(12) United States Patent
`Etchegoyen
`
`(10) Patent No.:
`(45) Date of Patent:
`
`US 9,414,199 B2
`Aug. 9, 2016
`
`US00941.4.199B2
`
`(54) PREDICTIVE DELIVERY OF INFORMATION
`BASED ON DEVICE HISTORY
`
`(56)
`
`References Cited
`
`|U.S. PATENT DOCUMENTS
`
`6,151,631 A 11/2000 Ansell et al.
`7.057,556 B2
`6/2006 Hall et al.
`7,091,851 B2
`8/2006 Mason et al.
`7,826,409 B2 11/2010 Mock et al.
`8,320,938 B2 11/2012 Meyer et al.
`8,606,220 B2 12/2013 Soliman et al.
`2003/0046022 A1
`3/2003 Silverman
`2003/0134648 A1
`7/2003 Reed et al.
`2003/0176.196 A1
`9/2003 Hall et al.
`2003/0222820 A1 12/2003 Karr et al.
`2004/0002346 A1
`1/2004 Santhoff
`2004/0198392 A1 10/2004 Harvey et al.
`2005/0070306 A1
`3/2005 Kim et al.
`2005/0249 175 A1 * 1 1/2005 Nasu et al. .................... 370/338
`(Continued)
`
`FOREIGN PATENT DOCUMENTS
`
`EP
`EP
`
`1/2007
`1 739 879 A1
`9/2009
`2 096 597 A2
`(Continued)
`Primary Examiner — Viet Vu
`(74) Attorney, Agent, or Firm – Sean D. Burdick
`(57)
`ABSTRACT
`A server sends information to user devices based on not only
`the current location of those devices but also predicted future
`locations of those devices. A number of actions are associated
`with one or more predetermined locations, a predetermined
`maximum amount of time, and a predetermined minimum
`likelihood. When the server determines that a given user
`device is likely to be in one of the predetermined locations
`within the predetermined maximum amount of time with at
`least the predetermined minimum likelihood, the server per
`forms the associated acts with respect to the user device. An
`example of such an action is sending a promotion or adver
`tisement to the user device, e.g., as an SMS message.
`5 Claims, 6 Drawing Sheets
`
`{{}}
`
`106
`
`(71) Applicant: Uniloc Luxembourg S.A., Luxembourg
`(LU)
`(72) Inventor: Craig S. Etchegoyen, Plano, TX (US)
`Assignee:
`(73)
`Uniloc Luxembourg S.A., Luxembourg
`(LU)
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 135 days.
`
`(*) Notice:
`
`(21)
`(22)
`(65)
`
`Appl. No.:
`
`14/188,063
`
`Filed:
`
`Feb. 24, 2014
`
`Prior Publication Data
`|US 2014/0258471 A1
`Sep. 11, 2014
`
`Related U.S. Application Data
`Provisional application No. 61/774,305, filed on Mar.
`7, 2013.
`Foreign Application Priority Data
`
`(60)
`
`(30)
`
`Jun. 7, 2013 (AU) ................................ 2013 100804
`
`(2009.01)
`(2009.01)
`(2009.01)
`
`(51) Int. Cl.
`H04 W 4/02
`PH04W 4/14
`PH04W 4/20
`U.S. CI.
`CPC ................ H04W.4/028 (2013.01); H04W 4/14
`(2013.01); H04W 4/206 (2013.01)
`Field of Classification Search
`USPC .......................... 709/204, 217, 219, 223, 224
`See application file for complete search history.
`
`(52)
`
`(58)
`
`
`
`NETWORK
`103
`
`APPLE EXHIBIT 1001
`Page 1 of 12
`
`

`

`US 9,414,199 B2
` Page 2
`
`(56)
`
`References Cited
`
`us. PATENT DOCUMENTS
`
`11/2006 Phillips etal.
`2006/0270421 A1
`8/2007 Kalliola etal.
`2007/0197229 A1
`11/2007 Maier etal.
`2007/0270164 A1
`4/2008 Kratz
`2008/0085727 A1
`5/2008 Burman etal.
`2008/0102957 A1
`6/2008 Roese et al.
`2008/0155094 A1
`7/2008 Fast etal.
`2008/0167896 A1
`9/2008 Wyk etal.
`2008/0233956 A1
`2009/0319177 A1* 12/2009 Khosravy etal.
`
`4/2010 Agashe
`2010/0087166 A1
`1/2011 Priebatsch etal. ......... 705/14.58
`2011/0010245 A1*
`8/2011 Craig etal.
`2011/0196711 A1
`2012/0271884 A1* 10/2012 Holmes etal.
`
`................ 709/204
`
`.................. 709/204
`2/2013 Tseng et al.
`2013/0036165 A1*
`FOREIGN PATENT DOCUMENTS
`
`EP
`EP
`wo
`
`2182752
`2 287 820
`wo 2008/055865
`
`5/2010
`2/2011
`5/2008
`
`............. 701/207
`
`* cited by examiner
`
`APPLE EXHIBIT 1001
`
`Page 2 of 12
`
`APPLE EXHIBIT 1001
`Page 2 of 12
`
`

`

`U.S. Patent
`
`Aug. 9, 2016
`
`Sheet 1 of 6
`
`US 9,414,199 B2
`
`406
`E=E=m"
`EEE
`
`,
`
`
`
`NETWORK
`408
`
`APPLE EXHIBIT 1001
`Page 3 of 12
`
`

`

`U.S. Patent
`
`Aug. 9, 2016
`
`Sheet 2 of 6
`
`US 9,414,199 B2
`
`200
`
`202
`
`SERVER 106
`
`FOR LOCATHON REPORT
`
`204
`
`j}{}{TAi FNGERPRINT
`CHALLENGE
`
`£ETERM;\{{ {}{\#CE'S
`LOCATION
`
`206
`
`PRO?)i.jøE RESPONS:VE
`D.F.P, FROM CHAil:NGE
`
`208
`
`ÇRYPTOGRAPHCA.E.Y
`CCA;&#NE RESPONS:VE
`I.F.P. WiTH LOCATION
`?ATA
`
`240
`
`212
`
`
`
`$END COM3;NE)
`{}.F.P., AND OCATION
`
`STORE DEV;CE'S
`?CCATHON
`
`244
`
`246
`
`ANY TR}{3GBRED
`LOCATION-BASED ACTION(S)
`
`FIGURE 2
`
`APPLE EXHIBIT 1001
`Page 4 of 12
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`

`

`U.S. Patent
`
`Aug. 9, 2016
`
`Sheet 3 of 6
`
`US 9,414,199 B2
`
`?OCATION ATA RECORD 300
`
`i_OCATION-BASED ACTHCN RECORD 400
`
`DEVACE C.F.P. 302
`
`i_OCATHON REPORT 304
`
`i_{}{ATHON 306
`
`ºf ME STAMP 308
`
`FIGURE 3
`
`TRHGGER EVENT 402
`
`ACTHON 404
`
`FIGURE 4
`
`
`
`TRGGER EVENT 402
`
`ACTHOA 404
`
`THRESHOLD #&#_{HOOiD 502
`
`THRESHOLD TME 504
`
`APPi_{CABLE LOCAT:C^{ 606
`
`i_{}{ATHON 508
`
`RAD}{}S 540
`
`ACTj?h; i. Cºi? 632
`
`ACTHON CONTEN i 604
`
`FIGURE 5
`
`FIGURE 6
`
`APPLE EXHIBIT 1001
`Page 5 of 12
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`

`

`U.S. Patent
`
`Aug. 9, 2016
`
`Sheet 4 of 6
`
`US 9,414,199 B2
`
`GATHER i CCATHON
`|NFORMATION, DATE,
`AND THAft:
`
`702
`
`
`
`
`
`FOR EACH
`i_OCATHON-BASED
`ACTHON RECORD
`
`§C MORE
`
`
`
`
`
`
`
`
`
`TRHGGER
`EVENT
`DETECTED7
`
`740
`
`
`
`APPLE EXHIBIT 1001
`Page 6 of 12
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`

`

`U.S. Patent
`
`Aug. 9, 2016
`
`Sheet 5 of 6
`
`US 9,414,199 B2
`
`822
`
`BEV CE
`TRACKNG
`
`820
`
`
`
`
`
`CPU 802
`
`#NTERCONNECT 806
`
`
`
`
`
`OUTPUT
`
`840
`
`NETWORK
`ACCESS
`GPS
`C#FCUHTRY cº
`842
`
`FIGURE 8
`
`APPLE EXHIBIT 1001
`Page 7 of 12
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`

`

`US. Patent
`
`Aug. 9, 2016
`
`Sheet 6 of6
`
`US 9,414,199 B2
`
`MEMORY Q04
`
`WEB SERVER
`LOGEC
`
`gm
`
`LQCATEQN MONITORENG
`LOGIC
`
`926
`
`LOCATiON ANALYSES
`LOGIC
`
`928
`
`WEB APPLECATEQN LGGEC 922
`
`LOCATEON DATA
`940
`
`LOCATION ANALYSES
`LDC-SEC
`
`924
`
`ACTEON DATA
`942
`
`ENTERCONNECT 906
`
`
`
`NETWORK
`ACCESS
`CIRCUITRY
`912
`
`HQLEQE g
`
`APPLE EXHIBIT 1001
`
`Page 8 of 12
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`APPLE EXHIBIT 1001
`Page 8 of 12
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`

`

`1
`PREDICTIVE DELIVERY OF INFORMATION
`BASED ON DEVICE HISTORY
`
`US 9,414,199 B2
`
`This application claims priority to U.S. Provisional Appli
`cation 61/774,305, filed Mar. 7, 2013, which is fully incorpo
`rated herein by reference.
`
`BACKGROUND OF THE INVENTION
`
`1. Field of the Invention
`The present invention relates generally to computer data
`processing and, more particularly, methods of and systems
`for delivery of information to a device based on the location
`history of the device.
`2. Description of the Related Art
`Location-based services have been recognized as impor
`tant and valuable for years. Typically, providers of location
`based services arrange to have information regarding services
`delivered to device when the device is determined to be near
`a given location. However, the current location of a device
`provides very limited information about the device and there
`fore limits how relevant any location-based information sent
`to the device can be.
`What is needed is a way to provide information to a device
`where the information is selected based on more than just the
`current location of the device.
`
`10
`
`15
`
`20
`
`25
`
`SUMMARY OF THE INVENTION
`
`In accordance with the present invention, a server sends
`information to user devices based on not only the current
`location of those devices but also predicted future locations of
`those devices. Overtime, server gathers location information
`from the user devices to collect locations histories of the
`devices and uses the location histories to periodically predict
`future locations of the devices.
`A number of actions are associated with one or more pre
`determined locations, a predetermined maximum amount of
`time, and a predetermined minimum likelihood. When the
`server determines that a given user device is likely to be in one
`of the predetermined locations within the predetermined
`maximum amount of time with at least the predetermined
`minimum likelihood, the server performs the associated acts
`with respect to the user device. An example of such an action
`is sending a promotion or advertisement to the user device,
`e.g., as an SMS message.
`To make a prediction regarding future locations of the user
`device, the server considers the user device’s location history
`in a current context. One part of the current context is the
`current day and the current time. To appreciate this context, it
`is helpful to consider an example. Consider that a new depart
`ment store has opened at a given location. The manager of the
`department store can request that anyone that is at least 50%
`likely to visit a store considered to be in competition of the
`department store within one hour should be sent a promo
`tional code entitling that person to a discount. To do so, the
`manager can specify locations of all competing stores within
`a five-mile radius of the given location as the one or more
`predetermined locations. In addition, the manager can specify
`50% as the predetermined minimum likelihood and one hour
`as the predetermined maximum amount of time. The manager
`can also specify days and times at which the actions are
`applicable, e.g., only during hours at which the new depart
`ment store is open.
`Another part of the current context is the current location of
`the user device. Continuing in the example above, consider
`that a given user device has a history of shopping at the
`
`30
`
`35
`
`40
`
`45
`
`50
`
`55
`
`60
`
`65
`
`2
`department store to get excellent customer service in learning
`about new products and then immediately going to a discount
`store to buy the new products at a lower price—the classic
`free rider problem. The presence of the user device in the
`department store can indicate that the user device will soon be
`heading to a competitor of the department store. Recognizing
`this, the server can deliver a promotional code to the user
`device, encouraging the user of the user device to buy the
`product in the department store rather than at the competitor.
`In addition, if the manager of the department store sets up
`different actions for locations of competitors of a given type
`of store, the promotional code can be for a particular type of
`goods. Consider that all competitors selling electronics prod
`ucts are the predetermined locations. The action can be send
`ing a promotional code for a discount on electronic products
`to the user device.
`The current context can also be a combination of the cur
`rent day and time and the current location of the user device.
`Continuing in the above example, consider that the depart
`ment store includes a restaurant that does brisk business in the
`evenings but is nearly empty at lunch time on weekdays
`despite a flourishing business neighborhood in which many
`workers typically eat lunch at restaurants. The same manager
`can specify other nearby restaurants as the predetermined
`locations but limit the applicability of those locations to week
`days from 11:30 am to 2:00 pm, for example.
`Unlike conventional location-based services in which
`information is presented to a user device based on its current
`location only, the information presented to a user device in the
`manner described herein can actually influence the future
`location of the user device by offering an alternative trip the
`user can take rather than the trip typically taken in the current
`COntext.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`Other systems, methods, features and advantages of the
`invention will be or will become apparent to one with skill in
`the art upon examination of the following figures and detailed
`description. It is intended that all such additional systems,
`methods, features and advantages be included within this
`description, be within the scope of the invention, and be
`protected by the accompanying claims. Component parts
`shown in the drawings are not necessarily to scale, and may be
`exaggerated to better illustrate the important features of the
`invention. In the drawings, like reference numerals may des
`ignate like parts throughout the different views, wherein:
`FIG. 1 is a diagram showing a server computer that gathers
`and analyzes location data from a number of mobile devices
`through a computer network to send information to a user
`device based on predicted future locations in accordance with
`one embodiment of the present invention.
`FIG. 2 is a transaction flow diagram showing reporting of
`current location by a mobile device of FIG. 1.
`FIG. 3 is a block diagram of a location data record used by
`the server of FIG. 1 to represent a location report received
`from a mobile device.
`FIG. 4 is a block diagram of a location-based action record
`used by the server of FIG. 1 to take actions based on predicted
`future locations of mobile devices.
`FIG. 5 is a block diagram of a trigger event of the location
`based action record of FIG. 4 in greater detail.
`FIG. 6 is a block diagram of an action of the location-based
`action record of FIG. 4 in greater detail.
`
`APPLE EXHIBIT 1001
`Page 9 of 12
`
`

`

`US 9,414,199 B2
`
`3
`FIG. 7 is a logic flow diagram illustrating the manner in
`which the server of FIG. 1 processes location-based action
`records to take actions based on predicted future locations of
`mobile devices.
`FIG. 8 is a block diagram showing a mobile device of FIG.
`1 in greater detail.
`FIG. 9 is a block diagram showing the server of FIG. 1 in
`greater detail.
`
`DETAILED DESCRIPTION
`
`5
`
`10
`
`15
`
`4
`network 108 or any network will not authenticate properly if
`used in response to a different digital fingerprint challenge.
`In step 206, user device 102A determines its geographic
`location. The manner in which user device 102A determines
`its geographical location is described in U.S. Application
`61/746,719, which was filed Dec. 31, 2012, and which is fully
`incorporated herein by reference.
`In step 208, user device 102A produces a responsive digital
`fingerprint data using the challenge received in step 204 and
`digital fingerprint 822 (FIG. 8).
`In step 210 (FIG. 2), user device 102A cryptographically
`combines the responsive digital fingerprint data produced in
`step 208 with data representing the location of user device
`102A determined in step 208. By cryptographically combin
`ing the responsive digital fingerprint data and the location
`data, user device 102A makes the data tamper-evident and
`obscured.
`In step 212, user device 102A sends the combined data to
`server 106. In step 214, server 106 parses the responsive
`digital fingerprint data and location data and stores the loca
`tion of user device 102A in location data 940 (FIG. 9).
`Server 106 stores the location of user device 102A in a
`location data record 300 (FIG. 3). Device digital fingerprint
`302 is the digital fingerprint by which user device 102A is
`identified and authenticated. A number of location reports
`304 identify the location of user device 102A at a given date
`and time. Location 306 represents the location of user device
`102A, and time stamp 308 represents the date and time.
`In step 216 (FIG.2), server 106 sends information specified
`in any location-based actions stored by server that are trig
`gered by the location history of user device 102A. After step
`216, processing according to transaction logic diagram 200
`completes.
`Location-based actions specify actions to be taken if user
`device 102A is predicted to be in any of a number of locations
`in the future within a predetermined amount of time by a
`predetermined threshold likelihood. An example of such a
`location-based action is represented by location-based action
`record 400 (FIG. 4). Location-based action record 400
`includes a trigger event 402 that represents the conditions
`under which action is to take place and an action 404 that is to
`take place under the conditions represented by trigger event
`402.
`Trigger event 402 is shown in greater detail in FIG. 5. In
`essence, trigger event 402 asks whether user device 102A is
`likely to be in any of a number of locations within a prede
`termined amount of time in the future. Threshold likelihood
`502 specifies a predetermined threshold likelihood. Thresh
`old time 504 specifies a predetermined threshold amount of
`time into the future. Each of a number of application locations
`506 specifies the locations. In this illustrative embodiment,
`each applicable location 506 is specified by a location 508
`(such as latitude and longitude, for example) and a radius 510.
`Thus, trigger event 402 specifies, as a condition for perfor
`mance of action 404 (FIG. 4), that user device 102A must be
`determined to be at least as likely as threshold likelihood 502
`(FIG. 5) to be at any of applicable locations 506 within an
`amount of time represented by threshold time 504.
`Action 404 (FIG. 4) is shown in greater detail in FIG. 6.
`Action logic 602 specifies the behavior of server 106 in per
`forming action 404. For example, action logic 602 can cause
`server 106 to send an SMS or MMS message to user device
`102A or to register user device 102A as one to receive a
`special discount if used to pay for a transaction at a merchant.
`Action content 604 specifies content to be used in perfor
`mance of action logic 602, e.g., the content to send to user
`device 102A as a SMS or MMS message.
`
`In accordance with the present invention, a server 106
`(FIG. 1) sends information to user devices 102A-D based on
`not only the current location of those devices but also pre
`dicted future locations of those devices. Overtime, server 106
`gathers location information from user devices 102A-D and
`uses the gathered location information to periodically predict
`future locations of the devices.
`User devices 102A-D (FIG. 1) each can be any of a number
`of types of networked computing devices, including smart
`phones, tablets, netbooks, laptop computers, and desktops
`computers, though location information is expected to be
`more useful for devices that are portable. Each of user devices
`102A-D serves as a location proxy for a single user. In other
`words, the location of each of user devices 102A-D is pre
`sumed to be the location of a single user. In addition, each of
`user devices 102A-D communicates with server 106 through
`a network 108, which is the Internet in this illustrative
`embodiment. Network 108 can also be a mobile telephony
`network. User devices 102A–D are analogous to one another
`and description of user device 102A is equally applicable to
`user devices 102B-D unless otherwise noted herein. It should
`also be noted that, while four (4) user devices are shown in
`this illustrative example, more or fewer than four (4) user
`devices can report locations for receiving future-location
`based information in the manner described herein.
`Transaction flow diagram 200 (FIG. 2) illustrates the
`reporting by user device 102A of its location to server 106.
`In step 202, user device 102A sends its globally unique
`device identifier to server 106 along with data indicating an
`intent to report the current location of user device 102A.
`In step 204, server 106 sends a digital fingerprint challenge
`to user device 102A. Digital fingerprints and digital finger
`print challenges are known and described in U.S. Patent
`Application Publication 2011/0093503 for “Computer Hard
`ware Identity Tracking Using Characteristic Parameter-De
`rived Data” by Craig S. Etchegoyen (filed Apr. 21, 2011) and
`that description is incorporated herein in its entirety by ref
`erence.
`Digital fingerprints offer the advantage of being more
`stable and less amenable to spoofing that are IP addresses and
`MAC addresses and, of particular significance here, require
`no user intervention. Accordingly, location reporting in trans
`action flow diagram 200 is secure, reliable (no device spoof
`ing), and requires no action on the part of the user.
`To avoid frequent communication of digital fingerprints
`through network 108, device identification and authentication
`uses only part of the digital fingerprints of user devices 102A
`D. A digital fingerprint challenge specifies one or more parts
`of a digital fingerprint and a manner in which the parts are
`combined and cryptographically obscured. In addition, the
`digital fingerprint challenge can change each time device
`identification and authentication is needed. Accordingly, each
`time a given device sends its digital fingerprint in response to
`a different digital fingerprint challenge, the digital fingerprint
`sent is different. Any digital fingerprint intercepted within
`
`20
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`25
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`30
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`Page 10 of 12
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`5
`In some embodiments, location-based action record 400
`can have multiple trigger events 402 combined with “AND”
`and/or “OR” relationships and/or multiple actions 404.
`The manner in which server 106 processes location-based
`action records such as location-based action record 400 is
`illustrated by logic flow diagram 700 (FIG. 7). In step 702,
`server 106 gathers the current location of user device 102A
`and the current date and time.
`Loop step 704 and next step 712 define a loop in which
`server 106 processes each of a number of location-based
`action records according to steps 706-710. During each itera
`tion of the loop of steps 704-712, the particular location
`based action record processed by server 106 is sometimes
`referred to as “the subject location-based action record.”
`In step 706, server 106 determines whether the subject
`location-based action record is currently triggered. There are
`generally two (2) predictive patterns checked by server 106 in
`determining the likelihood of user device 102A to be in a
`particular place at a particular time. The first is by analyzing
`the location data record 300 (FIG. 3) for user device 102A for
`location patterns associated with times of day, days of the
`week, days of the month, and days of the year. For example,
`the user of user device 102A might have lunch at the same
`place at least three (3) days each work week—typically at
`about 12:30 pm. If the current time is 12:00 pm and it is
`currently a work week day, server 106 can determine that the
`likelihood of user device 102A going to that same place
`within the next hour to be three in five, or 60%. Server 106 can
`also take into account other information such as whether user
`device 102A has not gone to that same place in the previous
`two (2) days of the current work week.
`The second is by analyzing the location data record 300
`(FIG. 3) for user device 102A for location patterns associated
`with other locations of user device 102A. In other words,
`server 106 tries to answer the question, “Given that user
`device 102A is at its current location, what are the odds that
`user device 102A will be in another given location within the
`predetermined amount of time according to the location his
`tory of user device 102A2” For example, a user may have the
`tendency to shop in a large department store to get help from
`sales clerks and then go around the corner to a discount shop
`to buy merchandise at a great discount. The presence of user
`device 102A in the large department store can indicate that
`user device 102A is likely to be in the discount shop in the
`near future.
`Server 106 can identify such a tendency by identifying
`each location report 304 (FIG. 3) representing a location of
`user device 102A within a predetermined distance of its cur
`rent location and determining how many of those location
`reports 304 are followed within the predetermined amount of
`time of threshold time 504 (FIG. 5) of a location report 304
`(FIG. 3) of user device 102A at one or more of applicable
`locations 506 (FIG. 5).
`Server 106 can also combine the current time and the
`current location of user device 102A in testing trigger event
`402. For example, server 106 can consider only location
`reports 304 (FIG. 3) that are near the current location of user
`device 102A and that have time stamps 308 that are between
`the current time and the future time represented by threshold
`time 504 (FIG. 5) for relevant days of the week, month, year,
`etc. Considering only those location reports 304 (FIG. 3),
`server 106 can determine how frequently user device 102A
`visits an applicable location 506 after being at its current
`location.
`It is helpful to consider the example of a trigger event 402
`(FIG. 5) in which threshold likelihood 502 represents 70%,
`threshold time 504 represents one hour, and applicable loca
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`tions 506 represent various locations of a retail business. This
`trigger can be satisfied (i) if user device 102A goes to the retail
`business in a predictable pattern, such as every Friday evening
`at around 6:30 pm and it’s currently 5:45 pm, of (ii) if user
`device 102A typically visits a competitor retail business
`before visiting the subject retail business and user device
`102A is currently at the competitor retail business.
`Intest step 708 (FIG. 7), server 106 determines whether the
`trigger event of the subject location-based action record is
`satisfied. If so, processing transfers to step 710 in which
`server 106 performs the action of the subject location-based
`action record. If not, server 106 skips step 710.
`After steps 708–710, processing by server 106 transfers
`through next step 712 to loop step 704 and server 106 pro
`cesses the next location-based action record according to the
`loop of steps 704-712. When all location-based action records
`have been processed according to the loop of steps 704-712,
`processing according to logic flow diagram 700 completes.
`In one embodiment, user device 102A is configured to
`report its location according to transaction logic diagram 200
`at regular time intervals. In an alternative embodiment, user
`device 102A is configured to report its location according to
`transaction logic diagram 200 in response to a number of
`triggering events, including for example, determination of the
`location of user device 102A for reasons independent of
`reporting of the location to server 106 and connecting to a
`wireless networking access point. Thus, any time the user of
`user device 102A uses GPS circuitry of user device 102A
`resulting in determination of the location of user device
`102A, user device 102A reports the location to server 106 in
`the manner described above.
`User device 102A is a personal computing device and is
`shown in greater detail in FIG. 8. User device 102A includes
`one or more microprocessors 802 (collectively referred to as
`CPU 802) that retrieve data and/or instructions from memory
`804 and execute retrieved instructions in a conventional man
`ner. Memory 804 can include generally any computer-read
`able medium including, for example, persistent memory such
`as magnetic and/or optical disks, ROM, and PROM and vola
`tile memory such as RAM.
`CPU 802 and memory 804 are connected to one another
`through a conventional interconnect 806, which is a bus in
`this illustrative embodiment and which connects CPU 802
`and memory 804 to one or more input devices 808, output
`devices 810, and network access circuitry 812. Input devices
`808 can include, for example, a keyboard, a keypad, a touch
`sensitive screen, a mouse, a microphone, and one or more
`cameras. Output devices 310 can include, for example, a
`display—such as a liquid crystal display (LCD)—and one or
`more loudspeakers. Network access circuitry 812 sends and
`receives data through computer networks such as network
`108 (FIG. 1). GPS circuitry 814 determines the location of
`user device 102A in a conventional manner.
`A number of components of user device 102A are stored in
`memory 804. In particular, device tracking logic 820 is all or
`part of one or more computer processes executing within
`CPU 802 from memory 804 in this illustrative embodiment
`but can also be implemented using digital logic circuitry. As
`used herein, “logic” refers to (i) logic implemented as com
`puter instructions and/or data within one or more computer
`processes and/or (ii) logic implemented in electronic cir
`cuitry. Device tracking logic 820 causes user device 102A to
`report its location in the manner described above.
`Digital fingerprint 822 is persistent data stored in memory
`804.
`Server 106 is a computing device and is shown in greater
`detail in FIG. 9. Server 106 includes one or more micropro
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`cessors 902 (collectively referred to as CPU 902), memory
`904, an interconnect 906, and network access circuitry 912
`that are analogous to CPU 802 (FIG. 8), memory 804, inter
`connect 806, and network access circuitry 812, respectively.
`A number of components of server 106 are stored in
`memory 904. In particular, web server logic 920 and web
`application logic 922, including location analysis logic 924,
`are each all or part of one or more computer processes execut
`ing within CPU 902 from memory 904 in this illustrative
`embodiment but can also be implemented using digital logic
`circuitry. Location monitoring logic 926 and location analy
`sis logic 928 are also each all or part of one or more computer
`processes executing within CPU 902 from memory 904 in
`this illustrative embodiment but can also be implemented
`using digital logic circuitry.
`Web server logic 920 is a conventional web server. Web
`application logic 922 is content that defines one or more pages
`of a web site and is served by web server logic 920 to user
`devices such as user device 102A. Location analysis logic 924
`specifies the behavior of server 106 in providing location
`analysis services in the manner described above. For
`example, location analysis logic 924 determines the likeli
`hood that user device 102A will be in a particular location
`within a predetermined amount of time. In addition, location
`analysis logic 924 analyzes location data 940, invoking loca
`tion analysis logic 928 in some embodiments.
`Location monitoring logic 926 specifies the behavior of
`server 106 in receiving location reports in the manner
`described above and in the UN-003 Application. Location
`analysis logic 928 specifies the behavior of server 106 in
`analyzing location data 940 in the manner described herein
`and in the UN-003 Application.
`Location data 940 and action data 942 are each data per
`sistently stored in memory 904 and are each organized as one
`or more databases in this illustrative embodiment. Location
`data 940 includes location data records such as location data
`record 300 (FIG. 3). Action data 942 includes location-based
`action records such as location-based action record 400 (FIG.
`4).
`The above description is illustrative only and is not limit
`ing. The present invention is defined solely by the claims
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`which follow and their full range of equivalents. It is intended
`that the following appended claims be interpreted as includ
`ing all such alterations, modifications, permutations, and sub
`stitute equivalents as fall within the true spirit and scope of the
`present invention.
`What is claimed is:
`1. A method for delivering information to two or more user
`devices, the method comprising:
`retrieving the information from one or more data records
`that associate the information with one or more prede
`termined locations, a predetermined maximum amount
`of time, a predetermined likelihood, and one or more
`predetermined actions; and
`for each of the two or more user devices:
`predicting whether the user device will be at any of the one
`or more predetermined locations within the predeter
`mined maximum amount of time with at least the pre
`determined likelihood; and
`in response to the predicting that the user device will be at
`any of the one or more predetermined locations within
`the predetermined maximum amount of time with at
`least the predetermined likelihood, performing the one
`or more predetermined actions;
`wherein at least one of the actions includes delivering the
`information to the user device.
`2. The method of claim 1 wherein predicting comprises:
`analyzing a location history of the user device.
`3. The method of claim 1 wherein predicting comprises:
`analyzing a location history of the user device for day- and
`time-based patterns related to a current time and a cur
`rent day.
`4. The method of claim 1 wherein predicting comprises:
`analyzing a location history of the user device for move
`ment patterns related to a current location of the user
`device.
`5. The method of claim 1 further comprising:
`analyzing a location history of the user device for patterns
`that involve day- and time-based and movement related
`to a current time, a current day, and a current location of
`the user device.
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