Estimation system and estimation method

Abstract

A position estimation system 1 comprises an acquisition unit 11 that acquires, from a plurality of drones, notification information including position information and information indicating radio wave intensity, and a position estimation unit 13 that performs position estimation by inputting the notification information acquired by the acquisition unit 11 from the plurality of drones into a position estimation model for estimating position information on the basis of the notification information.

Description

Estimation system and estimation method

[0001] One aspect of the present invention relates to an estimation system and an estimation method.

[0002] Patent Document 1 discloses an indoor location estimation model construction device that includes an information acquisition unit that acquires wireless LAN information consisting of received signal strength for each access point, and a location estimation model learning unit that uses a set of pairs of wireless LAN information associated with location information and the location information, and the wireless LAN information acquired by the information acquisition unit as learning data, to learn a location estimation model that estimates location information from wireless LAN information.

[0003] Japanese Patent Application Laid-Open No. 2023-129115

[0004] Here, in a system that performs location estimation based on wireless LAN information (received signal strength for each access point) as described above, a problem arises in that Wi-Fi temporarily present in the environment, such as tethering on a smartphone or a mobile Wi-Fi router, becomes noise, deteriorating the accuracy of location estimation.

[0005] One aspect of the present invention has been made in view of the above circumstances, and relates to an estimation system and an estimation method that can improve the accuracy of indoor position estimation.

[0006] An estimation system according to one embodiment of the present invention includes an acquisition unit that acquires notification information from multiple drones, the notification information including location information and information indicating radio wave intensity, and a position estimation unit that performs position estimation by inputting the notification information from the multiple drones acquired by the acquisition unit into a position estimation model that estimates location information based on the notification information.

[0007] In an estimation system according to one aspect of the present invention, position estimation is performed by inputting notification information from multiple drones (information indicating the drone's position information and radio wave intensity) into a position estimation model. For example, when performing indoor position estimation, there is a technique for performing position estimation using wireless LAN information. However, when performing position estimation using wireless LAN information, a problem arises in that Wi-Fi temporarily present in the environment, such as from smartphone tethering or a mobile Wi-Fi router, becomes noise, degrading the accuracy of the position estimation. In contrast, when performing position estimation using notification information from drones, such noise is not a problem, thereby improving the accuracy of the position estimation. Furthermore, by using notification information from multiple drones, the accuracy of the position estimation can be further improved. Furthermore, while, for example, position estimation using wireless LAN does not directly link position estimation with GPS information, position estimation using drone notification information uses the GPS information included in the notification information, allowing for position estimation that directly infers GPS information. Furthermore, when the position estimation model is not a machine learning model but one that estimates position information based on real-time information, highly accurate position estimation can be performed based solely on real-time information.

[0008] According to one aspect of the present invention, it is possible to improve the accuracy of position estimation.

[0009] Fig. 1 is a diagram illustrating an overview of a position estimation system according to an embodiment. Fig. 2 is a diagram schematically illustrating a system configuration of a position estimation system according to an embodiment. Fig. 3 is a block diagram illustrating a functional configuration of a processing server included in the position estimation system illustrated in Fig. 2. Fig. 4 is a diagram illustrating notification information collected from a plurality of drones. Fig. 5 is a flowchart illustrating a position estimation process executed by the position estimation system according to an embodiment. Fig. 6 is a diagram illustrating a hardware configuration of a processing server.

[0010] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same or equivalent elements are designated by the same reference numerals, and redundant description will be omitted.

[0011] First, an overview of indoor position estimation according to this embodiment will be described. FIG. 1 is a diagram illustrating an overview of a position estimation system according to this embodiment. As shown in FIG. 1, in indoor position estimation according to this embodiment, when a mobile communication terminal 10, such as a smartphone, is located in the indoor space of a building P, its own position is estimated based on broadcast information from multiple (four drones in this example) drones D1 to D4 flying around the building P. Positioning using Wi-Fi is known as a method of indoor position estimation outside of GPS coverage. However, with Wi-Fi positioning, a problem arises in that Wi-Fi temporarily present in the environment, such as smartphone tethering or a mobile Wi-Fi router, becomes noise, degrading the accuracy of the position estimation. In this regard, when position estimation is performed using broadcast information from drones, such noise is not an issue, and the accuracy of indoor position estimation can be improved.

[0012] 2 is a diagram schematically illustrating a system configuration of a location estimation system 1 according to an embodiment. As illustrated in FIG. 2, the location estimation system 1 (estimation system) includes a mobile communication terminal 10 and a processing server 20.

[0013] 2, in the position estimation system 1, when locating a mobile communication terminal 10 located in an indoor space, the mobile communication terminal 10 collects notification information from multiple (four drones in this example) drones D1 to D4 flying in the vicinity. The notification information includes remote ID information and radio wave intensity. The remote ID information includes at least information indicating the latitude, longitude, and altitude of the drone.

[0014] Then, the mobile communication terminal 10 transmits the collected notification information of each drone D1 to D4 to the processing server 20.

[0015] The processing server 20 estimates the position of the mobile communication terminal 10 based on the notification information of each of the drones D1 to D4 acquired via the mobile communication terminal 10 (details will be described later). The processing server 20 transmits the position estimation result (position information of the mobile communication terminal 10) to the mobile communication terminal 10. Through this processing, the mobile communication terminal 10 can identify its own position information.

[0016] Fig. 3 is a block diagram showing the functional configuration of the processing server 20 included in the location estimation system 1 shown in Fig. 2. The following describes in detail the functions of the processing server 20. Note that some or all of the functions described as functions of the processing server 20 in this embodiment may be provided in the mobile communication terminal 10.

[0017] The processing server 20 includes an acquisition unit 11 , a notification information exclusion unit 12 , and a position estimation unit 13 .

[0018] The acquisition unit 11 acquires notification information from multiple drones via the mobile communication terminal 10. The notification information includes location information and information indicating radio wave intensity. The location information is information on the drone's remote ID, and is information indicating latitude, longitude, and altitude. The notification information further includes information that uniquely identifies the drone and information indicating the time of acquisition. The acquisition unit 11 outputs the acquired information to the notification information exclusion unit 12.

[0019] FIG. 4 is a diagram illustrating broadcast information collected from multiple drones D1 to D4. As shown in FIG. 4, assume that the mobile communication terminal 10 is collecting broadcast information from four drones D1 to D4. The broadcast information from each drone D1 to D4 includes, for example, (latitude (x), longitude (y), altitude (z), radio wave strength (R)). The broadcast information from drone D1 includes (latitude (x1), longitude (y1), altitude (z1), radio wave strength (R1)). This indicates that radio waves with radio wave strength (R1) were received from drone D1, which is located at the position indicated by latitude (x1), longitude (y1), and altitude (z1). Similarly, the broadcast information from drone D2 includes (latitude (x2), longitude (y2), altitude (z2), radio wave strength (R2)). This indicates that radio waves with radio wave intensity (R2) have been received from drone D2, which is located at the position indicated by latitude (x2), longitude (y2), and altitude (z2). Similarly, the notification information from drone D3 includes (latitude (x3), longitude (y3), altitude (z3), radio wave intensity (R3)). This indicates that radio waves with radio wave intensity (R3) have been received from drone D3, which is located at the position indicated by latitude (x3), longitude (y3), and altitude (z3). Similarly, the notification information from drone D4 includes (latitude (x4), longitude (y4), altitude (z4), radio wave intensity (R4)). This indicates that radio waves with radio wave intensity (R4) have been received from drone D4, which is located at the position indicated by latitude (x4), longitude (y4), and altitude (z4).

[0020] The notification information exclusion unit 12 excludes some notification information from the notification information from multiple drones acquired by the acquisition unit 11 based on a predetermined exclusion rule.

[0021] The notification information exclusion unit 12 may exclude notification information in which the radio wave strength indicated in the information indicating the radio wave strength is equal to or less than a predetermined value from among the notification information from multiple drones acquired by the acquisition unit 11. When the radio wave strength is low, it is assumed that the drone related to the notification information is far from the mobile communication terminal 10. When the distance is far, errors in positioning are more likely to occur, so by excluding such notification information, it is possible to ensure the accuracy of position estimation.

[0022] The notification information exclusion unit 12 may identify a drone moving at high speed based on information identifying the drone, information indicating the time, and location information, and may exclude notification information from the drone. Specifically, the notification information exclusion unit 12 identifies multiple pieces of notification information from the same drone acquired within a predetermined period based on information identifying the drone and information indicating the time. Then, if the location information of the multiple pieces of notification information from the identified drone is separated by a predetermined distance or more, the notification information exclusion unit 12 determines that the multiple pieces of notification information are "notification information from a drone moving at high speed, traveling a long distance in a short period of time," and excludes them. Specifically, notification information from drones moving at speeds of 30 km / h or more may be excluded. Location information included in notification information from drones moving at high speeds is prone to errors. By excluding such notification information, the accuracy of position estimation can be ensured.

[0023] The notification information exclusion unit 12 may identify two or more nearby drones that are located within a predetermined distance from each other based on the location information included in the notification information related to multiple drones, and may exclude notification information from the two or more nearby drones. Specifically, notification information from drones that are located within 5 meters of each other may be excluded, for example. The notification information exclusion unit 12 may also exclude notification information related to nearby drones that are identical in appearance. In this way, drones that are identical in appearance and located in close proximity to each other may be used in drone shows, etc. Because notification information from such drones may be biased, excluding such information can ensure the accuracy of position estimation.

[0024] The position estimation unit 13 performs position estimation by inputting the notification information from the multiple drones acquired by the acquisition unit 11 into a position estimation model that estimates position information based on the notification information. In detail, the position estimation unit 13 may perform position estimation by inputting multiple pieces of notification information that were not excluded by the notification information exclusion unit 12, out of the notification information from the multiple drones acquired by the acquisition unit 11, into the position estimation model. The position estimation unit 13 transmits the position estimation result to the mobile communication terminal 10.

[0025] The position estimation model is, for example, a machine learning model created by performing machine learning using radio wave intensity and position information (latitude, longitude, and altitude) in the notification information from multiple drones as explanatory variables and position information of the mobile communication terminal 10 as a target variable. The position estimation model may be created in advance in the position estimation system 1, or may be created in advance by other configurations. Note that the position estimation model does not necessarily have to be a machine learning model. The position estimation model may be one that estimates position information based only on real-time information, for example.

[0026] Next, the position estimation process executed by the position estimation system 1 will be described with reference to Fig. 5. Fig. 5 is a flowchart showing the position estimation process executed by the position estimation system 1 according to the embodiment.

[0027] 5, for example, mobile communication terminal 10 collects notification information including remote IDs from multiple drones flying in the vicinity (step S1). The notification information includes remote ID information and radio wave intensity. The remote ID information includes at least information indicating the latitude, longitude, and altitude of the drone.

[0028] Next, the mobile communication terminal 10 uploads (transmits) notification information (information on the remote ID and information indicating the radio wave intensity) to the processing server 20 (step S2).

[0029] Next, in the processing server 20, the above-mentioned notification information is acquired from the multiple drones via the mobile communication terminal 10, and the notification information from the multiple drones is input into a position estimation model that estimates position information based on the notification information, thereby performing position estimation (step S3).

[0030] Next, the effects of the position estimation system 1 according to this embodiment will be described.

[0031] The position estimation system 1 according to this embodiment includes an acquisition unit 11 that acquires notification information including location information and information indicating radio wave intensity from multiple drones, and a position estimation unit 13 that performs position estimation by inputting the notification information from the multiple drones acquired by the acquisition unit 11 into a position estimation model that estimates location information based on the notification information.

[0032] In the position estimation system 1 according to this embodiment, position estimation is performed by inputting notification information from multiple drones (information indicating the drone's position information and radio wave intensity) into a position estimation model. For example, when performing indoor position estimation, there is a method of performing position estimation using wireless LAN information. However, when performing position estimation using wireless LAN information, a problem occurs in that Wi-Fi temporarily present in the environment, such as smartphone tethering or a mobile Wi-Fi router, becomes noise, degrading the accuracy of the position estimation. In this regard, when performing position estimation using notification information from drones, such noise is not a problem, and the accuracy of the position estimation can be improved. Furthermore, by using notification information from multiple drones, the accuracy of the position estimation can be further improved.

[0033] The location information may be information indicating the latitude, longitude, and altitude of the drone. By using detailed location information of the drone in this way, the accuracy of location estimation can be improved.

[0034] The position estimation system 1 further includes a notification information exclusion unit 12 that excludes some of the notification information from the multiple drones acquired by the acquisition unit 11 based on a predetermined exclusion rule, and the position estimation unit 13 may input, into a position estimation model, multiple pieces of notification information from the multiple drones acquired by the acquisition unit 11 that were not excluded by the notification information exclusion unit 12. In this way, position estimation is performed using only appropriate notification information based on a predetermined rule, thereby improving the accuracy of position estimation.

[0035] The notification information exclusion unit 12 may exclude notification information in which the radio wave strength indicated in the information indicating the radio wave strength is equal to or less than a predetermined value from among the notification information from multiple drones acquired by the acquisition unit 11. When the radio wave strength is low, it is assumed that the drone related to the notification information is far from the mobile communication terminal 10. When the distance is far, distance errors (positioning errors) are more likely to occur, so by excluding such notification information, the accuracy of position estimation can be ensured.

[0036] The notification information further includes information for identifying the drone and information indicating the time. The notification information exclusion unit 12 may identify a drone moving at high speed based on the information for identifying the drone, the information indicating the time, and the location information, and exclude notification information from the drone. Location information included in notification information from a drone moving at high speed is prone to errors. By excluding such notification information, the accuracy of position estimation can be ensured.

[0037] The notification information exclusion unit 12 may identify two or more nearby drones that are located within a predetermined distance from each other based on the location information, and may exclude notification information from the two or more nearby drones. Drones that are located close to each other may be used in drone shows, etc. Because notification information from such drones may be biased, excluding them can ensure the accuracy of position estimation.

[0038] Next, the hardware configuration of the processing server 20 included in the above-described location estimation system 1 will be described with reference to Fig. 6. The processing server 20 may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.

[0039] In the following description, the term "apparatus" can be interpreted as a circuit, a device, a unit, etc. The hardware configuration of each apparatus may be configured to include one or more of the apparatuses shown in the drawings, or may be configured to exclude some of the apparatuses.

[0040] Each function in each device is realized by loading specified software (programs) onto hardware such as processor 1001 and memory 1002, causing processor 1001 to perform calculations and control communication via communication device 1004 and reading and / or writing of data in memory 1002 and storage 1003.

[0041] The processor 1001 controls the entire computer by running, for example, an operating system. The processor 1001 may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control unit, an arithmetic unit, a register, etc. For example, the control functions of the acquisition unit 11 and the like may be realized by the processor 1001.

[0042] The processor 1001 also reads programs (program codes), software modules, and data from the storage 1003 and / or the communication device 1004 into the memory 1002, and executes various processes in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described in the above embodiments.

[0043] For example, the control functions of the acquisition unit 11 and the like may be realized by a control program stored in the memory 1002 and running on the processor 1001, and similar functions may be realized for other functional blocks. Although the above-described various processes have been described as being executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented on one or more chips. The program may be transmitted from a network via a telecommunications line.

[0044] The memory 1002 is a computer-readable recording medium and may be composed of at least one of, for example, a read-only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a random access memory (RAM), etc. The memory 1002 may also be called a register, a cache, a main memory (primary storage device), etc. The memory 1002 can store executable programs (program codes), software modules, etc. for implementing a wireless communication method according to one embodiment of the present invention.

[0045] Storage 1003 is a computer-readable recording medium, and may be, for example, at least one of an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray disc), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy disk, a magnetic strip, etc. Storage 1003 may also be referred to as an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, a server, or other appropriate medium including memory 1002 and / or storage 1003.

[0046] The communication device 1004 is hardware (transmission / reception device) for communicating between computers via a wired and / or wireless network, and is also called, for example, a network device, a network controller, a network card, or a communication module.

[0047] The input device 1005 is an input device (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that receives input from the outside. The output device 1006 is an output device (e.g., a display, a speaker, an LED lamp, etc.) that outputs to the outside. The input device 1005 and the output device 1006 may be integrated into one device (e.g., a touch panel).

[0048] Furthermore, each device such as the processor 1001 and the memory 1002 is connected to a bus 1007 for communicating information. The bus 1007 may be configured as a single bus, or may be configured as different buses between the devices.

[0049] Each device may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized by the hardware. For example, the processor 1001 may be implemented by at least one of these pieces of hardware.

[0050] Although the present embodiment has been described in detail above, it is clear to those skilled in the art that the present embodiment is not limited to the embodiment described in this specification. The present embodiment can be implemented in modified and altered forms without departing from the spirit and scope of the present invention as defined by the claims. Therefore, the description in this specification is intended to be illustrative and does not have any limiting meaning on the present embodiment.

[0051] Each aspect / embodiment described herein may be applied to systems utilizing LTE (Long Term Evolution), LTE-Advanced (LTE-A), SUPER 3G, IMT-Advanced, 4G, 5G, FRA (Future Radio Access), W-CDMA, GSM, CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, UWB (Ultra-Wide Band), Bluetooth, or other suitable systems and / or next generation systems enhanced thereon.

[0052] The order of the procedures, sequences, flowcharts, etc. of each aspect / embodiment described herein may be rearranged unless it is consistent. For example, the methods described herein present elements of various steps in an example order and are not limited to the particular order presented.

[0053] Input and output information may be stored in a specific location (for example, memory) or managed in a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be sent to another device.

[0054] The determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0055] The aspects / embodiments described herein may be used alone or in combination, or may be switched depending on the implementation. Notification of predetermined information (e.g., notification that "X is true") is not limited to explicit notification, but may be implicit (e.g., not notifying the predetermined information).

[0056] Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.

[0057] Software, instructions, etc. may also be transmitted or received over a transmission medium. For example, if the software is transmitted from a website, server, or other remote source using wired technologies such as coaxial cable, fiber optic cable, twisted pair, and Digital Subscriber Line (DSL), and / or wireless technologies such as infrared, radio, and microwave, these wired and / or wireless technologies are included within the definition of transmission media.

[0058] The information, signals, etc. described herein may be represented using any one of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0059] It should be noted that terms explained in this specification and / or terms necessary for understanding this specification may be replaced with terms having the same or similar meanings.

[0060] Furthermore, the information, parameters, etc. described in this specification may be expressed as absolute values, as relative values ​​from a predetermined value, or as corresponding other information.

[0061] A communications terminal may also be referred to by those skilled in the art as a mobile communications terminal, subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communications device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable terminology.

[0062] As used herein, the phrase "based on" does not mean "based only on," unless expressly specified otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0063] When designations such as "first," "second," etc. are used herein, any reference to such elements does not generally limit the quantity or order of those elements. These designations may be used herein as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed therein or that the first element must precede the second element in some way.

[0064] To the extent that the terms "include," "including," and variations thereof are used herein or in the claims, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, the term "or," as used herein or in the claims, is not intended to be an exclusive or.

[0065] In this specification, a plurality of devices is also included unless the context or the technology clearly indicates that only one device exists.

[0066] Throughout this disclosure, the plural is intended to be included unless the singular is clearly indicated by the context.

[0067] Finally, various exemplary embodiments included in the present disclosure are described below in [E1] to [E7].

[0068] [E1] An estimation system comprising: an acquisition unit that acquires notification information including location information and information indicating radio wave intensity from a plurality of drones; and a position estimation unit that performs position estimation by inputting the notification information from the plurality of drones acquired by the acquisition unit into a position estimation model that estimates location information based on the notification information.

[0069] [E2] The estimation system according to [E1], wherein the location information is information indicating the latitude, longitude, and altitude of the drone.

[0070] [E3] An estimation system according to [E1] or [E2], further comprising a notification information exclusion unit that excludes some notification information from the notification information from the multiple drones acquired by the acquisition unit based on a predetermined exclusion rule, wherein the position estimation unit inputs, into the position estimation model, multiple notification information that was not excluded by the notification information exclusion unit from the notification information from the multiple drones acquired by the acquisition unit.

[0071] [E4] The estimation system described in [E3], wherein the notification information exclusion unit excludes, from the notification information from multiple drones acquired by the acquisition unit, notification information in which the radio wave strength indicated in the information indicating the radio wave strength is below a predetermined value.

[0072] [E5] The notification information further includes information for identifying the drone and information indicating the time, and the notification information exclusion unit identifies a drone moving at high speed based on the information for identifying the drone, the information indicating the time, and the location information, and excludes notification information from the drone moving at high speed. An estimation system described in [E3] or [E4].

[0073] [E6] An estimation system described in any one of [E3] to [E5], wherein the notification information exclusion unit identifies two or more nearby drones that are located within a predetermined distance from each other based on the location information, and excludes notification information from the two or more nearby drones.

[0074] [E7] An estimation method executed by an estimation system, comprising: acquiring, from a plurality of drones, notification information including location information and information indicating radio wave intensity; and performing location estimation by inputting the notification information from the plurality of drones into a location estimation model that estimates location information based on the notification information.

[0075] 1... location estimation system, 11... acquisition unit, 12... broadcast information exclusion unit, 13... location estimation unit.

Claims

1. An estimation system comprising: an acquisition unit that acquires notification information including location information and information indicating radio wave intensity from multiple drones; and a position estimation unit that performs position estimation by inputting the notification information from the multiple drones acquired by the acquisition unit into a position estimation model that estimates location information based on the notification information.

2. The estimation system according to claim 1, wherein the location information is information indicating the latitude, longitude, and altitude of the drone.

3. An estimation system as described in claim 1 or 2, further comprising a notification information exclusion unit that excludes some of the notification information from the multiple drones acquired by the acquisition unit based on a predetermined exclusion rule, and the position estimation unit inputs multiple pieces of notification information from the multiple drones acquired by the acquisition unit that have not been excluded by the notification information exclusion unit into the position estimation model to perform position estimation.

4. The estimation system of claim 3, wherein the notification information exclusion unit excludes notification information from the multiple drones acquired by the acquisition unit, the notification information having a radio wave strength indicated in the information indicating the radio wave strength that is below a predetermined value.

5. The estimation system of claim 3, wherein the notification information further includes information identifying the drone and information indicating the time, and the notification information exclusion unit identifies drones moving at high speeds based on the information identifying the drone, the information indicating the time, and the location information, and excludes notification information from the drones moving at high speeds.

6. The estimation system of claim 3, wherein the notification information exclusion unit identifies two or more nearby drones that are located within a predetermined distance of each other based on the location information, and excludes notification information from the two or more nearby drones.

7. An estimation method executed by an estimation system, comprising: acquiring, from a plurality of drones, report information including location information and information indicating radio wave intensity; and performing location estimation by inputting the report information from the plurality of drones into a location estimation model that estimates location information based on the report information.