Information processing device and program

Abstract

To ensure the anonymity of personal information and to assist a delivery work.SOLUTION: An information processing device 200 that is for assisting a delivery work includes: obtaining means 202 for obtaining the number of at-home addresses that is the number of addresses determined as respective residents being at home for a plurality of designated addresses; and arithmetic means 203 for obtaining information that compares the number of at-home addresses obtained by the obtaining means 202 with the number of designated addresses. The arithmetic means 203 obtains, for each area, such information.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an information processing device and a program for supporting delivery operations. [Background technology]

[0002] Patent document 1 discloses a configuration in which a delivery management server determines whether a recipient of a delivery package is present at the delivery destination (whether they are at home or not) based on the power usage status detected by a smart meter or distribution board, with the aim of reducing the effort and cost associated with delivering and receiving packages. Furthermore, Patent Document 2 discloses a technique for acquiring personal information (age, relationship, behavior, etc.) of people present in a facility such as a house, and determining the usage state of the facility based on a combination of the personal information. Furthermore, Patent Document 3 discloses a technique for acquiring vehicle entry and exit information for each parking space in a parking lot, and predicting the rate at home of residents who own vehicles. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2019-109847 A [Patent Document 2] JP 2020-21260 A [Patent Document 3] JP 2022-190534 A Summary of the Invention [Problem to be solved by the invention]

[0004] Although technologies to determine whether a user is at home or not have been proposed, this information is personal information, and permission to use it must be obtained from each user. As a result, it is difficult to use this information to support delivery operations.

[0005] The present invention has been made in consideration of the above-mentioned points, and has an object to ensure the anonymity of personal information and to support delivery operations. [Means for solving the problem]

[0006] The information processing device of the present invention is an information processing device for supporting delivery operations, and is characterized by having an acquisition means for acquiring an at-home count, which is the number of addresses that are determined to be at home, for a number of specified addresses, and a calculation means for obtaining information comparing the at-home count acquired by the acquisition means with the number of addresses targeted by the address. In addition, the information processing device of the present invention is an information processing device for supporting delivery operations, and is characterized by having an acquisition means for acquiring a number of at-home cases, which is the number of addresses that are determined to be at-home, for a specified area, and a calculation means for obtaining information comparing the number of at-home cases acquired by the acquisition means with the number of addresses in the target area. In addition, the program of the present invention is a program for supporting delivery operations, and causes a computer to function as an acquisition means for acquiring the number of at-home cases, which is the number of addresses that are determined to be at home, for a number of specified addresses, and as a calculation means for obtaining information that compares the number of at-home cases acquired by the acquisition means with the number of targeted addresses. In addition, the program of the present invention is a program for supporting delivery operations, and causes a computer to function as an acquisition means for acquiring the number of home-at-home cases, which is the number of addresses that are determined to be home, for a specified area, and as a calculation means for obtaining information that compares the number of home-at-home cases acquired by the acquisition means with the number of addresses in the target area. Effect of the Invention

[0007] According to the present invention, it becomes possible to support delivery operations while ensuring the anonymity of personal information. [Brief description of the drawings]

[0008] [Figure 1] 1 is a diagram showing a schematic configuration of a delivery operation support system according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, preferred embodiments of the present invention will be described with reference to the accompanying drawings. [First embodiment] FIG. 1 shows a schematic configuration of a delivery business support system 1 according to an embodiment. The delivery operation support system 1 includes a network system 2 constructed by a delivery company. The network system 2 is configured so that a mobile terminal 100 carried by a delivery person of the delivery company and a server 150 can communicate with each other via a network 301 such as the Internet. Although only one mobile terminal 100 is illustrated in FIG. 1, multiple mobile terminals exist. The server 150 is also configured to be able to communicate with a server 200 for providing services from an infrastructure provider, for example, via a network 302 such as the Internet.

[0010] The mobile terminal 100 includes a request unit 101 that requests a delivery route with the current location added to the server 150, and a presentation unit 102 that presents the delivery route sent from the server 150 to the delivery person.

[0011] Server 150 includes a reception unit 151 that receives a request from mobile terminal 100, a request unit 152 that requests support information from server 200 by specifying multiple addresses for delivery in response to the request received by reception unit 151, an acquisition unit 153 that acquires support information from server 200, a calculation unit 154 that calculates a delivery route based on the support information acquired by acquisition unit 153, and an output unit 155 that outputs the delivery route calculated by calculation unit 154 to mobile terminal 100. Hereinafter, a request for support information from server 150 will also be referred to as an inquiry.

[0012] The server 200 has a database 205 in which at least one of mobile phone location information, electricity usage information, gas usage information, water usage information, and communication infrastructure usage information provided by an infrastructure provider is stored. The server 200 includes a reception unit 201 that receives a request (inquiry) for support information from the server 150, an acquisition unit 202 that acquires the number of at-home cases, which is the number of addresses that are determined to be at-home at the time of the inquiry, using the database 205 for a plurality of specified addresses, a calculation unit 203 that calculates support information using the number of at-home cases and the number of target addresses, and an output unit 204 that outputs the support information calculated by the calculation unit 203 to the server 150 that originated the inquiry. The server 200 is an example of an information processing device for supporting delivery work to which the present invention is applied.

[0013] The processes executed by the server 150 and the server 200 will be described in detail below. In the server 150, when the receiving unit 151 receives a request from the mobile terminal 100, the request unit 152 requests the server 200 for support information, for example by specifying a plurality of addresses to which delivery is scheduled to be made within the same day. Here, deliveries are classified into (a) no time specified, (b) time specified, (c) postbox possible, and (d) delivery box available (data held by the delivery company). The possibility of redelivery is low for attributes (c) and (d), so it is preferable to be able to provide support for delivery operations for attributes (a) or attributes (a) and (b). The request unit 152 creates a list of multiple addresses for delivery schedules with attributes (a) or attributes (a) and (b), and passes it to the server 200.

[0014] In the server 200, the reception unit 201 receives a request (inquiry) for support information from the server 150.

[0015] In server 200, acquisition unit 202 targets multiple specified addresses and acquires the number of at-home cases, which is the number of addresses for which the person is determined to be at home when making an inquiry, by using database 205. Acquisition unit 202 determines whether the person is at home / away from each address based on at least one of mobile phone location information, electricity usage information, gas usage information, water usage information, and communication infrastructure usage information managed in database 205, and acquires the number of at-home cases.

[0016] When using mobile phone location information, the GPS information for each mobile phone during the time period when the person is likely to be at home (for example, 1:00 to 5:00) is compared with the GPS information at the time of the inquiry, and if it is close, it is determined that the person is at home. Note that since the contract address of a mobile phone may differ from the owner's residence, it is preferable to build a database that matches the contract holder's name with the GPS information for the time period when the person is likely to be at home and the address.

[0017] Furthermore, when using information on electricity, gas, and water usage, past low consumption (when not at home) for a time period that includes the same time as the inquiry for an individual address, or past low consumption (when not at home) during delivery times (for example, 8:00-21:00) is compared with the consumption at the time of the inquiry (smart meter value, etc.), and if the consumption at the time of the inquiry is greater, it is determined that the person is at home. Since it is expected that home appliances, etc. will be used with timers, it is determined whether the person is at home or not by comparing with past records that take delivery times into account. In this way, by capturing the time-zone trends of past usage (consumption amount), it becomes possible to make more accurate judgments.

[0018] In addition, when using the usage status of the communication infrastructure, past low traffic information (absent) for all time periods for each household is compared with the traffic at the time of the inquiry, and if the traffic at the time of the inquiry is high, the household is determined to be at home. Since regular updates are expected, the household is determined to be at home not only using the time period including the same time as the inquiry, but also using past records for other time periods. In this way, capturing the time period trends of past traffic volume makes it possible to make more accurate determinations.

[0019] In the server 200, the calculation unit 203 obtains, as support information, information that compares the number of at-home cases acquired by the acquisition unit 202 with the number of target addresses (referred to as the number of at-home inquiries). In this embodiment, the calculation unit 203 calculates, as support information, a value that expresses (number of at-home cases) / (number of at-home inquiries) as a percentage (hereinafter referred to as the at-home possibility rate). By referring to the at-home possibility rate, it is possible to know how many of the multiple addresses for which delivery is scheduled have a high possibility of being at home. Here, the area is divided in advance (for convenience, called small areas), and the at-home possibility rate is calculated for each small area. The area is divided, for example, by block. The area may be divided in a different way (size of small areas) between densely populated areas such as urban areas and sparsely populated areas such as rural areas.

[0020] In this case, if the small area contains only one target address, i.e., if there is only one home-at-home inquiry, this may lead to the identification of an individual, and anonymity will be lost. Therefore, when the small area contains only one target address, the calculation unit 203 calculates the home-at-home probability rate for a medium area that combines the small area with the other small area closest to it. In this way, regrouping is performed so that multiple target addresses are included, and the home-at-home probability rate is calculated.

[0021] Furthermore, when the at-home possibility rate calculated for a small area is 100%, i.e., when the ratio between the number of at-home cases acquired by acquisition unit 202 and the number of target addresses is 1, this may also lead to the identification of individuals, resulting in a loss of anonymity. Therefore, when the at-home possibility rate calculated for a small area is 100%, calculation unit 203 recalculates the at-home possibility rate for a medium area that combines that small area with the other small area closest to it. In this way, regrouping is performed so that the at-home possibility rate becomes less than 100%, and the at-home possibility rate is calculated.

[0022] In the server 200, the output unit 204 outputs the at-home possibility rate for each small area (or each medium area) calculated by the calculation unit 203 to the server 150 that originated the inquiry.

[0023] In the server 150, the calculation unit 154 optimizes the delivery route based on the at-home probability rate acquired by the acquisition unit 153 from the server 200, and the output unit 155 outputs this delivery route to the mobile terminal 100. In the mobile terminal 100, the presentation unit 102 displays the delivery route sent from the server 150, for example, on a display unit (not shown), to present it to the delivery person. There are no limitations on the way to optimize the delivery route, and existing optimization methods can be used. For example, a delivery route is calculated based on the delivery destination information of attribute (b) (probability rate of at home for each area, number of deliveries) so that the total travel cost for all areas is minimized. Then, for this delivery route, information on the delivery destinations of attribute (a), which is not a constraint, is added to the grace time between delivery destinations, and a delivery route is calculated so that the travel cost is minimized. Also, for this delivery route, a delivery route is calculated so that the travel cost is minimized based on the delivery destination information of attributes (c) and (d) for the grace time between delivery destinations. By successively calculating the probability of the delivery being at home based on the latest information during delivery and optimizing the delivery route, accuracy can be improved.

[0024] The servers 150 and 200 thus constructed are configured by computers equipped with, for example, a CPU, a ROM, a RAM, etc., and the functions of the respective units 151-155 and 201-204 are realized by the CPU executing a predetermined program stored in, for example, the ROM.

[0025] As described above, by grouping at-home / absent information, which is personal information that is difficult to use from the perspective of privacy protection, and treating it as a rate of at-home probability, it becomes possible to support delivery operations while ensuring anonymity and protecting privacy. This will lead to a reduction in redelivery, reduce carbon dioxide emissions, and contribute to GX (Green Transformation) activities.

[0026] In this embodiment, the number of cases where the person is at home is obtained and the probability of being at home is calculated based on the time of the inquiry. However, it is also possible to allow the person to specify a future date and time when requesting support information, and to obtain the number of cases where the person is at home and calculate the probability of being at home based on the specified date and time. Furthermore, in the present embodiment, the acquisition unit 202 of the server 200 determines whether the person is at home or not, but this determination may be performed by an external device, and the acquisition unit 202 may acquire the resultant number of times the person is at home. In addition, in this embodiment, the calculation unit 154 of the server 150 optimizes the delivery route and presents it on the mobile terminal 100, but it is also possible to support delivery operations by simply presenting the probability of the customer being at home on the mobile terminal 100.

[0027] [Second embodiment] In the first embodiment, a request for support information is made to the server 200 by specifying multiple addresses, but a request for support information may be made to the server 200 by specifying an area. Note that the schematic configuration of the delivery operation support system 1 is similar to that shown in Fig. 1, and the following description will omit a description of the points in common with the first embodiment and will focus on the points of difference from the first embodiment.

[0028] In the server 150, when the receiving unit 151 receives a request from the mobile terminal 100, the requesting unit 152 requests support information from the server 200, for example, by specifying an area to which delivery is scheduled to be made on the same day. The area here may be an area that has been divided in advance as described in the first embodiment, or may be an area that is arbitrarily specified by the delivery person.

[0029] In the server 200, the reception unit 201 receives a request (inquiry) for support information from the server 150.

[0030] In the server 200, the acquisition unit 202 acquires the number of at-home cases, which is the number of addresses that are determined to be at-home at the time of inquiry, for a specified area using the database 205. As in the first embodiment, the acquisition unit 202 determines whether the person is at home or not for each address based on at least one of mobile phone location information, electricity usage information, gas usage information, water usage information, and communication infrastructure usage information managed in the database 205, and acquires the number of at-home cases.

[0031] In the server 200, the calculation unit 203 obtains, as support information, information that compares the number of at-home cases acquired by the acquisition unit 202 with the number of addresses in the target area (referred to as the number of at-home inquiries). In this embodiment, the calculation unit 203 calculates, as support information, a value that expresses (number of at-home cases) / (number of at-home inquiries) as a percentage (hereinafter referred to as the at-home possibility rate). By referring to the at-home possibility rate, it is possible to know how many addresses in the scheduled delivery area are likely to be at home. Even in this embodiment, if the at-home possibility rate calculated in the target area becomes 100%, that is, if the ratio between the number of at-home cases acquired by the acquisition unit 202 and the number of addresses in the target area becomes 1, the area is expanded and the at-home possibility rate is calculated again.

[0032] In the server 200, the output unit 204 outputs the at-home possibility rate of the area calculated by the calculation unit 203 to the server 150 that originated the inquiry.

[0033] In the server 150, the calculation unit 154 optimizes the delivery route based on the at-home probability rate acquired by the acquisition unit 153 from the server 200, and the output unit 155 outputs this delivery route to the mobile terminal 100. In the mobile terminal 100, the presentation unit 102 displays the delivery route sent from the server 150, for example, on a display unit (not shown), and presents it to the delivery person. The optimization is as described in the first embodiment.

[0034] Although the present invention has been described above with reference to the embodiments, the above embodiments are merely illustrative of the specific examples of the present invention, and the technical scope of the present invention should not be interpreted as being limited by these embodiments. In other words, the present invention can be embodied in various forms without departing from its technical concept or main features. In this embodiment, a configuration including the mobile terminal 100, the server 150, and the server 200 has been described, but the present invention is not limited to this. (Other embodiments) The present invention can also be realized by a process in which a program for implementing one or more of the functions of the above-described embodiments is supplied to a system or device via a network or a storage medium, and one or more processors in a computer of the system or device read and execute the program. The present invention can also be realized by a circuit (e.g., ASIC) that implements one or more of the functions. [Explanation of symbols]

[0035] 100: mobile terminal, 101: request unit, 102: presentation unit, 150: server, 151: reception unit, 152: request unit, 153: acquisition unit, 154: calculation unit, 155: output unit, 200: server, 201: reception unit, 202: acquisition unit, 203: calculation unit, 204: output unit, 205: database, 301, 302: network

Claims

1. An information processing device for supporting delivery operations, An acquisition means for acquiring the number of addresses determined to be at home from among a plurality of designated addresses; An information processing device comprising: a calculation means for calculating information by comparing the number of at-home cases acquired by the acquisition means with the number of target addresses.

2. 2. The information processing apparatus according to claim 1, wherein said calculation means determines said information for each area.

3. 3. The information processing apparatus according to claim 2, wherein, when an area contains one address of interest, said calculation means integrates said area with other areas to obtain said information.

4. The information processing device described in claim 2 or 3, characterized in that when the ratio of the number of people at home acquired by the acquisition means to the number of target addresses in the information acquired for a certain area becomes 1, the calculation means merges the area with other areas and re-acquires the information.

5. An information processing device for supporting delivery operations, An acquisition means for acquiring the number of addresses determined to be at home within a specified area; An information processing device comprising: a calculation means for calculating information by comparing the number of people at home acquired by the acquisition means with the number of addresses within the target area.

6. The information processing device according to claim 1 or 5, characterized in that the acquisition means acquires the number of cases where the person is determined to be at home based on at least one of information on the location of a mobile phone, information on electricity usage, information on gas usage, information on water usage, and information on communication infrastructure usage.

7. A program for supporting delivery operations, An acquisition means for acquiring the number of addresses determined to be at home from among a plurality of designated addresses; A program for causing a computer to function as a calculation means for obtaining information by comparing the number of people at home obtained by the obtaining means with the number of addresses to be targeted.

8. A program for supporting delivery operations, An acquisition means for acquiring the number of addresses determined to be at home within a specified area; A program for causing a computer to function as a calculation means for obtaining information by comparing the number of people at home obtained by the acquisition means with the number of addresses within the target area.

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