Classifications

• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
  • G06K7/00—Methods or arrangements for sensing record carriers, e.g. for reading patterns
  • G06K7/10—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation
  • G06K7/10009—Methods or arrangements for sensing record carriers, e.g. for reading patterns by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation sensing by radiation using wavelengths larger than 0.1 mm, e.g. radio-waves or microwaves
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q30/00—Commerce
  • G06Q30/06—Buying, selling or leasing transactions
  • G06Q30/0601—Electronic shopping [e-shopping]
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q30/00—Commerce
  • G06Q30/06—Buying, selling or leasing transactions
  • G06Q30/0601—Electronic shopping [e-shopping]
  • G06Q30/0609—Qualifying participants for shopping transactions
• • A—HUMAN NECESSITIES
  • A24—TOBACCO; CIGARS; CIGARETTES; SIMULATED SMOKING DEVICES; SMOKERS' REQUISITES
  • A24F—SMOKERS' REQUISITES; MATCH BOXES; SIMULATED SMOKING DEVICES
  • A24F40/00—Electrically operated smoking devices; Component parts thereof; Manufacture thereof; Maintenance or testing thereof; Charging means specially adapted therefor
  • A24F40/50—Control or monitoring

Definitions

• identification cards increasingly include some form of machine-readable data. Often many different entities (e.g., corporations, states, or government organizations) use different encoding for this machine-readable data. Summary of Example Embodiments
• Embodiments of the present disclosure include devices comprising input devices for scanning passive data-sources, and processing ability to decode machine-readable data stored in the passive data-source. This information is then used to verify the age of a user. Once the user’s age has been verified an activation signal is sent to an electronic device that dispenses age- restricted material (e.g., an e-cigarette or“vape” device).
• age- restricted material e.g., an e-cigarette or“vape” device.
• One illustrative system comprises a system for activating an age-restricted device, the system comprising: a scanner configured to scan a passive data source on an identification card; and a processor coupled to the scanner, the processor configured to: receive a scanner signal from the scanner; verify an age of a user based on the scanner signal; and transmit a verification signal to an age-restricted device.
• an illustrative system of the present disclosure comprises a system for activating an age-restricted device, the system comprising: a processor configured to receive an age verification signal and activate the age-restricted device based on the age verification signal; and a network interface configured to receive a verification signal from a remote device, wherein the remote device comprises: a scanner configured to scan a passive data source on an identification card; and a processor coupled to the scanner, the processor configured to: receive a scanner signal from the scanner; verify an age of a user based on the scanner signal; and transmit the verification signal to the age-restricted device.
• a method comprises: receiving a scanner signal from a scanner configured to scan a passive data source on an identification card; verifying an age of a user based on the scanner signal; and transmitting a verification signal to an age-restricted device.
• a method comprises: receiving an age verification signal from a remote device, wherein the remote device comprises: a scanner configured to scan a passive data source on an identification card; and a processor coupled to the scanner, the processor configured to: receive a scanner signal from the scanner; verify an age of a user based on the scanner signal; transmit the verification signal to the age-restricted device; and activating the age-restricted device based on the age verification signal.
• the remote device comprises: a scanner configured to scan a passive data source on an identification card; and a processor coupled to the scanner, the processor configured to: receive a scanner signal from the scanner; verify an age of a user based on the scanner signal; transmit the verification signal to the age-restricted device; and activating the age-restricted device based on the age verification signal.
• a non-transitory computer readable medium may comprise program code, which when executed by a processor is configured to cause the processor to: receive a scanner signal from a scanner configured to scan a passive data source on an identification card; verify an age of a user based on the scanner signal; and transmit a verification signal to an age-restricted device.
• a non-transitory computer readable medium may comprise program code, which when executed by a processor is configured to cause the processor to: receive an age verification signal from a remote device, wherein the remote device comprises: a scanner configured to scan a passive data source on an identification card; and a processor coupled to the scanner, the processor configured to: receive a scanner signal from the scanner; verify an age of a user based on the scanner signal; transmit the verification signal to an age-restricted device; and activate the age-restricted device based on the age verification signal.
• Figure 1 shows an illustrative system for age-restricted product registration according to one embodiment of the present disclosure
• Figure 2A shows another illustrative system for age-restricted product registration according to one embodiment of the present disclosure
• Figure 2B shows another illustrative system for age-restricted product registration according to one embodiment of the present disclosure
• Figure 3 shows another illustrative system for age-restricted product registration according to one embodiment of the present disclosure
• Figure 4A shows yet another illustrative system for age-restricted product registration according to one embodiment of the present disclosure
• Figure 4B shows yet another illustrative system for age-restricted product registration according to one embodiment of the present disclosure
• Figure 4C shows yet another illustrative system for age-restricted product registration according to one embodiment of the present disclosure
• Figure 4D shows yet another illustrative system for age-restricted product registration according to one embodiment of the present disclosure
• Figure 5 shows a flow chart of method steps for implementing a method for age- restricted product registration according to one embodiment of the present disclosure
• Figure 6 shows a flow chart of method steps for implementing a method for age- restricted product registration according to one embodiment of the present disclosure.
• the system 100 comprises an age-restricted device 112, such as an electronic cigarette (e-cigarette), which are sometimes referred to as vaping devices.
• e-cigarette dispenses a vapor that contains nicotine, and which a user inhales.
• An e-cigarette is not authorized for use for people under the age of eighteen.
• An illustrative embodiment herein provides systems and methods for restricting the use of an e-cigarette by people under the age of eighteen.
• the illustrative embodiment further comprises a mobile device 106 (e.g., a wearable device, smartphone, tablet, portable music device, or laptop).
• the mobile device 106 comprises a scanner 108 for reading data from an identification card 102 comprising a passive data source 104.
• the identification card may include, e.g., a State Issued Driver License, State Issued Real ID Compliant Driver License, State issued identification card, Federally issued Passport or Military Identification.
• the identification card 102 may comprise an electronic identification card, e.g., an electronic ID stored in an application on, e.g., the user’s mobile device.
• the scanner 108 comprises a digital camera configured to capture images.
• this camera comprises a standard camera found on mobile devices, without any specialized hardware.
• the illustrative embodiment further comprises a network connection, such as a wired or wireless internet connection.
• the illustrative embodiment further comprises a network interface 110 (e.g., Bluetooth, Near Field Communication (“NFC”), or RFID) to connect to a similar network interface 114 on the age- restricted device 112.
• a network interface 110 e.g., Bluetooth, Near Field Communication (“NFC”), or RFID
• the user accesses an application configured to verify the user’s age by capturing an image of the user’s identification card 102.
• the user captures an image of either the front or back face of a driver’s license.
• the user may load a mobile application that includes a widget to execute an age-verification application.
• this widget may appear as a button, switch, graphical user interface, or other user interface available for use with the mobile application.
• the mobile device 106 may be configured to enter an image capture mode.
• the mobile device 106 may access a digital camera coupled to the mobile device and display the output on a display of the mobile device 106.
• the user may then direct the camera toward the user’s identification card 102 (such as a driver’s license).
• the user may direct the camera toward passive data source 104, which may comprise machine-readable data (e.g., a barcode encoded in PDF-417 appearing on the back of the identification card). Examples of PDF-417 are shown in Figures 4A and 4B below.
• the application may exit the image capture screen, and return to another screen of the mobile application.
• a processor on the mobile device 106 may process the image to extract encoded data. In some embodiments, this processing may comprise cropping and compressing the data contained on the image. The mobile device 106 may then use a network interface (e.g., a wired or wireless network interface) to transmit the image data to a server.
• a network interface e.g., a wired or wireless network interface
• the server may comprise algorithms developed to quickly process and determine information associated with the cards.
• these algorithms may have been developed utilizing a database of data associated with identification cards.
• entities e.g., corporations, states, government organizations, military, or post office.
• some states change the encoding used on their drivers licenses every few years. However, those states may leave the older drivers licenses in rotation.
• these identification cards may comprise out of date encoding.
• some states may use multiple different types of encryption.
• the remote database may comprise data associated with a large number of these entities. Algorithms developed based on the data in this database may enable the server to quickly process and parse the data on an identification card. Further, in some other embodiments, data comparison software or string searches may enable the database to be quickly searched to determine information about the received data.
• the server may track whether the user has recently activated a different age-restricted device or bought more than a certain number of age-restricted devices.
• the server may be configured to deny access to a user that has activated another age- restricted device within a certain time period (e.g., one day or one-week), thus ensuring that one user who is of age (e.g., over eighteen or twenty-one) cannot activate multiple age-restricted devices for users that are not of age.
• the server may be configured to compare information associated with the user to a no sell list. If the user is on the no sell list the server may send information to the mobile device 106 to prevent the mobile device 106 from activating the age-restricted device 112.
• the server may use a network connection to transmit the decoded data back to the mobile device 106.
• the mobile device Once the mobile device receives this data, it will confirm that the user is over an age required to access the age-restricted device. If the user is over the age required to access the age-restricted device, the computing device will transmit an activation signal to the age-restricted device 112. Once the age-restricted device receives this activation signal, it will be activated and allow users to access the age-restricted material 116.
• the age-restricted material 116 may comprise one or more of e.g., a nicotine or a cannabinoid such as THC or CBD containing substance, or some controlled medication (e.g., anxiety or depression medication), opioids, or some other controlled substance, which may be configured to be vaporized or otherwise dispensed by age-restricted device 112.
• a nicotine or a cannabinoid such as THC or CBD containing substance
• some controlled medication e.g., anxiety or depression medication
• opioids e.g., opioids, or some other controlled substance, which may be configured to be vaporized or otherwise dispensed by age-restricted device 112.
• FIG. 2A shows an illustrative system 200 for age-restricted product registration.
• system 200 comprises a computing device 201 such as, e.g., a wearable device, smartphone, tablet, portable music device, laptop, desktop, kiosk, or dedicated computer terminal.
• computing device 201 has one or more processor(s) 202 interfaced with other hardware via bus 206.
• a memory 204 which can comprise any suitable tangible (and non-transitory) computer-readable medium such as RAM, ROM,
• computing device 201 further includes one or more network interface devices 210, input/output (I/O) interface components 212, and additional storage 214.
• network interface devices 210 input/output (I/O) interface components 212
• additional storage 214 additional storage 214.
• Network device 210 can represent one or more of any components that facilitate a network connection. Examples include, but are not limited to, wired interfaces such as Ethernet, ETSB, IEEE 1394, and/or wireless interfaces such as IEEE 802.11, Bluetooth, Near Field
• Communication, RFID, and/or radio interfaces for accessing cellular telephone networks e.g., transceiver/antenna for accessing a CDMA, GSM, UMTS, or other mobile communications network(s)).
• I/O components 212 may be used to facilitate connection to devices such as one or more user interfaces 216 (e.g., keyboards, mice, speakers, microphones, and/or other hardware used to input data or output data) and display 220 (e.g., a display such as a plasma, liquid crystal display (LCD), electronic paper, cathode ray tube (CRT), light emitting diode (LED), or some other type of display known in the art).
• user interfaces 216 and display 220 may comprise a single component, e.g., a touch screen display.
• I/O components 212 may include speakers configured to play audio signals provided by processor 202.
• Storage 214 represents nonvolatile storage such as magnetic, optical, or other storage media.
• Scanner 218 comprises a sensor configured to detect a passive data-source, such as data encoded in a multidimensional code.
• scanner 218 may comprise an optical sensor such as a digital camera.
• processor 202 may use scanner 218 to take an image of a passive data-source, e.g., a matrix barcode such as a QR code, bar code, or multidimensional bar code encoded in PDF-417.
• the digital camera may comprise no specialized hardware capability, for example, in some embodiments, the digital camera may be a standard digital camera found on mobile devices such as smartphones and tablets.
• the digital camera may comprise an auto-focus capability that enables the camera to capture an image of the multidimensional code at sufficient resolution to reliably extract the encoded data.
• processor 202 may use software stored in memory 204 (discussed below) to determine data encoded in the multidimensional bar code.
• scanner 218 may comprise another component, such as a laser scanner, CCD, reader, video camera reader, or other type of scanner configured to scan a passive data-source such as a multidimensional bar code.
• scanner 218 may comprise a scanner configured to detect data from a magnetic code (e.g., a magnetic strip), an RFID, NFC, a SmartCard, an Integrated Circuit Card (ICC) or some other type of passive data.
• a magnetic code e.g., a magnetic strip
• RFID e.g., NFC, a SmartCard, an Integrated Circuit Card (ICC) or some other type of passive data.
• ICC Integrated Circuit Card
• an image detection module 224 configures processor 202 to monitor the input from scanner 218 to detect an image comprising machine-readable data.
• module 224 may configure processor 202 to enter an image capture mode in which display 220 shows the output from scanner 218.
• image detection module 224 may be configured to determine the quality of data received from scanner 218. For example, in one embodiment, this may comprise measuring the resolution and focus of the received image.
• image detection module 224 may further comprise software to enable processor 202 to determine that the image is of sufficient quality, and therefore capture the image.
• Image-parsing module 226 represents a program component that analyzes image data received from scanner 218.
• image-parsing module 226 may comprise software configured to enable processor 202 to crop and/or compress the captured image for transmission via network 210 to a remote server.
• image-parsing module 226 may comprise program components configured to enable processor 202 to perform an image comparison between the captured image and data stored on a local database.
• image-parsing module 226 may comprise algorithms that enable the processor 202 to quickly determine the data encoded in a label, e.g., the name, date of birth, address, driver’s license number, height, weight, state, county, race, organ donor status, issue date, expiration date, driver restriction, class of vehicle, passport information, criminal record information, or any other information stored in the encoded data. In some embodiments, some of this information may be withheld, e.g., due to privacy concerns. Thus, in some embodiments, information such as a person’s height, weight, race, organ donor status, driver restrictions, or class of vehicle may be withheld.
• a label e.g., the name, date of birth, address, driver’s license number, height, weight, state, county, race, organ donor status, issue date, expiration date, driver restriction, class of vehicle, passport information, criminal record information, or any other information stored in the encoded data. In some embodiments, some of this information may be withheld, e.g., due to privacy concerns
• program components 224 and 226 may be comprise software components configured to enable processor 202 to process other types of passive data-sources, e.g., magnetic strips, RFIDs, NFC, SmartCards, or Integrated Circuit Cards (ICC).
• passive data-sources e.g., magnetic strips, RFIDs, NFC, SmartCards, or Integrated Circuit Cards (ICC).
• ICC Integrated Circuit Cards
• computing device 201 may comprise additional components, such as motion detectors, accelerometers, or GPS receivers that processor 202 may use to determine other information, such as the movements or orientation of computing device 201.
• additional components such as motion detectors, accelerometers, or GPS receivers that processor 202 may use to determine other information, such as the movements or orientation of computing device 201.
• system 250 comprises an age-restricted device 251, e.g., an e-cigarette device.
• an age-restricted device 251 e.g., an e-cigarette device.
• the system 250 has one or more processor(s) 252 interfaced with other hardware via bus 256, age-restricted material 254 (e.g., a nicotine or a cannabinoid such as THC or CBD containing substance, or some controlled medication (e.g., anxiety or depression medication), opioids, or some other controlled substance, which may be configured to be vaporized or otherwise dispensed by age-restricted device 251), a network interface 260, and input/output (I/O) interface components 262.
• age-restricted material 254 e.g., a nicotine or a cannabinoid such as THC or CBD containing substance, or some controlled medication (e.g., anxiety or depression medication), opioids, or some other controlled substance, which may be configured to be vaporized or otherwise dispensed by age-restricted device 251
• a network interface 260 e.g., a network interface 260
• I/O input/output
• Network device 260 can represent one or more of any components that facilitate a network connection. Examples include, but are not limited to, wired interfaces such as Ethernet, USB, microUSB, Firewire, IEEE 1394, and/or wireless interfaces such as IEEE 802.11,
• network interface 260 is configured to receive an activation signal from computing device 201, described above with regard to Figure 2A, transmit this activation signal to processor(s) 252, which then activate the age-restricted device 251 based on the activation signal.
• I/O components 262 may be used to facilitate connection to devices such as one or more user interfaces 266 (e.g., keyboards, mice, speakers, microphones, and/or other hardware used to input data or output data) and display 220 (e.g., a display such as a plasma, liquid crystal display (LCD), electronic paper, cathode ray tube (CRT), light emitting diode (LED), or some other type of display known in the art).
• I/O components 262 may include speakers configured to play audio signals provided by processor 262.
• FIG. 3 illustrates another illustrative system for age-restricted product registration 300.
• system 300 comprises a computing device 310, comprising a processor 311, memory 312 comprising instructions 313, and a network interface 314.
• computing device 310, and its components may operate similarly to the components of computing device 201 described above with regard to Figure 2A.
• the components of computing device 310 may enable the computing device to scan a passive data-source, process the data, and transmit the processed data via access network 330.
• the access network 330 may be a 3 GPP network, a 3GPP2 network, a WiMAX network, 4G LTE, HSPA+, UMTS, a Wi-Fi network (e.g., a network that operates in accordance with an IEEE 802.11 standard), or some other wireless access network.
• access network 330 may comprise a wired network such as Ethernet, USB, microUSB, Firewire, IEEE 1394, cable, or telephone networks. In some embodiments, access network 330 may comprise a plurality of different types of wired and/or wireless networks configured to transmit data between computing device 310 and server 320. [0046] As shown in Figure 3, the access network 330 is further coupled to a server 320. Server 320 is configured to receive data sent from computing device 310 via access network 330 using network interface 323.
• Network interface 323 may comprise a wired and/or wireless network interface configured to receive data using access network 330.
• Server 320 further comprises a processor 321 coupled to a database 322.
• Database 322 may comprise a database of data associated with identification cards.
• the database 322 may comprise data associated with identification cards issued by one or more of corporations, states, and government organizations.
• Processor 321 may be configured to use data comparison software to compare data received from computing device 310 to data stored in database 322 to determine the type of encoding associated with an image and then quickly decode the data, e.g., by parsing the data to determine the stored information, e.g., the name, date of birth, address, driver’s license number, height, weight, state, county, or any other information stored in the encoded data.
• processor 321 may instead comprise algorithms configured to determine information about a passive data source without having to search database 322. In some embodiments, these algorithms may have been developed using the data available in database 322. Further, in some embodiments, these algorithms may enable the processor 321 to quickly determine the jurisdiction that issued a card, e.g., by determining the Issuer Identification Number (“UN Number”) associated with the card, or the type of encryption used in the card. Once this is determined, processor 321 may access an algorithm associated with that IIN number to quickly determine data associated with the passive data source. In some embodiments, processor 321 may be configured to determine the stored data in 2 seconds or less.
• UN Number Issuer Identification Number
• processor 321 may be configured to determine the stored data in 2 seconds or less.
• processor 321 and database 322 may be configured to adapt to new data types.
• the administrators of database 322 may periodically update database 322 with new data associated with new entities (e.g., states, government organizations, or corporations).
• processor 321 may be configured to update database 322 based on new data received from entities as the entities post new information (e.g., as a state releases a new type of identification card).
• processor 321 and database 322 may be configured to analyze received data that is not associated with a known type, and based on patterns of other received data, make a determination about the received data. For example, in one embodiment, processor 321 and database 322 may be configured to compare the encoding to known encoding types and thus determine that the encoded data is associated with North Carolina. The processor 321 and database 322 may be configured to further determine that some component of the encoding or encryption is incorrect, for example, because the person who set up the multidimensional code for the drivers’ licenses in a jurisdiction (e.g., a state or county) used the wrong type of encoding.
• a jurisdiction e.g., a state or county
• processor 321 may update database 322 with new information about this jurisdiction (e.g., the state or county), to thus enable processor 321 to use database 322 to determine data associated with that jurisdiction in the future.
• computing device 310 and server 320 may comprise additional components, such as additional memory and processing components or network components configured to provide faster or more convenient access via access network 330.
• the parsed data may be stored on the server 320.
• this information may be used for future processing and authentication.
• a user may not be able to authenticate more than one device within a set time period (e.g., one-day, one-week, one-month) to prevent a user from authenticating multiple age-restricted devices and distributing them.
• the server 320 may store the total amount of an age-restricted substance purchased by the user. In some embodiments, this information may be used to restrict the user’s access to additional amounts of an age restricted substance.
• one user may not be able to purchase over a certain quantity of the age-restricted substance in a set time period.
• the user’s age, the total amount of a substance the user has purchased, and the time since the user’s last purchased may all be used together to determine whether the user can purchase more of the age-restricted substance.
• the server may be configured to determine whether the user is on a no sell list, and, if so, prevent the user from being able to activate the age-restricted device.
• the user may be able to deactivate an age-restricted device, e.g., if the user loses the age-restricted device.
• users may verify their identity by scanning an ID card as described above and sending data to the server 320 indicating that an age-restricted device should be deactivated.
• the server 320 may send a signal to the age-restricted device or to a computing device associated with the age-restricted device to deactivate the age-restricted device so it cannot be operated.
• Figures 4A and 4B comprise images 400 and 450 of data encoded on the back of drivers licenses from two different states.
• the data is encoded using PDF-417.
• PDF-417 is a stacked linear barcode format.
• PDF stands for Portable Data File.
• the 417 signifies that each pattern in the code consists of 4 bars and spaces, and that each pattern is 17 units long.
• data encoded using PDF-417 may further comprise some type of compression or encryption. These types of encryption and compression are applied irregularly amongst jurisdictions such as Federal and State organizations.
• the present disclosure comprises a database that takes into account these differences and is usable for all jurisdictions (e.g., using a prior technology a Georgia government body may be able to scan identification cards issued by Georgia but cannot effectively scan cards issued by other states). Further, in some embodiments, additional data may be encoded into the identification card. For example, in Florida some information associated with the driver may be embedded into the driver’s license number. Thus, in some embodiments, a database associated with Florida driver’s licenses may be useful only if it is designed to store this information.
• Figure 4C illustrates an example embodiment of the front face of an identification card 460.
• the identification card is an example similar to many states’ driver’s licenses and includes a picture as well as written information identifying the holder of the driver’s license.
• Figure 4D shows the reverse side 470 of the identification card 460.
• the identification card includes a PDF-417 label (e.g., labels 400 or 450 described above).
• this label may comprise all or some part of the data on the front of the identification card.
• the label may instead be located on the front.
• some military identification cards e.g., CAC cards
• Some of these cards further include additional passive data-sources, such as ICC,
• the driver’s license may instead comprise one of these other types of passive data-sources.
• the identification card may comprise an electronic identification card, e.g., an electronic ID stored in a computer associated with the user, e.g., stored in an application on the user’s mobile device.
• FIG. 5 is a flowchart showing an illustrative method 500 for age-restricted product registration.
• the steps in flow chart 500 may be implemented in program code executed by a processor, for example, the processor in a general purpose computer, mobile device, or server. In some embodiments, these steps may be implemented by a group of processors. In some embodiments the steps shown in Figure 5 may be performed in a different order. Alternatively, in some embodiments, one or more of the steps shown in Figure 5 may be skipped or additional steps not shown in Figure 5 may be performed.
• the steps below are described with reference to components described above with regard to the systems described above with regard to Figures 2A, 2B, and 3.
• the method 500 is described with regard to image capture of a passive data source (e.g., of an image of a multidimensional bar code).
• a passive data source e.g., of an image of a multidimensional bar code
• the steps below are equally applicable to processing data extracted from other types of passive data sources.
• these method steps may be applied to capturing data from a magnetic code (e.g., a magnetic strip), an RFID, NFC, a SmartCard, an Integrated Circuit Card (ICC) or some other type of passive data.
• the methods described below may be used to extract data appearing as printed text on the front of an identification card.
• the processor 202 may be configured to perform an optical character recognition (OCR) of this text.
• OCR optical character recognition
• the method 500 begins at step 502 when processor 202 receives a scanner signal from scanner 218.
• scanner 218 may comprise one of a plurality of devices configured extract data from a passive data source (e.g., a barcode or other information printed on an identification card).
• scanner 218 may comprise a camera configured to capture an image of the front or the back of an identification card.
• the image may comprise an image of machine-readable data encoded in an identification card (e.g., on the back of the identification card).
• the machine-readable data may comprise a multidimensional encoding, such as data encoded using PDF-417.
• the image may comprise an image of text printed on the front or the back of the identification card.
• the scanner 218 may comprise a scanner configured to scan other types of passive data sources, e.g., a magnetic code (e.g., a magnetic strip), an RFID, NFC, a SmartCard, an Integrated Circuit Card (ICC) or some other type of passive data.
• a magnetic code e.g., a magnetic strip
• RFID e.g., a RFID
• NFC e.g., a magnetic strip
• SmartCard e.g., a SmartCard
• ICC Integrated Circuit Card
• Next processor 202 determines a type of encryption associated with the scanner signal 504. In some embodiments, determining the type of encryption may comprise
• determining a type of encoding associated with the scanner signal or determining that the scanner signal is not encoded or encrypted may comprise determining how data is encoded, e.g., encoded in a matrix barcode such as a QR code, bar code, or multidimensional bar code encoded in PDF-417.
• determining a type of encoding may comprise determining a type of scanner, e.g., determining that the scanner signal is received from one or more different types of scanners 218, e.g., scanners configured to detect information embedded in one or more of an image, a magnetic code (e.g., a magnetic strip), an RFID, NFC, a SmartCard, an Integrated Circuit Card (ICC) or some other type of passive data.
• the type of encryption may be determined by processor 321 on a server connected to computing device 201 via a network connection.
• the processor 202 extracts known data elements from the scanner signal.
• the processor may be configured to extract data elements such as e.g., the name, date of birth, address, driver’s license number, height, weight, state, county, race, organ donor status, issue date, expiration date, driver restriction, class of vehicle, passport information, criminal record information, or any other information stored based on the scanner signal.
• the processor 202 may extract this information by comparing the scanner signal to data stored in a local data store.
• the processor 202 may execute algorithms to extract certain encoded data from the scanner signal.
• known data elements may be determined by processor 321 on a server connected to computing device 201 via a network connection.
• processor 202 transmits data associated with the scanner signal to a server 320.
• processor 202 may compress data prior to transmission, e.g., the processor 202 may perform one or more compression algorithms to reduce network overhead and upload time in transmitting data associated with the scanner signal.
• Processor 202 may use network 210 to transmit the data.
• network 210 may comprise any type of wired and/or wireless network available to computing device 201.
• processing the image data may comprise extracting known elements from the image.
• the image may comprise non-encrypted PDF-417.
• processor 202 may extract available known data from the image.
• the processor 202 may resize the image to 640x480 pixels, transform the image to 24-bit grayscale with a quality of 80%, and convert the image to Base64 string representation.
• Processor 321 on server 320 may process the scanner signal to extract data from the scanner signal. Alternatively, in some embodiments, the processing may occur on processor 202 local to computing device 201. In some embodiments, processing the scanner signal may comprise determining information about the scanner signal, e.g., a type of encoding or encryption type associated with the scanner signal. In some embodiments, processing the data may comprise comparing the data to a database. In other embodiments, rather than performing a line-by-line comparison to a database, the server may instead use a series of algorithms developed based on previous cards to determine the data. For example, the server may comprise a database 322 of data associated with identification cards. The server may further comprise a series of algorithms configured to determine information about identification cards.
• these algorithms may have been developed using the data stored in database 322.
• these algorithms may enable the server to quickly determine identification data.
• the server may use algorithms and logic to quickly determine the IIN Number associated with the card.
• the server may use low overhead string functions to perform a lookup in a specially formatted string that contains all of the applicable values.
• this may comprise using a Supertanker String Lookup technique during the data discovery process.
• These may comprise low overhead string functions to perform a lookup in a specially formatted string that contains all of the applicable values.
• processing the image data comprises determining that there is enough captured data to start the process. In some embodiments, processing may also determine whether the data was extracted from a magnetic stripe (e.g., via swiping a reader rather than a captured image) or a barcode. In some embodiments, processing the data may further comprise replacing any invalid binary characters and standardizing on the Track
• processing the data may further comprise checking binary data points to determine if any information is encrypted (e.g., if the data comprises an encrypted driver’s license or identification card). In some embodiments, the processing may further comprise replacing any invalid binary characters and determining the type of data (e.g., driver’s license, military identification, passport, or some other data type).
• Processing the scanner signal enables data associated with the scanner signal to be determined.
• determining the data associated with the scanner signal comprise parsing the data to determine the stored information, e.g., the name, date of birth, address, driver’s license number, height, weight, state, county, issue date, expiration date, or any other information stored in the encoded data.
• this parsing process may comprise identifying and consolidating the field separators and delimiters in the
• the parsed data may be stored on the server 320. In some embodiments, this information may be used for future processing and authentication. For example, in some embodiments, a user may not be able to authenticate more than one device within a set time period (e.g., one-day, one-week, one-month) to prevent a user from a set time period (e.g., one-day, one-week, one-month) to prevent a user from a set time period (e.g., one-day, one-week, one-month) to prevent a user from a set time period (e.g., one-day, one-week, one-month) to prevent a user from a set time period (e.g., one-day, one-week, one-month) to prevent a user from a set time period (e.g., one-day, one-week, one-month) to prevent a user from a set time period (e.g., one-day, one-week, one-month) to prevent a
• the server 320 may store the total amount of an age-restricted substance purchased by the user. In some embodiments, this information may be used to restrict the user’s access to additional amounts of an age restricted substance. For example, one user may not be able to purchase over a certain quantity of the age-restricted substance in a set time period. In still other embodiments, the user’s age, the total amount of a substance the user has purchased, and the time since the user’s last purchased may all be used together to determine whether the user can purchase more of the age-restricted substance.
• server 320 transmits a data signal associated with the data extracted from the scanner signal.
• this data signal comprises information associated with the age or identity of the user who scanned the identification card. Further, in some embodiments, this data includes whether the user is authorized to activate an age-restricted device 251, e.g., the user is over a certain age and had not activated an age-restricted device within a certain time period.
• the computing device 201 receives the data signal from the server 320. Then at step 512, the computing device 201 transmits an activation signal to the age-restricted device 251.
• the activation signal may be transmitted via either a wired or wireless network connection, e.g., via one or more of a Ethernet, USB, microUSB, Firewire, IEEE 1394, and/or wireless interfaces such as IEEE 802.11, Bluetooth, Near Field Communication, RFID, and/or radio interfaces for accessing cellular telephone networks (e.g., transceiver/antenna for accessing a CDMA, GSM, UMTS, or other mobile communications network(s)).
• a wired or wireless network connection e.g., via one or more of a Ethernet, USB, microUSB, Firewire, IEEE 1394, and/or wireless interfaces such as IEEE 802.11, Bluetooth, Near Field Communication, RFID, and/or radio interfaces for accessing cellular telephone networks (e.g., transceiver/antenna for accessing
• the activation signal causes a processor 252 on the age-restricted device to activate the device and enable a user to access age-restricted material 254 on the device.
• the activation signal will enable the user to use the e-cigarette.
• the age-restricted device 251 is required to be activated only once. In other embodiments, the age-restricted device 251 must be activated each time a user attempts to use the device, or must be activated within a certain set period, e.g., every day, week, month, etc.
• FIG. 6 is a flowchart showing an illustrative method 600 for age-restricted product registration.
• the steps in flow chart 600 may be implemented in program code executed by a processor, for example, the processor in a general purpose computer, mobile device, or server. In some embodiments, these steps may be implemented by a group of processors. In some embodiments the steps shown in Figure 5 may be performed in a different order. Alternatively, in some embodiments, one or more of the steps may be skipped or additional steps may be performed. The steps below are described with reference to components described above with regard to the systems described above with regard to Figures 2A, 2B, and 3.
• an age-restricted device 251 receives a verification signal from computing device 201.
• the verification signal was determined based on scanning a passive data source and extracting data from the passive data source as described in the embodiments above.
• a processor 252 activates the age-restricted device based on the verification signal.
• the activation signal causes a processor 252 on the age-restricted device to activate the device and enable a user to access age-restricted material 254 on the device.
• the age-restricted device 251 is an e-cigarette, the activation signal will enable the user to use the e-cigarette.
• the age-restricted device 251 is required to be activated only once. In other embodiments, the age-restricted device 251 must be activated each time a user attempts to use the device, or must be activated within a certain set period, e.g., every day, week, month, etc.
• the systems and methods described above may be provided to application developers on a software development kit (SDK) that enables the developer (e.g., the developer of the webpage or iOS, Android, or Windows application) to quickly plug the functionality into their application or web page as a module.
• SDK software development kit
• an application or web page development company may develop its own image capture software, but may be given access to image processing capability using the database and algorithms described herein.
• the database of data associated with identification card data may be sold to application or web page development companies.
• only portions of the database may be sold or made available, e.g., only the segment of the database associated with a state, region, or government entity.
• algorithms developed to determine identification data associated only a certain region may be made available.
• the methods may be performed in an order different from that described, and/or various stages may be added, omitted, and/or combined.
• features described with respect to certain configurations may be combined in various other configurations. Different aspects and elements of the configurations may be combined in a similar manner.
• technology evolves and, thus, many of the elements are examples and do not limit the scope of the disclosure or claims.
• configurations may be described as a process that is depicted as a flow diagram or block diagram. Although each may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be rearranged. A process may have additional steps not included in the figure.
• examples of the methods may be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware, or microcode, the program code or code segments to perform the necessary tasks may be stored in a non-transitory computer-readable medium such as a storage medium. Processors may perform the described tasks.
• a computer may comprise a processor or processors.
• the processor comprises or has access to a computer-readable medium, such as a random access memory (RAM) coupled to the processor.
• RAM random access memory
• the processor executes computer- executable program instructions stored in memory, such as executing one or more computer programs including a sensor sampling routine, selection routines, and other routines to perform the methods described above.
• Such processors may comprise a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), field programmable gate arrays (FPGAs), and state machines. Such processors may further comprise programmable electronic devices such as PLCs, programmable interrupt controllers (PICs), programmable logic devices (PLDs), programmable read-only memories (PROMs), electronically programmable read-only memories (EPROMs or EEPROMs), or other similar devices.
• PLCs programmable interrupt controllers
• PLDs programmable logic devices
• PROMs programmable read-only memories
• EPROMs or EEPROMs electronically programmable read-only memories
• Such processors may comprise, or may be in communication with, media, for example tangible computer-readable media, that may store instructions that, when executed by the processor, can cause the processor to perform the steps described herein as carried out, or assisted, by a processor.
• Embodiments of computer-readable media may comprise, but are not limited to, all electronic, optical, magnetic, or other storage devices capable of providing a processor, such as the processor in a web server, with computer-readable instructions.
• Other examples of media comprise, but are not limited to, a floppy disk, CD-ROM, magnetic disk, memory chip, ROM, RAM, ASIC, configured processor, all optical media, all magnetic tape or other magnetic media, or any other medium from which a computer processor can read.
• various other devices may include computer-readable media, such as a router, private or public network, or other transmission device.
• the processor, and the processing, described may be in one or more structures, and may be dispersed through one or more structures.
• the processor may comprise code for carrying out one or more of the methods (or parts of methods) described herein.

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• 2019
  • 2019-10-09 EP EP19797866.1A patent/EP3868091A1/de not_active Withdrawn
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