JP2022035221A - Information processor, positioning support method, and program - Google Patents

Abstract

To improve the accuracy of positioning.SOLUTION: An information processor 10 has a weighting part 101 and a specifying part 102. The weighting part 101 weights the degree of retention of a mobile device in a fixed device, indicated by identification data included in beacon data based on the beacon data. The beacon data includes strength data relating to radio wave intensity of radio communication between the mobile device and any one of the plurality of fixed devices, and identification data indicating the fixed device. The specifying part 102 specifies beacon data having a large tolerance in radio wave intensity due to the influence of the environment of radio communication among the series of beacon data based on the weighting result.SELECTED DRAWING: Figure 1

Description

The present invention relates to an information processing apparatus and the like.

There is a technology for positioning moving objects using beacons and the like indoors where satellite signals cannot be used. Patent Document 1 discloses a technique in which a large number of beacons are attached to the ceiling in a building such as a warehouse to perform positioning of a moving object.

Further, in Patent Document 2, the position of the moving body is determined based on the radio wave strength between the receiver that is attached to the moving body and receives the radio wave from the beacon and the beacon that emits the radio wave, and the identification data of the beacon. The technology to be detected is disclosed.

International Publication No. 2019/031264 International Publication No. 2019/151159

However, the receiver may erroneously detect data due to the radio wave characteristics of the beacon. For example, there is a phenomenon that the radio wave from the beacon is attenuated by a shield, and a phenomenon that the radio wave from the beacon is strengthened or weakened by the radio wave reflection by an interfering object. The shield is, for example, moisture contained in the worker itself or the wooden device. In addition, examples of the interfering substance include equipment made of metal or concrete. Due to these factors, the radio field intensity between the beacon and the receiver changes, and there is a problem that a position different from the actual position is estimated.

An example of an object of the present invention is to provide an information processing device for improving the accuracy of positioning in order to solve the above-mentioned problems.

The information processing device in one form is intensity data regarding the radio field intensity of wireless communication between the first device and the second device of any one of the plurality of second devices, and identification data indicating the second device. Based on the communication data including, the weighting means for weighting the degree of retention of the first device in the second device indicated by the identification data included in the communication data, and the weighting result by the weighting means. Based on the above, the present invention includes a specific means for identifying the communication data in which the radio wave strength is erroneously detected due to the influence of the wireless communication environment from the series of the communication data.

The positioning support method in one form includes intensity data regarding the radio field intensity of wireless communication between the first device and the second device of any one of the plurality of second devices, and identification data indicating the second device. Based on the communication data including From the data, the communication data in which the radio wave strength is erroneously detected due to the influence of the wireless communication environment is specified.

The program in one embodiment tells the computer the strength data regarding the radio strength of the radio communication between the first device and the second device of any of the plurality of second devices, and the identification indicating the second device. Based on the data and the communication data including, the degree of retention of the first device in the second device indicated by the identification data included in the communication data is weighted, and a series of the above based on the weighting result. From the communication data, the processing for identifying the communication data in which the radio wave strength is erroneously detected due to the influence of the wireless communication environment is executed.

According to the present invention, the accuracy of positioning is improved.

FIG. 1 is a block diagram showing a configuration example of an information processing apparatus according to the first embodiment. FIG. 2 is a flowchart showing an operation example of the weighting process by the information processing apparatus 10 according to the first embodiment. FIG. 3 is a flowchart showing an operation example of the specific processing of the information processing apparatus 10 according to the first embodiment. FIG. 4 is an explanatory diagram showing a configuration example of the positioning support system according to the second embodiment. FIG. 5 is an explanatory diagram showing examples of various beacon data. FIG. 6 is a block diagram showing a configuration example of the information processing apparatus 20 according to the second embodiment. FIG. 7 is an explanatory diagram showing an installation example of the fixed device 22 in the factory. FIG. 8 is an explanatory diagram showing an example of the retention characteristic DB 221. FIG. 9 is an explanatory diagram showing an example of the BLE beacon data DB 222. FIG. 10 is an explanatory diagram showing an example of the latest reception time DB 223. FIG. 11 is an explanatory diagram showing the residence characteristic DB 221 after the initial setting. FIG. 12 is an explanatory diagram showing an example of time series data used for weighting. FIG. 13 is an explanatory diagram showing an example of weighting the beacon data 233 at the reception time “0:00:0”. FIG. 14 is an explanatory diagram showing an example of weighting the beacon data 233 at the reception time “0:00: 1”. FIG. 15 is an explanatory diagram showing an example of weighting the beacon data 233 at the reception time “0:00: 2”. FIG. 16 is an explanatory diagram showing an example of weighting the beacon data 233 at the reception time “0:00: 3”. FIG. 17 is an explanatory diagram showing an example of weighting the beacon data 233 at the reception time “0:00: 4”. FIG. 18 is an explanatory diagram showing Example 1 of the time series data and the retention characteristic DB 221. FIG. 19 is an explanatory diagram showing Example 2 of the time series data 241 and the retention characteristic DB 221. FIG. 20 is a sequence diagram showing an operation example of the positioning support system 2 according to the second embodiment before operation. FIG. 21 is a flowchart showing an operation example (addition example) of weighting by the information processing apparatus 20 according to the second embodiment. FIG. 22 is a flowchart showing an operation example (subtraction example) of weighting by the information processing apparatus 20 according to the second embodiment. FIG. 23 is a flowchart showing an operation example of correction by the information processing apparatus 20 according to the second embodiment. FIG. 24 is an explanatory diagram showing an example of hardware configuration when the information processing apparatus is realized by a computer.

Hereinafter, embodiments of the information processing apparatus, positioning support method, and program according to the present invention will be described in detail with reference to the drawings. The present embodiment does not limit the disclosed technology.

First, a general technique used in the description according to the embodiment of the present invention will be described. Further, in the present embodiment, the wireless communication method is not particularly limited, but an example using a beacon will be described. In particular, examples of the beacon include, but are not limited to, a BLE (Bluetooth (registered trademark) Low Energy) beacon and the like. Further, in the present embodiment, for example, an RSSI (Received Signal Strength Indicator) value is used as the value of the radio wave intensity.

For example, positioning of a moving object using a beacon is performed, for example, indoors where satellite signals cannot be used. Positioning of a moving body is to estimate the position of the moving body. The mobile body stays in various places, for example. In the present embodiment, positioning improves the accuracy of the position of the moving body when it stays. Examples of indoors include various stores and various facilities related to various industries. Examples of various industries include food service, distribution, retail, amusement, medical care, and long-term care. In addition, examples of the indoors include factories related to the manufacturing industry and warehouses related to the logistics industry. In addition, a beacon may be used as long as it can be used for positioning regardless of whether satellite signals are used or indoors or outdoors.

Further, examples of the moving object to be positioned include animals such as humans and devices. Examples of the person include a person who works indoors, such as a factory worker and a warehouse worker. Examples of the device include a trolley, a heavy object carrier, an automated guided vehicle (AGV), and the like. Further, the moving body may be an object that can be pushed and moved by a human, such as a dolly.

In positioning using a beacon, for example, a beacon device and a receiver are used. The receiver is a variety of devices capable of receiving Bluetooth radio waves, such as a single board computer such as a Raspberry Pi or a smartphone. Further, when positioning is performed using the beacon device and the receiver, which device (second device) is fixedly arranged among the beacon device and the receiver, and which device (first device) is a moving body. May be attached to. As a first example, a plurality of beacon devices are fixedly arranged and a receiver is attached to a mobile body. As a second example, a plurality of receivers are fixedly arranged and a beacon is attached to the mobile body. As a third example, a plurality of beacon devices are fixedly arranged, and the beacon device is also attached to a mobile body. Positioning in each of the first to third examples will be described.

In the case of the first example, the beacon devices are fixedly arranged indoors in a grid pattern. A receiver attached to a mobile body receives radio waves from multiple beacon devices. Then, the position of the beacon device having the highest radio field strength is detected as the current position of the moving body.

Further, in the case of the second example, a plurality of receivers are fixedly arranged indoors in a grid pattern. The fixedly arranged receiver receives radio waves from the beacon device attached to the mobile body. The position of the receiver received at the highest value among the radio wave intensities of the radio waves received by the fixed receiver group is detected as the current position of the moving body.

Further, in the case of the third example, the beacon devices are fixedly arranged in a grid pattern. The fixedly arranged beacon device receives radio waves from the beacon device attached to the mobile body. The position of the fixed beacon device received at the highest value among the radio wave intensities received by the fixedly arranged beacon device group is detected as the current position of the moving object.

Further, in the first to third examples, the fixedly arranged devices do not have to be fixedly arranged in a grid pattern. For example, receivers and beacon devices may be arranged in a distributed manner so that the accuracy of positioning is improved according to the mobile body, the use of the positioning result, and the like. In this embodiment, any of the first to third examples may be used.

(Embodiment 1)
FIG. 1 is a block diagram showing a configuration example of an information processing apparatus according to the first embodiment. Referring to FIG. 1, the information processing apparatus 10 has a weighting unit 101 and a specific unit 102.

The first device is a device included in the mobile body. The moving body may hold the first device or may be equipped with the first device. Therefore, hereinafter, the first device is referred to as a mobile device. Further, the plurality of second devices are fixedly arranged in advance. Therefore, the second device is hereinafter referred to as a fixed device. For example, a plurality of fixed devices are distributed and fixedly arranged indoors. Wireless communication can be performed between a mobile device and a plurality of fixed devices. As described above, an example of using a beacon as wireless communication will be described. Here, as described above using the first to third examples, the mobile device and the plurality of fixed devices may be either a receiver and any beacon device, or both. May be a beacon device. In the first embodiment, as an example, a mobile device transmits a radio wave of a beacon, and a plurality of fixed devices receive the radio wave. The information processing device 10 is a device that collects communication data obtained by wireless communication between a mobile device and a plurality of fixed devices.

The communication data includes, for example, intensity data regarding the radio field strength of wireless communication between a mobile device and a fixed device among a plurality of fixed devices, and identification data indicating the fixed device. Here, since a beacon device is used, this communication data is referred to as beacon data. Further, the beacon data may include time data relating to the reception time of the radio wave intensity. The reception time of the radio wave strength is a time related to communication between the mobile device and the fixed device. The reception time is not limited to the reception date and time, and the reception date may be used. However, the reception time will be used here. The time related to the communication here may be the time when the information processing apparatus 10 acquires the beacon data. Further, the mobile device or the fixed device may have a function of adding time data indicating the time to the beacon data. For example, when a radio wave is broadcast from a mobile device, the mobile device may transmit beacon data including identification data indicating its own device and time data indicating the time at the time of broadcasting. Alternatively, when the fixed device has a function of managing the time, the fixed device assigns the time data indicating the time at the time of reception and the identification data indicating the own device to the beacon data from the mobile device. You may.

Based on the beacon data, the weighting unit 101 weights the degree of retention of the mobile device in the fixed device indicated by the identification data included in the beacon data. The degree of retention is represented by a weight value or the like. For example, it is assumed that the larger the weight value, the higher the degree of retention. On the other hand, the smaller the weight value, the lower the degree of retention.

The weighting unit 101 may perform weighting each time the information processing device 10 acquires beacon data for any of the fixed devices. Further, the weighting unit 101 calculates the weight value based on the beacon data at each timing so that the degree of retention of the fixed device indicated by the identification data included in the beacon data is higher. Each timing is a timing such as time, date and time, and date. The weighting unit 101 weights, for example, based on the beacon data having the strongest reception strength among the beacon data at the same time. Here, when a radio wave signal is transmitted from each fixed device, it is assumed that the strength of the radio wave signal at the time of transmission is substantially the same. More specifically, the weighting unit 101 adds a predetermined value to the weight value for the fixed device indicated by the identification data included in the beacon data. As a result, the value of the weight becomes large, and the degree of the weight becomes higher than that before the addition. Such a weight value is an example of a weighting result.

Further, the specifying unit 102 identifies, among a series of beacon data (a series of communication data), the beacon data having a large error in radio wave intensity due to the influence of the wireless communication environment, based on the weighting result. In the case of the present embodiment, the series of beacon data (series of communication data) is time-series beacon data (communication data) by wireless communication between the mobile device and the plurality of fixed devices. Beacon data with a large error is called false detection beacon data. Various methods for identifying false detection beacon data based on the weighting result can be mentioned depending on the weighting method and the like.

For example, the specifying unit 102 may specify the beacon data for a fixed device having a low degree of retention as the erroneous detection beacon data among a series of beacon data based on the weighting result. For example, the specifying unit 102 may specify the false detection beacon data based on the comparison between the weight value related to the degree of retention and the threshold value. Specifically, the specific unit 102 may be erroneous detection beacon data as long as the weight value is equal to or less than the threshold value.

Specifically, the specifying unit 102 specifies the first residence time representing the residence time of the mobile device in the fixed device in which the identification data is included in the series of beacon data, based on the series of beacon data. Then, the specifying unit 102 identifies the erroneous detection beacon data based on the specified first residence time and the weighting result.

Further, for example, a series of beacon data such as the following is targeted for processing. For example, a series of beacon data to be processed has a plurality of beacon data for a certain fixed device in chronological order from the earliest. A fixed device is called a point device from beginning to end. Of the series of beacon data, the beacon data following these beacon data in chronological order is the beacon data for a fixed device different from the starting point device. This different fixed device is called a waypoint device. The number of waypoint devices may be multiple or may be one. Then, of the series of beacon data, the last beacon data in the time series is the beacon data for the starting point device again. That is, this series of beacon data indicates that the mobile device is first in the vicinity of the start point device. Then, this series of beacon data indicates that the mobile device has once moved to the vicinity of the waypoint device and then returned to the vicinity of the start point device, and the mobile device is always in the vicinity of the start point device. It may indicate that you were there. If the mobile device is always in the vicinity of the point device, the beacon data for the waypoint device out of the series of beacon data is likely to be a false positive beacon. Here, in the series of beacon data, it is not clear whether the mobile device went near the waypoint device or whether the beacon data was erroneously detected due to the influence of the communication environment.

Therefore, by targeting such a series of beacon data for processing, the beacon data for the waypoint device becomes a candidate for the beacon data for erroneous detection. Therefore, the specific unit 102 calculates the first residence time for the waypoint device. On the other hand, the beacon data for the start point device is not a candidate for false detection beacon data. Therefore, the specific unit 102 may not calculate the first residence time for the start point device. The specific unit 102 receives the time (starting point time) at which the radio wave from the mobile device is received earliest in the time series and the radio wave from the mobile device at the latest in the time series in the series of beacon data for each waypoint device. The first residence time is calculated based on the difference between the received time (end point time) and. Not limited to the time, it may be a date or a date and time. The specific unit 102 sets the time obtained by subtracting the start point time from the end point time as the first residence time.

Further, the specifying unit 102 identifies erroneous detection beacon data from a series of beacon data by using the second residence time and the first residence time. The second residence time is the residence time of the mobile device in the fixed device based on the weighting result. Specifically, the specific unit 102 calculates the second residence time using, for example, the standard residence time for each fixed device and the weighting result. The standard residence time is specified in advance by the user or the administrator. Further, the standard residence time is specified, for example, based on the characteristics of the room where the fixed device is arranged and the characteristics of the movement of the moving body. For example, in the morning hours, it is highly likely that workers are generally in a certain workplace. For example, the standard dwell time for fixed equipment placed in the workplace is longer than the standard dwell time for other fixed equipment.

For example, the standard residence time is set as the maximum value of the second residence time, and the higher the degree of residence, the closer to the maximum value of the second residence time. Alternatively, the weighting unit 101 may perform weighting so that the maximum value of the second residence time is the standard residence time. Then, the specific unit 102 may calculate the second residence time based on the product of the weight value and the standard residence time.

Then, the specifying unit 102 identifies the false detection beacon data from the series of beacon data based on the comparison between the first residence time and the second residence time for each waypoint device. Specifically, the specific unit 102 determines, for example, whether or not the first residence time is less than the second residence time for all the waypoint devices. Then, for example, when the first residence time is less than the second residence time for all the waypoint devices, the specifying unit 102 specifies the beacon data for all the waypoint devices as the erroneous detection beacon data. That is, when the false positive beacon data is identified, the mobile device is always in the vicinity of the point device, according to the set of beacon data. On the other hand, when the first residence time is not less than the second residence time for any of the waypoint devices, the specifying unit 102 does not specify the erroneous detection beacon data. That is, when the false detection beacon data is not specified, the mobile device is in the vicinity of the start point device according to the series of beacon data. Then, according to a series of beacon data, the mobile device passes through the vicinity of the waypoint device and then returns to the vicinity of the start point device.

Further, there is no particular limitation on how the user of the information processing apparatus 10 or the like uses the specified false detection beacon data. Further, the specific unit 102 may add data indicating that an error is large to the specified false detection beacon data. Further, the information processing device 10 may output the false detection beacon data to an output device or the like.

FIG. 2 is a flowchart showing an operation example of the weighting process by the information processing apparatus 10 according to the first embodiment. Here, the processing result of each step by the information processing apparatus 10 in FIG. 2 is stored in a storage unit accessible to the information processing apparatus 10 such as a memory. As shown in FIG. 2, first, the information processing apparatus 10 acquires the beacon data (step S101). In step S101, the information processing device 10 may receive the beacon data from the fixed device. Further, the information processing apparatus 10 may receive the beacon data from the gateway or the like. When the beacon data here does not include the time data, the information processing apparatus 10 adds the time data indicating the reception time when the beacon data is received to the beacon data.

Next, the information processing apparatus 10 identifies the beacon data having the maximum reception intensity (step S102). For example, at each time, beacon data is transmitted from one or more fixed devices. Therefore, in step S102, when there are a plurality of beacon data at each time, the information processing apparatus 10 identifies the beacon data having the stronger radio wave strength.

Next, the information processing apparatus 10 performs weighting based on the beacon data specified in step S102 (step S103). The information processing apparatus 10 adds a predetermined value to, for example, a weight value for a fixed device indicated by identification data included in the specified beacon data. As a result, the value of the weight becomes large, and the degree of the weight becomes higher than that before the addition.

Then, the information processing apparatus 10 stores the weighting result and the identified beacon data (step S104). The information processing apparatus 10 ends the flow operation after step S104.

FIG. 3 is a flowchart showing an operation example of the specific processing of the information processing apparatus 10 according to the first embodiment. Here, the processing result of each step by the information processing apparatus 10 in FIG. 3 is stored in a storage unit accessible to the information processing apparatus 10 such as a memory. As shown in FIG. 3, first, the information processing apparatus 10 extracts a series of beacon data from each beacon data stored in step S104 of FIG. 2 (step S111).

Next, the information processing apparatus 10 identifies the false detection beacon data based on the weighting result (step S112). Then, the information processing apparatus 10 outputs a specific result (step S113). The information processing apparatus 10 ends the flow operation after step S113.

Next, the effect of the first embodiment will be described. The information processing apparatus 10 in the present embodiment described above identifies beacon data having a large error in radio wave intensity due to the influence of the communication environment, based on the weighting result of the degree of retention of the mobile device in the fixed device. As a result, it is possible to notify the user of beacon data having a large error in radio wave strength due to the influence of the communication environment. Therefore, the user can perform positioning in consideration of the false detection beacon data. In addition, the user may analyze obstacles and the like that affect the communication environment and the degree of the influence by using the false detection beacon data.

The information processing apparatus 10 uses, for example, beacon data having a large error in radio field strength due to the communication environment based on the first residence time and the weighting result of the residence of the mobile device in the fixed device in which the identification data is included in the series of beacon data. Identify. Thereby, the information processing apparatus 10 can specify how much the mobile device actually stays in each fixed device from the series of beacon data. Therefore, the information processing apparatus 10 can improve the accuracy of specifying the false detection beacon data.

In addition, a standard time (standard residence time) for the moving body to stay in the fixed device is prepared in advance. Then, the information processing apparatus 10 identifies the false detection beacon data by using the weighting result based on the movement of the actual moving body, the second residence time based on the standard residence time, and the first residence time. The standard residence time is corrected from the set uniform standard residence time and the weighting result based on the actual movement. Then, the information processing apparatus 10 can more accurately identify the false detection beacon data by comparing the first residence time in the series of beacon data with the corrected standard residence time (second residence time). ..

In addition, which fixed device the moving object stays in the vicinity of is different depending on the moving object, the work of the moving object, the time zone, and the like. Therefore, a standard residence time is prepared for each fixed device, and the information processing apparatus 10 obtains a standard residence time for each fixed device and a second residence time based on the weighting result obtained by weighting. Then, based on the comparison between the first residence time and the second residence time in the series of beacon data, the erroneous detection beacon data is specified. As a result, if the first residence time in the series of beacon data is longer than the second residence time, it is highly possible that the mobile body actually stayed near the fixed device. On the other hand, when the first residence time is less than the second residence time, it is unlikely that the moving body has accumulated near the fixed device. As a result, the characteristics of the movement of the moving body are taken into consideration, and the beacon data of false detection can be specified more accurately.

Further, the series of beacon data has a plurality of beacon data for the starting point device in the order of earliest in chronological order. Then, the series of beacon data has the beacon data for the waypoint device different from the start point device. Further, among the series of beacon data, the slowest beacon data in the time series includes identification data indicating the starting point device. As a result, attention is paid to the retention of the mobile device in a certain fixed device (starting point device). Then, it is specified whether or not the mobile device has actually moved from one fixed device (starting point device) to another fixed device (via point device). Then, when it is presumed that the mobile device is not actually moving, it is specified that a large error has occurred in the radio field strength of the communication between the mobile device and the waypoint device due to the influence of the communication environment. This makes it possible to more accurately identify the false detection beacon data.

That is, if the first residence time based on a series of beacon data is equal to or longer than the second residence time, which is the standard residence time considering the weighting result, it is possible that the mobile device actually moved near the waypoint device. Highly sex. On the other hand, if the first residence time based on the series of beacon data is less than the second residence time, which is the standard residence time considering the weighting result, the mobile device is actually moving near the waypoint device. Not likely. That is, if the first residence time is less than the second residence time, there is a high possibility that a large error has occurred in the reception strength due to the influence of the communication environment. In addition, the standard residence time is just an estimated value by the user or administrator. Therefore, the information processing apparatus 10 corrects the standard residence time based on the weighting result. As a result, the information processing apparatus 10 can obtain a standard residence time (second residence time) in which the mobile device is likely to actually be in the waypoint device. Therefore, the information processing apparatus 10 can more accurately identify the false detection beacon data.

(Embodiment 2)
Next, Embodiment 2 of the present invention will be described in detail with reference to the drawings. Hereinafter, to the extent that the description of the second embodiment is not unclear, the description of the contents overlapping with the above description will be omitted.

FIG. 4 is an explanatory diagram showing a configuration example of the positioning support system according to the second embodiment. In FIG. 4, the positioning support system 2 includes an information processing device 20, a plurality of fixed devices 22, a mobile device 23, a gateway 21, and a visualization terminal device 24. The positioning support system 2 according to the second embodiment will be described with reference to the third example described above, but is not particularly limited. For this reason, the plurality of fixed devices 22 and the mobile device 23 use different pictures in FIG. 4 for easy understanding, but they are all beacon devices.

The mobile device 23 is the first device. For example, one mobile device 23 is provided for the mobile device. Then, the mobile device 23 is attached to the mobile body. As a result, the mobile device 23 moves together with the mobile device. The mobile device 23 transmits beacon data including mobile device ID (IDentify) data, which is identification data of the mobile body, to the surroundings. An example of beacon data will be described later with reference to FIG. In the example of FIG. 4, since there is only one mobile body, only one mobile device 23 is shown, but when there are a plurality of mobile bodies, the mobile device 23-1 to the mobile device 23-m, etc. Each mobile unit has a mobile device 23. Note that m is a positive integer of 2 or more.

The plurality of fixed devices 22-1 to 22-n are second devices. The plurality of fixed devices 22-1 to 22-n are distributed and fixedly arranged in a predetermined area 25. n is a positive integer greater than or equal to 2. The predetermined area 25 is, for example, indoors as described above. When the indoor space is, for example, a manufacturing factory, the plurality of fixed devices 22-1 to 22-n are fixedly arranged in a manufacturing line, an office, a resting place, each device (for example, a manufacturing device, etc.). An example of arranging a plurality of fixed devices 22 when the predetermined area 25 is a factory will be described later with reference to FIG. 7.

Further, each fixed device 22 receives the beacon data transmitted from the mobile device 23. The fixed device 22 adds fixed device ID data and intensity data to the received beacon data. The fixed device ID data is identification data indicating the fixed device 22. The intensity data is data indicating the value of the radio wave intensity when the beacon data is received from the mobile device 23. Then, the fixed device 22 transmits the beacon data including the mobile device ID data, the fixed device ID data, and the intensity data to the gateway 21 or the information processing device 20. An example of beacon data transmitted from the fixed device 22 to the gateway 21 or the information processing device 20 will be described later with reference to FIG. The plurality of fixed devices 22-1 to 22-n may use multi-hop communication or the like without directly transmitting the beacon data to the gateway 21 or the information processing device 20.

Further, the gateway 21 receives the beacon data transmitted from the plurality of fixed devices 22. Then, the gateway 21 converts the beacon data into a data structure that can be received by the information processing apparatus 20. The data structure here means a protocol. Then, the gateway 21 transmits the converted beacon data to the information processing apparatus 20. When the beacon data transmitted by the fixed device 22 has a data structure that can be received by the information processing device 20, the positioning support system 2 may be configured to be directly received by the server without providing the gateway 21. good.

Further, the information processing apparatus 20 receives and aggregates beacon data from each fixed device 22 or the gateway 21. In FIG. 4, the information processing device 20 is a server. However, the information processing device 20 does not have to be a server. The information processing device 20 may add time data to the received beacon data. The time data indicates, for example, the reception time when the information processing apparatus 20 receives the beacon data. It has mobile device ID data, intensity data, fixed device ID data, and time data.

For example, when there are a plurality of mobile devices 23, the information processing device 20 aggregates beacon data for each mobile device 23. Further, the information processing device 20 generates data that can be output by the visualization terminal device 24 based on the aggregation result of the beacon data. Then, the information processing device 20 transmits the generation result to the visualization terminal device 24, the storage server accessible to the visualization terminal device 24, and the like. Alternatively, the information processing device 20 may store the generation result in the storage unit of its own device, and the visualization terminal device 24 may acquire the generation result stored in the storage unit of the information processing device 20. The detailed functions of the information processing apparatus 20 will be described later with reference to FIG.

The visualization terminal device 24 outputs the generation result to the output device. Examples of the output device include a display and the like. For example, the visualization terminal device 24 displays, for example, a screen based on the generation result on the display. The visualization terminal device 24 may display the generation result by a Web browser or the like. Alternatively, if a dedicated application capable of displaying the positioning result or the like is installed in advance, the visualization terminal device 24 may output the generation result by the dedicated application. Further, the information processing device 20 and the visualization terminal device 24 may be the same device.

FIG. 5 is an explanatory diagram showing examples of various beacon data. The beacon data 231 is transmitted from the mobile device 23.

Beacon data 232 is transmitted from the fixed device 22. The beacon data 232 includes mobile device ID data, fixed device ID data, and intensity data. The fixed device ID data is identification data of the fixed device 22. The intensity data indicates the radio wave intensity when the fixed device 22 receives the beacon data from the mobile device 23.

The beacon data 233 is used by the information processing apparatus 20. The beacon data 233 has mobile device ID data, fixed device ID data, intensity data, and time data. The time data is time data relating to the time of wireless communication between the mobile device 23 indicated by the mobile device ID data and the fixed device ID indicated by the fixed device ID data. Specifically, the time data is data indicating the reception time when the information processing apparatus 20 receives the beacon data 232 from the fixed device 22 or the gateway 21. Further, the data included in the beacon data 233 is not limited to the time data, but may be data indicating the reception date and time or data indicating the reception date.

Further, the fixed device 22 may have a function such as a real-time clock that can specify the time and date. In such a case, the fixed device 22 is the time when the fixed device 22 receives the beacon data 231 from the mobile device 23 as time data indicating the time of wireless communication between the mobile device 23 and the fixed device 22. The time data indicating the above may be added to the beacon data 231. Alternatively, the gateway 21 adds time data indicating the reception time to the beacon data 232. Then, the gateway 21 may transmit the added beacon data 233 to the information processing apparatus 20.

Further, the beacon data 231 and the beacon data 232 and the beacon data 233 may have other data depending on the purpose of positioning.

FIG. 6 is a block diagram showing a configuration example of the information processing apparatus 20 according to the second embodiment. In FIG. 6, the information processing apparatus 20 has a storage unit 211 and each functional unit. The information processing apparatus 20 has, as each functional unit, an acquisition unit 203, a setting unit 204, an aggregation unit 205, a weighting unit 201, a specific unit 202, a correction unit 206, and an output control unit 207. First, the storage unit 211 stores the processing results of each function of the information processing apparatus 20. Further, the storage unit 211 stores data used for processing of each unit. The storage content of the storage unit 211 in FIG. 6 is an example and is not particularly limited.

Further, the information processing apparatus 20 may be able to access various data, and a part of the stored contents of the storage unit 211 shown in FIG. 6 is stored in the storage unit 211, and the data other than the part of the data is information. It may be stored in a storage unit or the like of another device that the processing device 20 can access. However, as will be described in detail with reference to the hardware configuration example shown in FIG. 24, the information processing apparatus 20 loads and executes a program including various instructions for realizing each functional unit in the storage unit 211. Further, for the sake of facilitation of explanation, one storage unit 211 is shown, but the storage unit 211 is not limited to this. For example, the storage unit 211 may be various combinations such as ROM (Read Only Memory), RAM (Random Access Memory), semiconductor memory, HDD (Hard Disk Drive), SSD (Solid State Drive), and the like.

Specifically, the storage unit 211 stores the retention characteristic DB (Database) 221, the BLE beacon data DB 222, and the latest reception time DB 223. Further, the storage unit 211 stores various data indicating the retention coefficient, the non-retention coefficient, the non-reception determination time, the non-reception determination interval, and the like.

The retention characteristic DB 221 stores a weighting result regarding the degree of retention of the mobile device 23 in the fixed device 22 and various numerical values used for the weighting. Various numerical values may be set for the retention characteristic DB 221 for each fixed device 22. For facilitation of understanding and explanation, an installation example of the fixed device 22 will be described before the detailed description of the retention characteristic DB 221.

FIG. 7 is an explanatory diagram showing an installation example of the fixed device 22 in the factory. The case where the indoor is a factory of products is shown as an example. In the factory, there are parts shelves, repair lines, various product lines, various packing materials storage, temporary storage storage, shipping storage, garbage dump, shipping storage, office, smoking area, etc. In FIG. 7, fixed devices 22-1 to 22-8 are installed in the factory. The installation location of each fixed device 22 is determined based on the retention characteristics and movement characteristics of the moving body to be positioned.

For example, the worker who is the target moving body stays in front of the production line or the parts shelf while working on the production line or the parts shelf. No workers are in the workplace outside of working hours such as at night or on holidays. In addition, workers take a break at a resting place. Also, for example, trolleys and AGVs stop in front of production lines, parts shelves, etc. for unloading. In addition, due to changes in the production line and movement of parts storage locations, the residence locations of workers and trolleys change daily.

In this way, depending on the target mobile body, working hours of the day, non-working hours, etc., the mobile body may stop for a certain period of time at the work place, change the staying place or time, or leave the work place for a long time. There are properties such as. Therefore, the fixing device 22 is installed according to the position based on the target moving body.

Next, the retention characteristic DB 221 will be described. FIG. 8 is an explanatory diagram showing an example of the retention characteristic DB 221. The retention characteristic DB 221 has various information about the degree of retention, a weighting result, and the like for each fixed device ID. The retention characteristic DB 221 has fields of a fixed device ID, a standard residence time, a weight A, a weight B, and a weight C. For example, by setting information in each field, one record 2000 (for example, 2000-1) is stored in the retention characteristic DB 221.

The fixed device ID is an identifier indicating the fixed device 22. Here, for example, when the fixed device ID is "1" as in the record 2000-1, the fixed device 22-1 is indicated. The standard residence time is information about the characteristics of retention. Specifically, the standard residence time is the standard time for the moving body to stay in the vicinity of the fixed device 22 indicated by the fixed device ID. The standard residence time may be, for example, a uniquely determined value, or may be set by the administrator of the information processing apparatus 20, the user of the information processing apparatus 20, or the like. For example, the standard residence time may be set to an initial value at the start of operation. Then, after the operation of the positioning support system 2 is started, the value of the standard residence time is changed by the user of the positioning support system 2 according to the change of the factory environment such as the change of the factory production line and the change of the working style of the worker. May be done. For example, in record 2000-1, the standard residence time is 300 seconds.

The weight A, the weight B, and the weight C are used for weighting. Here, the value of the weight A is a fixed value. The weight B and the weight C indicate the degree of retention of the moving body in the vicinity of the fixed device 22 indicated by the fixed device ID. Specifically, for example, the larger the value, the higher the degree of retention of the weight A, the weight B, and the weight C, and the smaller the value, the lower the degree of retention. If the degree of retention is high, the retention time of the moving body in the fixed device 22 is long. On the other hand, if the degree of retention is low, the residence time of the moving body in the fixed device 22 is short.

The value of the weight B is a value that changes due to the weighting of the information processing apparatus 20 after the operation of the positioning support system 2 is started. The value of the weight C is a value based on the value of the weight A and the value of the weight B. The value of the weight C is a value that changes by weighting like the value of the weight B. Further, the value of the weight C is used to correct the standard residence time specified by the user. As will be described later, the standard residence time based on the degree of residence can be obtained by the product of the standard residence time specified by the user and the value of the weight C.

Specifically, for example, "51" is set for the weight A. Further, the maximum value of the weight A is set, and for example, the maximum value is "51". For the weight B, for example, "0" is set as an initial value. Further, for the weight B, for example, a maximum value and a minimum value are defined. The maximum value of the weight B is smaller than the value of the weight A. When the value of the weight A is "51", the maximum value of the weight B is set to, for example, "49". The minimum value of the weight B is, for example, an initial value. The value of the weight C is determined by the following (Equation 1).

Value of weight C = (value of weight A + value of weight B) ÷ (maximum value of weight A + maximum value of weight B)
... (Equation 1)

Further, the retention characteristic DB 221 is not limited to the example of FIG. As described above, the characteristics of retention differ depending on whether the moving body is a person or a device, which work is performed by the worker, and the like. Therefore, each record may be set for the retention characteristic DB 221 for each mobile device 23, for example. Alternatively, the retention characteristic DB 221 may be prepared for each moving body. The standard residence time of the retention characteristic DB221 may be prepared for each time zone, day of the week, weekdays / holidays, and the like.

FIG. 9 is an explanatory diagram showing an example of the BLE beacon data DB 222. The BLE beacon data DB 222 stores, for example, the beacon data at each timing for each mobile device ID. In the BLE beacon data DB 222 in FIG. 9, the beacon data may be stored in chronological order. In the BLE beacon data DB 222 in FIG. 9, the series of beacon data is time-series beacon data for each mobile device ID. That is, in the BLE beacon data DB 222 in FIG. 9, a plurality of beacon data in the row direction is a series of beacon data.

FIG. 10 is an explanatory diagram showing an example of the latest reception time DB 223. The latest reception time DB 223 is a database for managing the latest reception time for each mobile device 23 or for each combination of the mobile device 23 and the fixed device 22. The latest reception time DB 223 has fields for a mobile device ID, a fixed device ID, and the latest reception time. By setting information in each field, one record is stored in the latest reception time DB223.

The mobile device ID is an identifier indicating the mobile device 23. Here, for the sake of facilitation of explanation, for example, when the mobile device ID is "1", the mobile device 23-1 is shown. The fixed device ID is an identifier indicating the fixed device 22. For example, as the latest reception time, the reception time of the beacon data 233 most recently received by the information processing apparatus 20 is set for each mobile device 23 or for each combination of the mobile device 23 and the fixed device 22. The details will be described later, but for example, the reception time of the beacon data 233 aggregated by the aggregation unit 205 is set. Further, the field of the latest reception time is not limited to the latest reception time, and the latest reception date / time or the latest reception date may be set. "//" Indicates the date in the Christian era. "::" Indicates the time. "20xx / xx / xx xx: xx: xx" indicates, for example, "20xx year xx month xx day xx hours xx minutes xx seconds".

This is the end of the explanation of storage examples of various databases. Next, returning to the description of FIG. 6, various functional units of the information processing apparatus 20 will be described. As described above, the information processing apparatus 20 includes an acquisition unit 203, a setting unit 204, an aggregation unit 205, a weighting unit 201, a specific unit 202, a correction unit 206, and an output control unit 207. First, the initial setting process before the start of operation of the positioning support system 2 and various processes during operation will be described separately.

<Initial setting>
The acquisition unit 203 acquires various data. The acquisition unit 203 may acquire various data via, for example, a reception unit of a communication interface that can be connected to a communication network. Further, the acquisition unit 203 may acquire various data via an input device capable of accepting various inputs. Further, the acquisition unit 203 may be a reception unit or an input device itself.

The acquisition unit 203 acquires, for example, the standard residence time, residence coefficient, non-retention coefficient, non-reception determination time, non-reception determination interval, etc. for each fixed device 22 before the operation of the positioning support system 2 starts. For example, the visualization terminal device 24 displays a screen on which a quasi-residence time, a retention coefficient, a non-retention coefficient, a non-reception determination time, a non-reception determination interval, and the like can be input. Then, for example, the user inputs these data by using the input device of the visualization terminal device 24 or the like. The visualization terminal device 24 accepts the input of these data. Then, the visualization terminal device 24 transmits these data to the information processing device 20. The acquisition unit 203 receives each standard residence time, residence coefficient, non-retention coefficient, non-reception determination time, non-reception determination interval, etc. transmitted from the visualization terminal device 24 that has received the input.

The retention coefficient is used for weighting to increase the degree of retention. The value that can be set as the retention coefficient is 0 or more, and is a numerical value equal to or less than the maximum value of the weight B. The value of the retention coefficient may be a value including a decimal value such as "0.1" or "1.1". The non-reception determination time is used as a threshold value for the time during which communication between the mobile device 23 and the fixed device 22 is not performed. The non-retention coefficient is used for weighting in which the degree of retention is low when the communication between the mobile device 23 and the fixed device 22 is not performed for the non-reception determination time. The value of the non-retention coefficient is, for example, 0 or more and is a numerical value equal to or less than the maximum value of the weight B. The value of the non-retention coefficient may be a value including a decimal value such as "0.1" or "1.1". The non-reception determination interval is used as a processing interval for weighting processing to reduce the degree of retention.

For example, in the second embodiment, the following is used as the initial setting value.

・ Retention coefficient: 1
-Non-reception judgment time: 3600 [seconds]
・ Non-retention coefficient: 1
-Non-reception judgment interval: 1 [second]
The setting unit 204 sets the standard residence time acquired by the acquisition unit 203 in the residence characteristic DB 221. Further, the setting unit 204 stores the retention coefficient, the non-retention coefficient, the non-reception determination time, and the non-reception determination interval acquired by the acquisition unit 203 in the storage unit 211.

Further, the setting unit 204 sets the initial value (fixed value) of the weight A and the initial value of the weight B. As the initial value (fixed value) of the weight A and the initial value of the weight B, a predetermined value may be set. Alternatively, the initial value of the weight B and the initial value of the weight B may be specified by the user in the same manner as various data. Further, the setting unit 204 sets the value of the weight C based on the value of the weight A after the setting, the value of the weight B, and (Equation 1).

FIG. 11 is an explanatory diagram showing the residence characteristic DB 221 after the initial setting. In FIG. 11, for the fixed device 22-X, the standard residence time is set to 60 seconds. For the fixed device 22-Y, the standard residence time is set to 5 seconds. For the fixed equipment 22-Z, the standard residence time is set to 10 seconds. Further, the value of the weight A is set to "51" as an initial value (fixed value). As the value of the weight B, "0" is set as an initial value. Further, the value of the weight C is set based on the value of the weight A, the value of the weight B, and (Equation 1). Therefore, the value of the weight C is set to 0.51. A sequence diagram before the start of operation of the positioning support system 2 is shown in FIG. This is the end of the explanation before the start of operation of the positioning support system 2.

<During operation of positioning support system 2>
Next, various processes related to the operation of the positioning support system 2 will be described. The acquisition unit 203 acquires the beacon data 232. Specifically, the acquisition unit 203 receives the beacon data 232 from the gateway 21 or the fixed device 22 via a communication interface or the like that can be connected to the communication network. Further, the acquisition unit 203 generates the beacon data 233 by adding the time data to the received beacon data 232. Examples of the time data here include date and time data indicating the reception date and time when the information processing apparatus 20 received the beacon data 232 and time data indicating the reception time.

The aggregation unit 205 aggregates the beacon data 233 acquired by the acquisition unit 203. Specifically, the aggregation unit 205 aggregates the beacon data 233 so that the beacon data 233 can be managed for each mobile device ID, for example.

The aggregation unit 205 aggregates the beacon data 233 so as to leave the beacon data 233 for the fixed device 22 in which the mobile body is presumed to be closest to the plurality of fixed devices 22. Specifically, the aggregation unit 205 identifies, for example, the beacon data 233 having the highest radio field intensity indicated by the intensity data among a plurality of beacon data 233s having time data indicating the same reception time. Then, the aggregation unit 205 registers the specified beacon data 233 in the BLE beacon data DB 222. More specifically, for example, the aggregation unit 205 stores the "latest beacon data" as "immediately preceding beacon data" in the BLE beacon data DB 222. Then, the aggregation unit 205 stores the newly specified beacon data 233 as "latest beacon data". In this way, the aggregation unit 205 stores the beacon data in time series in the BLE beacon data DB 222.

On the other hand, the aggregation unit 205 discards the beacon data 233 other than the beacon data 233 having the highest radio field strength among the plurality of beacon data 233s. Discarding simply means not storing in the storage unit 211 or the like. The aggregation unit 205 may separately store the beacon data 233 other than the beacon data 233 having the highest radio wave strength in the storage unit 211 or the like for information collection.

Further, the aggregation unit 205 may exclude the beacon data 233 and the like having an extremely large radio wave intensity value in advance. As a result, the beacon data 233 whose radio wave intensity value is an abnormal value is excluded in advance, such as when the radio wave intensity is larger than the radio wave intensity generated in the communication between the mobile device 23 and each fixed device 22.

The aggregation unit 205 updates the latest reception time DB 223 based on the beacon data 233 having the highest radio field strength. Specifically, the aggregation unit 205, for example, among the data included in the beacon data 233 having the highest radio wave intensity, the mobile device ID data, the fixed device ID data, and the date / time data or the reception time indicating the reception date / time. The indicated time data and the latest reception time DB 223 are stored.

This is the end of the description of the aggregation of the beacon data 233 by the aggregation unit 205. Next, the weighting by the weighting unit 201 will be described. The weighting unit 201 has the function of the weighting unit 101 described in the first embodiment. The weighting by the weighting unit 201 is performed based on the characteristics of retention. Here, there are cases where weighting is performed so that the degree of retention is higher, and cases where weighting is performed so that the degree of retention is lower. In the second embodiment, increasing the degree of retention means increasing the value of the weight B. Further, when the degree of retention becomes lower, the value of the weight B decreases. First, a case where the degree of retention is high will be described.

The weighting unit 201 weights the retention characteristics of the mobile device 23 in the fixed device 22 based on the beacon data 233. The fixed device 22 is indicated by the fixed device ID data included in the beacon data 233. The weighting regarding the characteristic of retention is, for example, the weighting regarding the degree of retention. Here, the weighting unit 201, for example, weights so that the degree of retention is higher. The weighting unit 201 increases the degree of retention by adding the value of the retention coefficient to the value of the weight B for the fixed device 22 indicated by the fixed device ID data included in the latest beacon data 233, for example. More specifically, the weighting unit 201 updates the value of the weight B based on the following (Equation 2).

Value of weight B after update = Min ((value of weight B before update + value of retention coefficient), 49)
... (Equation 2)

Here, Min (a, b) is a function that returns the smallest value among a and b. Further, 49 is the maximum value of the weight B. As described above, the maximum value of the weight B is not greater than or equal to the value of the weight A. Since the value of the weight A is set to "51" as shown in FIG. 11, the maximum value of the weight B is set to "49". Further, by preventing the value of the weight B from exceeding the maximum value of the weight B, it is possible to prevent the result of the product of the weight C and the standard residence time from becoming larger than the standard residence time.

Further, the weighting unit 201 may perform weighting when the "immediately preceding beacon data" and the "latest beacon data" include the same fixed device ID data in the same mobile device ID. On the other hand, the weighting unit 201 may not perform weighting when the immediately preceding beacon data and the latest beacon data do not include the same fixed device ID data in the same mobile device ID. As a result, the value of the weight B is updated when the mobile device 23 is continuously received from the same mobile device 23.

The weighting unit 201 calculates the residence time in which the mobile device 23 stays in the vicinity of the fixed device 22 by using each beacon data 233 stored in the BLE beacon data DB 222. Then, the weighting unit 201 may perform weighting based on the residence time. Specifically, the weighting unit 201 weights, for example, so that the longer the residence time, the higher the degree of retention of the fixed device 22. The weighting unit 201 sets, for example, a larger value of the weight B according to the residence time. For example, the weighting unit 201 may add a residence coefficient according to the residence time to the value of the weight B. Next, an example in which weighting for increasing the degree of retention is performed will be described with reference to FIGS. 12 to 17.

FIG. 12 is an explanatory diagram showing an example of time series data used for weighting. FIG. 12 shows the beacon data 233 after aggregation by the aggregation unit 205. That is, FIG. 12 shows a communication device having the highest radio field strength of communication with the mobile device 23-1 at each time. Here, for the sake of facilitation of explanation, in FIG. 12, the reception time indicated by the time data included in the beacon data 233 and the fixed device ID indicated by the fixed device ID data included in the beacon data 233 are shown. The time data indicates the reception time in the information processing apparatus 20.

According to FIG. 12, at the reception time “0:00:0”, the radio wave intensity of the communication between the mobile device 23-1 and the fixed device 22-X is the highest. At the reception time "0:00: 1", the radio field strength of the communication between the mobile device 23-1 and the fixed device 22-X is the highest. At the reception time "0:00:2", the radio field strength of the communication between the mobile device 23-1 and the fixed device 22-Y is the strongest. At the reception time "0:00: 3", the radio field strength of the communication between the mobile device 23-1 and the fixed device 22-Z is the highest. At the reception time "0:00:4", the radio field strength of the communication between the mobile device 23-1 and the fixed device 22-X is the strongest.

Here, for ease of understanding, the reception time is shown in chronological order, but the weighting unit 201 performs weighting after aggregation by the aggregation unit 205 each time the beacon data 233 is received. Next, FIGS. 13 to 17 show an example of weighting at each reception time.

FIG. 13 is an explanatory diagram showing an example of weighting the beacon data 233 at the reception time “0:00:0”. The weighting unit 201 adds the retention coefficient value "1" to the value of the weight B for the fixed device 22-X in the retention characteristic DB 221 for the latest reception time "0:00:0" in the latest reception time DB223. .. Therefore, in the retention characteristic DB 221 of FIG. 13, "1" is set as the value of the weight B with respect to the fixed device 22-X. Further, the weighting unit 201 sets the value of the weight C based on the new value of the weight B for the fixed device 22-X and (Equation 1). In the retention characteristic DB 221 of FIG. 13, "0.52" is set as the value of the weight C with respect to the fixed device 22-X.

FIG. 14 is an explanatory diagram showing an example of weighting the beacon data 233 at the reception time “0:00: 1”. The weighting unit 201 adds the retention coefficient value "1" to the value of the weight B for the fixed device 22-X in the retention characteristic DB 221 for the latest reception time "0:00: 1" in the latest reception time DB 223. .. Therefore, in the retention characteristic DB 221 of FIG. 14, "2" is set as the value of the weight B with respect to the fixed device 22-X. Further, the weighting unit 201 sets the value of the weight C based on the new value of the weight B for the fixed device 22-X and (Equation 1). In the retention characteristic DB 221 of FIG. 14, the value of the weight C with respect to the fixed device 22-X is set to "0.53".

FIG. 15 is an explanatory diagram showing an example of weighting the beacon data 233 at the reception time “0:00: 2”. The weighting unit 201 adds the retention coefficient value "1" to the value of the weight B for the fixed device 22-Y in the retention characteristic DB 221 for the latest reception time "0:00: 2" in the latest reception time DB 223. .. Therefore, in the retention characteristic DB 221 of FIG. 15, "1" is set as the value of the weight B with respect to the fixed device 22-Y. Further, the weighting unit 201 sets the value of the weight C based on the new value of the weight B for the fixed device 22-Y and (Equation 1). In the retention characteristic DB 221 of FIG. 15, "0.53" is set as the value of the weight C with respect to the fixed device 22-Y.

FIG. 16 is an explanatory diagram showing an example of weighting the beacon data 233 at the reception time “0:00: 3”. The weighting unit 201 adds the retention coefficient value "1" to the value of the weight B for the fixed devices 22-Z in the retention characteristic DB 221 for the latest reception time "0:00: 3" in the latest reception time DB 223. .. Therefore, in the retention characteristic DB 221 of FIG. 16, "1" is set as the value of the weight B with respect to the fixed device 22-Z. Further, the weighting unit 201 sets the value of the weight C based on the new value of the weight B for the fixed devices 22-Z and (Equation 1). In the retention characteristic DB 221 of FIG. 16, "0.52" is set as the value of the weight C with respect to the fixed devices 22-Z.

FIG. 17 is an explanatory diagram showing an example of weighting the beacon data 233 at the reception time “0:00: 4”. The weighting unit 201 adds the retention coefficient value "1" to the value of the weight B for the fixed device 22-X in the retention characteristic DB 221 for the latest reception time "0:00: 4" in the latest reception time DB 223. .. Therefore, in the retention characteristic DB 221 of FIG. 17, “3” is set as the value of the weight B with respect to the fixed device 22-X. Further, the weighting unit 201 sets the value of the weight C for the fixed device 22-X based on the new value of the weight B and (Equation 1). In the retention characteristic DB 221 of FIG. 17, “0.54” is set as the value of the weight C with respect to the fixed device 22-X.

This is the end of the description of the example of increasing the degree of retention. Next, an example of reducing the degree of retention will be described. For example, when the non-reception time is long, the mobile device 23 is likely to be in a position where each fixed device 22 cannot receive radio waves. Therefore, the weighting unit 201 lowers the degree of retention in the fixed device 22 when the non-reception time is long.

When it is detected based on the beacon data 233 that the communication between the mobile device 23 and the plurality of fixed devices 22 has not been performed for a predetermined time (non-reception determination time), the weighting unit 201 has a plurality of fixed devices. Weighting is performed so that the weight of each of the devices 22 is lower. Specifically, the weighting unit 201 determines whether or not the non-reception time is longer than the non-reception determination time for each non-reception determination interval, for example. When the non-reception time is longer than the non-reception determination time, the weighting unit 201 sets the value of the weight B so that the degree of retention of the mobile device 23 in each fixed device 22 is lower. Here, the non-reception time is, for example, the time during which the beacon data 233 is not received from any of the fixed devices 22. Specifically, the weighting unit 201 calculates the non-reception time based on, for example, the latest reception time and the current time. Then, when the non-reception time is longer than the non-reception determination time, the weighting unit 201 subtracts the value of the non-retention coefficient from the value of the weight B related to the fixed device 22. More specifically, the weighting unit 201 updates the value of the weight B by the following (Equation 3).

Value of weight B = Max ((value of weight B before update-value of non-retention coefficient), 0))
... (Equation 3)

Here, Min (a, b) is a function that returns the maximum value among a and b. 0 is the initial value of the weight B and is the minimum value. Therefore, the larger value of "(value of weight B before update-value of non-retention coefficient)" and 0 is the value of weight B. Then, the weighting unit 201 sets the value of the weight C based on the updated value of the weight B and (Equation 1). Further, according to (Equation 3), the value of the weight B should not be smaller than the initial value "0" before the start of operation of the positioning support system 2.

Further, the weighting unit 201 may set the value of the weight B so that when the non-reception time elapses, the longer the non-reception time, the lower the degree of retention. The weighting unit 201 subtracts the value of the non-retention coefficient from the value of the weight B for each fixed device 22, for example, every 1 second of the non-reception time. For example, when the non-reception time is "5 seconds", the weighting unit 201 subtracts "5 seconds" × the value of the non-retention coefficient "1" from the value of the weight B. Then, the weighting unit 201 sets the value of the weight C based on the value of the weight B after subtraction and (Equation 1). Here, an example of subtraction in units of 1 second is given, but various changes can be made.

Taking FIG. 13 as an example, the reception times are "0:00:00", "0:00:01", "0:00:02", "0:00:03", and "0:00:04". At any timing, the result of subtracting the latest reception time from the current time (non-reception time) does not exceed the non-reception determination time. Therefore, in the example of FIG. 13, the weighting unit 201 does not perform the process of subtracting the value of the weight B.

Further, an example is the case where the reception time is "0:00:00", "0:00:01", "0:00:02", "0:00:03", "1:01: 00". Listed in. That is, in this example, the information processing apparatus 20 receives the beacon data 233 from any of the fixed devices 22 for the target mobile device 23 from the time "0:00:03" to "1:01: 00". do not have. When the current time is "0:00:04", the latest reception time is the time "0:00:03". The weighting unit 201 sets the non-reception time as the subtraction result obtained by subtracting the latest reception time "0:00:03" from the current time "0:00:04". At the current time "0:00:04", the non-reception time is "1 second". Then, the weighting unit 201 determines whether or not the non-reception time is longer than the non-reception determination time "3600 seconds". Here, the weighting unit 201 determines that the non-reception time "1 second" is shorter than the non-reception determination time "3600 seconds". When the weighting unit 201 is short, the weighting unit 201 does not perform processing such that the weighting is low.

Next, when the current time is "1:00:01", the latest reception time is the time "0:00:03". The weighting unit 201 subtracts the latest reception time "0:00:03" from the current time "1:00:04". Then, the weighting unit 201 obtains the non-reception time "3601 seconds" as the subtraction result. The non-reception time "3601 [seconds]" is longer than the non-reception determination time "3600 seconds". Therefore, the weighting unit 201 updates the value of the weight B for all the fixed devices 22 based on (Equation 3). Then, the weighting unit 201 sets the value of the weight C based on the value of the weight B after subtraction and (Equation 1).

This is the end of the explanation of weighting by the weighting unit 201. Next, the specific unit 202 shown in FIG. 6 will be described. The specific unit 202 has the function of the specific unit 102 described in the first embodiment. The specifying unit 202 identifies, for example, the beacon data 233 having a large error in radio wave intensity due to the influence of the wireless communication environment among a series of beacon data based on the weighting result. The series of beacon data is time-series beacon data for the same mobile device 23 in the BLE beacon data DB 222. That is, in the BLE beacon data DB 222 in FIG. 9, a plurality of beacon data in the row direction () is a series of beacon data.

The series of beacon data here is time-series beacon data that matches the false positive determination data pattern. The false detection required determination data pattern is a pattern including the following conditions 1 to 3. Condition 1 includes a plurality of beacon data 233s having fixed device ID data indicating a certain fixed device 22 in the order of earliest in chronological order. Similar to the first embodiment, a certain fixed device 22 is referred to as a start point device. The condition 2 is, for example, that the beacon data 233 including the fixed device ID data indicating the fixed device 22 different from the starting point device is included. This different fixed device 22 is called a waypoint device. In condition 2, a plurality of beacon data 233 for the waypoint device may be consecutive in time series. Condition 3 is that the slowest beacon data 233 in the time series includes the fixed device ID data indicating the starting point device. The specific unit 202 extracts, for example, a series of beacon data matching the false detection required determination data pattern from the BLE beacon data DB 222 as time series data.

Taking the case where the starting point device is the fixed device 22-X as an example, the extracted time-series data has a plurality of beacon data 233 including the fixed device ID data indicating the fixed device 22-X in the order of the earliest time series. Then, the extracted time-series data has beacon data 233 including fixed device ID data indicating a waypoint device other than the fixed device 22-X. The number of beacon data 233 from the waypoint device here may be plural, or may be one. Further, the extracted time-series data has beacon data including the fixed device ID data indicating the receiver-X, next to the beacon data 233 from the waypoint device. The beacon data 233 is the slowest beacon data 233 in the time series among the series of beacon data.

FIG. 18 is an explanatory diagram showing Example 1 of the time series data and the retention characteristic DB 221. In the retention characteristic DB 221 in FIG. 18, the value of the weight B of the fixed device 22-X is "49", which is the largest. The value of the weight C of the fixed device 22-X is "1". Further, the value of the weight B of the fixed device 22-Y is "9". The value of the weight C of the fixed device 22-Y is "0.6". The value of the weight B of the fixed device 22-Z is "0". The value of the weight C of the fixed device 22-Z is "0.51".

Regarding the time series data 241-1 in FIG. 18, the illustration of the intensity data is omitted for the sake of simplification of explanation. The time-series data 241-1 has a plurality of beacon data 233s for the fixed devices 22-X in the order of earliest in the time series. Then, the time-series data 241-1 has the beacon data 233 for the fixed device 22-Y and the beacon data 233 for the fixed device 22-Z next to the beacon data 233. The time-series data 241-1 has the beacon data 233 for the fixed device 22-X as the slowest beacon data 233 in the time series after the beacon data 233 for the waypoint device.

Further, the timing at which the processing by the specific unit 202 is started is not particularly limited. For example, the specific unit 202 may perform a process of extracting a series of beacon data matching the false detection required determination pattern from the BLE beacon data DB 222 every reception time or every second.

At each timing of the reception time "0:00:00", "0:00:01", "0:00:02", and "0:00:03", a series of beacons stored in the BLE beacon data DB 222. The data does not match the false positive determination data pattern. In the specific unit 202, at the reception time “0:00:04”, a series of beacon data stored in the BLE beacon data DB 222 matches the erroneous detection required determination data pattern. Therefore, the specific unit 202 extracts a series of beacon data from the reception time “0:00:00” to the reception time “0:00:04” as time-series data 241-1.

Next, the specifying unit 202 calculates the first residence time in the fixed device 22 indicated by the fixed device ID data for each of the fixed device ID data included in the time series data 241. Further, the specific unit 202 may calculate the first residence time of the waypoint device in the time series data 241. In the example of FIG. 18, the waypoint devices are the fixed device 22-Y and the fixed device 22-Z. Therefore, the specific unit 202 does not have to calculate the residence time for the fixed device 22-X. Then, the specific unit 202 calculates the first residence time for the fixed device 22-Y and the first residence time for the fixed device 22-Z based on the time series data 241-1.

Specifically, the specific unit 202 calculates the time obtained by subtracting the start point time from the end point time as the first residence time for each waypoint device. The starting point time is the reception time indicated by the beacon data 233 that appears earliest in the time series for the waypoint device in the time series data 241-1. The end point time is the reception time indicated by the beacon data 233 that appears the latest in the time series for the waypoint device in the time series data 241-1. If the time-series data 241-1 includes only one beacon data 233 for the waypoint device for each waypoint device, the start point time and the end point time are the same.

For example, the first residence time for the fixed device 22-Y obtained from the time series data 241-1 is the time "0." obtained by subtracting the start time "0:00:02" from the end time "0:00:02". 00 seconds ".

For example, the first residence time for the fixed device 22-Z obtained from the time series data 241-1 is the time "0." obtained by subtracting the start time "0:00:03" from the end time "0:00:03". 00 seconds ".

Next, the specific unit 202 calculates the second residence time for the waypoint device based on the standard residence time and the weighting result. More specifically, the specific unit 202 calculates the second residence time, for example, by using the integration of the standard residence time and the value of the weight C for each waypoint device. The value of the weight B is set by the weighting unit 201 so that the second residence time, which is the result of the product of the weight C and the standard residence time, does not become longer than the standard residence time.

The standard residence time for the fixed device 22-Y is "5 seconds", and the value of the weight C is "0.60". Therefore, the second residence time for the fixed device 22-Y is "3.00 seconds" by "5 x 0.60".

The standard residence time for the fixed device 22-Z is "10 seconds", and the value of the weight C is "0.51". Therefore, the second residence time for the fixed device 22-Z is "5.10 seconds" by "10 x 0.0.5".

The identification unit 202 identifies the false detection beacon data 233 from the time series data 241-1 based on the comparison between the first residence time and the second residence time. For example, when the first residence time is less than the second residence time for all the waypoint devices, the specifying unit 202 identifies the beacon data 233 for the waypoint devices as the false detection beacon data 233.

In FIG. 18, for the fixed device 22-Y, the first residence time "0.00 seconds" is less than the second residence time "3.00 seconds". For the fixed device 22-Z, one residence time "0.00 seconds" is less than the second residence time "5.10 seconds". Therefore, the specifying unit 202 identifies the beacon data 233 for the fixed device 22-Y and the fixed device-Z in the time-series data 241-1 as the false detection beacon data 233. Then, the specific unit 202 may store the specific result in the storage unit 211.

Further, the correction unit 206 corrects the specified beacon data 233 in the BLE beacon data DB 222. Specifically, the correction unit 206 replaces, for example, the fixed device ID data included in the specified beacon data 233 in the BLE beacon data DB 222 with the fixed device ID data indicating the starting point device. FIG. 18 shows an example in which the fixed device IDs “Y” and “Z” of the time series data 241-1 are corrected to “X” for the sake of simplification of explanation, but in reality, the BLE beacon is shown. The beacon data 233 of the data DB 222 is corrected. As a result, the beacon data 233, which is presumed to have a large error in radio wave strength, is replaced with the beacon data 233 when there is no influence of the communication environment. Therefore, the information processing apparatus 20 can provide a series of beacon data when it is not affected by the communication environment. The information processing device 20 can improve the accuracy of positioning.

Although not shown, the correction method can be changed in various ways. The correction unit 206 may delete the specified beacon data 233 from the BLE beacon data DB 222, for example. Thereby, the BLE beacon data DB 222 excluding the false detection beacon data 233 can be provided. Further, the correction unit 206 may correct the value of the reception intensity so that the reception intensity of the specified beacon data becomes weaker, for example.

FIG. 19 is an explanatory diagram showing Example 2 of the time series data 241 and the retention characteristic DB 221. The storage content of the retention characteristic DB 221 in FIG. 19 is the same as the storage content of the retention characteristic DB 221 in FIG. The time-series data 241-2 in FIG. 19 continuously has the beacon data 233 for the fixed devices 22-X in the order of the earliest in the time series. Then, the time-series data 241-2 has a plurality of beacon data 233 for the fixed device 22-Y next to these beacon data 233. The time-series data 241-2 has the beacon data 233 for the fixed device 22-X as the slowest beacon data 233 in the time series after the beacon data 233 for the fixed device 22-Y.

The specific unit 202 calculates the first residence time and the second residence time of the fixed device 22-Y, which is the waypoint device, in the time series data 241-2. The first residence time for the fixed device 22-Y is the time "3.00 seconds" obtained by subtracting the start point time "0:00:02" from the end point time "0:00:05". The second residence time for the fixed device 22-Y is "3.00 seconds" by "5 x 0.60". Since the first residence time is not less than the second residence time, the identification unit 202 does not specify the false detection beacon data 233 from the time series data 241-2.

Next, the output control unit 207 generates data to be output to an output device or the like based on the specific result. The specific result here may be information indicating which beacon data 233 was specified. Further, the specific result may be information indicating that none of the beacon data 233 has been specified.

When the correction unit 206 corrects the beacon data 233, the output control unit 207 generates data to be output to an output device or the like based on the correction result. This output device may be an output device included in the information processing device 20. Further, this output device may be an output device possessed by another device connected via a communication network. To output to an output device or the like includes, for example, displaying on a display or the like. In the example of the positioning support system 2 shown in FIG. 4, the output control unit 207 generates, for example, data to be displayed on the display of the visualization terminal device 24. Then, the output control unit 207 may transmit the generated data to the visualization terminal device 24, for example.

Further, the information processing apparatus 20 may allow the user or the like to select whether or not to correct the false detection beacon data 233. After the output control unit 207 outputs the specific result of the specific unit 202 to an output device such as the visualization terminal device 24, the acquisition unit 203 may accept the presence or absence of correction via the communication network, the input device, or the like. For example, when the instruction with correction is received, the correction unit 206 corrects the erroneous detection beacon data. On the other hand, when the instruction without correction is received, the correction unit 206 does not correct the false detection beacon data.

FIG. 20 is a sequence diagram showing an operation example of the positioning support system 2 according to the second embodiment before operation. First, the visualization terminal device 24 displays an input screen on which various data can be input (step S201). Here, various data include a retention coefficient, a non-retention coefficient, a non-reception determination time, a non-reception determination interval, each standard residence time, and the like. The standard residence time may be accepted for each fixed device 22. Next, the visualization terminal device 24 accepts input of various data to the input screen (step S202). The visualization terminal device 24 transmits various received data (step S203).

The information processing device 20 receives various data from the visualization terminal device 24 (step S204). Next, the information processing apparatus 20 sets various data by the setting unit 204 (step S205). In step S205, the information processing apparatus 20 sets, for example, each standard residence time in the residence characteristic DB 221. In step S205, the information processing apparatus 20 sets the initial values of the weight A and the weight B in the retention characteristic DB 221. Further, in step S205, the information processing apparatus 20 stores, for example, a retention coefficient, a non-retention coefficient, a non-reception determination time, and a non-reception determination interval in the storage unit 211. Following step S205, the information processing apparatus 20 ends the flow operation. FIG. 21 is a flowchart showing an operation example (addition example) of weighting by the information processing apparatus 20 according to the second embodiment. First, the information processing device 20 receives the beacon data 232 from the fixed device 22 or the gateway 21 (step S211). Next, the information processing apparatus 20 adds time data indicating the reception time to the beacon data 232 (step S212). In step S212, the information processing apparatus 20 generates beacon data 233 including each data of the beacon data 232 and the time data indicating the reception time.

The information processing device 20 identifies the beacon data 233 having the strongest radio wave strength for each mobile device ID (step S213). In step S213, the information processing apparatus 20 identifies the beacon data 233 having the largest radio wave intensity value from the plurality of beacon data 233s having the same reception time for each mobile device ID. For example, in the positioning of a mobile body, it is presumed that the mobile body was near the fixed device indicated by the fixed device ID data possessed by the specified beacon data 233. The information processing apparatus 20 updates the latest reception time DB 223 based on the specified beacon data 233 (step S214). The information processing apparatus 20 stores the specified beacon data 233 in the BLE beacon data DB 222 (step S215). Then, the information processing apparatus 20 updates the weight B and the weight C of the retention characteristic DB 221 based on the specified beacon data 233 (step S216). In step S216, the information processing apparatus 20 updates the value of the weight B for the fixed device ID data included in the specified beacon data 233 by using (Equation 2). That is, the information processing apparatus 20 adds the retention coefficient to the value of the weight B within a range not exceeding the maximum value of the weight. Then, in step S216, the information processing apparatus 20 updates the value of the weight C for the fixed device ID data by using (Equation 1). The information processing apparatus 20 ends the flow operation after step S216.

FIG. 22 is a flowchart showing an operation example (subtraction example) of weighting by the information processing apparatus 20 according to the second embodiment. The information processing apparatus 20 determines whether or not the non-reception determination interval has elapsed (step S221). That is, in step S221, weighting is performed to reduce the degree of retention at each non-reception determination interval.

When it is determined that the non-reception determination interval has not elapsed (step S221: No), the information processing apparatus 20 returns to step S221. On the other hand, when it is determined that the non-reception determination interval has elapsed (step S221: Yes), the information processing apparatus 20 performs the process of step S222. The information processing apparatus 20 acquires the latest reception time of the target mobile device 23 from the latest reception time DB223 or the latest beacon data of the BLE beacon data DB222 (step S222). The information processing device 20 calculates the non-reception time (step S223). In step S223, the information processing apparatus 20 obtains a subtraction result obtained by subtracting the latest reception time from the current time as the non-reception time. Next, the information processing apparatus 20 determines whether or not the non-reception time is less than the non-reception determination time (step S224). By step S224, the information processing apparatus 20 can detect that wireless communication has not been performed between the plurality of fixed devices 22 and the mobile device 23 for the non-reception determination time or longer.

When the non-reception time is not less than the non-reception determination time (step S224: No), the information processing apparatus 20 updates the weight B and the weight C of the retention characteristic DB 221 for all the fixed devices 22 related to the target mobile device 23. (Step S225). In step S225, the information processing apparatus 20 obtains the value of the updated weight B by using (Equation 3). That is, the information processing apparatus 20 subtracts the non-retention coefficient from the value of the weight B within a range not less than the initial value of the weight B. Then, the information processing apparatus 20 obtains the value of the weight C by using (Equation 1). The information processing apparatus 20 ends the flow operation after step S225.

On the other hand, when the non-reception time is less than the non-reception determination time (step S224: Yes), the information processing apparatus 20 ends the flow operation. Further, after the flow operation is completed, the information processing apparatus 20 can repeat the weighting process shown in FIG. 22 by starting the process of step S221. The information processing device 20 may perform the processing shown in FIG. 22 for each mobile device 23 (parallel processing). Further, the information processing apparatus 20 may select the mobile device 23 as the target mobile device 23 in order. Then, the information processing apparatus 20 may execute the flow shown in FIG. 22 for the selected target mobile device 23 (sequential processing). Further, the flow shown in FIG. 22 and the flow shown in FIG. 21 are performed asynchronously, for example.

FIG. 23 is a flowchart showing an operation example of correction by the information processing apparatus 20 according to the second embodiment. The information processing apparatus 20 extracts time-series data 241 matching the false positive determination data pattern from the retention characteristic DB 221 (step S231). The information processing apparatus 20 calculates the first residence time for each waypoint device based on the extracted time-series data 241 (step S232). As described above, the first residence time is the residence time of the mobile device 23 in the waypoint device based on the time series data 241.

The information processing apparatus 20 calculates the second residence time for each waypoint device based on the retention characteristic DB 221 (step S233). The information processing apparatus 20 obtains the second residence time by integrating the standard residence time included in the residence characteristic DB 221 and the value of the weight C. Next, the information processing apparatus 20 determines whether or not the first residence time is less than the second residence time for all the waypoint devices (step S234). When the first residence time is less than the second residence time for all the waypoint devices (step S234: Yes), the information processing apparatus 20 specifies the beacon data related to the waypoint devices as the erroneous detection beacon data (step S235). ). Then, the information processing apparatus 20 corrects the false detection beacon data (step S236). In step S235, the information processing apparatus 20 fixes the fixed device ID data indicating the waypoint device included in the beacon data related to the waypoint device corresponding to the time-series data 241 in the BLE beacon data DB 222, indicating the point device from beginning to end. Replace with device ID data.

Then, the information processing apparatus 20 ends the flow operation after step S236. Further, when the first residence time is not less than the second residence time for any of the waypoint devices (step S234: No), the information processing apparatus 20 ends the flow operation.

Next, the effect of the second embodiment will be described. The information processing device 20 according to the second embodiment described above identifies beacon data having a large error in radio wave intensity due to the influence of the communication environment, based on the weighting result regarding the degree of retention of the mobile device 23 in the fixed device 22. As a result, the information processing apparatus 20 can notify the positioning user of, for example, beacon data having a large error in radio wave strength due to the influence of the communication environment. Therefore, the user can perform positioning in consideration of the false detection beacon data. Therefore, the information processing apparatus 20 can improve the accuracy of positioning. In addition, the user may analyze obstacles and the like that affect the communication environment and the degree of the influence by using the false detection beacon data.

Further, for example, the moving body may move out of the area where a plurality of fixed devices 22 are installed, such as performing work different from the original work. That is, the mobile device 23 and the plurality of fixed devices 22 cannot communicate with each other for a long time. For example, when communication is not performed between the mobile device 23 and the plurality of fixed devices 22 for a predetermined time, it is highly possible that the mobile device 23 is separated from the plurality of fixed devices 22 such as going outdoors. .. Therefore, when the information processing device 20 detects that wireless communication has not been performed between the plurality of fixed devices 22 and the mobile device 23 for the non-reception determination time or longer, the mobile device 23 in each fixed device 22 The weighting is updated so that the degree of retention of is lower. As a result, weighting is performed in consideration of the case where the moving body is not in the vicinity of any of the fixed devices 22. Then, the accuracy of the characteristics of the false detection beacon data can be improved. As a result, the accuracy of positioning can be further improved.

The information processing device 20 identifies false detection beacon data based on, for example, the first residence time of the mobile device 23 in the fixed device 22 in which the fixed device ID data is included in the series of beacon data and the weighting result. As a result, the information processing apparatus 20 identifies false detection beacon data based on how much the mobile device 23 stays with respect to each fixed device 22 in the series of beacon data. Therefore, the information processing apparatus 20 can more accurately identify the false detection beacon data.

Further, the series of beacon data has a plurality of beacon data for the starting point device in chronological order from the earliest. Then, the series of beacon data has the beacon data about the waypoint device following these beacon data. Further, among the series of beacon data, the slowest beacon data in the time series includes the fixed device ID data indicating the starting point device. As a result, attention is paid to the retention of the mobile device 23 in a certain fixed device 22 (starting point device). Then, in a series of beacon data, it is specified whether the mobile device 23 has actually moved from one fixed device 22 (starting point device) to another fixed device 22 (via point device), or whether it is an error in radio field strength. Will be done. As a result, the false detection beacon data is identified more accurately.

In addition, the moving body has a peculiar retention characteristic. For example, which fixed device 22 the moving body stays in the vicinity of is different depending on the moving body, the work of the moving body, the time zone, and the like. Therefore, the standard residence time of the mobile device 23 in the fixed device 22 is prepared for each fixed device 22. However, the standard residence time is just an estimated value by the user or administrator. The information processing apparatus 20 obtains a second residence time based on the standard residence time and the weighting result obtained by weighting for each fixed device 22. As a result, the information processing apparatus 20 can obtain a standard residence time (second residence time) in which the mobile body is likely to actually be in the waypoint device. Further, if the first residence time based on the series of beacon data is equal to or longer than the second residence time, which is the standard residence time considering the weighting result, it is possible that the moving body actually moved near the waypoint device. Is high. On the other hand, if the first residence time based on the series of beacon data is less than the second residence time, which is the standard residence time considering the weighting result, the moving body is actually moved near the waypoint device. However, there is a high possibility that a large error has occurred in the reception strength of radio waves due to the influence of the communication environment. Therefore, the information processing apparatus 20 identifies the false detection beacon data based on the comparison between the second residence time and the first residence time. For example, when the first residence time of the waypoint device is less than the second residence time, the information processing apparatus 20 specifies the beacon data including the fixed device ID data indicating the waypoint device as the erroneous detection beacon data. .. As a result, the information processing apparatus 20 can more accurately identify the false detection beacon data by taking advantage of the retention characteristic peculiar to the mobile body.

Further, the information processing apparatus 20 corrects the identified false detection beacon data out of a series of beacon data. Examples of the correction method include deletion of false detection beacon data and replacement of fixed device ID included in false detection beacon data. As a result, the user of the information processing apparatus 20 and the user who actually performs the positioning can perform the positioning of the moving object without considering the error of the radio wave strength. As described above, the information processing apparatus 20 can improve the accuracy of positioning of the mobile body by correcting the beacon data by utilizing the retention characteristic peculiar to the mobile body. Further, the second embodiment is not limited to the above description. For example, without weighting, the information processing apparatus 20 may specify erroneous detection beacon data by comparing the above-mentioned first residence time with the standard residence time based on a series of beacon data. Then, the information processing apparatus 20 may correct the false detection beacon data as described above. That is, the information processing device 20 may have a configuration that does not have the weighting unit 201. The first embodiment may have the same configuration as that of the second embodiment.

Next, a case where the information processing apparatus 10 according to the first embodiment and the information processing apparatus 20 according to the second embodiment are realized by a computer will be described. FIG. 24 is an explanatory diagram showing an example of hardware configuration when the information processing apparatus is realized by a computer. As shown in FIG. 24, the information processing device 30 is, for example, the information processing devices 10 and 20. The information processing device 30 includes a CPU (Central Processing Unit) 301, a ROM 302, a RAM 303, a storage device 304, and a communication interface 305. Each component is connected via a bus 306.

The CPU 301 controls the entire information processing apparatus 30. For example, the CPU 301 may operate an OS (Operating System) to control the entire information processing apparatus 30. The CPU 301 may have a plurality of cores.

The information processing device 30 has a ROM 302, a RAM 303, a storage device 304, and the like as storage units. Examples of the storage device 304 include semiconductor memories such as flash memories, HDDs, SSDs, and the like. For example, the storage device 304 stores various programs such as an OS program, an application program, and a program according to the first or second embodiment. Alternatively, the ROM 302 stores the application program. Further, the ROM 302 may store the program according to the first or second embodiment. Then, the RAM 303 is used as a work area of the CPU 301.

Further, the CPU 301 loads the program stored in the storage device 304, the ROM 302, or the like. Then, the CPU 301 executes each process coded in the program. Further, the CPU 301 may download various programs via the communication network 310. Further, the CPU 301 functions as a part or all of the information processing apparatus 30. Then, the CPU 301 may execute the process or the instruction in the illustrated flowchart based on the program.

The communication interface 305 is connected to a communication network 310 such as a LAN (Local Area Network) or a WAN (Wide Area Network) through a wireless or wired communication line. As a result, the information processing device 30 is connected to an external device or an external computer via the communication network 310. The communication interface 305 controls the interface between the communication network 310 and the inside of the information processing device 30. The communication interface 305 controls the input / output of data from an external device or an external computer.

However, the hardware configuration shown in FIG. 24 is an example, and components other than these may be added or may not include some components. For example, the information processing device 30 may have a drive device or the like. Then, the CPU 301 may read a program or data from a recording medium mounted on a drive device or the like to the RAM 303. Examples of the recording medium include an optical disk, a flexible disk, a magnetic optical disk, a USB (Universal Serial Bus) memory, and the like. Further, for example, the information processing device 30 may have an input device such as a keyboard and a mouse, and an output device such as a display.

As described above, the information processing devices 10 and 20 according to the first or second embodiment are realized by the computer hardware shown in FIG. 24. Further, the information processing devices 10 and 20 are realized by one physically connected device. Alternatively, the information processing devices 10 and 20 may be realized by connecting two or more physically separated devices by wire or wirelessly.

Further, there are various modifications in the method of realizing the information processing devices 10 and 20. For example, each device may be realized by any combination of a computer and a program, which are different for each component. Further, a plurality of components included in each device may be realized by any combination of one computer and a program.

Further, a part or all of each component of the information processing devices 10 and 20 may be realized by a circuit for a specific application. Further, a part or all of the information processing apparatus may be realized by a general-purpose circuit including a processor such as FPGA (Field Programmable Gate Array). Further, a part or all of the information processing apparatus may be realized by a combination of a circuit for a specific application, a general-purpose circuit, or the like. Further, these circuits may be a single integrated circuit. Alternatively, these circuits may be divided into a plurality of integrated circuits. Then, a plurality of integrated circuits may be configured by being connected via a bus or the like.

Further, when a part or all of each component of each device is realized by a plurality of computers and circuits, the plurality of computers and circuits may be centrally arranged or distributed.

The positioning support method described in each embodiment is realized by executing the information processing devices 10 and 20. Further, the positioning support method is realized by executing a program prepared in advance by a computer such as information processing devices 10 and 20. The program described in each embodiment is recorded on a computer-readable recording medium such as an HDD, SSD, flexible disk, optical disk, flexible disk, magnetic disk disk, or USB memory. Then, this program is executed by being read from the recording medium by a computer. The program may also be distributed via the communication network 310.

Each component of the information processing apparatus 10 and 20 in each of the embodiments described above may have its function realized by hardware as in the information processing apparatus 30 of the computer shown in FIG. 24. Alternatively, each component may be realized by a computer device or firmware based on program control.

Further, regarding the hardware configuration of the beacon device, for example, it has a beacon transmission / reception unit capable of transmitting / receiving a beacon signal via an antenna or the like. In the second embodiment, the beacon device, which is the mobile device 23, transmits a beacon signal at a predetermined cycle. Further, in the second embodiment, the beacon device, which is a fixed device, scans, for example, at a predetermined cycle. Scanning is the reception of a beacon signal. The beacon signal is the above-mentioned beacon data. Then, the beacon device transmits, for example, the received beacon data in the same cycle as the scan cycle. As described above, the beacon device transmits the beacon data directly to the gateway or server. Therefore, the beacon device may have a communication interface or the like that can be connected to the communication network, in addition to the beacon transmission / reception unit. Further, each beacon device may relay other beacon data as in multi-hop communication. Then, each beacon device may transmit the beacon data to the gateway or the server by relaying the beacon data.

Further, regarding the hardware configuration of the visualization terminal device 24, for example, it has an output device and an input device. In addition, the visualization terminal device 24 may have the same hardware configuration as the information processing device 30 shown in FIG. 24. Further, the gateway 21 is not particularly limited as long as it has hardware having a function of converting packets, a communication interface capable of connecting to a communication network, and the like.

Although the present invention has been described above with reference to each embodiment, the present invention is not limited to the above-described embodiment. The configuration and details of the present invention may include embodiments to which various modifications that can be grasped by those skilled in the art within the scope of the present invention are applied. The present invention may include embodiments in which the matters described herein are appropriately combined or replaced as necessary. For example, the matters described using a particular embodiment may be applied to other embodiments as long as they do not cause inconsistency. For example, although a plurality of operations are described in order in the form of a flowchart, the order of description does not limit the order in which the plurality of operations are executed. Therefore, when each embodiment is implemented, the order of the plurality of operations can be changed within a range that does not hinder the content.

Further, the information processing devices 10 and 20 described in the first and second embodiments of the present embodiment include, for example, flow line analysis and work process management of a moving body that moves indoors by a fixed route, as represented by the manufacturing industry and the logistics industry. May be used for. Further, the information processing devices 10 and 20 may be used for analysis of the flow line of the waiter in the food and drink industry, improvement of the efficiency of the flow line, improvement of work efficiency such as shortening of the residence time in the workplace, and the like. Further, the information processing devices 10 and 20 may be used for improving work efficiency such as analysis of the flow line of a clerk in the distribution industry, retail industry, etc., efficiency improvement of the flow line, and grasping of work time.

2 Positioning support system 10, 20, 30 Information processing equipment 21 Gateway 22 Fixed equipment 23 Mobile equipment 24 Visualization terminal equipment 101,201 Weighting unit 102, 202 Specific unit 203 Acquisition unit 204 Setting unit 205 Aggregation unit 206 Correction unit 207 Output control Section 211 Storage section 233 Beacon data

Claims (9)

Based on communication data including strength data relating to radio strength of wireless communication between the first device and any second device of the plurality of second devices, and identification data indicating the second device. A weighting means for weighting the degree of retention of the first device in the second device indicated by the identification data included in the communication data.
Based on the weighting result by the weighting means, the specific means for identifying the communication data in which the radio field intensity is erroneously detected due to the influence of the wireless communication environment from the series of the communication data, and the specific means.
Information processing device equipped with. A correction means for correcting the specified communication data in the series of communication data is provided.
The information processing apparatus according to claim 1. The specific means is
Based on the series of the communication data, the first residence time of the first device in the second device in which the identification data is included in the series of the communication data among the plurality of second devices is calculated.
Based on the calculated first residence time and the weighting result, the erroneously detected communication data is specified.
The information processing apparatus according to claim 1 or 2. The specific means is
The communication data erroneously detected based on the second residence time of the first device in the second device based on the standard residence time of the second device and the weighting result, and the first residence time. To identify,
The information processing apparatus according to claim 3. The series of the communication data has a plurality of the communication data including the same identification data in the order of earliest in chronological order, and has the communication data including the identification data different from the same identification data.
The communication data, which is the slowest in the time series of the series of communication data, includes the same identification data.
The information processing apparatus according to any one of claims 1 to 4. The series of the communication data includes the communication data having the strongest radio field strength at each timing in the time series.
The information processing apparatus according to any one of claims 1 to 5. The weighting means is
When it is detected that the wireless communication between the first device and the plurality of second devices has not been performed for a predetermined time based on the communication data, the said for each of the plurality of second devices. Weighting to lower the degree of retention,
The information processing apparatus according to any one of claims 1 to 6. Based on communication data including strength data relating to radio field strength of wireless communication between the first device and any second device of the plurality of second devices, and identification data indicating the second device. Then, the degree of retention of the first device in the second device indicated by the identification data included in the communication data is weighted.
Based on the weighting result, the communication data whose radio field strength is erroneously detected due to the influence of the wireless communication environment is specified from the series of communication data.
Positioning support method. On the computer
Based on communication data including strength data relating to radio field strength of wireless communication between the first device and any second device of the plurality of second devices, and identification data indicating the second device. Then, the degree of retention of the first device in the second device indicated by the identification data included in the communication data is weighted.
Based on the weighting result, the communication data whose radio field strength is erroneously detected due to the influence of the wireless communication environment is specified from the series of communication data.
A program that executes processing.

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