(12) United States Patent
`Putz
`
`(10) Patent No.:
`(45) Date of Patent:
`
`US 8,531,293 B2
`Sep. 10, 2013
`
`USOO8531293B2
`
`(54) PREDICTIVE GEOFENCE CROSSING
`(75) Inventor: Jason T. Putz, St. Louis, MO (US)
`(73) Assignee: Lockheed Martin Corporation,
`Bethesda, MD (US)
`s
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 448 days
`M
`YW-
`y
`yS.
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`(*) Notice:
`
`(21) Appl. No.: 12/908,293
`
`(22) Filed:
`
`(65)
`
`Oct. 20, 2010
`O
`O
`Prior Publication Data
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`• 1-- s
`O
`O
`Related U.S. Application Data
`(60) Provisional application No. 61/282,150, filed on Dec.
`23, 2009.
`(51) Int. Cl
`G08B I3/00
`E; WA,
`GOIC 22/00
`(52) U.S. Cl.
`USPC ........... 340/541; 340/.435; 340/945; 340/988:
`340/994: 701/23: 701/408; 701/465; 701/466;
`70/467.70/468. 701/30,701/303
`(58) Field of Classification Search
`None
`See application file for complete search history.
`References Cited
`
`(2006.01)
`3:08:
`(2006.01)
`
`(56)
`
`U.S. PATENT DOCUMENTS
`701,301
`4,646,244. A * 2/1987 Bateman et al. .
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`7,277,015 B1 10/2007 Morhard et al.
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`
`2/2008 Harvey
`7,327,250 B2
`6/2008 Horton et al.
`7,385.499 B2
`2/2009 Verechtchiagine
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`7,795,566 B2 * 9/2010 Koenig ........................ 244.3.15
`8,185.296 B2 * 5/2012 Yokoyama et al.
`TO1,117
`8,380,424 B2 * 2/2013 Bushnell ....................... TO1,122
`2006, OO30333 A1
`2/2006 Ward et al.
`2006/0293.842 A1 12/2006 Casino
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`Omerantz et al.
`2007,0185728 A1
`8, 2007 Schwarz et al.
`2007/0262861 A1 11/2007 Anderson et al.
`2008/0129490 A1
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`6/2008 Ruperto
`2008. O164984 A1
`7, 2008 Sheffer
`2008. O1744.85 A1
`7/2008 Carani et al.
`2008/0234935 A1
`9, 2008 Wolfetal.
`
`2009/0088.972 A1* 4/2009 Bushnell ....................... TO1,210
`2009. O140886 A1* 6/2009 Bender ......................... 340.988
`2009. O150070 A1
`6/2009 Alewine et al.
`2011/O153143 A1* 6, 2011 O'Neil et al. ................... 7O1/29
`2012/02094.57 A1* 8, 2012 Bushnell ......................... TO1/13
`* cited by examiner
`
`Primary Examiner — Julie Lieu
`Firm – Oblon,
`(74) Attorney,
`Agent,
`Of
`McClelland, Maier & Neustadt, L.L.P.
`
`Spivak,
`
`ABSTRACT
`(7)
`A predictive geofence system predicts a geofence crossing for
`a distance-horizon and/or a time-horizon. The predictive
`geofence system includes a predictive geofence platform that
`predicts future positions of objects, and generates an alert if
`the predicted future positions of the objects result in a
`geofence crossing or the predicted future positions cross a
`geofence in less than a set time.
`
`17 Claims, 10 Drawing Sheets
`
`Textron Specialized Vehicles Inc., Exh. 1007, p. 1
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`U.S. Patent
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`Sep. 10, 2013
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`Sheet 1 of 10
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`US 8,531,293 B2
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`Textron Specialized Vehicles Inc., Exh. 1007, p. 2
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`U.S. Patent
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`Sep. 10, 2013
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`Sheet 2 of 10
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`Textron Specialized Vehicles Inc., Exh. 1007, p. 3
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`U.S. Patent
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`Sheet 3 of 10
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`Textron Specialized Vehicles Inc., Exh. 1007, p. 4
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`U.S. Patent
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`Sep. 10, 2013
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`Textron Specialized Vehicles Inc., Exh. 1007, p. 5
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`Sep. 10, 2013
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`Textron Specialized Vehicles Inc., Exh. 1007, p. 6
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`Textron Specialized Vehicles Inc., Exh. 1007, p. 7
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`U.S. Patent
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`Sep. 10, 2013
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`Sheet 7 of 10
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`Textron Specialized Vehicles Inc., Exh. 1007, p. 8
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`Textron Specialized Vehicles Inc., Exh. 1007, p. 9
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`U.S. Patent
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`Sep. 10, 2013
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`GENERATE NEW PERMETER AND CENTROD OF GEOFENCE
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`CALCULATE SPEED AND DIRECTION OF MOVEMENT
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`PREDICT FUTURE POSITION BASED ON TIME AND/OR DISTANCE-HORIZONS
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`GENERATE PREDCTED GEOFENCE CROSSENGS
`1116
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`GEOFFNCE CROSSING
`YES
`SEND SIGNAL TO ALERT PROCESS
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`1 18
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`FIG. 11
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`Textron Specialized Vehicles Inc., Exh. 1007, p. 10
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`U.S. Patent
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`Sep. 10, 2013
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`Sheet 10 of 10
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`US 8,531,293 B2
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`Textron Specialized Vehicles Inc., Exh. 1007, p. 11
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`

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`1.
`PREDICTIVE GEOFENCE CROSSING
`
`2
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`US 8,531,293 B2
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`INCORPORATION BY REFERENCE
`
`This application claims the benefit of U.S. Provisional
`Application No. 61/282,150, “Predictive Geofence Crossing
`Alerts' filed on Dec. 23, 2009, including all cited references
`which are incorporated herein by reference in their entirety.
`
`BACKGROUND
`
`Using modern geographical information systems, a party
`may be alerted when a conveyance enters an area that should
`be avoided due to various reasons such as preventing hazard
`ous material from entering a high density population area.
`These alerts may be used to help prevent undesirable circum
`stances, for example.
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`SUMMARY
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`40
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`A predictive geofence system is disclosed that predicts a
`geofence crossing for a specified distance-horizon or a speci
`fied time-horizon. A distance-horizon is a distance that an
`object is predicted to travel for a set time in the future. A
`25
`geofence crossing for the object is predicted if the distance
`horizon is less than a distance between the object and the
`geofence. A time-horizon is a time-to-crossing for a set dis
`tance. A time-horizon is the time-to-crossing of the geofence
`by the object.
`The predictive geofence system includes a predictive
`geofence platform that receives information relating to spatial
`characteristic for objects such as position, speed of travel,
`direction of travel, etc. The predictive geofence platform
`stores the information in a database and predicts future posi
`tions of the objects based on the stored information. The
`future positions may be determined based on a history of past
`positions and/or based on map data if available. The predic
`tive geofence platform generates an alert if the predicted
`future positions of the objects result in a geofence crossing, or
`if predicted time-to-crossings of a geofence are less than a set
`time.
`If a geofence is moving and changing its shape, the predic
`tive geofence platform determines a new perimeter for the
`45
`geofence based on the received information. Movements of
`the geofence may be characterized by generatingaposition of
`a centroid for each new perimeter, and tracking a history of
`movements of the generated centroids. A geofence crossing
`may be determined by a position of a point on the geofence
`nearest to an object. If geofence involve two geofences, then
`the predictive geofence platform may determine a geofence
`crossing based on points on the geofences nearest to each
`other. The predictive geofence platform may generate pre
`dicted positions of relevant portions of the perimeter based on
`the centroid movements and movements of the relevant por
`tions of the perimeter relative to the centroid.
`If a geofence crossing is predicted, the predictive geofence
`platform generates an alert to one or more parties designated
`by a user or client. The client may provide a list of parties that
`should be alerted and the communication method used Such
`as email, facsimile or alarm, for example. The client may also
`specify a more complex alert process such as a logical for
`mula, an inference engine, an artificial neural network, etc.
`This more complex process may address fast moving
`dynamic circumstances involving security matters, for
`example.
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`Various embodiments of this disclosure that are proposed
`as examples will be described in detail with reference to the
`following figures, wherein like numerals reference like ele
`ments, and wherein:
`FIG. 1 illustrates a predictive geofence system;
`FIG. 2 illustrates a first example of a predictive geofence
`system operation;
`FIG. 3 illustrates a second example of a predictive
`geofence system operation;
`FIG. 4 illustrates an example of a geofence with a centroid:
`FIG. 5; illustrates X-axis area moments of the geofence of
`FIG. 4;
`FIG. 6 illustrates Y-axis area moments of the geofence of
`FIG. 4;
`FIG. 7 illustrates an example of a moving geofence;
`FIG. 8 illustrates an example list of tasks processed by the
`predictive geofence system;
`FIG. 9 illustrates an example block diagram of a predictive
`geofence platform;
`FIG. 10 is an exemplary flowchart of a geofence crossing
`prediction process for a target and a stationary geofence;
`FIG. 11 is an exemplary flowchart of a geofence crossing
`prediction process for moving geo fences; and
`FIG. 12 is an exemplary flowchart of an alert process.
`
`DETAILED DESCRIPTION OF EMBODIMENTS
`
`FIG. 1 shows an exemplary diagram of a predictive
`geofence system 100 that includes a predictive geofence plat
`form 104, clients 106, alert monitors 108, mobile reporting
`units 110 and stationary reporting units 112. Clients 106, alert
`monitors 108, mobile reporting units 110 and stationary
`reporting units 112 may be singular or plural depending on
`particular circumstances. These components 104-112 are
`connected through a network 102 that enables the compo
`nents 104-112 to communicate with each other. Network 102
`may be any communication system such as wired, wireless,
`optical, etc. and may include the Internet, private networks,
`peer-to-peer networks, etc.
`Predictive geofence platform 104 receives information
`from Sources such as mobile and stationary reporting units
`110-112, clients 106, alert monitors 108 and/or other infor
`mation providers such as the government, for example. Based
`on the received information, predictive geofence platform
`104 establishes one or more perimeters called geofences, and
`generates an alert when one of mobile reporting units 110
`Such as a conveyance of interest is predicted to cross a
`geofence. Although a geofence is represented by an area
`perimeter in some of the examples discussed below, a
`geofence may be reduced to a single point representing a
`position of an object. Additionally, a geofence may be repre
`sented by 3 dimensional surfaces for air or under water situ
`ations.
`A conveyance may be a tractor trailer, a truck, a train, etc.
`for moving cargo on land; airplanes, balloons, air-ships, etc.
`are conveyances for air, ships or boats are conveyance for
`water Surfaces; and Submarines are for under water convey
`ances. In general, a conveyance is a shipping platform in any
`particular medium of travel including space travel.
`Clients 106 are parties that desire to know when an object
`Such as a conveyance is predicted to cross a geofence. For
`example, a government organization Such as the Department
`of Homeland Security (DHS) may be interested in protecting
`one or more sites from certain materials. A site may be a high
`population concentration area Such as a large city, and DHS
`
`Textron Specialized Vehicles Inc., Exh. 1007, p. 12
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`US 8,531,293 B2
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`desires to keep hazardous materials from coming within a
`certain distance such as a 100 miles of the site.
`A conveyance of these hazardous materials may have a
`General Packet Radio Service (GPRS)/Global Positioning
`System (GPS) tag. The GPRS/GPS tag may be configured to
`periodically transmit a message that contains position infor
`mation Such as latitude and longitude. Other information Such
`as speed, direction, acceleration, content identification, etc.
`may also be transmitted. In addition to the GPRS/GPS tag, the
`conveyance may include a device such as a transponder, for
`example, that relays similar information to stationary report
`ing units 112 that are placed along the road and/or at Strategic
`places such as weighing stations. The information may be
`generated as electronic data interchange (EDI) information,
`for example. The information relating to a conveyance may
`also be generated by a person who observes arrival and/
`departure times and/or locations, and reports this information
`to predictive geofence platform 104. Devices such as cell
`phones, satellite tags, truck in-cab computers, etc. may also
`be used to report this information.
`Predictive geofence platform 104 receives the information
`either directly or through other sources such as clients 106 or
`alert monitors 108, and predicts a distance-horizon for T time
`into the future specified by client 106, for example, to deter
`mine whether the conveyance will cross a geofence in T time.
`Predictive geofence platform 104 may also predict a time
`horizon for D distance to be traveled in the future. If D is the
`distance between the object and the geofence, then the time
`horizon is the time-to-crossing of the geofence by the object.
`A geofence crossing for an object is predicted if the distance
`horizon is greater than a distance between the object and the
`geofence. A geofence crossing is also predicted if the time
`horizon is less than a set time specified by client 106, for
`example.
`FIG.2 shows an example of a conveyance 202 of hazardous
`materials that is not desired to cross a geofence 204 of 60
`miles around Memphis, Tenn. Conveyance 202 is currently
`traveling East on Interstate-40 (I40) and is heading toward an
`intersection where I40 turns left toward Memphis and Inter
`state-30 (I30) starts and goes West toward Dallas.
`If client 106 is a shipping company that subscribes to
`services of predictive geofence platform 104 to track convey
`ance 202 as a target, predictive geofence platform 104 may
`send alerts to the shipping company and/or a designated alert
`monitor 108 if a predicted geofence crossing will occur. Pre
`dictive geofence platform 104 may receive, from the shipping
`company or other available sources, information relating to
`conveyance 202 Such as contents, expected route, shipping
`schedule, etc. All the information associated with conveyance
`202 may be store in a database. Predictive geofence platform
`104 may track conveyance 202 through periodic reports from
`a GPRS/GPS tag mounted on conveyance 202, through
`reports from stationary reporting units 206 disposed along
`I30 and I40 and/or through other techniques such as satellite
`imaging, airplane Surveillance, etc.
`Predictive geofence platform 104 determines a future posi
`tion of conveyance 202 based on current and historical infor
`mation. For example, assume that the last 4 hourly reports for
`conveyance 202 indicate an average traveling speed of about
`55 mile per hour (mph) along I40, and the current position
`60
`indicates that conveyance 202 has traveled about 220 miles. A
`predicted position of conveyance 202 for a distance-horizon
`for 1 hour in the future is about 55 miles by dead reckoning
`(i.e., 1 hr 55 mph=55 miles). If the distance between the
`current position of conveyance 202 and geofence 204 along
`the expected route on I40 is greater than 55 miles, then an alert
`will not be generated. However, if conveyance 202 is less than
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`55 miles from geofence 204, then predictive geofence plat
`form 104 will generate an alert and send the alert to client 106
`and/or to any designated party specified by, client 106. Alerts
`may be sent periodically until conveyance 202 is not pre
`dicted to cross geofence 204. Client 106 may require the alert
`to be sent to an alert monitor 108 such as the Highway Patrol
`and/or the operator of conveyance 202, for example.
`The dead reckoning discussed above utilizes map data to
`predict the distance that conveyance will travel along I40.
`However, if map data is not available, then a predicted dis
`tance along a line of sight in a direction of travel may be used.
`For example, the velocity of conveyance 202 may be repre
`sented by a vector having a magnitude equal to a speed of
`conveyance 202 and a direction determined by a position
`history.
`If the position history is set to be the last 2 reported posi
`tions, then conveyance 202 has a Velocity direction pointing
`to Memphis for positions 208 and 210. For positions 208 and
`210, predictive geofence platform 104 will predict a straight
`line distance that conveyance 202 will travel toward Mem
`phis. Thus, ifa distance from conveyance 202 along a straight
`line containing positions 208 and 210 that is 55 miles long
`crosses geofence 204, then an alert will be generated to pre
`dict a geofence crossing. However, if positions 212 and 214
`are the last 2 reported positions, then the velocity direction
`does not intersect geofence 204, and a geofence crossing will
`not be predicted even if a line connecting position 214 and
`Memphis is less than 55 miles.
`In general, if a distance between two consecutive reported
`positions is short, the Velocity direction may be very sensitive
`to Small bends in a road. Thus, predictive geofence platform
`104 may perform position history analysis to determine the
`appropriate processing of historical positions for generating a
`vector direction. For example, when a Velocity direction con
`tinues to change erratically for a period of time, predictive
`geofence platform 104 may filter historical velocity direc
`tions to remove high frequency components to determine a
`general movement direction of conveyance 202. A filter may
`simply be averaging the Velocity direction for a window of
`positions, where a number of positions in the window may be
`predetermined or adaptively adjusted based on a history of
`direction changes, geographical location, etc. For example,
`mountainous or metropolitan areas may have high frequency
`direction changes in short distances, but desert or less popu
`lated areas may have less direction changes.
`The accuracy of the alert may be enhanced by improving
`the accuracy of the predicted distance. For example, the
`weight of conveyance 202 and characteristics of the traveled
`medium such as the terrain of the relevantportions of I40 may
`be taken into account. If the terrain has many turns or moun
`tainous and/or the load carried by conveyance 202 is very
`heavy, then the traveling speed of conveyance 202 may be
`adjusted based on a table of coefficients obtained by prior
`experience, calculated based on weight, grade of the road, etc.
`For example, assume that the stretch of I40 between Okla
`homa City and Little Rock is mountainous while the stretch
`between Little Rock and Memphis is generally flat. If the
`coefficient for the stretch between Oklahoma City and Little
`Rock is 0.8 (80% speed compared to straight and flat road),
`then the speed of conveyance 202 is 0.8 multiplied by the
`speed of a Substantially straight and flat road. Since convey
`ance 202 was traveling at 55 mph between Oklahoma City
`and Little Rock, then the conveyance would travel at about
`55/0.8 or 68.75 mph between Little Rock and Memphis if the
`coefficient along this stretch is 1. However, assuming that the
`speed limit is 65 mph between Little Rock and Memphis, the
`speed of conveyance 202 would be predicted to be at 65 mph
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`5
`along this stretch. If the history of conveyance 202 is to
`disregard the speed limit, then 68.75 mph may be used until
`data is obtained to confirm actual speed. Other adjustments
`may also be included such as weather conditions, traffic, and
`road construction, for example.
`In the above discussion, the target is conveyance 202. How
`ever, the target may be geofence 204, client 106 may be DHS,
`and the designated party for receiving alerts may be the FBI as
`alert monitor 108, for example. In this case, predictive
`geofence platform 104 may receive information regarding all 10
`carriers for states Surrounding Tennessee and then track only
`those carriers within a larger area encompassing geofence
`204. For example, an area within a radius of 250 miles around
`Memphis could be used. Predictive geofence platform 104
`may receive carrier information from an external Source Such 15
`as DHS, for example. Conveyances may include carriers on
`land, in the air and/or on the waterways, as may be appropri
`ate for a target location. Predictive geofence platform 104
`may filter the information for those identified conveyances
`that are carrying hazardous materials, for example.
`Predictive geofence platform 104 tracks each identified
`conveyance within the larger area. When an identified con
`Veyance is predicted to cross geofence 204 within a specified
`distance-horizon or have a time-horizonless than the set time,
`then the FBI is alerted so that possible preventive action may 25
`be taken. The alert may also be sent to the operator of the
`identified conveyance and or other alert monitors 108 such as
`the Highway Patrol, for example.
`FIG.3 shows an operation of predictive geofence platform
`104, where geofences 302 and 304 encompass two groups of 30
`people moving along respective planned routes in Washing
`ton D.C. For example, geofence 302 encompasses a group of
`anti-war activist moving along Pennsylvania Ave NW South
`East toward the White House. Geofence 304 encompasses a
`patriotic parade marching West on Constitution Ave NW
`35
`toward the Lincoln Memorial. The Capital Police wants to
`make Sure that the two potentially conflicting groups do not
`come within 2 blocks of each other to prevent any violent
`interactions.
`The Capital Police has assigned personnel that move along
`perimeters of each group. Capital Police officers may carry a
`position reporting device such as a GPS enabled cell phone,
`for example, that periodically reports its position to predictive
`geofence platform 104 through network 102. Based on the
`periodic reports, predictive geofence platform 104 generates
`geofences 302 and 304, which are contours of outer perim
`eters of each of the crowds of people. Based on a history of
`geofences 302 and 304, predictive geofence platform 104
`may predict distance- and/or time-horizons of geofences 302
`and 304.
`Unlike geofence 204 that is fixed around Memphis,
`geofences 302 and 304 are dynamic because they move and
`their shapes change. One way of characterizing the move
`ments of geofences 302 and 304 may be in terms of the
`movements of their respective centroids.
`Centroids of 2 dimensional geofences may be generated
`based on area moments. FIG. 4 shows an example geofence
`400 having a centroid 402. Coordinates of centroid 402X,Y,
`may be determined by using area moments M, and M. X.
`(1/A)XM, for all x, and Y, (1/A)XM, for ally, where A is the
`area of geofence 400, a is an area of a vertical slice of the
`geofence at X, and a, is an area of a horizontal slice of
`geofence 400 aty.
`FIGS. 5 and 6 show geofence 400 sliced up vertically and
`horizontally, respectively. In FIG. 5, vertically sliced
`geofence 500 is divided into rectangles Ay wide. The length
`of each rectangle is determined by a perimeter of geofence
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`400 for a particular X coordinate. For X, the length of the
`corresponding rectangle is y-y. Thus, the area of the slice
`corresponding to X is Ay(y-y), and the area moment Mat
`X is X*Ay*(y,y). Following the same procedure, Matys
`is y Ax*(x-x). If all M, are summed and the sum divided
`by A, the area of geofence 400, the result is X, the X coordi
`nate of centroid 402. Similarly, if all M, are summed and the
`sum divided by A, the result is Y, they coordinate of centroid
`402.
`FIG. 7 shows an example of a geofence 700 that has a
`centroid 702 and a geofence 704 morphing into geofences
`712 and 720 moving toward geofence 700. Geofences 704,
`712 and 720 may represent people traveling on foot, for
`example. Arrows 728 and 730 between successive centroids
`706, 714 and 722 may characterize the movements of the
`sequence of geofences 704, 712 and 720. Thus, a movement
`speed and direction of successive geofences 704,712 and 720
`may be generated based on centroid movements. For
`example, if arrow 728 has a length of 1 mile and the time
`elapsed between geofences 704 and 712 is 10 minutes, then
`geofence 704 moved to geofence 712 at a speed of (1 mile/12
`minutes)*60 minutes per hour-5 mph.
`If geofences 704, 712 and 720 are progressing along a path
`Such as a roadway, then predictive geofence platform 104
`may predicta crossing for a time or distance horizon based on
`the path. For example, based on the speed and distance cor
`responding to arrow 728, predictive geofence platform 104
`may predict the location of centroid 714 by dead reckoning.
`As discussed earlier in connection with conveyance 202, the
`prediction may incorporate conditions of the traveled
`medium Such as terrain, resistance (e.g., density of other
`people not part of the geofence that are also on the path), etc.
`If no recognizable path is present, then a line of sight may be
`used to calculate distance as modified by medium character
`istics Such as rocky areas, water, etc. that may be accounted
`for in a predicted travel path.
`Predictive geofence platform 104 may use points of
`geofences nearest to each other to determine a geofence
`crossing. In FIG.7, points 708, 716 and 724 of geofences 704,
`712 and 720, respectively, are nearest to geofence 700 at
`points 728, 732 and 730, respectively. To determine a
`geofence crossing between geofences 700 and 712, the dis
`tance between point 716 of geofence 712 and point 732 of
`geofence 700 may be used as a remaining distance R of
`separation. If geofences 704 and 712 are progressing down a
`road, prediction of point 716 for a distance-horizon D may be
`obtained by dead reckoning using the speed of centroid 706
`multiplied by T time in the future to obtained a distance D that
`point 716 will progress down the road. If D is greater than R.
`then a geofence crossing is predicted to occur and an alert is
`generated.
`Instead of using the speed of the centroid, the speed calcu
`lated by dividing the distance between nearest points 708 and
`716 by an elapsed time for geofence 704 to morph into
`geofence 712 may be used. Other methods may also be used
`based on measured accuracy for specific circumstances. For
`example, possible estimated movement speed may be:
`1. the average movement of 10% of an area of geofence 712
`closest to geofence 700;
`2. the speed of centroid 714 increased by a speed that point
`716 is moving away from centroid 714. This may be
`calculated by subtracting the distance between point 708
`and centroid 706 from the distance between point 716
`and centroid 714 and dividing the result by the elapsed
`time; and/or
`
`Textron Specialized Vehicles Inc., Exh. 1007, p. 14
`
`

`

`US 8,531,293 B2
`
`7
`3. the speed of centroid 714 increased by an average expan
`sion rate calculated based on changes between
`geofences 704 and 712 and their respective centroids.
`Geofence 700 may also be dynamic and morph. In this
`case, predicting a geofence crossing also requires determin
`ing a movement and change of shape of geofence 700 similar
`to the discussion above in connection to Successive geofences
`704, 712 and 720. Ageo fence crossing may then be predicted
`using the methods discussed above based on the nearest
`points between the geofences 700 and 704, 712 or 720.
`FIG. 8 shows an example of contents of a database 800 that
`stores information used by predictive geofence platform 104.
`For example Oracle(R) Spatial (Oracle) may be such a data
`base that is Suited to store spatial information Such as posi
`tion, terrain characteristics, etc. Additionally, Oracle per
`forms many functions relating to perimeters such as a
`geofence. For example, Oracle may be commanded to per
`form changes in position or shape which may be used for
`geofence updates. Further, Oracle may determine closest
`points of two perimeters, distances between two perimeters,
`perimeter crossings, etc. These functions may be used effec
`tively by predictive geofence platform 104 to predict geo
`fence crossings.
`The first column identifies a target such as conveyance 202
`in the first row, for example. The second column identifies
`contents of interest of the target. As noted earlier, conveyance
`content may be obtained from the shipping company, etc. For
`conveyance 202, its cargo contains hazardous materials
`(HAZMAT). For parade 5 in the third row, there is no carrier
`and the content is the activists who are part of parade 5.
`The third column indicates what predictive geofence plat
`form 104 is tasked to do in connection with the target. For
`conveyance 202, predictive geofence platform 104 is tasked
`to generate an alert for potential relevant geofence crossing of
`conveyance 202. In this case, the geofences of interest are
`normally spatially fixed such as cities and residential neigh
`borhoods, etc. However, for Hijack FT 325 in row 2, the task
`is National Security 1 that may require fast changes resulting
`in more dynamic variations depending on development of a
`crisis situation. Thus, the task assigned to predictive geofence
`platform 104 may change based on prior alerts, and database
`contents may be updated on a frequent basis.
`The fourth column stores spatial information associated
`with the target. The spatial information may include latitude
`and longitude that identify the position of a target Such as
`conveyance 202. For other targets such as parade 5 in row 3.
`the spatial information is geofence 1 that is constantly
`updated as parade 5 proceeds. The last column indicates the
`parties to be alerted when a predicted geofence crossing
`occurs. Some alerts may be simply sending an alert message
`to a single party such as the police in row 4 in connection with
`demonstrations 2, 3 and 4. Here, the police department may
`wish to keep demonstrators from interacting with each other.
`Other columns may be added such as task termination time,
`for example, or deleted as appropriate.
`Alerts may be more complex and may involve logical
`processes depending on specific circumstances. For example,
`for row 7, the target is Memphis, a current position of con
`veyance 202 is about 90 miles before reaching Little Rock,
`and the distance between Little Rock and geofence 204 is
`about 66 miles. Thus, conveyance 202 is predicted to be about
`3 hours away from crossing geofence 204 assuming a speed
`of about 55 mph. Conveyance 202 turns left toward Memphis
`at Little Rock and increases its speed to much higher than the
`speed limit. In this case, alert 20 may include logic that
`identifies this potentially dangerous situation and alerts the
`FBI, DHS, Memphis security and emergency Hazmat teams
`
`40
`
`45
`
`8
`in the Memphis area. If, on the other hand, conveyance 202
`turns toward Memphis, but slows down or comes to a stand
`still, then alert 20 may only direct an alert to the Highway
`Patrol for visual contact, for example. Perhaps conveyance
`202 simply made a wrong turn and is confused regarding the
`planned route that avoids Memphis.
`In rows 5 and 6, the targets are tracked for entirely different
`purposes from security concerns discussed above. Here, con
`veyance576 and conveyance 267 are delivering toys and lawn
`tractors for a retail outlet. The receiving department is pro
`vided alerts for arrival of shipped items for scheduling work
`crews at receiving and/or for providing merchandize avail
`ability to customers. The geofence is the location of the
`receiving dock, and the set time is 8 hours that accounts for
`scheduled down times when conveyance operators (e.g.,
`truck drivers) take breaks, for example. Thus, predictive
`geofence platform 104 will send alert emails to the retail
`outlet that includes time-to-crossings (here it is the same as
`time-of-arrivals) for conveyance 576 and conveyance 267
`when these times are less than the set time of 8 hours. Each
`day, based on received alert emails, the retail store can plan
`receiving activities for the next day, and customers may be
`contacted for the arrival of their ordered items.
`Row N has Air Force 1 as a target and the President is the
`content. Geofence 0 may be a sphere of 60 miles and a
`distance-horizon for 1 hour in a 30 degree cone in the direc
`tion of flight, 15 minutes in a 30 degree cone in the opposite
`direction, and 30 minutes in all other directions. Predictive
`geofence platform 104 may be tasked with generating alerts
`for any unauthorized objects that is within the specified