Patent Publication Number: US-2023132810-A1

Title: Systems and methods for using augmented reality to locate objects, identify persons, and interact with inanimate objects

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. Non-Provisional patent application Ser. No. 17/582,284 filed Jan. 24, 2022, now U.S. Pat. No. 11,538,242, which is a continuation of U.S. Non-Provisional patent application Ser. No. 17/234,587 filed on Apr. 19, 2021, now U.S. Pat. No. 11,232,307, which is a continuation-in-part of U.S. Non-Provisional patent application Ser. No. 16/941,149 filed on Jul. 28, 2020, now U.S. Pat. No. 10,984,243, which is a continuation of U.S. Non-provisional application Ser. No. 16/825,733 filed on Mar. 20, 2020, now U.S. Pat. No. 10,726,267, which is a continuation-in-part of U.S. Non-Provisional patent application Ser. No. 16/514,048 filed on Jul. 17, 2019, now U.S. Pat. No. 10,598,507, which claimed the benefit of U.S. Provisional Application Ser. No. 62/772,205, filed on Nov. 28, 2018, all of which are incorporated herein by reference. 
    
    
     TECHNICAL FIELD 
     The field of the invention broadly relates to augmented reality. More specifically, the field of the invention relates to systems, methods, and processes, which authenticate ownership through the use of visual identification, and which further allow for interaction with otherwise inanimate objects via the use of a code or marker thereon. 
     BACKGROUND 
     In many situations, tracking of physical objects and positive identification of an owner are useful. For example, in the context of air travel, luggage is many times separated from its owner intentionally or unintentionally creating the need to locate it. Locating lost luggage is hampered by the differing and labyrinthine systems used by airports generally to transport luggage and the now standard size and shape of luggage required by major air carriers. Once located, identifying lost luggage among a myriad of “look-a-like” bags can also create the problem of misidentification, even if the general location of luggage has been identified. 
     In the context of a warehouse, similar problems arise. For example, internet commerce has provided fulfillment companies that are tasked with the responsibility of moving countless shipping packages in standardized shipping boxes through complex routing systems to arrive at local carriers for delivery. Despite barcoding, many packages are misrouted and require physical tracking to be located which creates system inefficiencies, increased shipping costs and shipping delays. 
     There is also a need to positively identify physical objects in a variety of physical locations. For example, in an airport, there are many barriers to the use of known tracking devices. In general, GPS tracking of physical objects is difficult to accomplish inside concrete and steel buildings, thereby rendering it mostly ineffective in an airport terminal. In much the same way, large scale use of RFID tracking alone is ineffective because of radio interference of steel structures, such as baggage claim carousels and steel security barriers. Further, blueprinting an entire building may impede large scale RFID tracking because of its expense and the time required. 
     In much the same way, GPS tracking and RFID tracking systems are rendered ineffective in a warehouse due to steel racks, conveyor tracks and moving robotic forklift systems. 
     There is a need to positively associate the owner and message of physical objects once they have been located to prevent mistaken identification and to verify the ownership claims made. The prior art has failed to provide a system whereby the ownership of baggage is certified beyond a physical paper tag with a number and bar code. Further, paper tags are often lost or disfigured, rendering them useless. Further, paper identification tags do little to thwart theft and cannot provide a positive identification of luggage if the matching identification cards are lost. 
     In the same way, in a warehouse, positive identification of shipping packages cannot be made in the prior art without the use of paper labels and bar codes. Even so, the paper labels require identification by a scanner and are subject to being damaged or disfigured rendering them useless. 
     Therefore, a need exists to overcome the limitations of prior art systems to locate physical objects inside concrete and steel buildings with large numbers of steel barriers. 
     A need also exists for a system that can reliably locate physical items and positively associate them with their owners without the use of fragile and ineffective paper tags or other known methods. 
     In the prior art, many modern systems exist for tracking objects by use of radio frequency identifier (RFID) tags and global positioning systems. However, none of them satisfactorily address the needs in the industry. 
     For example, U.S. Pat. No. 9,664,510 to Nathan, et al. discloses a system and method of tracking objects by combining data obtained from multiple sensor types. However, Nathan does not employ a combination of tagging systems with image recognition, augmented reality, or with verified visual authentication of ownership. 
     U.S. Pat. No. 6,489,244 to August, et al. discloses tracking baggage using radio frequency (RF) tags. However, a combination of global positioning, RFID or beacon signals with image recognition, and augmented reality mapping is not disclosed. 
     U.S. Pat. No. 9,305,283 to Lauka, et al. discloses associating RF identifier (RFID) tags with barcodes using images. However, Lauka does not disclose a combination of global positioning data, beacon signals and/or RFID tags with image recognition and a display of user information associated with a tagged object. 
     U.S. Publication No. 2006/0256959 to Hymes discloses spatial addressing to identify the location of objects in a display. However, a combination of beacon signals with image recognition and global positioning is not disclosed. [00.16] U.S. Pat. No. 8,237,564 to Chang discloses visualizing locations of RFID tagged items. However, Chang does not disclose a combination of global positioning and beacon signals with image recognition nor does it disclose augmented reality in combination with user identification. 
     SUMMARY OF EXAMPLE EMBODIMENTS 
     In a preferred embodiment, a beacon tag provides a radio signal that is received by a first user device. The first user device sends location information to a server that identifies the beacon tag and the location of the first user device. The server then stores the location information and, when a second user device requests the location of the object, the server sends the location information from the first user device to the second user device. When the object is located, the second user device displays either a picture of the owner, and/or a picture of the object of value including showing relevant descriptive details of the object and/or instructions, so that ownership verification can be made. 
     In another preferred embodiment, a beacon tag broadcasts multiple radio signals that are in range of and received by a user device. After receiving the signals, the user device determines the location of the tag with respect to the location of the user device. The user device then calculates a direction vector and displays it on any augmented reality display to direct the user to the object. 
     In another preferred embodiment, a video of an object is created that includes several thousand images from different perspectives. The video is uploaded to the server. The server then generates an object recognition file using the video. The object recognition file is downloaded to the user device. An image recognition program compares the object recognition file to a live video feed from the camera of the user device. When the object is located, an arrow or other graphic is then displayed (e.g., on a screen or augmented reality device) that indicates the location of the object. 
     In another preferred embodiment, the system provides a plurality of user devices, a plurality of tags, and printed media attached to objects. Each of the user devices is in communication with each of the tags. However, each of the user devices is paired with one unique tag. In this embodiment, each of the user devices reports the location of the tag to which it is the nearest to a server. The server then tabulates the locations of all the user devices and all the tags. The server then correlates the locations of the tags to the identities of the user devices to which they are paired and reports the location of each tag to its paired user device using the location of the closest user device as an estimate of the location of the paired tags. 
     In another preferred embodiment, the system provides for identification of the objects by recognition of the printed media attached to the exterior of the objects, and then displays a notification to a user via augmented reality (e.g., screen overlay on camera display of smartphone). 
     In another preferred embodiment, the system provides a plurality of modules including an RFID antenna, a receiver and a processor. The modules scan for RFID tags and when one is identified, the modules communicate their GPS location to the server. The proximity of the tag and the GPS location of the module is then communicated to the associated user device. In this embodiment, the RFID system is deployed in physical locations where it is advantageous as a supplemental location mechanism. 
     In another preferred embodiment, the system provides a plurality of user devices which each individually comprise a processor, a network adaptor and a GPS transponder. Each processor is programmed to periodically report its GPS location through the network adapter to the system server, which then, in turn, communicates the information to the user devices. 
     In another embodiment, a hybrid tag is provided which incorporates a beacon tag, an RFID tag and a GPS tag so that each of the systems may be used in combination. 
     In another embodiment a system is provided which utilizes beacon tags, RFID tags, and GPS tags in a hybrid system that receives location information from all the location tags to inform users of the locations of objects. 
     In another embodiment, the system provides immediate user feedback via augmented reality in association with the printed media, beacons, RFID tags, GPS tags, or other related actionary devices to visually display real-time location and tracking services with the visual display on the user&#39;s device with, or without, proof of ownership information. 
     In one embodiment, an augmented reality system comprises a user device with augmented reality software and an augmented reality fingerprint marker positioned on an object, such as a credit card, debit card, check, or other financial item, etc. As used herein, an “augmented reality fingerprint marker” means a unique code, symbol, or other identifier that is scannable by a user device to activate an augmented reality, which may also include image recognition of the object itself. The user device may be a smartphone, computer, tablet, glasses, wearable, or any device that is capable of performing augmented reality. The user device and the augmented reality software maps the environment and reads the augmented reality fingerprint marker, which superimposes digital information received from the augmented reality fingerprint marker over the real-world objects displayed on the user&#39;s device. For example, a user, such as a store clerk, could take a customer&#39;s credit card during the check-out process and scan the credit card with the user device, which could then superimpose digital information about the customer on the user device (i.e., augment reality), such as photo identification of the owner of the card or other relevant information to better secure the transaction. 
     In one embodiment, the object may be a pharmaceutical vial. The user device and the augmented reality software maps the environment and reads the augmented reality fingerprint marker on the pharmaceutical vial, which superimposes digital information received from the augmented reality fingerprint marker over the pharmaceutical vial displayed on the user&#39;s device in real-time, and is capable of receiving real-time updates (such as from an internet-connected server). This information may be patient verification information, such as a photo of the patient with name and birthdate, medication, dosage, doctor, or other information. In a further embodiment, a patient may use a user device (e.g., smartphone, tablet, wearable, etc.) to scan the augmented reality fingerprint marker and perform certain actions in the augmented reality, such as request a refill, call the pharmacy, call the prescribing physician, or other beneficial tasks. While a pharmaceutical vial is used as an example, it will be appreciated that other containers may also be used, which may include uses in other than medicine. 
     In one embodiment, the augmented reality fingerprint marker could be placed on a person&#39;s clothing or other belonging, on their personal file information (e.g., hospital file), or in any other location. This allows a third party to verify ownership of an item, or that the correct person is present. For example, if the marker is on clothing, the marker may be scanned, which would then identify the owner by name and photo (and other information, as determined by a user, such as phone number, contact info of guardian, caretaker, physician assistant, doctor, pharmacist, etc.). In a hospital setting, a nurse may scan a patient&#39;s pharmaceutical prescription before dosing to ensure the medicine is being administered to the correct patient. Additionally, a nurse, or other hospital worker, may perform certain actions in the augmented reality, such as add annotations to the client file, request prescriptions, or other actions. 
     In one embodiment, the object may be a vehicle license plate. For example, the license plate may have an augmented reality fingerprint marker embedded therein, which, when scanned, displays information relating to the vehicle and driver. This information may include, but is not limited to, driver&#39;s license information, Department of Transportation licensing or information, professional licensing, etc. 
     In one embodiment, the object may be a pet. The augmented reality fingerprint marker may be placed on a pet&#39;s collar so that the pet may be identified through the user device. For example, a user may scan the augmented reality fingerprint marker on a pet, such as a dog, with the user device. The displayed information may include, but is not limited to, medications, allergies, and food type and brand, among others. 
     In one embodiment, an object may be a military ID or file. When military personnel must enter a secured area, a user can obtain their identification and scan the augmented reality fingerprint marker located thereon, allowing the user to see information displayed about the military personnel on the user device. In one embodiment, beacons and/or RFID tags may also be used to obtain and display information. 
     In one embodiment, the object may include, but is not limited to, print media or digital media. For example, printed ads, such as newspapers, may include augmented reality markers, which, when scanned, superimpose media as selected by the advertiser. Further, digital ads, such as digital graphics or video ads, may also include augmented reality markers, allowing a user to scan and interact with the advertiser, as selected by the advertiser. Such interactions may include prices, reviews, location, or additional information about the product, service, or business. 
     In one embodiment, the object may include, but is not limited to, headstones, in-wall internments, urns, etc. For example, a headstone may include an augmented reality marker, which, when scanned, can superimpose information about the deceased on a user device. Some of the information displayed on a user device may include a photo, biography, inspirational information, etc. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The disclosed embodiments will be described with reference to the accompanying drawings. 
         FIG.  1 A  is a system architecture diagram of a preferred embodiment of a system for tracking objects. 
         FIG.  1 B  is a system architecture diagram of a preferred embodiment of a supplemental system for tracking objects associated with an RFID tag. 
         FIG.  1 C  is a system architecture diagram of a preferred embodiment of a supplemental system for tracking objects associated with a GPS tag. 
         FIG.  2    is a component architecture diagram of a server for tracking and locating objects. 
         FIG.  3    is a component architecture diagram of a user device for tracking and locating objects. 
         FIG.  4 A  is a component architecture diagram of a beacon tag for tracking and locating objects. 
         FIG.  4 B  is a component architectural of an RFID tag for tracking and locating objects. 
         FIG.  4 C  is a component architectural tag of a GPS tag for tracking and locating objects. 
         FIG.  4 D  is a drawing of a preferred embodiment of baggage to be tracked with a location tag. 
         FIG.  4 E  is a drawing of a shipping package to be tracked with a location tag. 
         FIG.  5 A  is a sequence diagram of a routine to initialize a preferred embodiment of the system. 
         FIG.  5 B  is a sequence diagram of a preferred method in which a first user device identifies and reports the long-range location of a beacon tag that is associated with a second user device. 
         FIG.  5 C  is a sequence diagram of a preferred embodiment which reports the location of an object fitted with an RFID tag. 
         FIG.  5 D  is a sequence diagram of a preferred embodiment which reports the location of an object fitted with a GPS tag. 
         FIG.  6 A  is a flowchart of a preferred method for tracking a beacon tag, an RFID tag or a GPS tag in long-range mode, short-range mode and ultra-short-range mode. 
         FIG.  6 B  is a flowchart of a method for calculating and displaying a directional element. 
         FIG.  6 C  is a diagram showing a preferred coordinate system for a user device. 
         FIG.  6 D  is a flowchart of a preferred method of determining the orientation of a display arrow. 
         FIG.  6 E  is a graphical example of a preferred method of determining the orientation of a display arrow. 
         FIG.  7 A  is a flowchart of a preferred embodiment of a method to determine a short-range beacon tag location and return a direction vector definition. 
         FIG.  7 B  is a graphical depiction of probability circles and centroids used in a preferred method to determine a beacon tag location. 
         FIG.  7 C  is a graphical depiction of a centroid of a planar body derived from probability circles. 
         FIG.  8    illustrates a sequence diagram of a method of identifying an object from a video image when the system is in ultra-short-range. 
         FIG.  9 A  is an illustration of a display screen of a user device in long-range mode. 
         FIG.  9 B  is an illustration of a display screen of a user device in short-range mode. 
         FIG.  9 C  is an illustration of a display screen of a user device in ultra-short-range mode. 
         FIG.  9 D  is an illustration of an alternate display screen of a user device in ultra-short-range mode. 
         FIG.  10    is an illustration of a financial transaction card augmented on a user device. 
         FIG.  11    is an illustration of a pharmaceutical vial augmented on a user device. 
         FIG.  12    is an illustration of a pet augmented on a user device. 
         FIG.  13    is an illustration of a headstone augmented on a user device. 
     
    
    
     DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS 
     Aspects of the present disclosure may be implemented entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or combining software and hardware implementation that may all generally be referred to herein as a “circuit,” “module,” “component,” or “system.” Further, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer readable media having computer readable program code. 
     Any combination of one or more computer readable media may be utilized. The computer readable media may be a computer readable signal medium or a computer readable storage medium. For example, a computer readable storage medium may be, but not limited to, an electronic, magnetic, optical, electromagnetic, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the computer readable storage medium would include, but are not limited to: a universal serial bus (USB) stick, a hard disk, a random access memory (“RAM”), a read-only memory (“ROM”), a flash memory, an appropriate optical fiber with a repeater, a portable compact disc read-only memory (“CD-ROM”), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. Thus, a computer readable storage medium may be any tangible medium that can contain or store a program for use by or in connection with an instruction, system, apparatus, or device. More specific examples of the computer readable storage medium include, but are not limited to, smart devices, phones, tablets, wearables, X-Code software platforms, or any suitable combination of the foregoing. 
     Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including, but not limited to, an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, Objective-C, C++, C#, VB.NET, Python or the like, conventional procedural programming languages, such as the “C” programming language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages such as Python, PHP, HTML, AJAX, Ruby and Groovy, or other programming languages such as X-Code. The program code may execute entirely or partially on one or more of the devices of the system. 
     Aspects of the present disclosure are described with reference to flowchart illustrations and/or block diagrams of methods, systems, and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable instruction execution apparatus, create a mechanism for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     These computer program instructions may also be stored in a computer readable medium that when executed can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions when stored in the computer readable medium produce an article of manufacture including instructions which when executed, cause a computer to implement the function/act specified in the flowchart and/or block diagram block or blocks. The computer program instructions may also be loaded onto a computer, or other devices to cause a series of operational steps to be performed or to produce a computer implemented process that implements the functions specified in the flowcharts. 
     Aspects of the present disclosure are described with reference to printed media. The term “printed media” means anything that can be printed including, but not limited to, photos, vector images, GIFs, JPEGS, PNGs, stickers, emojis, posters, pages, bar code, matrix bar code such as a quick response (QR) code, labels, and combinations thereof. Additionally, “printed media” also includes etching, laser engraving, or any process of adding a symbol, code, or other fingerprint marker to an object. 
     Referring to  FIG.  1 A , system  100  includes server  102 , which is connected to database  104 . Server  102  is connected to user devices  108 ,  110  and  112  through internet  106 . User devices  108 ,  110  and  112  are also connected through a wireless network to tags  118 ,  120 ,  122 ,  124 ,  126  and  128 . In a preferred embodiment, each tag is physically attached to one of objects  130 ,  132 ,  134 ,  136 ,  138  and  140 . In this preferred embodiment, at least one tag is associated with each user device. It should be understood that  FIG.  1 A  shows only examples and that the system includes a large number of user devices and a large number of tags.  FIG.  1 A  shows that each user device communicates with all the tags. However, in one embodiment, each user device is uniquely associated with only one tag. For example, user device  108  is uniquely associated with tag  118 , user device  110  is uniquely associated with tag  124 , and user device  112  is uniquely associated with tag  126 . In another preferred embodiment, each user device may be associated with more than one tag, or with more than one type of tag. In various preferred embodiments, the tags may be beacon tags, RFID tags, or GPS tags, and may incorporate printed media, as will be further described. In other embodiments, one or more of objects  130 - 140  includes identifying printed media  141 ,  142 ,  144 ,  146 ,  148 , or  149  located on an exterior portion of the respective one or more of objects  130 ,  132 ,  134 ,  136 ,  138  or  140 . 
     In a preferred embodiment, the connections between the tags and the user devices are direct wireless connections using the Bluetooth Low Energy standard and specification. In other preferred embodiments, these connections include repeaters, routers, switches, and access points that provide for extended range communication capability. 
     Internet  106  includes one or more land-based wire networks and all forms of wireless networks. The messages passed between server  102  and user devices  108  through  112  use one or more protocols including, but not limited to, transmission control protocol/internet protocol (TCP/IP), user datagram protocol (UDP), hypertext transfer protocol (HTTP), and HTTP secure (HTTPS). 
     In different embodiments, the objects may take the form of any physical item to be tracked including, but not limited to, shipping boxes, shipping pallets, shipping containers, trailers, vehicles, pieces of luggage, or any objects of value. The objects may have printed media attached, formed, stitched, or otherwise placed on the object exterior. 
     Referring to  FIG.  1 B , a preferred embodiment of a system incorporating RFID tags is shown. System  150  includes processor  151  operatively connected to reader  152 . Reader  152  is operatively connected to antenna  153 . Processor  151  is also operatively connected to Wi-Fi interface  154 . Wi-Fi interface  154  is wirelessly connected to internet  155 . System  150  includes processor  156  operatively connected to reader  159 . Reader  159  is operatively connected to antenna  158 . Processor  156  is also operatively connected to Wi-Fi interface  157 . Wi-Fi interface  157  is wirelessly connected to internet  155 . System  150  also includes processor  160  operatively connected to reader  178 . Reader  178  is operatively connected to antenna  162 . Processor  160  is also operatively connected to Wi-Fi interface  163 . Wi-Fi interface  163  is wirelessly connected to internet  155 . System  150  includes processor  177  operatively connected to reader  164 . Reader  164  is operatively connected to antenna  165 . Processor  177  is also operatively connected to Wi-Fi interface  166 . Wi-Fi interface  166  is wirelessly connected to internet  155 . 
     Internet  155  is connected to server  170 . Server  170  is, in turn, wirelessly connected to user devices  171 ,  172  and  173 . The system includes exemplary RFID tag  175  physically attached to object  176 . In this exemplary figure, RFID tag  175  is shown positioned next to and in communication with antenna  165 . However, in a preferred embodiment, the system includes a plurality of RFID tags which are mobile and so can be positioned in proximity to any one or more of antennas  153 ,  158 ,  162  and or  165 . 
     In a preferred embodiment, each processor, reader, Wi-Fi interface and antenna are contained in a single antenna base module. The system comprises a plurality of modules located at places where objects are likely to pass or be deposited such as luggage or shipping container transport conveyors, racks, turnstiles and storage bins. 
     In a preferred embodiment, each processor  151 ,  156 ,  160  and  177  includes a Raspberry Pi 3, Model B ARM Version 8, product number 3055 available from Adafruit. In a preferred embodiment, each reader is a 2.4 GHz active RFID reader product ID 800025 including data buffering available from GAO RFID, Inc. of Ontario, Canada. In a preferred embodiment, each reader includes a 2.45 GHz active personal RFID card tag, product ID 127002 which provides a range of 100 meters and is available from GAO RFID, Inc. of Ontario, Canada. In another embodiment, the reader includes, but is not limited to, a mobile device, a smart phone, a tablet, a wearable device, an X-Code software platform, or any suitable combination of the foregoing. 
     Referring to  FIG.  1 C , a preferred embodiment of a system incorporating location tags is shown. System  180  includes GPS tag  181  physically attached to object  182 . Likewise, the system includes GPS tag  183  physically connected to object  184 , GPS tag  185  physically connected to object  186 , and GPS tag  187  physically connect to object  188 . Another preferred embodiment, of course, there can be many GPS tags connected to different objects at many different locations. In each case, this disclosure envisions that the GPS tags and objects will be moveable and will be physically incorporated into objects such as luggage or shipping containers. 
     System  180  further includes network  189 . A preferred embodiment, network  189  is the internet. System  180  further comprises telephone networks  190  and  191  in operative communication with the internet. In a preferred embodiment, these telephone networks are cellular networks. Network  189  is connected to server  190  which is in turn wirelessly connected to user devices  192 ,  193 , and  194 . 
     Referring to  FIG.  2   , exemplary server  202  includes processor  204 , memory  206 , and network adapter  208 . Server  202  communicates with the user devices and the database through network adapter  208 . In a preferred embodiment, applications  210  and data  212  in memory  204 , include a web server that is accessed by the user devices. Server  202  operates with database  104  ( FIG.  1 A ) to store, generate, and process location and identification information received about the location tags from the user devices and from the location tags themselves. 
     Referring to  FIG.  3   , exemplary user device  308  includes processor  302  operatively connected to memory  304 , camera  310 , display  312 , global positioning system transceiver  314 , positioning sensors  315 , and network adapters  316  and  318 . Exemplary user device  308  communicates with the server utilizing network adapter  316  and receives the beacon signal broadcast messages from one or more tags with network adapter  318 . Memory  304  includes apps  320  and data  322 . In preferred embodiments, the exemplary user device  308  include, but are not limited to, smart phones, tablet computers, notebook computers, laptop computers, and desktop computers. 
     Exemplary user device  308  generates location information using global positioning system  314 . The location information includes longitude, latitude, and altitude information for the location of the user devices. Positioning sensors  315  include accelerometers, gyroscopes, and magnetometers in a nine-axis sensor (three axes for the accelerometers, three axes for the gyroscopes, and three axes for the magnetometers) that allows the device to register relative changes in position and orientation fairly accurately and report them to the processor. 
     Network adapter  316  is a medium or long-range wireless network adapter, such as a mobile network adapter used with cellular communications technology, without limitation. Network adapter  318  is a short-range wireless network adapter that uses protocols such as Wi-Fi and Bluetooth, without limitation. Network adapter  316  is used to request information from and provide information to the server. 
     Short-range network adapter  318  receives beacon signal broadcasts from one or more beacon tags. The broadcast signals are used by the user device to identify instructions stored in memory and to execute them when required. 
     Referring to  FIG.  4 A , a preferred embodiment of a location tag will be described. Beacon tag  420  includes processor  404 , memory  406 , and network adapter  408 . Memory  406  includes apps  410  and data  412 . In a preferred embodiment, beacon tag  420  includes, but is not limited to, a Blue Giga BLE112 Bluetooth low energy single mode module, available from Digi-Key (www.digikey.com/product-detail/en/BLE112-A-V1/1446-1017-1-ND). Beacon tag  420  includes short-range wireless transceiver  414 , that is used by the user devices to locate beacon tags. The transceiver transmits a beacon signal using a short-range wireless protocol and standard, examples of which include, but are not limited to, the Bluetooth Low Energy (BLE) beacon standard, Apple iBeacon, Google Eddystone, and AltBeacon. Each of the beacon tags is capable of transmitting a beacon signal periodically. In a preferred embodiment, the time period between signals can range from about 20 milliseconds to about 10 seconds, and in a preferred embodiment is about 200 milliseconds. The beacon signal includes a numeric code that uniquely identifies each individual beacon tag. 
     Referring then to  FIG.  4 B , an alternate embodiment of a location tag will be described. RFID tag  440  includes RFID antenna  444  and memory  446 . In a preferred embodiment a serial number of RFID tag  440  is included in memory  446  and is returned when an activation signal is received from RFID antenna  444 . In a preferred embodiment, the location tag includes a 2.45 GHz active personal RFID card tag, product ID 127002 which provides a range of 100 meters and is available from GAO RFID, Inc. of Ontario, Canada. 
     Referring then to  FIG.  4 C , an alternate preferred embodiment of a location tag will be described. GPS tag  460  includes processor  464  operatively connected to memory  466 . Memory  466  includes program code  470  and data  472  which are used to boot up the processor and implement the functions of the device. Processor  464  is also operatively connected to cellular adaptor  468 . Cellular adaptor  468  is used to communicate information to and from the processor in operation. The processor, memory and cellular adaptor are each powered by battery  474  which is subject to power use restriction from program code  470 , during operation. In a preferred embodiment, processor  464  includes, but is not limited to, a Raspberry Pi 3, Model B, ARM Version 8, product number 3055 available from Adafruit. Memory  466 , in a preferred embodiment, is a one gigabit RAM located on the Raspberry Pi 3 board. In a preferred embodiment, cellular adapter  468  is a particle electron cellular IOT adapter product number 3234 available from Adafruit. The cellular adapter is capable of 3G cellular connection with web access. 
     Each of the beacon tag, the RFID tag and/or the GPS tag, or any of them alone or together, can be combined in a single location tag, as will be further described. 
       FIG.  4 D  shows a preferred embodiment of a location tag  403  and an object to be tracked  401 . In this embodiment the object to be tracked is luggage, such as a backpack. Location tag  403  is operatively disposed within pocket  405  so that it may be removed for charging or maintenance. Location tag  403  can be a beacon tag, an RFID tag or a GPS tag in different embodiments. 
       FIG.  4 E  shows a preferred embodiment of a location tag  480  and an object to be tracked  482 . In this embodiment, the object to be tracked is a shipping package. Location tag  480  is operatively disposed within the package so that it is concealed from outside view and yet still free to operate through radio communications. 
       FIG.  5 A  shows method  500 , which initializes various files and subsystems to enable a preferred embodiment of the system. At step  521 , a user device is used to input personal identification information such as a user name, address, fingerprint, picture, and trip identifier. An example of a “trip identifier” can include a flight number, a flight time, a departure location and a destination location. This information is stored in memory. Optionally, at step  522  a location tag type is chosen, including a beacon type, an RFID type and/or a GPS type. 
     Optionally, at step  523 , the camera of the user device is directed toward the object with which the tag is associated and initiates recording of an image recognition training video. The image recognition training video is a series of video frames used to train or teach image recognition software to identify the object. Each frame of the video includes an image of the object. In a preferred embodiment, the camera provides images of the object from different angles. In a preferred embodiment, the image recognition training video provides images at 30 frames per second for about 30 seconds, which provides about 900 separate images of the object. In other embodiments, the image recognition training video provides images at any video frame rate useful for image recognition. In a preferred embodiment, the image recognition training video is generated only when the system is first initialized. 
     Optionally, at step  524 , if the location tag type is either a beacon tag or a GPS tag, then the tag is powered up. Optional step  524  may include booting up a beacon tag or a GPS tag. At step  526 , the tag enters a wait state. 
     At step  527 , user device  108  sends a “system initialize message,” to server  102 . The message includes the personal identification information, the tag type, the image recognition training video, a user device identifier, or serial number. 
     At step  528 , the personal identification information, the tag type, the image recognition training video, and the user device identifier are stored in memory. 
     At step  529 , the server associates or “pairs” user device  108  with tag  128  and registers the association in memory. The association is used by the system to notify the user device when the tag is located. In a preferred embodiment, the memory is organized into a database format capable of storing and accessing thousands of sets of user information (or more) and associated location tags. 
     At step  530 , server  102  generates an object token. The object token includes a tag identifier. In one preferred embodiment, the tag identifier is a unique serial number that is stored in 4 bytes. In another preferred embodiment, the object token is formed by hashing the tag identifier and a random number. The random number is associated with the tag identifier and is stored in the database for later use. 
     Optionally, at step  531 , server  102  generates an object recognition file. The object recognition file identifies the configuration, topology, and weights used by an image recognition algorithm to identify the object, as will be further described. 
     At step  532 , server  102  sends the object recognition file to user device  108 . User device  108 , in this example, is associated (or paired) with tag  128 . The object recognition file allows user device  108  to recognize and identify the object when it appears in an image captured by the camera of user device  108 , as will be further described. 
     At step  533 , server sends the object token and the random number to user device  112 . User device  112 , in this example, is not associated (or paired) with tag  128 . 
     At step  534 , server  102  sends the object token and the random number to user device  108 . 
     At step  535 , user device  108  is associated with the tag identifier, so that the user device will recognize the tag identifier as the object associated with user device  108 . 
     Optionally, if the tag is GPS type or beacon type, then at step  536 , the object token and the random number are sent by user device  108  to tag  128 . 
     Optionally, if the tag is GPS type or beacon type, then at step  537 , the object token is authenticated by tag  128 . Tag  128  authenticates the object token by decrypting it, using the random number to access the tag identifier. The tag identifier is compared with the tag identifier stored in the tag memory. If the tag identifiers match then the tag activates itself. If the tag identifiers do not match then the tag shuts down. 
     Optionally, if the tag is GPS type or beacon type, then at step  538 , the tag identifier is stored in memory by tag  128 . 
     Optionally, if the tag is a GPS type or beacon type then, at step  539 , the tag sends an acknowledgment signal to user device  108 . At step  540 , user device  108  initializes the system. At step  541 , user device  108  reports system initialization to the server. 
       FIG.  5 B  shows method  501 , which describes the system in use where a first user device identifies and reports the long-range location of a beacon tag that is associated with a second user device. In this example, user device  108  is paired with beacon tag  502 . It is assumed that beacon tag  502  and user device  112  are both at a great distance from user device  108 . It is assumed that beacon tag  502  and user device  108  are not in close proximity to each other. It is also assumed that user device  112  is at a short distance from beacon tag  502 . 
     At step  542  the beacon tag  502  begins transmitting a beacon signal and its serial number or token. In a preferred embodiment, the beacon tag  502  is pre-set to send a signal once about every 200 milliseconds at a power level of about 50 mW. At step  543 , user device  112  polls its onboard GPS transceiver to determine its GPS coordinates. In a preferred embodiment, the GPS coordinates are updated about once every minute. 
     At step  544 , beacon tag  502  sends the beacon signal to user device  112 . At step  546 , user device  112  records a time stamp and then processes the beacon signal to decode the object token to determine the tag identifier. 
     At step  547 , user device  112  measures the strength of the beacon signal and consults a predetermined calibration table to translate the strength into a range of distances that approximates the distance from the tag to user device  112 . 
     In a preferred embodiment the following table is used: 
     
       
         
           
               
               
               
             
               
                   
                 TABLE 1 
               
               
                   
                   
               
               
                   
                 Signal Strength 
                 Estimated Tag Distance 
               
               
                   
                   
               
             
            
               
                   
                 0.98-0.85 mW 
                 25-30 ft 
               
               
                   
                 1.13-0.98 mW 
                 20-25 ft 
               
               
                   
                 1.30-1.13 mW 
                 15-20 ft 
               
               
                   
                 1.50-1.30 mW 
                 10-15 ft 
               
               
                   
                 1.73-1.50 mW 
                  5-10 ft 
               
               
                   
                 1.94-1.73 mW 
                  1-5 ft 
               
               
                   
                   &gt;1.94 mW 
                   &lt;1 ft 
               
               
                   
                   
               
            
           
         
       
     
     At step  548 , user device  112  generates a “tag location message” that includes its user device identifier, the tag identifier, the range of distances, the GPS coordinates of user device  112  and the time stamp showing when the beacon signal was received. It should be understood that in a preferred embodiment, many tag location messages will commonly be generated by a plurality of user devices, such as user device  112 , each being reported back to the server. 
     At step  550 , user device  112  sends the tag location message to the server. 
     At step  551 , the server decrypts the tag location message (if encrypted) using the random number associated with the tag to identify the tag identifier. At step  552 , the tag identifier, the GPS coordinates of user device  112 , the time stamp, and the random number associated with the tag identifier are then stored in the database. 
     At step  553 , user device  108  detects and stores its GPS coordinates. At step  554 , an object location request message is sent from user device  108  to server  102 . The object location request includes the device identifier for user device  108  and the GPS coordinates of user device  108 . 
     At step  555 , the server decrypts the object location message using the random number or serial number associated with the user device (if encrypted). At step  556 , the information is stored in the database. At step  557 , the server retrieves all tag location messages from the database and then compares them to the tag identifier to locate those messages which match the tag identifier for beacon tag  502 . These are “matched tag identifiers.” At step  558 , the server sorts the matched tag identifiers to determine the GPS coordinates of the user device that is closest to the beacon tag. 
     At step  559 , an “object location alert” is generated by server  102 . The object location alert includes the GPS coordinates of user device  112  (or the closest set of GPS coordinates reported) and the associated time stamp. 
     At step  560 , the object location alert is transmitted from server  102  to user device  108 . 
     At step  561 , user device  108  decodes the object location alert. At step  562 , the GPS coordinates of user device  112  (or the closest set of coordinates) located in the object location alert are stored in memory. 
     At step  563 , a direction vector is generated by user device  108 . In this embodiment, the direction vector is taken as positive from the location of user device  108  to the location of user device  112 . The angle of the direction vector is taken as positive clockwise from true north as 0°. The magnitude of the direction vector is taken in feet positive from the location of user device  108  to the location of user device  112 . At step  564 , the direction vector is returned for further processing. 
     Referring to  FIG.  5 C , a method  570  of determining an RFID tag location will be described. 
     At step  571 , user device  594  generates an RFID tag location request. The RFID tag location request incudes the serial number of the user device. At step  573 , the RFID tag location request is sent to server  591 . At step  574 , the server logs the request location and the serial number of the user device. At step  575 , the server consults a lookup table which includes a list of all user devices and associated RFID tag serial numbers. The RFID tag serial number associated with the user device serial number is identified. At step  576 , the server sends a scan request to all antenna base modules in the system, including antenna base module  593 , which includes the RFID tag serial number. 
     At step  578 , antenna base module  593  stores its fixed GPS location. At step  578  the antenna based module begins a scanning loop in which the antenna is repeatedly polled for the presence of an RFID tag signal. At step  579 , antenna base module  593  receives an RFID signal. At step  580 , the antenna base module decodes the serial number from the RFID signal. At step  581 , the antenna base module records a date and time stamp at which the RFID signal was received. At step  582 , the serial number and date/time stamp are stored in a table in onboard memory. At step  583 , the antenna base processor utilizes an onboard wifi network adaptor to report the serial number, date/time stamp and GPS location to server  591 . 
     At step  584 , server  591  stores the serial number date/stamp and GPS location of the antenna base module. At optional step  585 , server  591  consults a look up table for the client device or fixed coordinates that are associated with the serial number. At step  586 , server  591  sends a request for GPS coordinates to user device  594 . At step  587 , user device  594  derives its GPS coordinates from the onboard GPS transceiver. At step  588 , user device  594  sends the derived GPS coordinates to server  591 . At step  530 , server  589  calculates a direction vector. In this embodiment, the direction vector is directed from the GPS location of the user device  594  to the GPS location of the antenna base module  593 . In this embodiment, the direction of the direction vector is taken as the number of degrees from true north. The magnitude is taken as positive from the location of the user device to the location of the antenna base module. The magnitude of the vector is reported in feet. At step  590 , server  591  reports the direction vector to user device  594 . At step  592 , the user device returns the direction vector and the process concludes. 
     Referring then to  FIG.  5 D , a preferred method  502  of reporting GPS tag location will be further described. At step  503 , user device  504  generates a GPS tag location request. In a preferred embodiment, the request includes the GPS coordinates of the user device, a 4-byte request code and the serial number of the user device. At step  507 , user device  504  sends the location request to server  507 . At step  508 , server  505  decodes the location request and logs the user device serial number and its GPS coordinates. At step  509 , server  505  consults a lookup table to determine the GPS tag serial number associated with the user device serial number. At step  510 , server  505  sends a request to the associated GPS tag processor  506  for GPS tag location. At step  511 , GPS tag processor  506  resolves its GPS location from the onboard GPS transceiver. At step  512 , GPS tag processor  506  stores a date and time stamp associated with the GPS location and the location request. At step  513 , GPS processor  506  returns the GPS location and the date and time stamp to server  505 . At step  514 , server  505  stores the GPS location and the date and time stamp. 
     At step  515 , server  505  calculates a direction vector. In this embodiment the direction vector is the vector from the GPS location of the user device  504  to the GPS location of the GPS tag processor  506 . The direction of the direction vector is taken as the number of degrees from true north. The magnitude is taken as positive from the location of the user device  504  to the location of the GPS tag processor  506 . The magnitude of the vector is reported in feet. At step  516 , server  505  reports the magnitude and direction of the direction vector to user device  504 . At step  517 , user device  504  returns the direction vector and the method concludes. 
     Referring to  FIG.  6 A , a tag range determination tracking routine  600  operates on user device  108  to locate, identify, and display the location of an object which is physically attached to a beacon tag, and RFID tag and/or a GPS tag. The location tag will be responsive to the various systems described based on which of the functionalities, namely, beacon tags, RFID tags, GPS tags and/or printed media are included. 
     At step  602 , the method starts. 
     At step  603 , a request for tag location information is sent to server  102 . 
     At step  604 , a decision is made as to whether or not tag location information has been received. If so, the method proceeds to step  605 . If not, the method returns to step  603 . In one preferred embodiment, the tag location information is a direction vector. In another embodiment the tag location information is a beacon signal. 
     At step  605 , the user device decodes and stores the tag location information. At step  606 , a decision is made. If the tag information is a beacon signal from a beacon tag paired with a user device, then the method moves directly to short-range mode at step  629 . If not, then the method continues to step  607 . At step  607 , a user interface is enabled, which allows a user to choose between “long-range mode” and “short-range mode.” In long-range mode, the user device is presumed to be a relatively long distance from the tag. In short-range mode, the user device is presumed to be a relatively short distance from the tag. At step  610 , the user device receives a selection of long-range mode or short-range mode or no decision. If the short-range mode is chosen, the method proceeds to step  629 . If long-range mode is chosen, then the method proceeds to step  612 . If no decision is received, then the method moves to step  611 . At step  611 , the magnitude of the direction vector is compared to a predetermined distance “x”. In a preferred embodiment, x is between about 50 feet and 150 feet, but other distances can be chosen. In other embodiments, “long-range” can be up to hundreds of miles. If the magnitude of the direction vector is greater than x, then the method proceeds to step  612 . If not, then the method proceeds to step  629 . 
     At step  612 , the user device enters long-range mode. In long-range mode, the direction vector may be generated by the long-range beacon tag system, the RFID tag system, the GPS tag system, or a combination of the three. 
     At step  614 , the user device generates and displays a tag identifier, a trip identifier, a name and picture of the owner of the object, and an image of object  140 . 
     At step  616 , the user device determines its GPS location. 
     At step  620 , the user device retrieves the direction vector from memory. 
     At step  621 , the user device generates and displays a map section. In a preferred embodiment, the map section is downloaded from a third-party provider such as Google maps. The coordinates for the perimeter of the map section displayed are, in a preferred embodiment, scaled to approximately four times the length of the direction vector. 
     At step  622 , the location of the user device is centered in the map section and displayed. In one preferred embodiment, the location of the user device is taken as the beginning point of the direction vector. In another preferred embodiment, the location of the user device is taken from the on-board GPS transceiver. In a preferred embodiment, the user device location is rendered using a specific recognizable icon. 
     At step  624 , the tag location is rendered on the map. The location of the tag is taken as the end point of the direction vector. In a preferred embodiment, the tag location is represented as a different icon including, but not limited to, a diamond, arrow, emoji, text, or other geometric shape. 
     At step  625 , the direction vector is displayed on the map. 
     Since it is assumed that the user device will be moving toward the location tag, and that the tag itself may be moving, it is necessary to frequently update the map and determine relative range. At step  626 , the user device determines if it is in short-range. To do this, it compares the GPS coordinates of the user device to the GPS coordinates of the tag in the direction vector to arrive at a difference. The difference is then compared to a predetermined distance, such as about 100 feet. Other distances can suffice depending on the accuracy of the tag location desired. If the distance is smaller than the predetermined distance, then the method moves to step  629 . If not, the method moves to step  627 . 
     At step  627 , the user device queries the user as to whether or not the process should terminate. If not, the method returns to step  614 . If so, the method moves to step  628  and terminates. 
     Moving then to step  629 , the user device enters “short-range mode.” In a preferred embodiment, “short-range” is less than about 50 feet to about 150 feet, but other distances can be chosen so long as they are less than “long-range” mode. In short-range mode, the direction vector may be generated by the short-range beacon tag system, the RFID tag system, the object recognition system, or a combination of the three. 
     At step  630 , a video stream from the camera of user device  108  is generated and displayed. A video stream is a sequence of static images generated by the camera of the user device. 
     At step  631 , a tag identifier, a trip identifier, a name of the user of the user device, an image of the owner of the object and an image of the object are retrieved from memory and displayed. 
     At step  632 , the process determines and displays the orientation of a directional element and updates the display, as will be further described. In a preferred embodiment, the directional element is displayed as either a “left direction arrow”, a “right direction arrow”, or a “bullseye”. At step  633 , the directional element is overlaid on top of the video stream and displayed. In a preferred embodiment, this step is repeated as long as the user device is moving. 
     At step  634 , a determination of whether or not the tag is in “ultra-short” range. To do this the magnitude of the direction vectors are compared to a predetermined distance “y”. In a preferred embodiment, y is between about 5 feet and 10 feet, but other distances may be chosen, so long as they are less than “short-range” mode. If the magnitude of the direction vector is less than y, then the method proceeds to step  635 . If not, the method proceeds to step  637 . 
     At step  635 , the method calls an image recognition routine, to be further described. 
     At step  636 , the method displays an identification frame, as will be further described. The method then proceeds to step  638  and terminates. 
     At step  637 , the user is queried as to whether or not the process should terminate. If so, the process stops at step  638 . In not, then the process returns to step  630 . 
     Turning to  FIG.  6 B , a preferred embodiment of a method  645  of determining and displaying a direction element will be described. At step  639 , the position and orientation of the user device is determined. In a preferred embodiment, the user device polls its onboard position sensors to determine roll, pitch and yaw. 
     At step  640 , the orientation of user device is checked to see if it is “correct.” In this step, the current position of the user device is compared to an ideal position to determine a difference. If the user device orientation is “correct,” then the method moves to step  642 . If not, the method moves to step  641  and displays instructions to the user as to the correct orientation of the user device. The method then returns to step  639 . 
     At step  642 , the direction vector is retrieved from memory. 
     At step  643 , the orientation of the display element is determined, as will be further described. 
     At step  644 , the method generates and displays a directional element that directs the user to the tag location. This directional element may be displayed as superimposed on an augmented reality display (e.g., smart device). 
     Referring to  FIG.  6 C , a “correct” orientation of user device  232  will be described using a preferred coordinate system  650 . Axis  652  is defined as the “x” axis or “yaw”. Axis  654  is defined as the “y” axis or “pitch”. Axis  656  is the “z” or “roll”. User device  232  is shown in an orientation where the onboard camera is hidden. The camera faces in the direction “−z” along axis  656 . In a preferred embodiment, the user device is in “correct” orientation for use in short-range mode when axis  656  is directed toward the object in the “−z” direction. Axis  652  is held perpendicular to the horizon. Axis  654  is held parallel with the horizon. As a result, axis “y” is exactly horizontal and axis “x” is exactly vertical. Axis  656  is directed to the horizon and is presumed to be facing directly away from the user in the −z direction. Hence, in a preferred embodiment, the pitch angle should be 0°, the roll angle should be 0°, and the yaw angle should be 0°. The position and orientation are updated every time user device  108  is moved. Relative positions of the user device are determined by comparing the position sensor readings in short succession and then subtracting the later set of position readings from the earlier set of position readings to determine a delta. A delta in any position reading is considered a change in position. 
     Referring to  FIG.  6 D , a method of displaying a directional element on the user device will be described. At step  665 , a relative direction of the z-axis for the user device is determined from the position sensors and stored in memory. In a preferred embodiment, the relative direction is obtained by mapping a first GPS position of the user device to the first relative position reported by the position sensors and then mapping a second GPS position of the user device to the second relative position reported by the position sensors. The mapping process in one embodiment neglects changes in roll and yaw. As the user device moves, the most recent GPS position of the user device is taken as the second relative position and the next most recent GPS position is taken as the first relative position. The angle of the relative direction is taken clockwise from true north. The magnitude of the relative direction is taken as the distance between the first position and the second position. At step  666 , the direction vector is normalized to the relative direction by aligning the first set of GPS coordinates of the direction vector with the first set of GPS coordinates of the relative direction. In one embodiment, an alignment is achieved by changing the first set of GPS coordinates of the direction vector to match the first set of coordinates of the relative direction. 
     At step  667  a comparison is made between the angle of the relative direction and the angle of direction vector to arrive at a difference angle “alpha.” The comparison is made in a clockwise fashion from the relative direction to the direction vector. 
     At step  668 , a decision is made as to whether or not the angle of direction vector is greater than the angle of the relative direction. If so, then the method proceeds to step  669 . If not, the method proceeds to step  670 . At step  669 , 360° is added to alpha and the method moves to step  670 . 
     At step  670 , if the angle alpha is between 2° and 179° then the process moves to step  671  where an “arrow right” is reported. The process then moves to  676  and concludes. If not, the process moves to step  672 . At step  672 , if the angle alpha is between 180° and 358° then an “arrow left” is reported at step  673  and the method concludes at step  676 . If not, then a “bullseye” is reported at step  674 , and the process moves to step  675 . At step  675 , the ultra-short-range image recognition routine is triggered as will be further described. 
     Referring to  FIG.  6 E , a graphic example of the calculation of a “right” arrow decision is described. In this example, user device  232  is located at point  680  and relative direction  677  is shown at 90° from true north (0°). Direction vector  678  is shown at 180°. The offset angle “alpha” is calculated in a clockwise manner from the relative direction to the direction vector. In this example, a is reported to be 90° (180°-90°), which is between 20° and 179°, so an “arrow right” will be reported. 
     Referring to  FIG.  7 A , a preferred embodiment of a method  700  for locating a beacon tag in short-range mode will be described. 
     At step  750 , the method starts. At step  751 , the user device consults the onboard position sensors to locate its initial position coordinates. At step  752 , a beacon signal is received by the user device. At step  753 , the position coordinates are stored in memory along with a time stamp of when they were received. At step  754 , the beacon signal is analyzed for intensity. At step  755 , the beacon intensity is stored in memory. At step  756 , an estimated distance table is consulted to determine a maximum and a minimum estimated distance. In this way, the signal strength of the beacon signal is converted into a range of possible distances. The weaker the signal, the greater the distance between the user device and the tag. The stronger the signal, the lesser the distance between the user device and the tag. For any given signal strength, a maximum and a minimum distance are provided in the table. 
     At step  757 , a “probability circle” is constructed and mapped to the initial position of the user device as of the time of the time stamp, as will be further described. 
     Each probability circle is determined by drawing two concentric circles centered at the location of the user device. The larger of the two circles has a radius of the maximum distance from the estimated distance table. The smaller of the two circles has a radius of the minimum distance from the estimated distance table. The construct of the probability circle comprises the locus of points between the first circle and the second circle. 
     At step  758 , the locus of points comprising the probability circle and a timestamp of when it was recorded are stored in memory. 
     At step  759 , the position sensors are again polled to determine if the user device has been moved. This is done by comparing the present position to the initial position. If so, the method moves to step  760 . If not, the method returns to step  753 . At step  760 , a determination is made as to whether or not sufficient data exists to plot three (3) relative positions of the user device based on position sensor data and an overlap between all three probability circles. If not, the process returns to step  752 . If so, the process moves to step  761 . 
     At step  761 , the dimensions and relative positions of the last three probability circles are retrieved from memory. At step  762 , three (3) sets of overlaps are calculated, a first overlap set between the first and second probability circles, a second overlap set between the second and third probability circles, and a third overlap set, between the first, second, and third probability circles. Each set of overlaps forms a plane figure which consists of the locus of points which are common to each of the circles. A set can consist of one or more plane figures. At step  763 , a centroid is calculated for the third overlap and its GPS position determined, as will be further described. 
     At step  764 , the GPS coordinates of the most recent position of the user device are retrieved and stored. 
     At step  765 , a direction vector is calculated between the most recent GPS position of the user device and that of the centroid. The angle of the direction vector is positive from 0° due north from the user device to the centroid. The direction vector proceeds from the GPS coordinates of the user device to the centroid. The magnitude of the direction vector is the distance in feet, from the most recent position of the user device to the centroid. At step  766 , the direction vector, is returned. 
     Referring to  FIG.  7 B , diagram  700  is a graphical depiction of an example of the determination of three (3) probability circles and a centroid. For a first beacon signal, the user device is located at Position 1,  702  at time 1. For a second beacon signal, the user device is located at Position 2,  704  at time 2. For a third beacon signal, the user device is located at Position 3,  706  at time 3. 
     Probability circle  708  identifies a locus of points where the beacon tag may be when the user device is in Position 1 based only on beacon signal strength. Likewise, probability circle  710  identifies a locus of points where the beacon tag may be when the user device is in Position 2. Likewise, probability circle  712  identifies a locus of points where the beacon tag may be when the user device is in Position 3. 
     In this example, at Position 1 for a signal strength of 0-2-milliWatts (mW), a radius of 25 ft is shown at  720  and a radius of 30 ft is shown at  718 . The difference,  726 , is 5 feet. Probability circle  724  is plotted around Position 1 having inside radius  720 , outside radius  714 , and a width  726 . This probability circle represents the possible locations of the tag when the user device is in Position 1. 
     Likewise, when the user device is moved to Position 2, a radius of 15 ft is shown at  730  and radius of 20 ft is shown at  731 . This represents a signal strength of between 40-60 mw. The difference between  730  and  731  is 5 feet. A circle is drawn around Position 2 having an inside radius at  730 , an outside radius at  731 , and having a width  732  of 5 feet. This probability circle represents the possible locations of the tag when the user device is in Position 2. 
     Likewise, the user device is moved to Position 3, radius of 1 foot is shown at  733  and radius of 5 ft. is shown at  734 . This represents a signal strength of between 100-120 mw. The difference  735  between  733  and  734  is 4 ft. The circle is drawn around Position 3 having an inside radius at  733 , an outside radius at  734 , and having a width of 4 ft. This probability circle represents the possible locations of the tag when the user device is in Position 3. 
     Since all three probability circles are stored in memory and are associated with relative positions of the user device at different points in time, the overlaps between them can be used to calculate the location of the beacon tag when the user device is at Position 3. The overlap between probability circle one and probability circle two is shown at  736  and  737 . The overlap between probability circle two and probability circle three is shown at  738  and  739 . The overlap between probability circle one, probability circle two and probability circle three is shown at  740 . 
     The estimated location of beacon tag  128  is calculated as the centroid of area  740 . Direction vector  745  is then calculated having a start point  742  at the GPS coordinates associated with Position 3 and an end point  770  at the centroid of area  740 . 
     Referring to  FIG.  7 C , the centroid of area  740  is further described. For a plane figure, such as the third overlap  740 , the centroid, or barycenter is calculated as: 
     
       
         
           
             
               
                 
                   
                     C 
                     x 
                   
                   = 
                   
                     
                       ∫ 
                       
                         x 
                         ⁢ 
                            
                         
                           
                             S 
                             y 
                           
                           ( 
                           x 
                           ) 
                         
                         ⁢ 
                         dx 
                       
                     
                     A 
                   
                 
               
               
                 
                   Eq 
                   . 
                       
                   1 
                 
               
             
           
         
       
       
         
           
             
               
                 
                   
                     C 
                     y 
                   
                   = 
                   
                     
                       ∫ 
                       
                         y 
                         ⁢ 
                            
                         
                           
                             S 
                             x 
                           
                           ( 
                           y 
                           ) 
                         
                         ⁢ 
                         dx 
                       
                     
                     A 
                   
                 
               
               
                 
                   Eq 
                   . 
                       
                   2 
                 
               
             
           
         
       
     
     where:
 
A is the area of the area  740 ;
 
S y (x) is the length line  768 ; and,
 
S x (y) is the length line  767 .
 
     Turning to  FIG.  8   , sequence  800  shows a method of identifying an object using ultra-short-range with image recognition. Server  802  provides image recognition services. In a preferred embodiment, the image recognition services include, but are not limited to, Google Cloud Platform Cloud Vision API, Microsoft Azure Computer Vision API, 5G or other cellular service and Amazon Web Services Amazon Recognition. 
     At step  821 , the image recognition service is trained to recognize the object with the training video taken during system initialization. 
     At step  822 , user device  808  generates a real time video display. In a preferred embodiment, the video display is generated by the camera onboard user device  808 . 
     At step  824 , a fixed image is selected from the video display. In a preferred embodiment, the fixed images are taken from the video at 400 milliseconds intervals. In a preferred embodiment, the fixed image is captured when the ultra-short-range routine is triggered. 
     At step  826 , user device  808  generates an image recognition request that includes a selected fixed image and an object recognition model. The object recognition model is defined by the object recognition file that was generated by the system during system initialization and the required model parameters. 
     Alternatively, at step  826 , the image recognition request may not be sent because the user device  808  may recognize printed media on the object. For example, the camera on user device  808  may include QR reader software, or a processor with requisite corrective processing code (e.g., Reed-Solomon error correction) such that one or more images taken at step  822  may be used by user device  808  to recognize identifying printed media. 
     Alternatively, at step  826 , the image recognition request may include a printed media recognition model. 
     At optional step  827 , user device  808  generates a printed media recognition message. The printed media recognition message may allow for object identification by recognizing the identifying printed media as an alternative to requesting object identification from server  802 . Some embodiments use both object identification and printed media recognition. 
     At step  828 , the image recognition request is sent from user device  808  and is received by server  802 . Step  828  may include sending to server  802  the printed media recognition message, together with, or as an alternative to, the image recognition request. 
     At step  830 , server  802  analyzes the selected fixed image based on the object recognition model. In a preferred embodiment, the object recognition model describes weights, layers, and structure relevant to an artificial intelligence image recognition algorithm. 
     At step  832 , probabilities, labels and image location coordinates are generated by server  802 . In preferred embodiment the image location coordinates are defined by an upper left corner definition and a lower right corner definition of a rectangle within the selected fixed image where an image of object  830  should be present. The probabilities represent the confidence interval that the artificial intelligence image recognition algorithm has correctly identified the object. 
     At step  834 , server  802  generates an object recognition message that includes the probabilities, labels, and image location coordinates. 
     At step  836 , the object recognition message is sent from server  802  to user device  808 . 
     At step  838 , user device  808  generates a display. The display includes the probabilities, labels, and an image location rectangle generated from the upper left and lower right corner coordinates, overlaid onto the selected fixed image. The display also includes an image of the object and an image of the owner. In this way, at ultra-short-range, a visible rectangle is drawn around the object so that the user can easily locate it. The display may also include multiple arrows or other moving or flashing graphics, such as arrows to indicate the absolute location of the object. Alternatively, the multiple arrows or other moving or flashing graphics may indicate the absolute location of recognized printed media specific to the object, such as a QR code. 
     Referring to  FIG.  9 A , “long-range” mode display  900  is shown on user device  908 . Long-range mode display  900  includes map  902  and information box  910 . 
     Map  902  displays the current location of the user device as icon  904 . Map  902  also displays the location of the tag as icon  906 . The path between user device  908  is shown as arrow  909 . Arrow  909  indicates the direction of travel in order to bring user device  908  closer to the location tag with which it is paired. 
     Information box  910  shows image  915  of the object paired with the tag, image of the owner  916 , tag identifier  917 , flight identifier  919 , a name of the user  921 , and range information  923 . In this example, the range information indicates that the tag is greater than 100 meters away from the location of the user device. In this way, the information box displays both a picture of the object and a picture of the user, thereby permitting instant authentication of ownership of the object by the user. 
     Referring to  FIG.  9 B , a display in “short-range” mode is shown. Crosshairs  913  are shown in a fixed position in the display. Camera video image  914  displays a live video feed from the user device camera. Either “right” arrow  911  or “left” arrow  912  is displayed. Each arrow when displayed indicates a direction which the user device must be turned to reach the location tag. “Bullseye”  925  is central in the video image and is highlighted when the location tag is centered in the display. 
     Referring to  FIG.  9 C , “ultra-short-range” mode display  930  is shown. Range information  923  indicates tag proximity. In this example, the tag is less than 10 feet away from the user device. User picture  916  and object picture  915  are also displayed. Rectangle  927  indicates the image as recognized. Confidence interval  928  indicates the likelihood that the image of the object is correctly identified. 
     Referring to  FIG.  9 D , an alternate “ultra-short-range” display is shown. Four arrows,  932 ,  934 ,  936 , and  938  are displayed centered on the object associated with the tag. Augmented reality superimposes digital content over live video feeds to make it seem that it is part of the world. This allows a user to enhance the world around them in many ways. There are many inanimate objects that users interact with every day, including, but not limited to, credit cards, checks, street signs, prescription vials, trophies, etc. Augmented reality can bring these inanimate objects to life to provide entertainment, security, and everyday information. To bring objects to life via video feed, marker-based scanning must be performed by a user&#39;s augmented reality device, such as a smartphone, wearable, or other smart device. The device&#39;s camera is able to search and find marked objects when using a marker-based system. Once the augmented reality device scans the augmented reality fingerprint marker, the marker-based system superimposes a digital image or information onto the augmented reality device display. Accordingly, there is a need for an augmented reality system that can be used for numerous objects, such as financial items, clothes, prescriptions, and many other items. 
     In one embodiment, as shown in  FIG.  10   , an augmented reality system  1000  comprises a user device  1002  having a camera and screen  1003  with augmented reality software and an augmented reality fingerprint marker  1004  positioned on an object  1006 , such as a financial transaction card  1008  (e.g., credit card or debit card), check, or other financial item (collectively referred to as a “financial object”). The user device  1002  may be a smartphone, computer, tablet, glasses, wearable, or any device that is capable of performing augmented reality. The user device  1002  and the augmented reality software maps the environment and reads the augmented reality fingerprint marker  1004 , which superimposes digital information  1010  received from the augmented reality fingerprint marker  1004  over the real-world objects  1006  displayed on the user&#39;s device  1002 . For example, a user, such as a store clerk, could take a customer&#39;s credit card  1008  during the check-out process and scan the credit card  1008  with the user device  1002  (which may be coupled to a cash register or may be a standalone device), which could then superimpose digital information  1010  about the customer on the user device  1002  (i.e., augment reality), including photo identification  1012  of the owner of the card, as illustrated in  FIG.  10   . 
     Credit card theft and fraud are ongoing problems. To combat these problems, credit card companies have begun using chips in their cards. While this may aid in preventing cards from being copied, it does not prevent a thief from using a stolen card. However, an augmented display of the card&#39;s owner, at time of use, could reduce theft and fraud significantly. Accordingly, there is a need for an augmented reality system that enables verification of ownership of a credit card, check, professional license, security clearance, or other object. It is important to note that the credit card comprises the augmented reality fingerprint marker, which contains information about the customer. The user device  1002 , in tandem with the augmented reality software, produces digital information  1010  that is read from the augmented reality fingerprint marker. The information that is superimposed over the credit card  1006  may be, but is not limited to, a name, address, photo, etc. It will be appreciated that the augmented reality system  1000  can assist financial institutions in detecting fraud, having increased security, and creating an accurate financial system. If, for example, a credit card is stolen, the retailer or other credit card processor may scan the credit card to analyze the photo and other information to determine that the card is being used by its rightful owner. 
     The augmented reality system described above may also be used with digital wallets and touchless transactions (e.g., near field communication (NFC), Bluetooth®, etc.) as well. For example, where a user pays using a digital wallet, an augmented reality fingerprint marker may be displayed by the credit card issuer on the screen of the user&#39;s device and/or the screen of the clerk, allowing the clerk to scan the augmented reality fingerprint marker and verify the identity of the individual paying before authorizing the transaction. 
     In one embodiment, as shown in  FIG.  11   , the object  1006  may be a pharmaceutical vial  2008 . It will be appreciated that other vials may be used, such as a supplement vial. The user device  1002  and the augmented reality software maps the environment and reads the augmented reality fingerprint marker  1004  on the pharmaceutical vial  2008  (or other pharmaceutical item), which superimposes digital information  1010  received from the augmented reality fingerprint marker  1004  over the pharmaceutical vial  2008  displayed on the user&#39;s device  1002 . This information may be patient verification information, such as a photo  1012  of the patient with name and birthdate, allergies, dosage, or other information. In some embodiments, the displayed information may be the number of pills left in the vial based upon its weight. Once the pills reach a certain number (i.e., weight), the augmented reality fingerprint marker  1004  may automatically send instructions to the smart device to reorder the prescription or supplements via, for example, a transceiver. Additionally, in one embodiment, the pharmaceutical vial  2008  may comprise smart sensor strips, with possible accelerometer devices that will record date and time of consumption. 
     Also, in an alternate embodiment, the pharmaceutical vial may comprise a strip or lid which will glow or change color. In other words, the change in color of the strip or lid could notify a user when a pill has been taken, such as green when taken, or red as not taken. The color of the lid or strip may also reset automatically when starting the next day&#39;s requirement of pre-prescribed intake. It will be appreciated that the lids and/or colored strips on the vial  2008  will be additional measures of verification of intake instructions, will add more stability and improve health care management, and enhance prescriber&#39;s adherence to proper medication intake. It will further be appreciated that the lids and/or colored strips may help to monitor and coordinate with professionals, family, or other caregivers for improved health care management. 
     This information may not only be helpful to a pharmacy or the individual taking the medication but may also be useful in preventing opioid abuse. Opioid abuse has become a national concern and the augmented reality system could assist in combating the abuse. Similar to the credit card scenario, authorities, such as the police, could scan the prescription vial to find information quickly to determine the proper owner of the medication. 
     In some embodiments, a user may interact with the superimposed digital image or information of the augmented reality on the pharmaceutical vial  2008 . In particular, the user may view the augmented reality device display  1002 , which displays the superimposed digital image. The user may then place a hand between the pharmaceutical vial  2008  and the display and interact with the superimposed image or information. For example, in some embodiments, a user may place a closed first into the space between the vial  2008  and display, which may then send information to the device  1002  (e.g., the augmented reality software, detecting the action/gesture of the hand, executes an action) to call a pharmacy so as to allow the user to ask questions or order a new prescription. Additionally, the augmented reality fingerprint marker  1004  may be programmed to superimpose digital images with command buttons on the pharmaceutical vial  2008 , thereby allowing a user to visualize their hand on the display, with their hand between the vial  2008  and the device  1002  and select the command, such as by flicking a finger. Some of these commands may include, but are not limited to, call the doctor (auto-dial), call the pharmacist, order a refill (re-order), and check medication instructions. In one embodiment, communication may occur in real-time, allowing a user, who has scanned an object, such as a pharmaceutical vial, to discuss the medication with a pharmacist or prescriber of the medication. This may be beneficial for a user who is unable to read the instructions (due to age, disability, etc.) or that needs immediate assistance with the medication. In one example, calling a pharmacy is as simple as taking a photo of the vial. In other words, a user opens the augmented reality software, which activates the camera (in on embodiment, the software is built into the native camera application on a smart device), and then simply aims the camera at the vial, which, upon detecting and reading the augmented reality fingerprint marker, may automatically dial the pharmacy (or other action, as programmed). While a pharmaceutical vial is discussed above, a user may interact with the augmented reality with any object. It will be appreciated that a user may interact with any of the objects described herein or other objects that may or may not comprise an augmented reality fingerprint marker. 
     In one embodiment, the reality fingerprint marker  1004  may be utilized in a hospital setting. For example, the augmented reality fingerprint marker  1004  could be placed on a patient&#39;s clothing or other belonging, on their personal file information that is handled by the nurse, or in any other location. In a manner similar to previous embodiments, a medical provider could scan the augmented reality fingerprint marker  1004  with the user device to receive information about the patient. For example, the augmented reality fingerprint marker  1004  could be placed on the patient so that a medical provider could scan the marker with the user device  1002 , which would overlay digital information  1010  on the user device screen. It will be appreciated that the digital information  1010  displayed could be information about the status of the patient, their health issues, when medication was last taken, who was the last medical provider to review the patient, when medication was last administered and needs to be administered, insurance, and any other personal information important during a hospital stay. It will further be appreciated that the augmented reality system used in a hospital setting may assist hospital staff in taking better care of a patient. For example, when there is a shift change between nurses, it will be easier for the new nurse to quickly assess the status of the patient so that the nurse may take proper care of the patient. Additionally, in one embodiment, a nurse or other hospital staff may interact with the digital information  1010  displayed, such as ordering medication, logging notes, setting reminders, calling a treating physician, and others. 
     In one embodiment, the object may be a license plate. For example, the license plate may have an augmented reality fingerprint marker  1004  embedded thereon, which, when scanned, displays information relating to the vehicle and driver. To appreciate the benefits of the embedded augmented reality fingerprint marker, law enforcement, or other individuals, could scan the license plate with their user device to retrieve important information. In use, police officers, after pulling over a vehicle, could scan the license plate without exiting their vehicles. This would provide safety for the officer and vital information before approaching the driver. The digital information superimposed on the vehicle could include personal information (name, address, photo), driver&#39;s license information, make and model of the vehicle, outstanding warrants or crimes associated with the vehicle and its driver, and any other valuable information. 
     In one embodiment, a user may prove ownership of a vehicle or other object by scanning the augmented reality fingerprint marker, which superimposes ownership information on the object. Such information may be valuable, particularly when an ownership dispute has arisen. Some objects, such as bicycles, shoes, watches, and other items, lack ownership identifying information, such as title or tags, making them susceptible to theft. In an effort to reduce theft, an augmented reality fingerprint marker may be used in connection with the object, allowing a user to quickly and instantly prove ownership of an object. The augmented reality fingerprint marker may be a printed tag, sticker, symbol or code etched/lasered into the object, or, as described elsewhere herein, may be the unique characteristics/features of the object itself. In this way, a user may simply scan the augmented reality fingerprint marker to verify ownership of the object. In some instances, a history of ownership of the object may be desired, similar to the title of real property. In other words, a user purchasing a rare object may desire to not only have proof of ownership, but be able to readily illustrate the chain of title to the object. For example, a user, having acquired a pair of worn sneakers from an NBA® player such as Lebron James, may desire to show title to the sneakers, proving they were legitimately owned at one point by Lebron. In this way, any item of value may be safeguarded and properly valued by a user/purchaser/seller. This also aids to prevent knockoffs and theft. A purchaser may easily scan the augmented reality fingerprint marker to verify the seller&#39;s statements as to the authenticity of the goods. In one embodiment, Blockchain may be used to verify the history, transfers, transactions, or any other historical information about the object. While used in connection with this example, it will be readily apparent that Blockchain technology would be beneficially implemented into any of the embodiments disclosed herein. 
     In one embodiment, a user may interact with the augmented reality environment. In other words, a user may insert their hand between the object and the camera so as to place their hand in the augmented environment. With their hand in the augmented reality, certain motions of the hand or fingers may display different information or take certain actions. For example, a user may have the option of viewing current ownership, viewing past ownership, or taking certain actions, depending upon the object (e.g., ordering a refill of a prescription). In one example, a user may close their hand into a first to demonstrate list current ownership (although other actions may be used and is not limited to a fist). Flicking the index finger may bring up a list of previous owners, with the ability to click on any given owner by flicking or “air tapping” their name so as to view certain information, such as dates of ownership, etc. In one embodiment, an owner can determine how much information is provided to future owners beyond their name and photo, for example. 
     In addition to proving ownership of the goods, and as described elsewhere herein, a user may likewise find lost or stolen objects using augmented reality, such as the arrows on the screen described herein. 
     In one embodiment, an augmented reality system comprises a user device with augmented reality software and an augmented reality fingerprint marker for use on clothing, such as shirts, coats, pants, shoes, etc. For example, the augmented reality fingerprint marker may be placed on a child&#39;s coat. If a child were to be kidnapped, the augmented reality fingerprint marker could assist authorities to find the child. Law enforcement officers could scan children with a user device. When the user device locates the augmented reality fingerprint marker, information can be displayed about the child, such as name, address, phone number, etc. 
     Additionally, during a murder or kidnapping investigation, clothing may be found that can assist law enforcement. If humans remains are found with the clothing, the clothing may be scanned to immediately return an identity of the remains. The augmented reality system may also assist law enforcement, or other people, to locate and identify living individuals from their clothing. Further, it could also be envisioned that an augmented reality fingerprint marker could be placed on the clothing of an undercover law enforcement officer. For example, an undercover law enforcement officer could have an augmented reality fingerprint marker attached somewhere on his clothing. This would allow other law enforcement officers to scan a group of individuals to know whether there are other law enforcement officers so as to not interrupt an operation and protect their fellow officers. In yet another embodiment, an augmented reality fingerprint marker may be placed on a driver&#39;s license, cell phone case, or other object typically carried by an individual so that emergency responders may scan the augmented reality fingerprint marker to obtain important information, such as current medications, allergens, diagnosis, next of kin, etc. 
     Referring to  FIG.  12   , in one embodiment, an augmented reality system  1000  comprises a user device  1002  with augmented reality software and an augmented reality fingerprint marker  1004  for use on a pet  3008  (which, as defined herein, is still an “object”  1006 ). The augmented reality fingerprint  1004  marker may be placed on a pet&#39;s clothes or on the pet&#39;s collar so that the pet  3008  may be identified through the user device, or, as described elsewhere herein, a camera may map the pet and use software to create and/or identify an augmented reality fingerprint marker using the unique characteristics of the pet (e.g., colors/patterns, size, distinguishing features, etc. A user may scan the augmented reality fingerprint marker  1004  on a pet  3008  (or the pet itself), such as a dog, with the user device  1002 . After scanning the augmented reality fingerprint marker  1004 , digital information  1010  about the pet  3008  may overlay the live video feed displayed on the user device  1002 . The digital information  1010  may include, but is not limited to, a name and address of an owner, breed, medical needs, allergies, age, or any other information, such as a photo  1012  of the owner. Accordingly, the augmented reality fingerprint marker  1004  could be helpful when trying to find the owner of a lost pet  3008 . Additionally, the user device  1002  may display additional superimposed information, such as one or more animated arrows (e.g., illustrated in  FIG.  9 B ), guiding a user to an owner of a pet  3008 . As discussed earlier herein, one or more beacons may be used to determine the position of the owner. For example, the owner of the pet  3008  may have a beacon coupled to a leash of the pet  3008 . This allows a user to locate the owner of the pet  3008 . In an alternative, the pet owner&#39;s smartphone be used as a location device, such as by using the GPS or other technologies of the phone. For example, a pet owner could purchase a collar having a fingerprint marker  1004  thereon. The user may, during the setup of the fingerprint marker (e.g., inputting the information to be displayed on a user&#39;s screen when scanned by a user&#39;s device  1002 ) authorize the activation of the location technology of their smartphone when someone scan&#39;s the fingerprint marker  1004  on the collar. For short distances, other wireless technologies may also be utilized, such as Bluetooth®. When combined with short-distance technologies, the overlay of arrows on the user&#39;s screen is beneficial to direct the user to the pet owner in much the same way as locating the luggage in  FIG.  9 B- 9 D  and as discussed herein for the system for locating an object. The entire process of  FIGS.  9 A- 9 D  may be used not only with pets, but with other objects  1006  described herein, such as prescription vials, credit cards, clothing, cars, shoes, or other items that may become lost and be in need of return to a user. 
     In one embodiment, an augmented reality system comprises a user device with augmented reality software and an augmented reality fingerprint marker for use with an object, namely, military identifications. When military personnel enter a secured area, a user can obtain the identification and scan the augmented reality fingerprint marker, allowing the user to see information displayed about the military personnel on their user device. It will be appreciated that the augmented reality system increases security for the military and creates an in-depth verification step when a user can evaluate the digital information generated from the augmented reality fingerprint marker. Some of the information that may be superimposed on the military identification may be name, rank, branch of military, etc. 
     In one embodiment, an augmented reality system comprises a user device with augmented reality software and an augmented reality fingerprint marker to be used with an object, namely, for advertisements, such as TV ads, in-store ads, print ads, internet ads, etc. For example, a TV ad about a toy may be displayed on a screen with the augmented reality fingerprint marker in the corner thereof. A user may then scan the augmented reality fingerprint marker that can superimpose the instructions, price, and a 3D model of the toy onto the user&#39;s device. It will be appreciated that other information may also be displayed or may be displayed in place of the previously mentioned information, such as reviews or manufacturer information. 
     In one embodiment, as shown in  FIG.  13   , the object  1006  may include, but is not limited to, headstones  4008 , in-wall internments, urns, etc. For example, a headstone  4008  may include an augmented reality fingerprint marker  1004 , which, when scanned, can superimpose information  1010  about the deceased on a user device  1002  (e.g., smart device). Some of the information displayed on a user device  1002  may include, but is not limited to, a photo  1012 , video, biography  1010 , inspirational information, etc. A user may gain additional knowledge about the deceased easily and in an interactive manner. 
     In one embodiment, the object  1006  may be a hotel access card. For example, a user may scan the hotel access card using a user device  1002 , which would then superimpose any information desired by the hotel. Such information could be a directory, a listing of events, emergency escape routes, among others. 
     As shown above, an object may be any number of persons, animals, or things. Interacting with those objects using augmented reality has not been taught in the prior art and greatly enhances the world around us. 
     While the use of “fingerprint markers” has been disclosed herein in relation to objects  1006 , it is also contemplated that no marker is needed; rather, image recognition (as described earlier herein) or real-time recognition may be used to identify the object  1006  and superimpose information  1010  and owner photos  1012  thereon. For example, software for a camera may be able to identify an object based upon its shape, size, color, or other factors, allowing it to positively identify the object  1006  and display the ownership information  1010 ,  1012  associated therewith. Further, as discussed earlier herein regarding systems for locating an object, those methods and systems may be used with any object described herein that has a fingerprint marker. In other words, not only can the fingerprint marker be used to augment reality, but a user may also then locate the owner of the object using the systems and methods described earlier herein, which includes using a location tag or a smartphone of an owner. 
     For example, the object may be footwear that comprises an augmented reality fingerprint marker, which, when scanned, can superimpose information about the footwear on a user device (e.g., smart device), such as current ownership, ownership history, etc. Alternatively, instead of relying on the augmented reality fingerprint marker, the object itself, such as the footwear, may be scanned and mapped by the smart device&#39;s camera or another camera that may relay information to the smart device. It will be appreciated that the information may be stored on the camera, a remote database, or any other location. Once the object is scanned, information relating to the shoe may be stored, such as the shape, size, color, or distinguishing marks (the object&#39;s “fingerprint”). After the information is stored, a user may scan the shoe, which may display information relating to the shoe on the user device. Again, this information may include, but is not limited to, the owner of the shoes, the history of the shoes (e.g., all past owners), the purchase price, the estimated present-day value of the shoe, the size, and the manufacturer. 
     The augmented reality system can help a user obtain information about many objects that may help in purchasing decisions, preventing fraud, preventing drug abuse, etc. It will be appreciated that the augmented reality fingerprint marker may be placed on any object. The augmented reality system is not limited to the previously mentioned embodiments and may include many other items that can receive an augmented reality fingerprint marker, such as trophies, food, etc. 
     It will be appreciated by those skilled in the art that modifications can be made to the embodiments disclosed and remain within the inventive concept. Therefore, this invention is not limited to the specific embodiments disclosed but is intended to cover changes within the scope and spirit of the claims. 
     It will also be appreciated that systems and methods according to certain embodiments of the present disclosure may include, incorporate, or otherwise comprise properties or features (e.g., components, members, elements, parts, and/or portions) described in other embodiments. Accordingly, the various features of certain embodiments can be compatible with, combined with, included in, and/or incorporated into other embodiments of the present disclosure. Thus, disclosure of certain features relative to a specific embodiment of the present disclosure should not be construed as limiting application or inclusion of said features to the specific embodiment unless so stated. Rather, it will be appreciated that other embodiments can also include said features, members, elements, parts, and/or portions without necessarily departing from the scope of the present disclosure. 
     Moreover, unless a feature is described as requiring another feature in combination therewith, any feature herein may be combined with any other feature of a same or different embodiment disclosed herein. Furthermore, various well-known aspects of illustrative systems, methods, apparatus, and the like are not described herein in particular detail in order to avoid obscuring aspects of the example embodiments. Such aspects are, however, also contemplated herein. 
     Exemplary embodiments are described above. No element, act, or instruction used in this description should be construed as important, necessary, critical, or essential unless explicitly described as such. Although only a few of the exemplary embodiments have been described in detail herein, those skilled in the art will readily appreciate that many modifications are possible in these exemplary embodiments without materially departing from the novel teachings and advantages herein. Accordingly, all such modifications are intended to be included within the scope of this invention.