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`EXHIBIT A
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`USOO8676668B2
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`(12) United States Patent
`Wolfe
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`(10) Patent No.:
`(45) Date of Patent:
`
`US 8,676,668 B2
`Mar. 18, 2014
`
`(54) METHOD FOR THE DETERMINATION OF A
`TIME, LOCATION, AND QUANTITY OF
`GOODS TO BE MADE AVAILABLE BASED ON
`MAPPED POPULATION ACTIVITY
`
`(*) Notice:
`
`(75) Inventor: Andrew Wolfe, Los Gatos, CA (US)
`(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 672 days.
`(21) Appl. No.: 12/540,324
`(22) Filed:
`Aug. 12, 2009
`
`(65)
`
`Prior Publication Data
`US 2011 FOO4O603 A1
`Feb. 17, 2011
`
`(51) Int. Cl.
`G06O 30/00
`(52) U.S. Cl.
`USPC .................... 705/26.7; 705/1449; 705/14.58;
`705/7.31: 701/408; 701/487; 701/491: 701/516;
`701 1526
`
`(2012.01)
`
`(58) Field of Classification Search
`USPC ........................... 705/7.29, 7.31, 14.4, 14.49,
`705/14.57–14.58, 26.1-27.2: 701/400, 408,
`701/426, 465, 487,491, 500, 516, 517,526
`See application file for complete search history.
`
`(56)
`
`References Cited
`
`U.S. PATENT DOCUMENTS
`
`6,885,936 B2 * 4/2005 Yashio et al. ................. 701,515
`7,103,370 B1* 9/2006 Creemer ..........
`... 455,456.3
`7,386,485 B1* 6/2008 Mussman et al. ............ TO5, 14.1
`8,073,460 B1* 12/2011 Scofield et al. ............ 455,456.1
`2007/0260485 A1* 11/2007 Shibata et al. .................... 705/2
`2008/0004733 A1* 1/2008 Finley et al. .................... TOO/94
`
`2/2008 Reed .......................... 455,456.1
`2008/0045234 A1
`2009.0125343 A1* 5/2009 Cradick et al. .................... 705/7
`2009/0171749 A1* 7/2009 Laruelle et al. ................. 70.5/10
`2009,019761.6 A1* 8, 2009 Lewis et al. ................ 455,456.1
`2010.0042469 A1
`2/2010 Chandrasekar et al. ........ 70.5/10
`2010, 0121716 A1* 5, 2010 Golan ........................ TO5, 14.58
`2010/0153174 A1* 6/2010 Angell et al. ................... 70.5/10
`2010/0223641 A1* 9, 2010 Hubbard ......................... 725/35
`2011/0022469 A1
`1/2011 Fukui et al. .
`TO5/14.58
`2011/0035284 A1* 2/2011 Moshfeghi.
`TO5/14.58
`2011/0066479 A1
`3/2011 Benson ..............
`... 705,144
`2011/O124324 A9
`5, 2011 Friedenthal et al. .......... 455,418
`2011/0276382 A1* 11/2011 Ramchandani et al. ... 705/14.25
`
`OTHER PUBLICATIONS
`
`Personal Journal; Automotive Report: Mapping the Progress of Navi
`gation Tools falseSapsford, Jathon. Wall Street Journal, Europe
`Brussels Jul. 29, 2005: p. 4.*
`
`* cited by examiner
`Primary Examiner — William Allen
`(74) Attorney, Agent, or Firm — Moritt Hock & Hamroff
`LLP; Steven S. Rubin, Esq.
`(57)
`ABSTRACT
`A population activity mapping method may include detecting
`a plurality of wireless mobile devices within a geographic
`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 at least two different points in time. Input data
`may be provided based upon the detecting operation. A dis
`tance and speed at which the mobile devices travel within the
`geographic region may be discerned dependent upon the
`input data. The discerning operation is performed 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 deter
`mined dependent upon the discerning operation.
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`7 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)
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`provide inputdatabased upon the detecting operation (404)
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`discern a distance and speed at which the mobile
`devices travel within the geographic region (406)
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`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, andlor an amount
`of salable output to be made awailable to the people (408)
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`present a result of the determining
`operation on a user interface (410)
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`400
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`U.S. Patent
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`Mar. 18, 2014
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`Sheet 1 of 5
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`U.S. Patent
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`Mar. 18, 2014
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`Sheet 2 of 5
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`US 8,676,668 B2
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`U.S. Patent
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`Mar. 18, 2014
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`Sheet 4 of 5
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`US 8,676,668 B2
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`detect wireless mobile devices carried by people within a
`geographic region at at least two different points in time (402)
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`provide input data based upon the detecting operation (404)
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`
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`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)
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`present a result of the determining
`operation on a user interface (410)
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`400
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`FIG. 4
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`US 8,676,668 B2
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`1.
`METHOD FOR THE DETERMINATION OFA
`TIME, LOCATION, AND QUANTITY OF
`GOODS TO BE MADE AVAILABLE BASED ON
`MAPPED POPULATION ACTIVITY
`
`BACKGROUND
`
`Providing goods and/or services to a group of people at a
`particular time and place presents numerous logistical prob
`lems. A particular problem that arises is that some customers
`demand prompt service or otherwise a sales opportunity may
`be lost. A large number of businesses and other agencies
`provide goods and services that are valuable to consumers
`only when they can be provided at a proper time and place.
`Moreover, these goods and services may call for some
`advance planning immediately prior to providing the goods or
`services to Such customers. This may be a particular problem
`when dealing with crowds, e.g., when large numbers of
`potential customers demand prompt service at a given time,
`and if no Such service is provided, then opportunities to be a
`service provider may be lost.
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`BRIEF DESCRIPTION OF THE SEVERAL
`VIEWS OF THE DRAWING
`
`The foregoing and other features of the present disclosure
`will become more fully apparent from the following descrip
`tion and appended claims, taken in conjunction with the
`accompanying drawings. Understanding that these drawings
`depict only several embodiments in accordance with the dis
`closure and, therefore, are not to be considered limiting of its
`scope, the disclosure will be described with additional speci
`ficity and detail through use of the accompanying drawings.
`In the drawings:
`FIG. 1 is a block diagram of an example arrangement for
`determining and/or collecting the location of a mobile device;
`FIG. 2 is a block diagram of an example telemetrics-based
`location and/or tracking arrangement;
`FIG. 3 is a block diagram illustrating an example comput
`ing device that may be arranged for telemetrics-based loca
`tion and/or tracking;
`FIG. 4 is a flow chart showing the operation of an example
`population activity mapping method; and
`FIG. 5 is a diagram of a map, all arranged in accordance
`with at least some embodiments of the present disclosure.
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`DETAILED DESCRIPTION
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`sity maps, population activity maps, and/or transaction like
`lihood maps, in order to match-up clients and/or vendors.
`This disclosure may include methods and systems for pro
`viding details of where crowds of people are located, how the
`crowds are changing, where they are moving to, when they
`are transitioning from one activity to another, and/or what
`activity they are transitioning to. Because the people in the
`crowd may want or need to purchase a provider's goods or
`services, it may be valuable to the provider to know such
`information about the crowd.
`There are many example applications of the present dis
`closure which may enable goods and services to be provided
`in a better and/or more responsive fashion by virtue of having
`determined and/or reported a crowd's location, pattern of
`movement, and/or activity level. In one example, a taxi ser
`Vice may be informed of when and how many passengers will
`be arriving, are arriving, and/or have arrived at an airport, bus
`station or train station so that the taxi service may dispatch an
`appropriate number of taxis at an appropriate time to the
`airport, bus station or train station. The taxi service may be
`informed of how many passengers are arriving, how many
`passengers are exiting the airport, bus station or train station
`as opposed to making connections, and/or which exits the
`passengers are using. In addition, the taxi service may be
`informed of when and how many passengers have arrived at
`baggage claim areas. The earlier and more accurately Such
`crowd information can be predicted and/or provided, the
`greater the number of taxi fares that may be received with less
`time waiting on the part of the taxi drivers.
`In another example, outdoor food vendors may be
`informed of when exactly crowds begin to leave theaters or
`when office workers begin leaving for lunch. Being armed
`with such information, the food vendors may be better able to
`prepare and provide appropriate amounts of food at appropri
`ate times.
`In another example, a police force may be informed of the
`distribution of people around a city and/or changes in activity
`levels in specific locations around a city. Based on this infor
`mation, the police force may better position its patrol officers
`to locations around the city where the officers may be needed.
`In another example, a city government may be informed of
`the number of attendees at a city-sponsored event. Thus, the
`city government may gauge the level of the citizens interest
`in the event.
`In yet another example, an ambulance service may be
`informed of the locations of people, and consequently their
`vehicles, on the roadways. The ambulance service may use
`this information to create a traffic congestion model in order
`to determine the best, most uncongested, and/or quickest
`route for an ambulance to take to the location of an emer
`gency, and/or from the location of the emergency to a hospi
`tal.
`The present disclosure contemplates that a modern popu
`lation of consumers may include a substantial and relatively
`predictable percentage of people who possess a mobile phone
`or other wireless device that may be in contact with a network,
`Such as a wide area network. The disclosure may provide
`techniques that may be used to determine and/or report the
`locations of each of these terminal devices. These techniques
`may include GPS-based location determination techniques
`and/or Wi-Fi-based or cell-tower-based location determina
`tion techniques, which may involve triangulation.
`Once the individual location data is gathered, aggregation
`algorithms may be used to create a model of the distribution
`of the locations of the mobile device users. Population esti
`mation models may be used to determine or estimate size and
`location of crowds based on this aggregated information.
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`In the following detailed description, reference is made to
`the accompanying drawings, which form a parthereof. In the
`drawings, similar symbols typically identify similar compo
`nents, unless context dictates otherwise. The illustrative
`embodiments described in the detailed description, drawings,
`and claims are not meant to be limiting. Other embodiments
`may be utilized, and other changes may be made, without
`departing from the spirit or scope of the Subject matter pre
`sented here. It will be readily understood that the aspects of
`the present disclosure, as generally described herein, and
`illustrated in the Figures, may be arranged, Substituted, com
`bined, and designed in a wide variety of different configura
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`tions, all of which are explicitly contemplated and make part
`of this disclosure.
`This disclosure is drawn, interalia, to methods and systems
`related to telemetrics-based location and/or tracking technol
`ogy. An example embodiment may relate to determining the
`locations of wireless devices (e.g., cell phones), and this
`information may be used in conjunction with population den
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`and/or cell phone towers, and then wirelessly transmit its
`identity and its location to central office 116.
`Central office 116 may store the received mobile device
`locations in memory device 120. In one embodiment memory
`device 120 may store mobile device locations on a first in first
`out basis such that only the most recent locations are stored.
`In another embodiment, historical location data that is over a
`few hours old may be compressed to store only representative
`location data and/or sampled location data. For example,
`memory device 120 may store one to three locations that each
`mobile device spent the most time at during each day in the
`past.
`Central office 116 may also store demographic information
`related to each of the people who carry mobile devices 112.
`Central office 116 may receive such demographic informa
`tion from mobile device carrier companies that bill the people
`who carry mobile devices 112 for their use of the wireless
`network. Alternatively, or in addition, central office 116 may
`receive Such demographic information directly from the own
`ers of mobile devices 112 and/or from third parties.
`Central office 116 may be communicatively coupled to a
`data aggregation module 117. Central office 116 may store
`and run aggregation algorithms on the new location data from
`mobile devices 112 and/or on the demographic and historical
`data from memory device 120. The output of the aggregation
`algorithms may include a model of the distribution of the
`locations of mobile devices 112. This model may be used by
`central office 116 to estimate the size and/or location of
`crowds including the users of mobile devices 112. The demo
`graphic information retrieved from memory device 120 may
`be used to derive and/or estimate characteristics of the crowds
`represented by mobile devices 112, such as the number of
`men or women broken down by age groups, monetary income
`levels, and/or where the people live (which may be used as a
`proxy for where they are going).
`Central office 116 may transmit the crowd information,
`which may include the crowd's demographics, number of
`people, locations, and/or patterns of movement, to goods
`and/or services provider 118. Provider 118 may then estimate
`the demands of the crowd for the provider's goods and/or
`services, including quantities and/or times, based at least in
`part on the received crowd information. Hence, provider 118
`may prepare to Supply a level or number of goods and/or
`services that corresponds to, or is appropriate for, the antici
`pated demands of the crowd.
`Many central offices may be provided, and individual cen
`tral offices 116 may be associated with certain respective
`geographic areas. In one embodiment, each geographic area
`may measure about a square mile, which may correspond to
`an area that the crowd is expected, during the next one to two
`hours, to traverse on foot, and/or to purchase goods and/or
`services within. Central office 116 may filter the crowd infor
`mation on a geographic basis, and thus use, or transmit to
`provider 118, only the crowd information that is of interest to
`provider 118. For example, central office 116 may transmit to
`provider 118 information only about mobile devices 112 that
`are within a half-mile radius of provider 118.
`In one embodiment, central office 116 may be in commu
`nication with only mobile devices 112 that are within the
`geographic area with which central office 116 is associated. In
`another embodiment, mobile devices 112 may be in commu
`nication with their corresponding wireless service carriers,
`and the carriers may determine the locations of mobile
`devices 112. Each of the wireless service carriers may then
`send to each central office 116 only information about mobile
`devices 112 that are within the geographic area with which
`that particular central office 116 is associated.
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`Demographic information about each of the users may be
`collected, and this demographic information may be used to
`derive or estimate characteristics of the crowds, such as the
`number of men or women in a certain age group.
`The changing locations of the mobile device users may
`continue to be monitored, and the motion of individual ter
`minals may be aggregated to estimate the movement of a
`crowd or to estimate changes in activity levels. Alternatively,
`the flow of terminals from one geographic cell or area to
`another may be used to estimate motion or activity.
`Instead of tracking the changing locations of individual
`terminals, changes in the terminal locations as a group,
`regardless of their individual identities or individual motions,
`may be monitored. Thus, "snapshots of the group locations
`may be taken at periodic time intervals without regard to the
`identities of the individual terminals.
`Regardless of whether the aggregated information relates
`to individual terminals or only to a group of the terminals as
`a whole, the aggregated information may be provided to
`providers of goods and/or services. The aggregated informa
`tion may be provided directly to providers of goods and/or
`services in an unfiltered state. Alternatively, there may be
`applied an analysis protocol that may determine which infor
`mation is of interest to which provider. Thus, each provider
`may receive only the filtered information in which he is inter
`ested or is willing to purchase. The providers of goods and/or
`services may then use the filtered or unfiltered information to
`decide the location, timing and/or quantity of goods and
`services to provide.
`FIG. 1 is a block diagram of an example arrangement 100
`for determining and/or collecting the location of a mobile
`device, which is arranged in accordance with at least some
`embodiments of the present disclosure. The example arrange
`ment 100 includes a mobile device 112 which a user may
`carry with him or on his person. Mobile device 112 may be
`a cell phone and/or another form of wireless device which
`may include a radio receiver, radio transmitter, processor
`and/or user interface. Mobile device 112 may include a built
`in GPS receiver and may be in communication with satellites
`114, 114, 114 and 114. Mobile device may determine its
`global geographic coordinates via communication with the
`satellites in conjunction with trilateration and/or other tech
`niques. Mobile device 112 may then wirelessly communi
`cate its location to a central office 116 or other centralized
`depository of mobile device location information. Central
`office 116 may be communicatively coupled to a memory
`device 120 which may store mobile device locations.
`In another embodiment in which the mobile device is not
`GPS-equipped, the mobile device may communicate with
`cell phone towers to determine its approximate global loca
`tion and transmit the location to the central office. It is also
`possible for one or more of the cell phone towers or the
`wireless service provider company to determine the location
`of the mobile device and transmit the location to the central
`office. For example, the iPhone 3G from Apple Computer can
`determine its approximate location using either GPS or a
`combination of proximate wireless access points.
`FIG. 2 is a block diagram of an example telemetrics-based
`location and/or tracking arrangement 200 including mobile
`device 112 and central office 116, which were described
`above with regard to FIG. 1, as well as other mobile devices
`112, 112,..., 112, (where n is any number), a goods and/or
`services provider 118, and a memory device 120 storing
`demographic and historical information. Each of the n num
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`ber of mobile devices 112, 112, 112. . . . , 112, may
`determine its location via communication with GPS satellites
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`to search criteria. For example, the detected population of
`mobile device 112 users may be broken down by the sex, age,
`income level, and/or place of residence of the users. Estimat
`ing the population of interest may further involve applying an
`estimation function to predict the actual potential customer
`base. This function may depend on: detected client locations;
`client demographic and historical information; source of cli
`ent location data; and/or the day of week and time-of-day. For
`example, a formula or lookup table may be used to estimate an
`expected level of sales for individuals detected within the
`region. Variables in the formula/lookup table may include the
`current location of the person, his demographic and/or his
`torical location information, how reliable the source of the
`client location data is, and/or the day of the week, time-of
`day, and/or season of the year. The formula/lookup table may
`be based on and/or derived from historical sales data, which
`data may relate to any of the variables and/or parameters used
`in the formula.
`In one example, a taxi company may have derived a for
`mula based on historical data for the likelihood that an indi
`vidual at an airport will hail a cab. According to the formula,
`the likelihood may be estimated as the sum total of four
`parameters that depend on the above-described variables. For
`instance, the first parameter may be 0.02 if the 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 0.03 if the person
`lives in the state, and 0.08 if he does not. The third parameter
`may be 0.06 if the user location data was received from a
`wireless service provider, and 0.03 if received from a less
`reliable third party. The fourth parameter may be 0.05 on a
`weekday, and 0.03 on a weekend. Thus, for a person currently
`at the gate area (0.02), who lives in the state (0.03), whose
`information was received from a third party (0.03), and for a
`weekday (0.05), the formula may indicate a probability of
`0.13, or 13 percent, that the person will attempt to hail a cab.
`By summing the estimated probabilities for individuals deter
`mined to be in the region (e.g., airport), the taxi company may
`estimate the number of taxi cabs that may be needed at the
`airport. Thus, for example, if 1,000 people are determined to
`be at the airport, and individuals have, on average, a 13%
`likelihood of hailing a cab, then it may be estimated that 130
`taxi cabs may be needed at the airport during some period of
`time. A message related to the estimated sales level may be
`transmitted to a user interface associated with the taxi com
`pany, Such as a printer, display monitor, wireless mobile
`device, and/or email account, for example.
`A further operation of the static population density map
`process may involve providing goods or services by deter
`mining the appropriate location for each service provider
`based on the predicted customer base and/or determining the
`appropriate quantity of service providers, service activity,
`and/or goods to be provided at individual locations of interest
`based at least in part on the predicted customer base proxi
`mate to that location. Still using the taxi company as an
`example, if a city has two airports needing taxi service, the
`demand at both airports may be considered when dispatching
`taxi cabs to one airport or the other. For example, if 120 taxis
`are needed at airport A and 80 taxis are needed at airport B, but
`the company has only 150 taxis, then the company may dis
`patch 90 of the taxis (60%) to airport A and 60 (40%) of the
`taxis to airport B. Continuing this example, iffares at airport
`Aare historically higher than fares at airport B, and/or have a
`higher profit margin, then the company may dispatch 120
`taxis to airport A and the 30 remaining taxis to airport B. If
`profitability warrants, the taxi company may even dispatch
`more than 120 taxis to airport A to increase the probability
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`In another embodiment, central office 116 may include a
`wireless access point in a retail store, library, and/or other
`public place. Mobile devices 112 may connect with the wire
`less access point only within a range of about one hundred
`meters, and thus the locations of the individual mobile
`devices 112 may not need to be specified with any greater
`precision. However, in this embodiment, central office 116
`may still receive demographic information from a wireless
`carrier or other source about the mobile devices that are in
`communication with the wireless access point.
`Static Population Density Map
`In one embodiment contemplated by the present disclo
`Sure, a static population density map may be provided. A first
`operation of this process may include determining the loca
`tions of individual accessible phones and/or data terminal
`customers. For example, mobile devices 112 within the geo
`graphic area of a central office 116, and/or the wireless car
`riers of such mobile devices, may report the exact locations of
`the mobile devices within the geographic area to central office
`116.
`As alluded to above, determining the location of each
`accessible phone and/or data terminal customer may possibly
`involve aggregating data from multiple sources. For example,
`data from the wireless service carriers, cell phone towers,
`third parties connected to the wireless service carriers or cell
`phone towers, and/or from the mobile devices themselves
`may be collected and integrated together by central office
`116.
`Another operation of the static population density map
`process may involve assigning the detected mobile device
`locations to geographic regions. For example, each central
`office 116 may be associated with one or more respective
`geographic regions. Such as an area in which potential com
`mon customers and/or clients of retailers within the geo
`graphic region may be congregated. However, it is to be
`understood that one central computer system may be
`arranged to create the maps and the associated data structures
`for many or all of the regions. Such a central computer system
`may be communicatively coupled to each of a plurality of
`central office's 116. In one embodiment, the geographic
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`region may be a set rectangular area within a city, such as a
`one mile by one mile Square. In other embodiments, the
`geographic region may be defined at least in part by barriers
`to travel (e.g., foot travel). Such as a river, highway, lake,
`private property, fence, and/or difficult terrain, for example.
`Thus, central office 116 may determine in which of the geo
`graphic regions that each mobile device 112 is disposed.
`Yet another operation of the static population density map
`process may involve estimating the population of interest for
`individual regions. For example, not all people, and not all
`people carrying a mobile device 112, may realistically qualify
`as a potential client and/or customer for every product and/or
`service. The pool of people in the region may be filtered based
`upon the time-of-day, day of the week, calendar date, histori
`cal information, and/or demographic information to identify
`people who have above a threshold level of likelihood of
`purchasing the particular goods and/or services of a provider
`118. In one embodiment, the population of interest may be
`estimated by accessing stored demographic and/and histori
`cal information about each detected client. For example, cen
`tral office 116 may retrieve demographic and/and historical
`information about mobile devices 112 from memory device
`120. The historical information may include a number of
`times, and/or a frequency with which, a particular mobile
`device 112 has visited provider 118.
`Estimating the population of interest may also involve
`filtering and/or weighting detected potential clients according
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`US 8,676,668 B2
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`that no available fares are missed at airport A in the event that
`the estimate of 120 needed taxis turns out to be low.
`Population Activity Map I
`In one embodiment contemplated by the present disclo
`Sure, a population activity map may be provided. A first
`operation of this process may include determining the loca
`tion of individual accessible phone and/or data terminal cus
`tomers. For example, mobile devices 112 within the geo
`graphic area of a central office 116, and/or the wireless
`carriers of Such mobile devices, may report the exact loca
`tions of the mobile devices within the geographic area to
`central office 116.
`As alluded to above, determining the location of individual
`accessible phone and/or data terminal customer may possibly
`involve aggregating data from multiple sources. For example,
`data from the wireless service carriers, cell phone towers,
`third parties connected to the wireless service carriers or cell
`phone towers, and/or from the mobile devices themselves
`may be collected and/or integrated together by central office
`116.
`Another operation of the population activity map process
`may involve comparing the location of individual accessible
`phone and/or data terminal customers to prior locations. For
`example, the current location of a mobile device 112 may be
`compared to an immediately previous location of that same
`mobile device 112.
`Yet another operation of the population activity map pro
`cess may involve using the displacement of individual cus
`tomers and/or the time between measurements to determine
`an activity level for individual customers. For example, the
`current location of individual mobile devices 112 may be
`compared to their immediately previous locations to deter
`mine trends in where people are going. The time between
`measurements, coupled with the location displacement of the
`people, may indicate the speed and/or direction in which the
`people are moving, and hence the time at which they may be
`able to reach provider 118. The speed at which people move
`may also be used as an indication of their level of conviction
`in moving in their current direction. For instance, the faster
`people move, the more likely it may be that they will continue
`moving in same direction in which they are currently moving.
`Still another operation of the population activity map pro
`cess may involve assigning the activity levels to regions. For
`example, individual central offices 116 may be associated
`with respective geographic regions, such as an area in which
`potential common customers and/or clients of retailers within
`the geographic region may be congregated. In one embodi
`ment, the geographic region may be a predetermined rectan
`gular area within a city, such as a one mile by one mile square.
`In other embodiments, the geographic region may be defined
`at least in part by barriers to travel (e.g., foot travel). Such as
`a river, highway, lake, private property, fence, and/or difficult
`terrain, for example. Thus, central office 116 may determine
`in which of the geographic regions that individual moving
`mobile devices 112 are disposed. In one embodiment, only
`those mobile devices 112 moving at at least a minimum
`threshold speed and/or within a range of directions may be
`assigned to geographic regions.
`A further operation of the population activity map process
`may involve estimating the activity level of a population of
`interest for each region. For people who realistically qualify
`as a potential client and/or customer for a particular provider
`118, their direction, frequency, speed and/or degree of move
`ment may be determined at least partially by comparing cur
`rent locations to previous locations at certaintimes in the past.
`The previous locations may include the immediately preced
`ing location and/or locations that were determined further
`
`Case: 1:21-cv-00699-JG D