• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    prediction of potential for high intensity weather. methods and apparatus, including computer program products, are described for predicting the potential for high intensity weathering. data associated with lightning activity is received by a computing device. a location, a speed of movement, a direction of movement, and a lightning rate of one or more lightning activity cells are determined by the computing device based on the received data. the lightning rate is compared, by the computing device, with a threshold lightning rate. one or more geographical areas at risk are determined by the computing device based on the location, speed of movement and direction of movement of the one or more lightning activity cells. an alert is issued by the computing device to one or more remote devices monitoring geographic areas when lightning strikes exceed a threshold lightning rate value.
    公开号:BR112014000092B1
    申请号:R112014000092-1
    申请日:2012-06-18
    公开日:2021-07-20
    发明作者:Robert S. Marshall；Christopher Dale Sloop；Benjamin E. Beroukhim；Chonglin Liu；Stan Heckman；Mark A. Hoekzema
    申请人:Earth Networks, Inc；
    IPC主号:
    专利说明:

    Field of Invention
    [0001] The subject matter of this application generally refers to methods and apparatus, including computer program products, for predicting high intensity weathering potential. Background of the Invention
    [0002] Lightning includes electrical discharges within a cloud, discharges within clouds (IC), and cloud-to-ground discharges (CG). Lightning occurs when electric fields within a cloud intensify particles of opposite polarity grouped in different regions within the cloud. Lightning begins with an initial electrical break (ie, a pulse) followed by conductive channels from which a series of channel branches develop into a cloud forming a comprehensive branch channel structure. For lightning IC, the channel structure remains within the cloud. A CG discharge occurs when one or more branches extend from a cloud to the ground.
    [0003] An increase in lightning activity usually precedes even more severe weather phenomena such as very strong storms, tornadoes, hail, damaging gust winds and potentially deadly lightning from the cloud to the ground. Furthermore, such lightning activity often occurs in localized clusters, also called cells. Lightning cells exhibit certain characteristics (eg, lightning rate, IC/CG ratio) that are indicative of the potential for high intensity weathering. Furthermore, using detection methods and systems, data associated with lightning cells can be obtained and analyzed to determine the location and movement of specific cells across a geographic region.
    [0004] Accurate and efficient detection of early lightning activity, such as weaker initial IC discharges, is crucial for early prediction of high intensity weather phenomena. Integrated IC Lightning and CG Lightning Detection provides highly advanced prediction capabilities to characterize high intensity storm precursors, improving wait times and comprehensive weather management planning. Various lightning detection systems and methods have been developed, individually striving to determine the location, motion, frequency and intensity of lightning activity with better accuracy. Examples of such systems include the U.S. Precision Lightining Network (USPLN), the National Lighting Detection Network (NLDN) and the WeatherBug Total Lighting Network (WTLN).
    [0005] Previous weather warning systems relied on human intervention to determine the extent of high intensity weather activity and to initiate notification of remote devices configured to receive alerts (for example, through the use of a display where a person evaluates weather data and selects devices to receive alerts). To increase the speed and accuracy of weather warning systems, it is desirable to eliminate the need for manual processing of high intensity weather data and issuing warning messages. Invention Summary
    [0006] An important goal associated with accurate, early detection of high intensity weather activity is to timely issue automated warnings, or alerts, to entities that may be affected by high intensity weather. More accurate detection of atmospheric conditions that potentially result in high intensity weather, such as lightning rates, leads to a more comprehensive understanding of the risk of hazardous weather activity in specific geographic areas. Knowing the potential for bad weather before a serious storm hits a specific region allows for more waiting time to alert people or entities located close to risk areas, resulting in greater security for these people and entities.
    [0007] In an overview, the techniques described here are related to the prediction of high intensity weathering potential. The techniques advantageously provide automated high-intensity weather prediction for timely issuance of reliable warnings of high-intensity weather. The techniques use accurate detection of lightning events such as CG and IC lightning flashes to identify the boundaries of lightning cells. The techniques also consider differences in geographic location and weather conditions to produce more accurate forecasts of the course and weather of high intensity weather. The techniques also provide automatic identification of remote devices configured to receive alerts for a specific geographic area and automatic transmission of relevant alerts to remote devices.
    [0008] The invention, in one aspect, presents a computer-implemented method for predicting high intensity weather potential. Data associated with lightning activity is received by a computing device. A location, a speed of movement, a direction of movement, and a lightning rate of one or more lightning activity cells are determined by the computing device based on the received data. The determined lightning rate is compared by the computing device with a threshold lightning rate. One or more geographic areas at risk are determined by the computing device based on the location, speed of movement and direction of movement of one or more lightning activity cells. An alert is issued by the computing device to one or more remote devices monitoring geographic areas at risk when the lightning rate exceeds a threshold lightning rate value.
    [0009] The invention, in one aspect, presents a computer-implemented system to predict the potential of high intensity weather. The system includes a computing device configured to receive data associated with lightning activity. The computing device is further configured to determine a location, a speed of movement, a direction of movement, and a lightning rate of one or more lightning activity cells based on the received data. The computing device is further configured to compare the determined flash rate with a threshold flash rate. The computing device is further configured to determine one or more geographic areas at risk based on the location, speed of movement and direction of movement of one or more lightning activity cells. The computing device is further configured to issue an alert to one or more remote devices monitoring geographic areas at risk when the lightning rate exceeds a threshold lightning rate value.
    [0010] The invention, in another aspect, features a computer program product embodied tangibly in a computer readable storage device to predict the potential for high intensity weathering. The computer program product includes operable instructions to cause a data processing apparatus to receive the data associated with lightning activity, and determine a location, a speed of movement, a direction of movement and a lightning rate of one or more lightning activity cells based on the received data. The computer program product further includes operable instructions to cause the data processing apparatus to compare the determined lightning rate with a threshold lightning rate, and determine one or more geographical areas at risk based on location, speed of movement and in the direction of movement of the one or more lightning activity cells. The computer program product further includes operable instructions to cause the data processing apparatus to issue an alert to one or more remote devices monitoring geographical areas at risk when the lightning rate exceeds a threshold lightning rate value.
    [0011] The invention, in another aspect, presents a computer-implemented system to predict the potential for high intensity weather. The system includes means for receiving data associated with lightning activity. The system further includes means for determining a location, a speed of movement, a direction of movement, and a lightning rate of one or more lightning activity cells based on the received data. The system further includes means for comparing the determined flash rate with a threshold flash rate. The system further includes means for determining one or more geographical areas at risk based on the location, speed of movement and direction of movement of the one or more lightning activity cells. The system further includes means to issue an alert to one or more remote devices monitoring the geographical areas at risk when the lightning rate exceeds a threshold lightning rate value.
    [0012] In some embodiments, any of the above aspects may include one or more of the following features. In some modalities, one or more polygons corresponding to geographic areas at risk are generated. In some modalities, the generated polygons are placed on a map in which at least one of the geographical areas at risk is located. In some modalities, generated polygons are transmitted to one or more remote devices as part of the alert.
    [0013] In some embodiments, the threshold lightning rate is determined based on historical data associated with at least one of (i) the location of one or more lightning activity cells or (ii) the period of the year. In some embodiments, the lightning rate is determined based on a number of lightning events per minute associated with one or more lightning activity cells. In some modalities, lightning events include cloud-to-ground lightning, lightning within the clouds, or both. In some embodiments, lightning within the clouds includes aerial discharges, flashes within the clouds, flashes from the cloud to the ionosphere, or any combination thereof.
    [0014] In some embodiments, the data received includes cloud-to-ground lightning, lightning within clouds, vertical movement, condensation, moisture, or any combination thereof. In some embodiments, data associated with lightning activity is received from one or more geographically dispersed sensing devices. In some embodiments, one or more lightning activity cells are determined according to the density of lightning activity in the received data.
    [0015] In some modalities, the alert is issued before the storm of great intensity has reached the location of at least one of the geographical areas at risk. In some modes, a weather type is determined based on the lightning rate. In some modes, a probability of high intensity weather is determined based on the lightning rate. In some embodiments, remote devices are personal computing devices. In some embodiments, remote devices are horns, sirens, lights, or any combination thereof. In some embodiments, a change in lightning rate of one or more lightning activity cells is determined, and an alert is issued to one or more remote devices when the change in lightning rate exceeds a predetermined value.
    [0016] Other aspects and advantages of the invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, illustrating, by way of example only, the principles of the invention. Brief Description of Drawings
    [0017] The advantages of the invention described above, together with additional advantages, may be better understood by referring to the following description taken in conjunction with the accompanying drawings. The drawings are not necessarily to scale, with emphasis generally being placed on illustrating the principles of the invention.
    [0018] Figure 1 is a block diagram of a system to predict the potential for high intensity weather.
    [0019] Figure 2 is a flow diagram of a method to predict the potential for high intensity weather using the system.
    [0020] Figure 3 is a diagram illustrating the identification of a lightning cell via system 100 based on the lightning activity data.
    [0021] Figure 4 is a graph illustrating the total lightning rate of an individual lightning cell compared to a threshold lightning rate over a specific time period.
    [0022] Figure 5 is a diagram illustrating the identification by the system of a geographic area at risk of high intensity weather based on the lightning activity data.
    [0023] Figure 1 is a block diagram of a system 100 for predicting the potential for high intensity weather. System 100 includes a data collection module 102, a data analysis module 104, an alert generation module 106, a graphics processing module 108, and a data storage module 110. In some embodiments, the components (for example, 100, 102, 104, 106, 108, and 110) of system 100 reside in the same physical location or may be dispersed to different physical locations. In some embodiments, the components of system 100 are located on the same physical device (e.g., a server computing device), or are distributed across different physical devices. The components of system 100 communicate, for example, via a communication network (eg, WAN, LAN, WLAN).
    [0024] Figure 2 is a flow diagram of a method 200 for predicting the potential for high intensity weather using system 100. Data collection module 102 receives (202) the data associated with lightning activity. The data analysis module 104 determines (204) a location, a speed of movement, a direction of movement and a lightning rate of one or more lightning activity cells based on the data received by the data collection module 102. Data analysis module 104 compares (206) the determined flash rate to a threshold flash rate. The alert generation module 106 determines (208) one or more geographical areas at risk based on the location, the speed of movement, the direction of movement of the one or more lightning activity cells. The alert generation module 106 issues (210) an alert to one or more remote devices monitoring the geographical areas at risk when the determined lightning rate exceeds a value of the threshold lightning rate.
    [0025] Data collection module 102 provides an interface between external data sources (not shown) and data analysis module 104 of system 100. Data collection module 102 receives the data associated with lightning activity to from various external data collection and/or monitoring systems. For example, data collection module 102 receives data from a lightning detection system comprising a plurality of geographically dispersed weather sensors (e.g., the WeatherBug Total Lightning Network (WTLN)). In this example, the data collected by the weather sensors includes analog radio frequency (RF) energy (eg, pulses or flashes) at different frequencies as emitted by a lightning strike. Additional detail regarding lightning activity detection and lightning activity data collection is found in US Patent Application Serial No. 12/542,404 entitled "Method and Apparatus for Detecting Lightning Activity", which is incorporated herein fully. Other sources of lightning activity information include, but are not limited to, government agencies and private third-party companies. The data collection module 102 communicates with various systems and external data sources through standard communication networks and methods.
    [0026] The data collection module 102 also consolidates the lightning activity data received from a plurality of external data sources into a format conducive to processing by the data analysis module 104. For example, each data source to which the data collection module 102 is connected may transmit the data using a different syntax and/or different data structure. The data collection module 102 analyzes the incoming data according to an understanding of the data source and re-formats the data so that it conforms to an acceptable syntax or structure for the data analysis module 104. In some embodiments, external data sources transmit the lightning activity data in a standard format (eg XML) to reduce the processing required by the data collection module 102. The data collection module 102 communicates with the data collection module 102 data storage 110 for saving and retrieving the data received from external sources in preparation for transmitting the data to the data analysis module 104. When the data has been received, the data collection module 102 transmits the data to the data analysis module 104. In some embodiments, data collection module 102 transmits a notification to data analysis module 104 that data has been stored in the data analysis module. data storage 110 and are ready for processing by data analysis module 104. The notification includes a reference indicator (e.g., a database address) of the data storage location within data storage module 110.
    [0027] The data analysis module 104 processes the lightning activity data received by the data collection module 102 and/or stored in the data storage module 110 to determine the existence of high intensity weather hazard for one or more geographic regions.
    [0028] The data analysis module 104 determines the risk of high intensity weather for one or more geographic regions by monitoring the location, speed of movement, direction of movement and lightning rate of one or more lightning activity cells with based on the data received by system 100. A lightning cell is a cluster of flashes with a boundary like a polygon determined by the flash density value for a given period of time. Data analysis module 104 groups the flash data collected into lightning cells, and data analysis module 104 correlates the cell polygons over a period of time to determine the direction of movement (i.e., path) of the cells. . In addition, the data analysis module 104 counts the number of flashes in a specific lightning cell to determine a lightning flash rate (eg, flashes per minute). The data analysis module 104 further calculates the movement speed and location of the lightning cells.
    [0029] Figure 3 is a diagram illustrating the identification of a lightning cell 302 via system 100 based on the lightning activity data. The data analysis module 104 receives the lightning flash data from the data collection module 102 and positions each lightning flash (e.g., lightning flashes 304) according to its geographic location. Data analysis module 104 then analyzes the relative position of the lightning flashes to determine the potential boundaries or contours of specific lightning cells (eg, cell 302).
    [0030] In some embodiments, the data analysis module 104 performs a series of grid processes to determine the location and contours of a lightning cell 302. The data analysis module 104 uses the collected lightning flash data for a specific period of time (eg one minute) and puts the lightning flashes (eg 304 flashes) on a map. Data analysis module 104 then overlays a thick grid on the map to quickly locate areas of interest for further analysis. The data analysis module 104 identifies the grid sectors that contain a high percentage or density of lightning flashes and overlays the fine grid on the identified sectors. Data analysis module 104 employs density functions in the fine grid sectors to locate the closed contours associated with lightning cell 302. Data analysis module 104 generates a convex polygon (eg, convex polygon 306) from of each of the closed contours.
    [0031] The data analysis module 104 repeats this gridded process at the end of a specified period of time (eg, one minute) to monitor the changes in motion, direction, and lightning flash rate of the lightning cell 302. In most cases, the polymer 306 generated by the data analysis module 104 for a specific lightning cell at each time slot is similar to the polygon previously generated for that cell, so the data analysis module 104 correlates accordingly. efficiently and quickly the two polygons. However, in the case of a sharp increase in the lightning flash rate, lightning cell fusion or lightning cell division means, the correlation of subsequent polygons for a specific cell is not obvious. The data analysis module 104 links the individual lightning cell polygons based on the dynamically changing data to produce a path 308 of the moving lightning cell. For example, when a lightning cell is reassembled after fading, based on the cell trajectory and the time-distance of two polygons, the data analysis module 104 maintains a continuous cell trajectory 308.
    [0032] The data analysis module 104 also compares the lightning flash rate calculated from the received lightning activity data with a lightning threshold rate. Data analysis module 104 also monitors rate changes associated with the flash flash rate of the identified flash cells. By monitoring flash rates and rate changes, high intensity storm cells (and cells that will potentially become high intensity) are identified and monitored. The lightning threshold rate used by data analysis module 104 is relevant to the probability that the monitored lightning cell is associated with high intensity weather and can be used by system 100 to determine when to issue an alert. For example, if the lightning rate exceeds the threshold rate, the possibility that the lightning cell is associated with high intensity weather is sufficient to authorize an alert to be issued.
    [0033] Figure 4 is a graph 400 illustrating the total lightning rate 402 of an individual lightning cell (e.g. cell 302 of Figure 3) compared to a lightning threshold rate 404 over a specific time period . Data analysis module 104 determines the total lightning rate 402 of a lightning cell by analyzing the number of lightning events (eg, flashes) in a specific time interval (eg, one minute). In some modalities, lightning events include both CG lightning and IC lightning. In some embodiments, data analysis method 104 evaluates the collected lightning data to identify various types of IC lightning, including aerial discharges, in-cloud flashes, and/or cloud-to-ionosphere flashes.
    [0034] Through the action of continuously calculating the total lightning rate of a specific lightning cell at regular time intervals, the data analysis module 104 detects the changes in the total lightning rate between the time intervals. Based on this approach, the data analysis module 104 determines whether changes in lightning rate have occurred that may be indicative of high intensity weather in general or a specific type of high intensity weather (eg precipitation, wind events ). For example, the total lightning rate 402 in Figure 4 begins to increase sharply starting at time = t(0) and peaking at time = t(p), with the high intensity weather associated with the lightning cell occurring in the time = t(s). The data analysis module 104 determines whether the total lightning rate 402 meets the threshold lightning rate 304 at time = t(i) and transmits information to the alert generation module 106. In addition, the data analysis module 104 compares rate changes between time = t(0), time = t(p) and time = t(s) with a database of historical lightning rate activity to identify similarities or patterns in rate change of lightning. As an example, the specific rate changes illustrated in Figure 4 can occur multiple times during the duration of a lightning cell, and the high intensity weather resulting in time = t(s) can be the beginning of an intense hailstorm . As a result, the data analysis module 104 instructs the alert generation module 106 to provide a more detailed alert message in that additional information.
    [0035] The data analysis module 104 also uses the historical data to establish a threshold rate for a specific lightning cell. For example, the data analysis module 104 determines the threshold flash rate using a best-fit analysis method based on analysis of actual weather data. In some modalities, historical data is associated with a specific time of year and/or a specific geographic region. Based on a correlation between the historical period of the year and the period of the year during which the current lightning cell is being monitored, the data analysis module 104 adjusts the threshold rate to account for similarities or differences between the two data points. For example, if a lightning cell is being monitored during a period of the year that has traditionally had low occurrence of high intensity weather, the data analysis module 104 shifts the threshold rate up to require a total lightning rate higher before an alert is issued by system 100. Conversely, if a lightning cell is being monitored during a period of the year that is prone to increased high intensity weather activity, data analysis module 104 moves the threshold rate down to require a lower total lightning rate before issuing an alert.
    [0036] When the data analysis module 104 determines that the total lightning rate of the currently monitored lightning cell (for example, cell 302 of Figure 3) has exceeded the threshold lightning rate (i.e., is associated with a potential sufficient for high intensity weather), the data analysis module 104 transmits the data to the alert generation module 106. The alert generation module 106 uses the analyzed characteristics of the lightning cell to automatically determine the geographic areas that can be impacted by the lightning cell as it moves and changes in size and/or intensity.
    [0037] Figure 5 is a diagram 500 illustrating the identification by system 100 of a geographical area at risk 502 of high intensity weather based on the lightning activity data. To issue an alert that reaches people and/or entities that may be directly affected by the high intensity weather, or that may have an interest in the affected area, the alert generation module 106 determines one or more geographical areas at risk 502 based on the location, speed of movement and direction of movement of the lightning cell 302. In some embodiments, the alert generating module 106 determines a warning area that corresponds to the current location and expected trajectory of the cell over a period of time. to come. For example, the alert generation module 106 generates a polygon 502 that covers the range of distances and directions that a lightning cell could travel in a specific period of time (eg 45 minutes) by evaluating the speed of movement and the cell movement direction shown at the time the data analysis module 104 determines that the total flash rate of cell 302 has exceeded the threshold flash rate.
    [0038] After receiving notification from the data analysis module 104 and determining one or more areas at risk, the alert generation module 106 automatically identifies a set of one or more remote devices that are monitoring the areas at risk and automatically broadcasts an alert to remote devices. Remote devices can include computer-based devices such as mobile phones and global positioning system (GPS) hardware. Remote devices can also include other types of warning systems, such as lights, sirens, and horns that are configured to connect to a communication network. In some embodiments, data storage device 110 includes information relating to the identification of remote devices (e.g., IP address, telephone number, email address), and alert generation module 108 uses the identification information to prepare an alert for each remote device. Data storage device 110 also includes information mapping the identification of a remote device to a specific geographic area or areas that the remote device is monitoring (e.g., zip code, county name, street address). Alert generation module 106 utilizes any standard communication protocol or technique, such as packet-based delivery (eg text messaging, XML, email), circuit-based delivery (eg radio calling, phone exchange). voice messages), and the like. For example, a user can subscribe to receive alerts for a specific postal code on their mobile phone. System 100 stores the user's telephone number in data storage module 110. When alert generation module 106 identifies a geographic location that is at risk of high intensity weather and all or part of the identified location is comprised within the code user-presented, the alert generation module 108 issues an alert (e.g., a text message, a voice message) addressed to the telephone number of the user's mobile phone. In this modality, the user's mobile phone need not be located in the same geographic area as identified by the alert generation module 106 as “at risk”.
    [0039] In some modalities, the alert is additionally optimized through the inclusion of a graphical representation of the geographic area that is under threat of high intensity weather. The graphical representation provides an additional piece of information that can be easily recognized by the recipient of the alert. For example, the alert generation module 106 overlays a polygon 502 outlining the geographical area at risk associated with a specific lightning cell 302 on a map. Alert generation module 106 uses a graphical processing module 108 to generate a visual representation of the polygon 502 representing the area at risk as placed on the map. In some embodiments, the graphics processing module 108 is a separate graphics processing unit (GPU) (e.g., a graphics card) or a software module configured to produce graphic drawings and drawings based on the lightning activity data.
    [0040] The techniques described above can be implemented in digital and/or analog electronic circuits, or in hardware, firmware, computer software or combinations thereof. The implementation can be as a computer program product, that is, a computer program tangibly embedded in a machine-readable storage device, for execution by, or for controlling the operation of a data processing apparatus, by example, a programmable processor, a computer, and/or multiple computers. A computer program can be written in any form of programming or computer language, including source code, compiled code, interpreted code and/or machine code, and the computer program can be employed in any form, including as a standalone program or as a subroutine, element, or other unit suitable for use in a computing environment. A computer program can be employed to run on one computer or on multiple computers at one or more locations.
    [0041] The method steps can be performed by one or more processors executing a computer program to perform the functions of the invention by operating on input data and/or generating output data. The method steps can be performed using, and an apparatus can be implemented as a special-purpose logic circuit, for example, an FPGA (field programmable gate array), a FPAA (field programmable analog array), a CPLD ( complex programmable logic device), a PSoC (Chip Programmable System), ASIP (application specific instruction set processor), or an ASIC (application specific integrated circuit), or the like. Subroutines can refer to portions of the stored computer program and/or the processor, and/or special circuits that implement one or more functions.
    [0042] Processors suitable for executing a computer program include, for example, general purpose microprocessors as well as special purpose microprocessors, and any one or more processors of any type of digital or analog computer. Generally, a processor receives instructions and data from read-only memory or random access memory, or both. The essential elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and/or data. Memory devices, such as a cache, can be used to temporarily store data. Memory devices can also be used for long-term data storage. Generally, a computer also includes, or is operatively coupled to receive data from, or transfer the data to, or both, one or more mass storage devices for storing data, for example, magnetic disks, optical magnets, or optical discs. A computer may also be operatively coupled to a communication network to receive instructions and/or data from the network and/or to transfer instructions and/or data to the network. Computer readable storage media suitable for incorporating computer program instructions and data include all forms of volatile and non-volatile memory, including, as an example, semiconductor memory devices, e.g., DRAM, SRAM, EPROM, EEPROM, and flash memory devices; magnetic disks, for example internal hard disks or removable disks; magneto-optical discs; and optical discs, for example, CD, DVD, HD-DVD, and Blu-ray discs. Processor and memory can be supplemented by and/or incorporated into special purpose logic circuits.
    [0043] To provide interaction with a user, the techniques described above can be implemented on a computer in communication with a display device, for example, a CRT (cathode ray tube), plasma monitor, or LCD monitor (cathode ray tube) liquid crystal) to display information to the user and a keyboard and pointing device, for example, a mouse, trackball, touchpad, or motion sensor, through which the user can provide input to the computer (eg, interact with a UI element). Other types of devices can be used to provide interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, for example, visual feedback, auditory feedback, or tactile feedback; and input from the user can be received from any form, including acoustic, speech, and/or tactile input.
    [0044] The techniques described above can be implemented in a distributed computing system that includes a back-end component. The back-end component, for example, can be a data server, a middleware component, and/or an application server. The techniques described above can be implemented on a distributed computing system that includes a front-end component. The front-end component can, for example, be a client component that has a graphical user interface, a web browser through which a user can interact with an exemplary implementation, and/or other graphical user interfaces for a device of transmission. The techniques described above can be implemented in a distributed computing system that includes any combination of such back-end, middleware or front-end components.
    [0045] The components of the computing system can be interconnected through the transmission medium, which can include any form or means of data communication, digital or analog (for example, a communication network). The transmission medium may include one or more packet-based networks and/or one or more circuit-based networks in any configuration. Packet-based networks can include, for example, the Internet, a carrier Internet protocol (IP) network (eg, local area network (LAN), remote area network (WAN), campus area network ( CAN), metropolitan area network (MAN), native area network (HAN)), a private IP network, an IP private switchboard (IPBX), a wireless network (eg, radio access network (RAN) ), Bluetooth, Wi-Fi, WiMAX, general packet radio service network (GPRS), HiperLAN), and/or other packet-based networks. Circuit-based networks can include, for example, the public switched telephone network (PSTN), legacy private telephone exchange (PBX), a wireless network (eg RAN, code division multiple access network (CDMA), time division multiple access network (TDMA), global system network for mobile communication (GSM)), and/or other circuit-based networks.
    [0046] The transfer of information through the transmission medium can be based on one or more communication protocols. Communication protocols can include, for example, Ethernet protocol, Internet Protocol (IP), Voice over IP (VOIP), a Peer-to-peer Protocol (P2P), Hypertext Transfer Protocol (HTTP), Session Initiation Protocol (SIP ), H.323, Media Gateway Control Protocol (MGCP), Signaling System No. 7 (SS7), a Global System Protocol for Mobile Communications (GSM), a Push to Talk (PTT) protocol, a PTT over Cellular (POC) protocol, and/or other communication protocols.
    [0047] Computing system devices may include, for example, a computer, a computer with a navigation device, a telephone, an IP phone, a mobile device (e.g., cell phone, personal digital assistant device (PDA) ), laptop computer, e-mail device), and/or other communication devices. The navigation device includes, for example, a computer (eg desktop computer, laptop computer) with a World Wide Web browser (eg Microsoft® Internet Explorer® available through Microsoft Corporation, Mozilla® Firefox, available through from Mozilla Corporation). The mobile computing device includes, for example, a Blackberry®. IP phones include, for example, a Cisco® Unified IP Phone 7985G available from Cisco Systems, Inc, and/or a Cisco® Unified Wireless Phone 7920, available from Cisco Systems, Inc.
    [0048] Understand, include, and/or plural forms of each of them are unlimited and include related parts and may include additional parts that are not listed. And/or is unlimited and includes one or more of the listed parts and combinations of the listed parts.
    [0049] Those skilled in the art will realize that the invention can be incorporated in other specific forms without departing from its essence or its essential characteristics. The foregoing embodiments, therefore, are to be considered in all respects illustrative rather than limiting the invention described herein.
    权利要求:
    Claims (20)
    [0001]
    1. A computer-implemented method of predicting the potential for high intensity weather, the method comprising: receiving, by a computing device, data associated with lightning activity, wherein the data includes lightning flash data collected during an interval of specific time; characterized by the fact that it further comprises identifying, by the computing device, one or more lightning activity cells based on the lightning flash data, the identification comprising: positioning each lightning flash on a map according to its geographic location; overlay a first grid on the map and identify sectors of the first grid with a high density of lightning flashes; overlay a second grid on identified sectors of the map to locate closed contours associated with a lightning cell; egenerating a convex polygon from each of the closed contours; determining, by the computing device, a speed of movement, a direction of movement, and a lightning rate of the one or more lightning activity cells based on the received data; compare, by the computing device, the determined lightning rate with a threshold lightning rate; determine, by the computing device, one or more geographical areas at risk based on the location, speed of movement, and direction of movement of a or more lightning activity cells; and issue, by the computing device, an alert to one or more remote devices monitoring the geographical areas at risk when the illumination rate exceeds a value of the threshold rate of lightning.
    [0002]
    2. Method according to claim 1, characterized in that it additionally comprises generating one or more polygons corresponding to the geographical areas at risk.
    [0003]
    3. Method according to claim 2, characterized in that it further comprises positioning the generated polygons on a map in which at least one of the geographical areas at risk is located.
    [0004]
    4. Method according to claim 2, characterized in that it further comprises transmitting the generated polygons to the one or more remote devices as part of the alert.
    [0005]
    5. Method according to claim 1, characterized in that it further comprises determining the lightning threshold rate based on historical data associated with at least one of (i) the location of the one or more lightning activity cells or (ii) the period of the year.
    [0006]
    6. Method according to claim 1, characterized in that it further comprises determining the lightning rate based on a number of lightning events per minute associated with one or more lightning activity cells.
    [0007]
    7. Method according to claim 6, characterized in that the lightning events include cloud-to-ground lightning, lightning within clouds, or both.
    [0008]
    8. Method according to claim 7, characterized in that lightning within a cloud includes aerial discharges, flashes within a cloud, flashes from cloud to ionosphere, or any combination thereof.
    [0009]
    9. Method according to claim 1, characterized in that the received data includes cloud-to-ground lightning, cloud-to-ground lightning, cloud-in-cloud lightning, vertical movement, condensation, moisture, or any combination thereof.
    [0010]
    10. Method according to claim 1, characterized in that it further comprises receiving data associated with lightning activity from one or more geographically dispersed sensing devices.
    [0011]
    11. Method according to claim 1, characterized in that it additionally comprises issuing the alert before the storm of great intensity has reached at least one of the geographical areas at risk.
    [0012]
    12. Method according to claim 1, characterized in that it further comprises determining a type of weathering based on the lightning rate.
    [0013]
    13. Method according to claim 1, characterized in that it further comprises determining a probability of high intensity weathering based on the lightning rate.
    [0014]
    14. Method according to claim 1, characterized in that the remote devices are personal computing devices.
    [0015]
    15. Method according to claim 1, characterized in that the remote devices are horns, sirens, lights or any combination thereof.
    [0016]
    16. The method of claim 1, further comprising: determining, by the computing device, a change in the lightning rate of the one or more lightning activity cells; and issue, by the computing device, an alert to the one or more remote devices when the change in lightning rate exceeds a predetermined value.
    [0017]
    17. The method of claim 1, further comprising repeating the step of identifying one or more lightning activity cells for a subsequent time interval and correlating the convex polygons associated with a lightning cell to determine a lightning cell trajectory.
    [0018]
    18. A computer implemented system for predicting the potential for high intensity weathering, the system comprising a computing device configured to: receive data associated with lightning activity, wherein the data includes lightning flash data collected over a period of time specific; characterized in that it further comprises identifying one or more lightning activity cells based on the lightning flash data, the identification comprising: positioning each lightning flash on a map according to its geographic location; overlaying a first grid on the map and identify sectors of the first grid with a high density of lightning flashes; superimpose a second grid on identified map sectors to locate closed contours associated with a lightning cell; e generate a convex polygon from each of the closed contours; determine a movement speed, a movement direction, and a lightning rate of the one or more lightning activity cells based on the received data; compare the determined lightning rate with a lightning threshold rate; determine one or more geographic areas at risk based on the location, speed of movement, and direction of movement of the one or more cells of lightning activity; and issue an alert to one or more remote devices monitoring geographic areas when the lightning rate exceeds a threshold lightning rate value.
    [0019]
    19. Memory, characterized in that it comprises instructions stored therein, the instructions being executed by a computer to carry out the method as defined in any one of claims 1 to 17.
    [0020]
    20. A computer-implemented system for predicting the potential for high intensity weathering, the system comprising: means for receiving data associated with lightning activity, wherein the data includes lightning flash data collected during a specific time interval; fact further comprising means for identifying one or more lightning activity cells based on the lightning flash data, the means for identifying comprising: positioning each lightning flash on a map according to its geographic location; overlaying a first grid on the map and identify sectors of the first grid with a high density of lightning flashes; overlay a second grid on the identified sectors of the map to locate closed contours associated with a lightning cell; and generate a convex polygon from each of the closed contours; means to determine a location, a speed of movement, a direction of movement and a lightning rate of one or more lightning activity cells based on the received data; comparing the determined rate of lightning with a threshold rate of lightning; means for determining one or more geographical areas at risk based on the location, speed of movement, and direction of movement of the one or more lightning activity cells; and means to issue an alert to one or more remote devices monitoring geographic areas when the lightning rate exceeds a threshold lightning rate value.
    类似技术:
    公开号 | 公开日 | 专利标题
    BR112014000092B1|2021-07-20|PREDICTION OF HIGH INTENSITY WEATHER POTENTIAL
    US10877180B2|2020-12-29|Using lightning data to generate proxy reflectivity data
    AU2015200003B2|2016-10-20|Predicting the potential for severe weather
    Girisrinivaas et al.2017|Drainage overflow monitoring system using IoT |
    KR102074871B1|2020-02-07|Backtracking system and method for heat source
    同族专利:
    公开号 | 公开日
    WO2013006259A1|2013-01-10|
    DK2753959T3|2018-11-05|
    JP2017125863A|2017-07-20|
    EP2753959A4|2015-07-01|
    CN103907034B|2018-02-27|
    JP2014518393A|2014-07-28|
    JP6816215B2|2021-01-20|
    KR101929990B1|2018-12-18|
    JP6271421B2|2018-01-31|
    US20150134252A1|2015-05-14|
    EP2753959A1|2014-07-16|
    BR112014000092A2|2017-02-14|
    PL3425429T3|2021-09-13|
    JP2019164158A|2019-09-26|
    AU2012279462B2|2014-09-25|
    AU2012279462A1|2014-01-23|
    EP3425429A1|2019-01-09|
    EP3425429B1|2021-03-10|
    PT3425429T|2021-06-15|
    PT2753959T|2018-11-08|
    DK3425429T3|2021-06-14|
    US20130009780A1|2013-01-10|
    CN103907034A|2014-07-02|
    US9810811B2|2017-11-07|
    ES2876195T3|2021-11-12|
    US8836518B2|2014-09-16|
    PL2753959T3|2019-01-31|
    KR20140060493A|2014-05-20|
    EP2753959B1|2018-07-25|
    CA2840945A1|2013-01-10|
    ES2691197T3|2018-11-26|
    CA2840945C|2020-09-22|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US2864081A|1957-11-05|1958-12-09|Kenneth C Steelman|Telemetering system|
    US3121296A|1962-04-30|1964-02-18|Owens Illinois Glass Co|Mold polishing machine|
    US3772594A|1972-10-03|1973-11-13|I Kuehnast|Lightning flash-to-bang detector|
    US4543580B1|1982-01-15|1993-01-26|Atlantic Scient Corp|
    US4792806B1|1982-01-15|1993-01-26|Atlantic Scient Corp|
    US4996473A|1986-08-18|1991-02-26|Airborne Research Associates, Inc.|Microburst/windshear warning system|
    US4972195A|1986-08-18|1990-11-20|Airborne Research Associates|Interferometric lightning ranging system|
    US4801942A|1986-08-18|1989-01-31|Airborne Research Associates, Inc.|Interferometeric lightning ranging system|
    US4916455A|1987-02-20|1990-04-10|Scientific Development Inc.|Locating system and method|
    US4812852A|1987-02-20|1989-03-14|Scientific Development Corporation|Locating system and method|
    US4914444A|1987-08-11|1990-04-03|Lightning Location And Protection, Inc.|System and method for synchronizing lightning detectors|
    US4901564A|1987-11-02|1990-02-20|Williams Earle R|Electrical detection of thunderstorm microbursts|
    JP2774293B2|1988-12-19|1998-07-09|九州電力株式会社|Lightning Prediction Method Using Distribution Line Lightning Surge Information|
    US5057820A|1989-05-01|1991-10-15|Airborne Research Associates, Inc.|Optical warning system|
    US5140523A|1989-09-05|1992-08-18|Ktaadn, Inc.|Neural network for predicting lightning|
    US5036334A|1990-02-08|1991-07-30|The Research Foundation Of State University Of New York|Lightning direction finder controller |
    US5153508A|1990-08-23|1992-10-06|United States Of America As Represented By The Administrator, National Aeronautics And Space Administration|Method and apparatus for determining return stroke polarity of distant lightning|
    US5319553A|1992-04-29|1994-06-07|B. F. Goodrich Flight Systems, Inc.|Lightning strike detection and mapping system with auto control of mapping display|
    US5295071A|1992-04-29|1994-03-15|B. F. Goodrich Flightsystems, Inc.|Sampled data lightning strike detection and mapping system capable of generating frequency spectrum of input signal waveforms and displaying such on the mapping display|
    US5299127A|1992-04-29|1994-03-29|Bf Goodrich Flight Systems, Inc.|Lightning strike detection and mapping system capable of monitoring its power source and of displaying a representation thereof on the mapping display|
    US5303152A|1992-04-29|1994-04-12|Bfgoodrich Flight Systems, Inc.|Lightning strike detection system capable of quickly determining an invalid correlation of strike signaling|
    US5305210A|1992-04-29|1994-04-19|B. F. Goodrich Flight Systems, Inc.|Sampled data lightning strike detection and mapping system capable of early detection of an invalid strike from sampled data and quick resumption of monitoring an incoming signal|
    US5295072A|1992-04-29|1994-03-15|Bfgoodrich Flightsystems, Inc.|Sampled data lightning strike detection and mapping system capable of recovering a pre threshold sample history for detection and mapping processing|
    US5325299A|1992-04-29|1994-06-28|B. F. Goodrich Flight Systems, Inc.|System for classifying lightning strikes to enhance location estimation thereof|
    US5537318A|1994-07-13|1996-07-16|B. F. Goodrich Flightsystems, Inc.|Lightning strike detection and mapping system|
    WO1997005508A2|1995-07-26|1997-02-13|Airborne Research Associates, Inc.|Lightning locating system|
    US5699245A|1995-09-11|1997-12-16|Bfgoodrich Flightsystems, Inc.|Distributed lightning detection system|
    JPH09184890A|1995-12-28|1997-07-15|Akira Togashi|Lightning sensor and lightning countermeasuring apparatus|
    US5978738A|1997-02-13|1999-11-02|Anthony Brown|Severe weather detector and alarm|
    US6064340A|1998-07-02|2000-05-16|Intersil Corporation|Electrostatic discharge locating apparatus and method|
    US6298118B1|1999-07-28|2001-10-02|Fluke Corporation|System and method for processing of communication line test signals, such as enhancement processing|
    US6420862B2|2000-02-14|2002-07-16|The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration|System and method of locating lightning strikes|
    US6552521B1|2000-07-11|2003-04-22|The United States Of America As Represented By The United States National Aeronautics And Space Administration|Single station system and method of locating lightning strikes|
    US6599242B1|2000-07-19|2003-07-29|Medtronic, Inc.|Method and apparatus for data compression of heart signals|
    CN1426628A|2001-03-01|2003-06-25|酒井康江|Method and apparatus for compression, method and apparatus for decompression, compression/decompression system, record medium|
    US6753784B1|2001-03-28|2004-06-22|Meteorlogix, Llc|GIS-based automated weather alert notification system|
    JP2003021687A|2001-07-06|2003-01-24|Digital Weather Platform Kk|Method for weather forecasting for narrow area, method for distribution of weather forecast for narrow area, method for commodity sales promotion, weather forecasting device, and weather forecasting information providing system|
    JP2002049298A|2001-08-17|2002-02-15|Ohbayashi Corp|Program and method for predicting wind environment|
    KR20030016747A|2001-08-21|2003-03-03|엘지전자 주식회사|Wide band receiving apparatus for communication mobile device|
    JP2003067477A|2001-08-24|2003-03-07|Cdan:Kk|Area-oriented information providing system and computer readable recording medium with area-oriented information providing program recorded thereon|
    US6791311B2|2002-02-13|2004-09-14|Vaisala Oyj|Lightning detection and data acquisition system|
    US6788043B2|2002-02-13|2004-09-07|Vaisala Oyj|Lightning detection and data acquisition system|
    JP3752463B2|2002-03-29|2006-03-08|東京電力株式会社|Lightning strike location method, apparatus, system and program|
    US6559242B1|2002-05-02|2003-05-06|Ford Global Technologies, Inc.|Surface activation and coating processes of a thermoplastic olefin using an aqueous immersion bath and products produced thereby|
    JP4173701B2|2002-07-31|2008-10-29|関西電力株式会社|Winter lightning lightning forecasting method and forecasting device|
    US6868339B2|2003-03-24|2005-03-15|Vaisala Oyj|Systems and methods for time corrected lightning detection|
    CN2606362Y|2003-03-26|2004-03-10|中国科学院寒区旱区环境与工程研究所|Simple thunderstorm predicting devices|
    JP4095528B2|2003-09-30|2008-06-04|三菱電機株式会社|Rainfall movement prediction apparatus and rainfall movement prediction method|
    WO2005073752A1|2004-01-29|2005-08-11|Nowcast Mobile Gmbh|System and method for the recording transmission and analysis of data and information generated by electromagnetic radiation|
    US7200418B2|2004-03-04|2007-04-03|Nokia Corporation|Detection of lightning|
    US7016785B2|2004-03-04|2006-03-21|Nokia Corporation|Lightning detection|
    JP4266858B2|2004-03-15|2009-05-20|Ｎｅｃエンジニアリング株式会社|Local heavy rain monitoring system|
    JP3873060B2|2004-03-24|2007-01-24|東海旅客鉄道株式会社|Lightning strike prediction device and lightning strike prediction result notification system|
    US7327271B2|2004-05-19|2008-02-05|Lawrence Tibor Greenstein|Portable weather detector and alert system|
    JP2006145441A|2004-11-22|2006-06-08|Nippon Kouatsu Electric Co|Thunder-approach detector|
    CN101198994A|2005-06-21|2008-06-11|汤姆森许可贸易公司|Equipment with red alert function in favor of position selection|
    US7869953B1|2005-08-17|2011-01-11|Weather Central Holdings, Inc.|System and method for presenting lightning strike information|
    US7796951B2|2005-10-14|2010-09-14|Nokia Corporation|Detection of lightning|
    JP4526471B2|2005-12-02|2010-08-18|中国電力株式会社|End lightning notification system and end lightning notification method|
    US7868811B1|2006-03-07|2011-01-11|Rockwell Collins, Inc.|Weather radar system and method using data from a lightning sensor|
    US7949548B2|2006-03-08|2011-05-24|Guy Carpenter & Company|Spatial database system for generation of weather event and risk reports|
    US7558674B1|2006-04-24|2009-07-07|Wsi, Corporation|Weather severity and characterization system|
    US20070260151A1|2006-05-03|2007-11-08|Clifford Gari D|Method and device for filtering, segmenting, compressing and classifying oscillatory signals|
    US20080085096A1|2006-10-04|2008-04-10|Aws Convergence Technologies, Inc.|Method, system, apparatus and computer program product for creating, editing, and publishing video with dynamic content|
    US7970542B2|2007-04-17|2011-06-28|Toa Systems, Inc.|Method of detecting, locating, and classifying lightning|
    US20090164124A1|2007-12-21|2009-06-25|Advidyne Corporation|Ultra wideband receiver for lightning detection|
    US20090177343A1|2008-01-09|2009-07-09|Honeywell International Inc.|System and method for selectable weather object display|
    US7917291B2|2008-01-10|2011-03-29|Baron Services, Inc.|System and method for predicting tornado activity|
    US20090295587A1|2008-03-02|2009-12-03|Gorman Jr Thomas Leo|Severe weather, environmental and mass notification warning system and method|
    US8073622B2|2008-05-12|2011-12-06|The Board Of Trustees Of The Leland Stanford Junior University|Long-range lightning detection and characterization system and method|
    US8275548B2|2009-08-17|2012-09-25|Earth Networks, Inc.|Method and apparatus for detecting lightning activity|
    US8432306B2|2009-10-16|2013-04-30|Propagation Research Associates, Inc.|Method and apparatus for the nowcast of lightning threat using polarimetric radar|
    US8655951B2|2009-12-23|2014-02-18|Earth Networks, Inc.|Method and apparatus for conveying vehicle driving information|
    US8698640B1|2010-03-04|2014-04-15|Daniel R. Gropper|Monitored weather and emergency alert system|
    US8788606B2|2010-04-09|2014-07-22|Weather Decision Technologies, Inc.|Multimedia alerting|WO2011088473A2|2010-01-18|2011-07-21|The Regents Of The University Of California|System and method for identifying patterns in and/or predicting extreme climate events|
    EP2805189B1|2012-01-18|2018-11-07|Earth Networks, Inc.|Using lightning data to generate proxy reflectivity data|
    PH12013000136A1|2013-05-23|2015-01-21|De Antoni Ferdinand Evert Karoly|A domain agnostic method and system for the capture, storage, and analysis of sensor readings|
    WO2015179451A1|2014-05-20|2015-11-26|Allied Telesis Holdings Kabushiki Kaisha|Path determination of a sensor based detection system|
    US10084871B2|2013-05-23|2018-09-25|Allied Telesis Holdings Kabushiki Kaisha|Graphical user interface and video frames for a sensor based detection system|
    US9693386B2|2014-05-20|2017-06-27|Allied Telesis Holdings Kabushiki Kaisha|Time chart for sensor based detection system|
    CN103308956B|2013-06-25|2015-06-03|中国科学院遥感与数字地球研究所|Method for pre-judging future monthly average cloud cover in target area by utilizing cloud climatology data|
    US9748759B1|2014-05-09|2017-08-29|Donald J. Bergeron|Lightning electromagnetic pulsedetector and isolation device|
    US20150338447A1|2014-05-20|2015-11-26|Allied Telesis Holdings Kabushiki Kaisha|Sensor based detection system|
    US9779183B2|2014-05-20|2017-10-03|Allied Telesis Holdings Kabushiki Kaisha|Sensor management and sensor analytics system|
    US20160063387A1|2014-08-29|2016-03-03|Verizon Patent And Licensing Inc.|Monitoring and detecting environmental events with user devices|
    CN105791917B|2014-12-24|2019-04-09|中国电信股份有限公司|Lightning-arrest method and device is shut down in control outdoor advertising|
    US11240416B2|2015-04-01|2022-02-01|Dtn, Llc|Weather event visualization application for mobile devices|
    EP3078992B1|2015-04-10|2019-01-30|nowcast GmbH|System and method for the identification and/or prediction of hail events|
    CN105842756B|2016-03-30|2018-09-14|广州积雨云科技有限公司|A kind of thunderstorm information prediction method|
    US9812011B1|2016-07-28|2017-11-07|Here Global B.V.|Dangerous driving weather messages|
    US10782448B2|2016-07-29|2020-09-22|Vaisala, Inc.|Short-term thunderstorm forecast and severe weather alert system and method|
    CN106291766B|2016-08-31|2018-11-02|成都飞机工业（集团）有限责任公司|A kind of forecasting procedure of In Chengdu fair weather|
    US10296981B2|2016-09-14|2019-05-21|Swiss Reinsurance Company Ltd.|Method and system for automated location-dependent recognition of storm risks and exposure-based parametric risk-transfer|
    US20200110196A2|2016-09-19|2020-04-09|Instituto Tecnológico De Aeronáutica - Ita|Decision-making support method for issuing warnings and selection of mitigation actions parameterized by weather-climate decision index based on user preferences|
    US9933548B1|2016-12-28|2018-04-03|Here Global B.V.|Method, apparatus and computer program product for providing local hazard warnings|
    CN107272085A|2017-05-15|2017-10-20|安徽亿纵电子科技有限公司|A kind of each area in city is built, structures lightning protection early warning system|
    CN107332233A|2017-06-26|2017-11-07|安徽亿纵电子科技有限公司|Electric line lightening arresting method|
    KR101983938B1|2018-01-29|2019-05-29|신희경|System and method for warning lightning|
    CH714678A1|2018-02-23|2019-08-30|Marte Gerhard|Method for distance warning of a construction worker or a construction machine in front of a danger zone.|
    US10408972B1|2018-04-20|2019-09-10|Adam Baker|System and method for lightning strike prediction and warning|
    US11227477B2|2018-05-16|2022-01-18|University Of Hawaii|Systems and methods for determining maximum alert geography for a hazard|
    US10859396B2|2018-05-18|2020-12-08|Here Global B.V.|Warning polygons for weather from vehicle sensor data|
    US10657683B2|2018-07-24|2020-05-19|Here Global B.V.|Hazard warning polygons constrained based on end-use device|
    CN109727471A|2019-02-12|2019-05-07|合肥极光科技股份有限公司|Intelligent monitor system under a kind of bad weather condition based on technology of Internet of things|
    AT523068B1|2019-11-25|2021-05-15|UBIMET GmbH|Method for monitoring lightning activity in a surveillance area|
    AT523070B1|2019-11-25|2021-05-15|UBIMET GmbH|Method for monitoring lightning activity in a surveillance area|
    AT523069B1|2019-11-25|2021-05-15|UBIMET GmbH|Method for monitoring lightning activity in a surveillance area|
    CN111023400B|2019-12-30|2021-05-14|宁波奥克斯电气股份有限公司|Air conditioner outdoor environment temperature prediction method and device and air conditioner|
    KR102260990B1|2020-08-25|2021-06-04|주식회사 엘피에스코리아|Lightning Prediction Method|
    法律状态:
    2018-12-11| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|
    2020-03-24| B06U| Preliminary requirement: requests with searches performed by other patent offices: procedure suspended [chapter 6.21 patent gazette]|
    2021-05-04| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|
    2021-07-20| B16A| Patent or certificate of addition of invention granted [chapter 16.1 patent gazette]|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 18/06/2012, OBSERVADAS AS CONDICOES LEGAIS. |
    优先权:
    申请号 | 申请日 | 专利标题
    US13/177,266|US8836518B2|2011-07-06|2011-07-06|Predicting the potential for severe weather|
    US13/177,266|2011-07-06|
    PCT/US2012/042966|WO2013006259A1|2011-07-06|2012-06-18|Predicting the potential for severe weather|
    [返回顶部]