The invention relates to gas detection, and more particularly to sensor-based gas detection.
Methane (CH4) is an odorless and colorless naturally occurring organic molecule, which is present in the atmosphere at average ambient levels of approximately 1.85 ppm as of 2018 and is projected to continually climb. Methane is a powerful greenhouse gas, a source of energy (i.e., methane is flammable), and an explosion hazard, and so detection of methane is of utility to scientists as well as engineers. While methane is found globally in the atmosphere, a significant amount is collected or “produced” through anthropogenic processes including exploration, extraction, and distribution of petroleum resources as a component in natural gas. Natural gas, an odorless and colorless gas, is a primary fuel used to produce electricity and heat. The main component of natural gas is typically methane, and the concentration of methane in a stream of natural gas can range from about 70% to 90%. The balance of the gas mixture in natural gas consists of longer chain hydrocarbons, including ethane, propane, and butane, typically found in diminishing mole fractions that depend on the geology of the earth from which the gas is extracted. Once extracted from the ground, natural gas is processed into a product that must comply with specifications for both transport, taxation, and end-use in burners; specification of processed ‘downstream’ natural gas product control for the composition of the gas, so as to protect transport lines from corrosion and ensure proper operation of burners and turbines. While extraction of natural gas is one of the main sources of methane in the atmosphere, major contributors of methane also include livestock farming (i.e., enteric fermentation) and solid waste and wastewater treatment (i.e., anaerobic digestion). Anaerobic digestion and enteric fermentation gas products consist primarily of methane and lack additional hydrocarbon species.
A system embodiment may include: a gas sensor comprising one or more optical cells; a processor having addressable memory, the processor configured to: detect gas from the one or more optical cells of the gas sensor, where the detected gas may be one or more of: methane, carbon dioxide, hydrogen sulfide, water, ammonia, sulfur oxides, and nitrogen; record data corresponding to the detected gas, where the recorded data comprises at least one of: an ambient temperature from a temperature sensor, an ambient pressure from a pressure sensor, an aerial vehicle telemetry, and an aerial vehicle location from a global positioning system (GPS); and generate a map of atmospheric greenhouse gas concentration on a map based on the detected gas and the recorded data.
Additional system embodiments may include: a gas handling system configured to supply atmospheric gas to the gas sensor. In additional system embodiments, the gas handling system may comprise at least one of: a pump, a ram-air design, and a velocity-induced vacuum. Additional system embodiments may include: a thermal chamber configured to modify a temperature of the supplied atmospheric gas to a set temperature. Additional system embodiments may include: a pressure regulator configured to modify a pressure of the supplied atmospheric gas to a set pressure.
In additional system embodiments, the processor may be further configured to: actively adjust at least one operating parameter of the gas sensor based on the recorded data. In additional system embodiments, the at least one operating parameter of the gas sensor may be an acquisition rate. In additional system embodiments, the acquisition rate may be increased by the processor based on an increased speed of an aerial vehicle from the recorded data of the aerial vehicle location to maintain a substantially constant spatial distribution of sampled locations. In additional system embodiments, the acquisition rate may be increased by the processor based on an aerial vehicle traversing an area with increased turbulence based on the recorded data.
Additional system embodiments may include: an aerial vehicle, where the gas sensor is mounted on the aerial vehicle. In additional system embodiments, the aerial vehicle may be an unmanned aerial vehicle (UAV). In additional system embodiments, the gas sensor may be mounted in a fuselage of the aerial vehicle. In additional system embodiments, the gas sensor may be mounted distal from a fuselage of the aerial vehicle.
Additional system embodiments may include: a ground control station (GCS) in communication with the gas sensor, the GCS comprising a GCS processor having addressable memory, the GCS processor configured to: receive the detected gas from the one or more optical cells of the gas sensor; receive the recorded data corresponding to the detected gas; and provide instructions to the aerial vehicle to follow a flight path. Additional system embodiments may include: a power management and laser control logic system configured to supply a laser of each of the one or more optical cells with a drive current, an operating temperature, and a power consumption within operating bounds of each laser.
A method embodiment may include: providing an atmospheric gas to a gas sensor; detecting, by one or more optical cells of the gas sensor, gas from one or more of: methane, carbon dioxide, water, hydrogen sulfide, ammonia, sulfur oxides, and nitrogen oxides; recording, by a processor having addressable memory, data corresponding to the detected gas from at least one of: an ambient temperature, an ambient pressure, an aerial vehicle telemetry, and an aerial vehicle location; and generating, by the processor, an atmospheric greenhouse gas concentration data on a map based on the detected gas and recorded data.
Additional method embodiments may include: receiving atmospheric gas from a gas handling system. Additional method embodiments may include, prior to providing the atmospheric gas to the gas sensor: measuring or inferring a temperature of the received atmospheric gas from the gas handling system; and modifying the temperature of the received atmospheric gas to a set temperature via a thermal chamber. Additional method embodiments may include, prior to providing the atmospheric gas to the gas sensor: measuring or inferring a pressure of the received atmospheric gas from the gas handling system; and modifying the pressure of the received atmospheric gas to a set pressure via a pressure regulator.
Another system embodiment may include: an unmanned aerial vehicle (UAV); a gas handling system configured to supply atmospheric gas to a gas sensor; a thermal chamber configured to modify a temperature of the supplied atmospheric gas to a set temperature; a pressure regulator configured to modify a pressure of the supplied atmospheric gas to a set pressure; one or more optical cells of the gas sensor, where the gas sensor may be mounted to the UAV; a processor having addressable memory, the processor configured to: detect gas from the one or more optical cells of the gas sensor, where the detected gas may be one or more of: methane, carbon dioxide, hydrogen sulfide, water, ammonia, sulfur oxides, and nitrogen; record data corresponding to the detected gas, where the recorded data comprises at least one of: an ambient temperature from a temperature sensor, an ambient pressure from a pressure sensor, an aerial vehicle telemetry, and an aerial vehicle location from a global positioning system (GPS); actively adjust at least one operating parameter of the gas sensor based on the recorded data; and generate a map of atmospheric greenhouse gas concentration on a map based on the detected gas and the recorded data.
The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principals of the invention. Like reference numerals designate corresponding parts throughout the different views. Embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which:
The following description is made for the purpose of illustrating the general principles of the embodiments discloses herein and is not meant to limit the concepts disclosed herein. Further, particular features described herein can be used in combination with other described features in each of the various possible combinations and permutations. Unless otherwise specifically defined herein, all terms are to be given their broadest possible interpretation including meanings implied from the description as well as meanings understood by those skilled in the art and/or as defined in dictionaries, treatises, etc.
The present system allows for a gas sensor attached to an aerial vehicle, such as an unmanned aerial vehicle (UAV), to quantify gas concentrations at specific locations and times in locales that may be inaccessible by manned aircraft and/or risky flight environments. The disclosed greenhouse gas sensor may be flown as a payload on an airborne platform, such as a UAV, to take these measurements and acquire point concentration measurements of CO2, CH4, and/or H2O (gas) while in flight. The disclosed sensor provides a light sensor weight, resilience to temperature and pressure changes, operates with sufficient sampling rate, and complies with electrical power limits.
The airborne greenhouse gas sensor (GHGS) 102 may be carried as a payload on an airborne platform 104, and the GHGS 102 may acquire point concentration measurements of CO2, CH4, and/or H2O (gas) while in flight. The GHGS 102 may interface with UAV telemetry 106 and a global positioning system (GPS) 108 to localize gas measurements.
The GHGS 102 may be an ultra-lightweight, low power, part-per-billion (ppb) sensitivity, mid-Infrared (wavelength λ=3-8 μm), open path gas concentration sensor with sampling rate greater than or equal to 10 Hz; such a sensor infers gas concentration by measuring the absorption of laser light. In some embodiments, the GHGS 102 may weigh less than 1.4 kg. In some embodiments, the GHGS 102 may be tuned to detecting a single gas species. The single species may be methane, carbon dioxide, water, hydrogen sulfide, ammonia, sulfur oxides, or nitrogen oxides. In some embodiments, the GHGS 102 may be tuned to detect two or more different gas species, such as methane, carbon dioxide, water, hydrogen sulfide, ammonia, sulfur oxides, and/or nitrogen oxides. In some embodiments, a single optical cell 110 may be used. In other embodiments, multiple optical cells 110, 112, 114 may be used. Each optical cell 110, 112, 114 may contain a gas flow path, through which gas concentration may be interrogated for one or more species. In some embodiments, the one or more optical cells 110, 112, 114 may be open to the atmosphere. In other embodiments, the one or more optical cells 110, 112, 114 may be a closed system through which a gas sample flows through. Each optical cell 110, 112, 114 may provide a path for a laser beam to traverse. In some embodiments, the optical cell 110, 112, 114 may be a Herriott cell. In other embodiments, the optical cell 110, 112, 114 may be a high-finesse cavity. In other embodiments, the optical cell 110, 112, 114 may be a simple pitch-and-catch optical arrangement.
The system 100 may include a gas handling system 116 to deliver atmospheric air samples to the one or more optical cells 110, 112, 114. In some embodiments, the gas handling system 116 may use at least one pump 118. In other embodiments, the gas handling system 116 may use a ram-air design. In other embodiments, the gas handling system 116 may use velocity-induced vacuum. In some embodiments, the gas handling system 116 may use a combination of the pump 118, the ram-air design, and/or the velocity-induced vacuum.
Onboard sensors 120 may be used to determine ambient temperature and pressure in the GHGS 102 sensor head. In other embodiments, a pressure sensor 122 and/or a temperature sensor 124 of the aerial vehicle 104 may provide sensor measurements to the GHGS 102. In other embodiments, the ambient temperature and pressure in the GHGS 102 sensor head may be inferred from the measurements acquired in the optical cells 110, 112, 114.
In some embodiments, a thermal chamber 126 may be used to warm or cool atmospheric gas to a specific temperature before it reaches the GHGS 102 sensor head. In some embodiments, a pressure regulator 128 may be used to control the pressure of the gas sample in the GHGS 102 sensor head.
A power supply device 130 may be integrated into the GHGS 102 sensor head in some embodiments. In other embodiments, the power supply device 130 may be mounted remotely from the sensor payload and connected by cables to the sensor 102. A power supply 132 of the aerial vehicle 104 may be used to supply power to the sensor 102 in some embodiments. In some embodiments, the power supply 132 may be mounted elsewhere on the airframe of the aerial vehicle 104 and connected to the sensor 102 via cables.
A power management and laser control logic system 134 may be used to ensure that: lasers are supplied with drive current within the laser operating bounds, laser operating temperatures do not exceed laser operating bounds, and/or overall power consumption is within constraints specified by the aerial vehicle 104 payload specification. In some embodiments, heat ejected from the laser may be used to warm the thermal chamber 126.
A processor 136 and addressable memory 138 may contain the sensor 102 firmware and low-level data processing functions. In some embodiments, the processor 136 and/or addressable memory 138 may be mounted remotely from the sensor head and connected wirelessly or by cables to the sensor 102. In some embodiments, multiple processors may be used. In some embodiments, a processor 140 of the aerial vehicle 104 may be used with the sensor 102.
In some embodiments, the GPS 108 may be mounted remotely from the GHGS 102 sensor head and connected wirelessly or by cables to the processor 136 for positional data acquisition. A wireless radio or cellular connection, such as a transceiver 142, may provide remote uni- or bi-directional data transfer between the airborne sensor system and an AV telemetry system 106, an AV control system 144, a cloud server/processor 146, and/or a ground control station 148.
The aerial vehicle 104 and/or the sensor 102 may communicate with the ground control station 148. The ground control station may receive gas measurements from the gas sensor 102, location and sensor data from the aerial vehicle 104, and/or provide instructions to the aerial vehicle 104 to follow a flight path. The ground control station may include a processor 150, a memory 152, a display 156, and a transceiver 158. In some embodiments, the collected atmospheric greenhouse gas concentration data may be shown on a map on the display 156. This map may be a satellite image, aerial image, two-dimensional color map, two-dimensional contour map, and/or three-dimensional topographical surface/mesh map.
The aerial vehicle 104, the sensor 102, and/or the ground control station 148 may communicate with a cloud server 146. The cloud server 146 may include a processor 160, a memory 162, and/or a display 164. The aerial vehicle 104, sensor 102, ground control station 148, and/or cloud server 146 may perform additional processing on the readings of the gas sensor 102 combined with data on the aerial vehicle 104 location, pressure, temperature, time, and the like. Any components of the gas sensor 102 may be part of the aerial vehicle 104. The gas sensor 104 may receive measurements, data, and/or power from any components of the aerial vehicle 104.
The GCS 148 processor 150, gas sensor 102 processor 136, and/or aerial vehicle 104 processor 140 may control the gas sensor 102, interface with UAV telemetry, interface with the GCS 148, and/or adjust the gas sensor operating parameters, e.g., the sensor sampling rate, based on information collected from UAV telemetry or the ground control station. For example, the processor 150, 136, 140 may increase a gas sensor sampling rate to adjust for increased UAV speed so as to maintain a constant spatial distribution of sampled locations. As another example, the processor 150, 136, 140 may increase sampling rate if the computer infers that the UAV is traversing part of the atmosphere with relatively high turbulence.
The method 200 may then include modifying a temperature of the received atmospheric gas to a set temperature via a thermal chamber (step 204). In some embodiments, the thermal chamber may increase the temperature of the atmospheric gas to the set temperature. In other embodiments, the thermal chamber may decrease the temperature of the atmospheric gas to the set temperature. In other embodiments, the thermal chamber may not be needed and the atmospheric gas may remain at an ambient temperature. The method 200 may then include modifying a pressure of the received atmospheric gas to a set pressure via a pressure regulator (step 206). In some embodiments, the pressure regulator may increase the pressure of the atmospheric gas to the set pressure. In other embodiments, the pressure regulator may decrease the pressure of the atmospheric gas to the set pressure. In some embodiments, the pressure regulator may not be needed and the pressure of the atmospheric gas may remain at an ambient pressure. Control of gas sample temperature and pressure may be needed to either condition the gas to an appropriate temperature for concentration measurement diagnostic (e.g., laser absorption spectroscopy), or to remove certain compounds (e.g., water vapor) from the sample.
The method 200 may then include providing the atmospheric gas to a gas sensor (step 208). In some embodiments, the atmospheric gas may be provided directly to the gas sensor without any gas handling system, temperature modification, and/or pressure modification. The gas sensor may include one or more optical cells. In one embodiment, the optical cells may be connected in series, such as shown in
The method 200 may then include detecting, by the one or more optical cells of the gas sensor, gas from one or more of: methane, carbon dioxide, water, hydrogen sulfide, ammonia, sulfur oxides, and nitrogen oxides (step 210). In some embodiments, the gas sensor may only detect one type of gas. In other embodiments, the gas sensor may detect two or more types of gas. In some embodiments, different optical cells may be used to detect different types of gas.
The method 200 may also include recording, by a processor having addressable memory, data from at least one of: an ambient temperature, an ambient pressure, aerial vehicle telemetry, and an aerial vehicle location. This recorded data may correspond to gas detected by the gas sensor (step 212). For example, the processor may record information on the UAV location as well as any detected gas at that location. This data may be later processed to determine gas levels across a range of locations.
The method 200 may then include generating, by the processor, an atmospheric greenhouse gas concentration data on a map based on the detected gas and recorded data (step 214). This map may be a satellite image, aerial image, two-dimensional color map, two-dimensional contour map, and/or three-dimensional topographical surface/mesh map. The recorded data and detected gas may be combined, stored, and further processed.
Information transferred via communications interface 714 may be in the form of signals such as electronic, electromagnetic, optical, or other signals capable of being received by communications interface 714, via a communication link 716 that carries signals and may be implemented using wire or cable, fiber optics, a phone line, a cellular/mobile phone link, a radio frequency (RF) link, and/or other communication channels. Computer program instructions representing the block diagram and/or flowcharts herein may be loaded onto a computer, programmable data processing apparatus, or processing devices to cause a series of operations performed thereon to produce a computer implemented process.
The computer system 700 described above services, but is not limited to, several purposes. The computer system 700 may control the gas sensor. The computer system 700 may interface with UAV telemetry. The computer system 700 may interface with a ground control station (GCS). In certain embodiments, the computer system 700 may adjust the gas sensor operating parameters, e.g., the sensor sampling rate, based on information collected from UAV telemetry or the ground control station. For example, the computer may increase a gas sensor sampling rate to adjust for increased UAV speed so as to maintain a constant spatial distribution of sampled locations. As another example, the computer may increase sampling rate if the computer infers that the UAV is traversing part of the atmosphere with relatively high turbulence.
Embodiments have been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments. Each block of such illustrations/diagrams, or combinations thereof, can be implemented by computer program instructions. The computer program instructions when provided to a processor produce a machine, such that the instructions, which execute via the processor, create means for implementing the functions/operations specified in the flowchart and/or block diagram. Each block in the flowchart/block diagrams may represent a hardware and/or software module or logic, implementing embodiments. In alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures, concurrently, etc.
Computer programs (i.e., computer control logic) are stored in main memory and/or secondary memory. Computer programs may also be received via a communications interface 712. Such computer programs, when executed, enable the computer system to perform the features of the embodiments as discussed herein. In particular, the computer programs, when executed, enable the processor and/or multi-core processor to perform the features of the computer system. Such computer programs represent controllers of the computer system.
The server 830 may be coupled via the bus 802 to a display 812 for displaying information to a computer user. An input device 814, including alphanumeric and other keys, is coupled to the bus 802 for communicating information and command selections to the processor 804. Another type or user input device comprises cursor control 816, such as a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to the processor 804 and for controlling cursor movement on the display 812.
According to one embodiment, the functions are performed by the processor 804 executing one or more sequences of one or more instructions contained in the main memory 806. Such instructions may be read into the main memory 806 from another computer-readable medium, such as the storage device 810. Execution of the sequences of instructions contained in the main memory 806 causes the processor 804 to perform the process steps described herein. One or more processors in a multi-processing arrangement may also be employed to execute the sequences of instructions contained in the main memory 806. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement the embodiments. Thus, embodiments are not limited to any specific combination of hardware circuitry and software.
The terms “computer program medium,” “computer usable medium,” “computer readable medium”, and “computer program product,” are used to generally refer to media such as main memory, secondary memory, removable storage drive, a hard disk installed in hard disk drive, and signals. These computer program products are means for providing software to the computer system. The computer readable medium allows the computer system to read data, instructions, messages or message packets, and other computer readable information from the computer readable medium. The computer readable medium, for example, may include non-volatile memory, such as a floppy disk, ROM, flash memory, disk drive memory, a CD-ROM, and other permanent storage. It is useful, for example, for transporting information, such as data and computer instructions, between computer systems. Furthermore, the computer readable medium may comprise computer readable information in a transitory state medium such as a network link and/or a network interface, including a wired network or a wireless network that allow a computer to read such computer readable information. Computer programs (also called computer control logic) are stored in main memory and/or secondary memory. Computer programs may also be received via a communications interface. Such computer programs, when executed, enable the computer system to perform the features of the embodiments as discussed herein. In particular, the computer programs, when executed, enable the processor multi-core processor to perform the features of the computer system. Accordingly, such computer programs represent controllers of the computer system.
Generally, the term “computer-readable medium” as used herein refers to any medium that participated in providing instructions to the processor 804 for execution. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, optical or magnetic disks, such as the storage device 810. Volatile media includes dynamic memory, such as the main memory 806. Transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise the bus 802. Transmission media can also take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications.
Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, a CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read.
Various forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to the processor 804 for execution. For example, the instructions may initially be carried on a magnetic disk of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to the server 830 can receive the data on the telephone line and use an infrared transmitter to convert the data to an infrared signal. An infrared detector coupled to the bus 802 can receive the data carried in the infrared signal and place the data on the bus 802. The bus 802 carries the data to the main memory 806, from which the processor 804 retrieves and executes the instructions. The instructions received from the main memory 806 may optionally be stored on the storage device 810 either before or after execution by the processor 804.
The server 830 also includes a communication interface 818 coupled to the bus 802. The communication interface 818 provides a two-way data communication coupling to a network link 820 that is connected to the world wide packet data communication network now commonly referred to as the Internet 828. The Internet 828 uses electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals on the network link 820 and through the communication interface 818, which carry the digital data to and from the server 830, are exemplary forms or carrier waves transporting the information.
In another embodiment of the server 830, interface 818 is connected to a network 822 via a communication link 820. For example, the communication interface 818 may be an integrated services digital network (ISDN) card or a modem to provide a data communication connection to a corresponding type of telephone line, which can comprise part of the network link 820. As another example, the communication interface 818 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such implementation, the communication interface 818 sends and receives electrical electromagnetic or optical signals that carry digital data streams representing various types of information.
The network link 820 typically provides data communication through one or more networks to other data devices. For example, the network link 820 may provide a connection through the local network 822 to a host computer 824 or to data equipment operated by an Internet Service Provider (ISP). The ISP in turn provides data communication services through the Internet 828. The local network 822 and the Internet 828 both use electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals on the network link 820 and through the communication interface 818, which carry the digital data to and from the server 830, are exemplary forms or carrier waves transporting the information.
The server 830 can send/receive messages and data, including e-mail, program code, through the network, the network link 820 and the communication interface 818. Further, the communication interface 818 can comprise a USB/Tuner and the network link 820 may be an antenna or cable for connecting the server 830 to a cable provider, satellite provider or other terrestrial transmission system for receiving messages, data and program code from another source.
The example versions of the embodiments described herein may be implemented as logical operations in a distributed processing system such as the system 800 including the servers 830. The logical operations of the embodiments may be implemented as a sequence of steps executing in the server 830, and as interconnected machine modules within the system 800. The implementation is a matter of choice and can depend on performance of the system 800 implementing the embodiments. As such, the logical operations constituting said example versions of the embodiments are referred to for e.g., as operations, steps or modules.
Similar to a server 830 described above, a client device 801 can include a processor, memory, storage device, display, input device and communication interface (e.g., e-mail interface) for connecting the client device to the Internet 828, the ISP, or LAN 822, for communication with the servers 830.
The system 800 can further include computers (e.g., personal computers, computing nodes) 805 operating in the same manner as client devices 801, wherein a user can utilize one or more computers 805 to manage data in the server 830.
Referring now to
It is contemplated that various combinations and/or sub-combinations of the specific features and aspects of the above embodiments may be made and still fall within the scope of the invention. Accordingly, it should be understood that various features and aspects of the disclosed embodiments may be combined with or substituted for one another in order to form varying modes of the disclosed invention. Further, it is intended that the scope of the present invention herein disclosed by way of examples should not be limited by the particular disclosed embodiments described above.
This application is a 35 U.S.C § 371 National Stage Entry of International Application No. PCT/US2019/057305, filed Oct. 22, 2019, which claims the priority benefit of U.S. Provisional Patent Application Ser. No. 62/748,647, filed Oct. 22, 2018, all of which are incorporated herein by reference in their entirety for all purposes.
Filing Document | Filing Date | Country | Kind |
---|---|---|---|
PCT/US2019/057305 | 10/22/2019 | WO |
Publishing Document | Publishing Date | Country | Kind |
---|---|---|---|
WO2020/086499 | 4/30/2020 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
3780566 | Smith et al. | Dec 1973 | A |
4135092 | Milly | Jan 1979 | A |
4233564 | Kerbel | Nov 1980 | A |
4507558 | Bonne | Mar 1985 | A |
4988833 | Lai | Jan 1991 | A |
5047639 | Wong | Sep 1991 | A |
5075619 | Said | Dec 1991 | A |
5173749 | Tell et al. | Dec 1992 | A |
5291265 | Kebabian | Mar 1994 | A |
5317156 | Cooper et al. | May 1994 | A |
5767780 | Smith et al. | Jun 1998 | A |
5822058 | Adler-Golden et al. | Oct 1998 | A |
6064488 | Brand et al. | May 2000 | A |
6295859 | Hayden et al. | Oct 2001 | B1 |
6356350 | Silver et al. | Mar 2002 | B1 |
6509566 | Wamsley et al. | Jan 2003 | B1 |
6549630 | Bobisuthi | Apr 2003 | B1 |
7162933 | Thompson | Jan 2007 | B2 |
7800751 | Silver et al. | Sep 2010 | B1 |
7833480 | Blazewicz et al. | Nov 2010 | B2 |
8060270 | Vian et al. | Nov 2011 | B2 |
8294899 | Wong | Oct 2012 | B2 |
8451120 | Johnson, Jr. et al. | May 2013 | B2 |
8730461 | Andreussi | May 2014 | B2 |
9183371 | Narendra et al. | Nov 2015 | B2 |
9183731 | Bokhary | Nov 2015 | B1 |
9235974 | Johnson, Jr. et al. | Jan 2016 | B2 |
9250175 | McManus | Feb 2016 | B1 |
9494511 | Wilkins | Nov 2016 | B2 |
9599529 | Steele et al. | Mar 2017 | B1 |
9599597 | Steele et al. | Mar 2017 | B1 |
10023311 | Lai et al. | Jul 2018 | B2 |
10023323 | Roberts et al. | Jul 2018 | B1 |
10031040 | Smith et al. | Jul 2018 | B1 |
10126200 | Steele et al. | Nov 2018 | B1 |
10268198 | Mantripragada et al. | Apr 2019 | B2 |
10325485 | Schuster | Jun 2019 | B1 |
10365646 | Farnsworth et al. | Jul 2019 | B1 |
10429546 | Ulmer | Oct 2019 | B1 |
10677771 | Dittberner et al. | Jun 2020 | B2 |
10753864 | Kasten et al. | Aug 2020 | B2 |
10816458 | Kasten et al. | Oct 2020 | B2 |
10830034 | Cooley et al. | Nov 2020 | B2 |
10962437 | Nottrott et al. | Mar 2021 | B1 |
11105784 | Kukreja et al. | Aug 2021 | B2 |
11112308 | Kreitinger et al. | Sep 2021 | B2 |
11275068 | Willett | Mar 2022 | B2 |
11299268 | Christensen et al. | Apr 2022 | B2 |
11519855 | Black et al. | Dec 2022 | B2 |
11557212 | Hong | Jan 2023 | B2 |
11614430 | Buckingham et al. | Mar 2023 | B2 |
11619562 | Leen et al. | Apr 2023 | B2 |
11710411 | Van Meeteren et al. | Jul 2023 | B2 |
11748866 | Vargas | Sep 2023 | B2 |
12015386 | Gatabi et al. | Jun 2024 | B2 |
20020005955 | Kramer et al. | Jan 2002 | A1 |
20030160174 | Grant et al. | Aug 2003 | A1 |
20030189711 | Orr et al. | Oct 2003 | A1 |
20030230716 | Russell et al. | Dec 2003 | A1 |
20040012787 | Galle et al. | Jan 2004 | A1 |
20040017762 | Sogawa et al. | Jan 2004 | A1 |
20040212804 | Neff et al. | Oct 2004 | A1 |
20060015290 | Warburton et al. | Jan 2006 | A1 |
20060044562 | Hagene et al. | Mar 2006 | A1 |
20060232772 | Silver | Oct 2006 | A1 |
20060234621 | Desrochers et al. | Oct 2006 | A1 |
20070137318 | Desrochers et al. | Jun 2007 | A1 |
20080169934 | Lang et al. | Jul 2008 | A1 |
20080243372 | Bodin et al. | Oct 2008 | A1 |
20090201507 | Kluczynski et al. | Aug 2009 | A1 |
20090263286 | Isomura et al. | Oct 2009 | A1 |
20090326792 | McGrath | Dec 2009 | A1 |
20100004798 | Bodin et al. | Jan 2010 | A1 |
20100131207 | Lippert et al. | May 2010 | A1 |
20100140478 | Wilson et al. | Jun 2010 | A1 |
20100147081 | Thomas | Jun 2010 | A1 |
20110035149 | McAndrew et al. | Feb 2011 | A1 |
20110074476 | Heer et al. | Mar 2011 | A1 |
20110150035 | Hanson et al. | Jun 2011 | A1 |
20110164251 | Richter | Jul 2011 | A1 |
20110213554 | Archibald et al. | Sep 2011 | A1 |
20110242659 | Eckles et al. | Oct 2011 | A1 |
20110257944 | Du et al. | Oct 2011 | A1 |
20120120397 | Furtaw et al. | May 2012 | A1 |
20130044314 | Koulikov et al. | Feb 2013 | A1 |
20130076900 | Mrozek et al. | Mar 2013 | A1 |
20130208262 | Andreussi | Aug 2013 | A1 |
20140172323 | Marino | Jun 2014 | A1 |
20140204382 | Christensen | Jul 2014 | A1 |
20140236390 | Mohamadi | Nov 2014 | A1 |
20140336957 | Hanson et al. | Nov 2014 | A1 |
20150072633 | Massarella et al. | Mar 2015 | A1 |
20150145954 | Pulleti et al. | May 2015 | A1 |
20150226575 | Rambo | Aug 2015 | A1 |
20150275114 | Tumiatti et al. | Oct 2015 | A1 |
20150295543 | Brown et al. | Oct 2015 | A1 |
20150316473 | Kester et al. | Nov 2015 | A1 |
20150323449 | Jones et al. | Nov 2015 | A1 |
20150336667 | Srivastava et al. | Nov 2015 | A1 |
20160018373 | Pagé et al. | Jan 2016 | A1 |
20160070265 | Liu et al. | Mar 2016 | A1 |
20160104250 | Allen et al. | Apr 2016 | A1 |
20160146696 | Steele et al. | May 2016 | A1 |
20160161456 | Risk et al. | Jun 2016 | A1 |
20160202225 | Feng et al. | Jul 2016 | A1 |
20160214715 | Meffert | Jul 2016 | A1 |
20160307447 | Johnson et al. | Oct 2016 | A1 |
20160357192 | McGrew | Dec 2016 | A1 |
20170003684 | Knudsen et al. | Jan 2017 | A1 |
20170057081 | Krohne et al. | Mar 2017 | A1 |
20170089829 | Bartholomew et al. | Mar 2017 | A1 |
20170093122 | Bean et al. | Mar 2017 | A1 |
20170097274 | Thorpe et al. | Apr 2017 | A1 |
20170115218 | Huang et al. | Apr 2017 | A1 |
20170134497 | Harter et al. | May 2017 | A1 |
20170158353 | Schmick | Jun 2017 | A1 |
20170199647 | Richman et al. | Jul 2017 | A1 |
20170206648 | Marra et al. | Jul 2017 | A1 |
20170235018 | Foster et al. | Aug 2017 | A1 |
20170259920 | Lai et al. | Sep 2017 | A1 |
20170290034 | Desai et al. | Oct 2017 | A1 |
20170307519 | Black et al. | Oct 2017 | A1 |
20170336281 | Waxman et al. | Nov 2017 | A1 |
20170339820 | Foster et al. | Nov 2017 | A1 |
20180023974 | Otani et al. | Jan 2018 | A1 |
20180024091 | Wang et al. | Jan 2018 | A1 |
20180045561 | Leen et al. | Feb 2018 | A1 |
20180045596 | Prasad et al. | Feb 2018 | A1 |
20180050798 | Kapuria | Feb 2018 | A1 |
20180059003 | Jourdainne et al. | Mar 2018 | A1 |
20180067066 | Giedd et al. | Mar 2018 | A1 |
20180109767 | Li et al. | Apr 2018 | A1 |
20180122246 | Clark | May 2018 | A1 |
20180127093 | Christensen et al. | May 2018 | A1 |
20180188129 | Choudhury et al. | Jul 2018 | A1 |
20180209902 | Myshak | Jul 2018 | A1 |
20180259955 | Noto | Sep 2018 | A1 |
20180266241 | Ferguson et al. | Sep 2018 | A1 |
20180266946 | Kotidis et al. | Sep 2018 | A1 |
20180284088 | Verbeck, IV | Oct 2018 | A1 |
20180292374 | Dittberner et al. | Oct 2018 | A1 |
20180321692 | Castillo-Effen et al. | Nov 2018 | A1 |
20180322699 | Gray et al. | Nov 2018 | A1 |
20190011920 | Heinonen et al. | Jan 2019 | A1 |
20190011935 | Ham et al. | Jan 2019 | A1 |
20190025199 | Koulikov | Jan 2019 | A1 |
20190033194 | DeFreez et al. | Jan 2019 | A1 |
20190049364 | Rubin | Feb 2019 | A1 |
20190077506 | Shaw et al. | Mar 2019 | A1 |
20190086202 | Guan et al. | Mar 2019 | A1 |
20190095687 | Shaw et al. | Mar 2019 | A1 |
20190154874 | Shams et al. | May 2019 | A1 |
20190178743 | McNeil | Jun 2019 | A1 |
20190195789 | Pan et al. | Jun 2019 | A1 |
20190204189 | Mohr, Jr. et al. | Jul 2019 | A1 |
20190212419 | Jeong et al. | Jul 2019 | A1 |
20190220019 | Tan et al. | Jul 2019 | A1 |
20190228573 | Sen et al. | Jul 2019 | A1 |
20190234868 | Tanomura et al. | Aug 2019 | A1 |
20190331652 | Ba et al. | Oct 2019 | A1 |
20200050189 | Gu et al. | Feb 2020 | A1 |
20200065433 | Duff et al. | Feb 2020 | A1 |
20200109976 | Ajay et al. | Apr 2020 | A1 |
20200135036 | Campbell | Apr 2020 | A1 |
20200182779 | Kasten et al. | Jun 2020 | A1 |
20200249092 | Podmore et al. | Aug 2020 | A1 |
20200373172 | Suzuki | Nov 2020 | A1 |
20200400635 | Potyrailo et al. | Dec 2020 | A1 |
20210017926 | Alkadi et al. | Jan 2021 | A1 |
20210037197 | Kester et al. | Feb 2021 | A1 |
20210055180 | Thorpe et al. | Feb 2021 | A1 |
20210109074 | Smith et al. | Apr 2021 | A1 |
20210140934 | Smith et al. | May 2021 | A1 |
20210190745 | Buckingham et al. | Jun 2021 | A1 |
20210190918 | Li et al. | Jun 2021 | A1 |
20210199565 | John et al. | Jul 2021 | A1 |
20210247369 | Nottrott et al. | Aug 2021 | A1 |
20210255158 | Smith et al. | Aug 2021 | A1 |
20210300591 | Tian | Sep 2021 | A1 |
20210321174 | Sun et al. | Oct 2021 | A1 |
20210364427 | Smith et al. | Nov 2021 | A1 |
20210382475 | Smith et al. | Dec 2021 | A1 |
20220082495 | Kreitinger et al. | Mar 2022 | A1 |
20220113290 | Smith et al. | Apr 2022 | A1 |
20220170810 | Miller, II et al. | Jun 2022 | A1 |
20220268952 | Liang et al. | Aug 2022 | A1 |
20220341806 | Miller et al. | Oct 2022 | A1 |
20220357231 | Nahata et al. | Nov 2022 | A1 |
20230194487 | Buckingham et al. | Jun 2023 | A1 |
20230213413 | Mohr, Jr. et al. | Jul 2023 | A1 |
20230274651 | McGuire et al. | Aug 2023 | A1 |
20230392498 | Srivastav et al. | Dec 2023 | A1 |
Number | Date | Country |
---|---|---|
3401499 | Nov 1999 | AU |
101470072 | Jul 2009 | CN |
104458588 | Mar 2015 | CN |
205749271 | Nov 2016 | CN |
106568516 | Apr 2017 | CN |
106769977 | May 2017 | CN |
107703075 | Feb 2018 | CN |
109780452 | May 2019 | CN |
211508182 | Sep 2020 | CN |
112213443 | Jan 2021 | CN |
29601472 | May 1996 | DE |
69333010 | Apr 2004 | DE |
102014013822 | Mar 2016 | DE |
0450809 | Oct 1991 | EP |
1371962 | Jul 2011 | EP |
3339855 | Jun 2018 | EP |
3047073 | Jul 2017 | FR |
3047073 | Aug 2019 | FR |
2538563 | Nov 2016 | GB |
H08247939 | Sep 1996 | JP |
200975823 | Apr 2009 | JP |
20170062813 | Jun 2017 | KR |
101770254 | Aug 2017 | KR |
522226 | Mar 2003 | TW |
1999054700 | Oct 1999 | WO |
02066950 | Aug 2002 | WO |
2008021311 | Feb 2008 | WO |
2015073687 | May 2015 | WO |
2016045791 | Mar 2016 | WO |
2016162673 | Oct 2016 | WO |
2017069979 | Apr 2017 | WO |
2018121478 | Jul 2018 | WO |
2018227153 | Dec 2018 | WO |
2019246280 | Dec 2019 | WO |
2020007684 | Jan 2020 | WO |
2020028353 | Feb 2020 | WO |
2020086499 | Apr 2020 | WO |
2020206006 | Oct 2020 | WO |
2020206008 | Oct 2020 | WO |
2020206020 | Oct 2020 | WO |
2021055902 | Mar 2021 | WO |
2021158916 | Aug 2021 | WO |
2022093864 | May 2022 | WO |
2022211837 | Oct 2022 | WO |
Entry |
---|
International Search Report and Written Opinion for PCT/US23/13893, mailed Jun. 30, 2023. |
Lilian Joly, The evolution of AMULSE (Atmospheric Measurements by Ultra-Light Spectrometer) and its interest in atmospheric applications. Results of the Atmospheric Profiles of Greenhouse gasEs (APOGEE) weather balloon release campaign for satellite retrieval validation, p. 1-28, Sep. 25, 2019, Atmospheric Measurement Techniques Discussion (Joly). |
International Search Report and Written Opinion for PCT/US2023/023933 mailed Sep. 26, 2023. |
IEEE Conference Paper, “Research of the high pressure jet performance of small size nozzle,” ISBN :978-1-5090-1087-5, Publication Date : Oct. 1, 2016, Conference dates Oct. 10, 2016 thru Oct. 12, 2016.[retrieved from the Internet] on Sep. 1, 2023 at 4:14pm. |
Clilverd, Mark A. et al., Energetic particle injection, acceleration, and loss during the geomagnetic disturbances which upset Galaxy 15, Journal of Geophysical Research, vol. 117, A12213, doi: 10.1029/2012JA018175, 2012, pp. 1-16 (Year:2012). |
Kem, Christoph et al., Spatial Distribution of Halogen Oxides in the Plume of Mount Pagan Volcano, Mariana Islands, Geophysical Research Letters 10.1029/2018GL079245, Sep. 27, 2018, pp. 9588-9596 (Year:2018). |
Liao, J. et al. Observations of Inorganic bromine(HOBr, BrO, and Br2) speciation at Barrow, Alaska in spring 2009, Journal of Geophysical Research, vol. 117, D00R16, doi:10.1029/2011JD016641, 2012, pp. 1-11 (Year:2012). |
Liu, Siwen et al., Development of a UAV-Based System to Monitor Air Quality over an Oil Field, Montana Technological University, Montana tech Library Digital Commons @ Montana Tech Graduate Theses & Non-Theses, Fall 2018, pp. 1-85 (Year:2018). |
Miyama, Toru et al., Estimating allowable carbon emission for CO2 concentration stabilization using a GCM-based Earth system model, Geophysical Research Letters, vol. 36,L19709, doi:10.1029/2009GL039678, 2009, pp. 0094-8276 (Year:2009). |
Oppenheimer Clive et al., Ultraviolet Sensing of Volcanic Sulfur Emissions, Elements (An Internatioknal Magazine of Mineralogy, Geochemistry, and Petrology), Apr. 2010, vol. 6, pp. 87-92 (Year: 2010). |
Parazoo, Nicholas C. et al., Interpreting seasonal changes in the carbon balance of southern Amazonia using measurements of XCO2 and chlorophyll fluorescence from Gosat, Geophysical Research Letters, vol. 40.2829-2833, doi: 10.1002/grl.50452, 2013 pp. 0 2829-2833 (Year:2013). |
Queiber, Manuel et al., A new frontier in CO2 flux measurements using a highly portable Dial laser system, Scientific Reports, DOI: 10.1038/srep33834 1, Sep. 22, 2016, pp. 1-13(Year:2016). |
Queiber, Manuel et al., Large-area quantification of subaerial CO2 anomalies with portable laser remote sensing and 2d tomography, The Leading Edge Mar. 2018, pp. 306-313 (Year:2018). |
International Search Report and Written Opinion for PCT/US22/38951, mailed Nov. 28, 2022. |
Kelly J F et al. “A capillary absorption spectrometer for stable carbon isotope ratio (C/C) analysis in very small samples”, Review of Scientific Instruments, American Institute of Physics, 2 Huntington Quadrangle, Melville, NY 11747, vol. 83, No. 2, Feb. 1, 2012 (Feb. 1, 2012), pp. 23101-23101, XP012161835, ISSN: 0034-6748, DOI: 10.1063/1.3680593. |
Krings et al., Atmos. Meas. Tech., 11, 721-739, Feb. 7, 2018. |
Khan et al., “Low Power Greenhouse Gas Sensors for Unmanned Aerial Vehicles,” Remote Sens. 2012, 4, 1355-1368; doi: 10.3390/rs4051355 [retrieved on Dec. 6, 2019]. Retrieved from the internet: <URL: https://www.cfa.harvard.edu/˜kangsun/files/Khan_Low%20Power%20Greenhouse%20Gas%20Sensors%20for%20Unmanned%20Aerial%20Vehicles.pdf> pp. 1-14. |
Joly et al. “Atmospheric Measurements by Ultra-Light Spectrometer (AMULSE) Dedicated to Vertical Profile in Situ Measurements of Carbon Dioxide (CO2) Under Weather Balloons: Instrumental Development and Field Application,” Sensors 2016, 16, 1609; doi: 10.3390/s 16101609 www.mdpi.com/journal/sensors, [retrieved on Dec. 6, 2019]. Retrieved from the internet: <URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5087397/pdf/sensors-16-01609.pdf> pp. 1-14. |
White et al. “Development of an Unmanned Aerial Vehicle for the Measurement of Turbulance in the Atmospheric Boundary Layer,” Published in Atmosphere v. 8, issue 10, 195, p. 1-25. [retrieved on Dec. 6, 2019]. Retrieved from the Internet: <URL: https://uknowledge.uky.edu/cgi/viewcontent.cgi?article=1033&context=me_facpub> pp. 1-27. |
International Search Report and Written opinion for PCT/US19/57305 mailed Jan. 2, 2020. |
“Safesite Multi-Threat Detection System”, Jul. 11, 2012 (Jul. 11, 2012), pp. 1-6, XP055245980. |
International Search Report and Written Opinion for PCT/US19/38011 mailed Sep. 9, 2019. |
International Search Report and Written Opinion for PCT/US19/38015, mailed Oct. 18, 2019. |
International Search Report and Written Opinion for PCT/US19/44119, mailed Oct. 17, 2019. |
International Search Report and Written Opinion for PCT/US20/26228 mailed Jul. 1, 2020. |
International Search Report and Written Opinion for PCT/US20/26232 mailed Jun. 26, 2020. |
International Search Report and Written Opinion for PCT/US20/26246 mailed Jun. 29, 2020. |
International Search Report and Written Opinion for PCT/US20/51696, mailed Feb. 3, 2021. |
International Search Report and Written Opinion for PCT/US2020/044978, mailed Oct. 26, 2020. |
International Search Report and Written Opinion for PCT/US2021/016821 mailed Apr. 26, 2021. |
International Search Report and Written Opinion for PCT/US2021/024177, mailed Jun. 23, 2021. |
International Search Report and Written Opinion for PCT/US2021/056708, mailed Jan. 27, 2022. |
International Search Report and Written Opinion for PCT/US21/42061, mailed Nov. 26, 2021. |
International Search Report and Written Opinion for PCT/US21/44532, mailed Jan. 11, 2022. |
International Search Report and Written Opinion for PCT/US21/56710, mailed Feb. 23, 2022. |
International Search Report and Written Opinion of PCT/US19/57305, mailed Jan. 2, 2020. |
International Search Report and Written Opinion of PCT/US20/54117, mailed Dec. 22, 2020. |
Joly, “Atmospheric Measurements by Ultra-Light Spectrometer (AMULSE) Dedicated to Vertical Profile In Situ Measurements of Carbon Dioxide (CO2) Under Weather Balloons: Instrumental Development and Field Application,” Sensors 2016, 16, 1609. |
Khan, “Low Power Greenhouse Gas Sensors for Unmanned Aerial Vehicles”, Remote Snse. 2012, 4, 1355-1368. |
Villa. “An Overview of Small Unmanned Aerial Vehicles for Air Quality Measurements: Present Applications and Future Prospectives”. Sensors. Web . Jul. 12, 2016. |
White, “Development of an Unmanned Aerial Vehicle for the Measurement of Turbulence in the Atmospheric Boundary Layer”, Atmosphere, v.8, issue 10, 195, pp. 1-25. |
International Search Report and Written Opinion for PCT/US23/23905 mailed Oct. 5, 2023. |
Development of a mobile tracer correlation method for assessment of air emissions from landfills and other area sources, Atmospheric Environment 102 (2015) 323-330. T.A. Foster-Wittig et al. 2015. |
Measurements of Methane Emissions from Landfills Using a Time Correlation Tracer Method Based on FTIR Absorption Spectroscopy, Environ. Sci. Technol. 2001, 35, 21-25, B. Galle et al. 2001. |
Uehara, K: “Dependence of harmonic signals 1-15 on sample-gas parameters in wavelength-modulation spectroscopy for precise absorption measurements”, Applied Physics B, Springer Berlin Heidelberg, Berlin/Heidelberg, vol. 67, Jan. 2, 1998, pp. 517-523, XP 007921671, ISSN:0946-2171, DOI: 10.1007/S003400050537. |
Field Trial of Methane Emission Quantification Technologies, Society of Petroleum Engineers, SPE-201537-MS, Allen et al., Oct. 2020. |
Feng, Lingbing, Nowak, Gen, O'Neill, T.J., Welsh, A.H.“Cutoff; A spatio-temporal imputation method.” Journal of Hydrology 519 (2014) : 3591-3605 (Year:2014). |
Cabreira et al. “Survey on Coverage Path Planning with Unmanned Aerial Vehicles”, published: Drones, published: Jan. 2019, pp. 1-38, year 2019. |
Tao Lei et al:“Low-power, open-path mobile sensing platform for high-resolution measurements of greenhouse gases and air pollutants”, Applied Physics B, Springer Berlin Heidelberg, Berlin/Heidelberg, vol. 119, No. 1, Mar. 10, 2015 (Mar. 10, 2015), pp. 153.-164, XP035445836, ISSN: 0946-2171, DOI: 10.1007/S00340-015-6069-1 [retrieved on Mar. 10, 2015]. |
Tarsitano C G et al: Multilaser Herriott Cell for Planetary Tunable Laser Spectrometers', Applied Optics , Optical Society of America, Washington, DC, US, vol. 46, No. 28, Oct. 1, 2007 (Oct. 1, 2007), pp. 6923-6935, XP001508502, ISSN:0003-6935, DOI: 10.1364/AO.46.006923. |
Adame J A et al: “Application of cluster analysis to surface ozone, NOand SOdaily patterns in an industrial area in Central-Southern Spain measured with a DOAS system”, Science of The Total Environment, Elsevier, Amsterdam, NL, vol. 429, Apr. 11, 2012 (Apr. 11, 2012), pp. 281-291, XP028491183, ISSN: 0048-9697, DOI: 10.1016/J.SCITOTENV.2012.04.032. |
Coombes et al, “Optimal Polygon Decomposition for UAV Survey Coverage Path Planning in Wind”, published: Jul. 2018, publisher: ‘Sensors’ (Year:2018). |
He et al. “Static Targets' Track Path for UAVs Meeting the Revisit Interval Requirement”, published :2013, publisher : IEEE (Year:2013). |
Day, S., and et al. “Characterisation of regional fluxes of methane in the Surat Basin, Queensland, Phase 1: A review and analysis of literature on methane detection and flux determination.” (2013) (Year: 2013). |
Number | Date | Country | |
---|---|---|---|
20210382475 A1 | Dec 2021 | US |
Number | Date | Country | |
---|---|---|---|
62748647 | Oct 2018 | US |