process may involve providing goods or services by deter
`
`Case: 1:21-cv-00699-JG Doc #: 1-2 Filed: 03/30/21 11 of 19. PageID #: 44
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`

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`US 9 , 852 , 435 B2
`mining the appropriate location for each service provider
`embodiment , the geographic region may be a predetermined
`based on the predicted customer base and / or determining the
`rectangular area within a city , such as a one mile by one mile
`appropriate quantity of service providers , service activity ,
`square . In other embodiments , the geographic region may be
`and / or goods to be provided at individual locations of
`defined at least in part by barriers to travel ( e . g . , foot travel ) ,
`interest based at least in part on the predicted customer base 5 such as a river , highway , lake , private property , fence , and / or
`proximate to that location . Still using the taxi company as an
`difficult terrain , for example . Thus , central office 116 may
`example , if a city has two airports needing taxi service , the
`determine in which of the geographic regions that individual
`demand at both airports may be considered when dispatch -
`moving mobile devices 112 are disposed . In one embodi
`ing taxi cabs to one airport or the other . For example , if 120
`ment , only those mobile devices 112 moving at least a
`taxis are needed at airport A and 80 taxis are needed at 10 minimum threshold speed and / or within a range of direc
`airport B , but the company h