JP7756580B2 - Delivery management device and delivery management method - Google Patents

Description

Application of Article 30, Paragraph 2 of the Patent Act Yoon Seong-jae, Murakami Eiji, and Takahashi Taishi presented their invention, "Method for estimating customer profiles of LP gas users based on the temperature elasticity of gas usage," at the 2021 Annual Conference of the Japan Society for Management Information (June 13, 2021).

This disclosure relates to a delivery management device and a delivery management method.

A dynamic logistics automated navigation device has been disclosed that creates a delivery plan, including a route for delivery, in response to a package delivery request from a shipper (see Patent Document 1).

JP 6-290193

When gas cylinders installed in buildings that store gas fuel such as LPG (Liquefied Petroleum Gas) are used up and need to be replaced, a delivery person delivers a new gas cylinder to the building to replace the old one. Generally, the amount of gas used by such gas cylinders is not constant, making it difficult to manage the delivery of gas cylinders in response to changes in gas usage.

The present disclosure aims to provide a delivery management device and delivery management method that can manage the delivery of gas cylinders in response to changes in gas usage.

The delivery management device according to the present disclosure includes a gas usage acquisition unit that acquires information about gas usage from gas cylinders installed in a building, a weather information acquisition unit that acquires information about the weather in a location where the building is installed, a gas usage prediction unit that predicts gas usage in the building based on the information about gas usage acquired by the gas usage acquisition unit and the information about weather acquired by the weather information acquisition unit, and an information generation unit that generates delivery management information for managing the delivery of new gas cylinders to the building based on the prediction by the gas usage prediction unit, wherein the gas usage acquisition unit acquires gas usage in a unit period of the building, and the weather information acquisition unit acquires information about the weather in a location where the building is installed. The gas usage prediction unit obtains the temperature for a unit period at the location where the unit is installed, and predicts the gas usage in the building by simple regression analysis of the temperature and unit gas usage obtained for multiple unit periods, with the temperature for the unit period obtained by the weather information acquisition unit as the explanatory variable and the unit gas usage, which is the gas usage for that unit period obtained by the gas usage acquisition unit, as the objective variable, and classifies the building based on the slope of the regression equation calculated by the simple regression analysis, the total average temperature, which is the average temperature for the analysis period in which the simple regression analysis is performed, and the total average gas usage, which is the average value of multiple unit gas usages for the analysis period .

According to the present disclosure, gas usage in a building is predicted based on weather information, and delivery management information for managing the delivery of gas cylinders is generated based on the predicted gas usage, making it possible to manage the delivery of gas cylinders in response to changes in gas usage in the building.

1 is a configuration diagram showing a part of the configuration of a delivery management system according to a first embodiment. 1 is a block diagram showing a part of the configuration of a building according to embodiment 1. FIG. 1 is a block diagram showing a part of the configuration of a delivery management device according to a first embodiment. 1 is a configuration diagram showing an example of the hardware configuration of a delivery management device and a terminal according to a first embodiment. FIG. 1 is a configuration diagram showing an example of the hardware configuration of a delivery management device and a terminal according to a first embodiment. FIG. 10 is a flowchart showing a delivery management process performed by the delivery management device according to the first embodiment. FIG. 10 is a distribution diagram showing the distribution of buildings in the first embodiment, where the horizontal axis represents the slope of the regression equation and the vertical axis represents the total average gas consumption. FIG. 2 is a schematic diagram showing reference groups into which buildings according to the first embodiment are classified. FIG. 10 is a schematic diagram showing groups into which buildings in accordance with the first embodiment have been reclassified.

Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings.
Embodiment 1.
First, the configuration of a delivery management system 100 according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a configuration diagram showing a part of the configuration of the delivery management system 100. The delivery management system 100 according to the first embodiment is a system for managing the delivery of gas cylinders 301 for replacing gas cylinders 301 to buildings 300 in which gas cylinders 301 storing gas fuels used as fuels such as LPG (Liquefied Petroleum Gas) and LNG (Liquefied Natural Gas) are installed.

The delivery management system 100 includes a database (DB) that stores statistical information related to weather, multiple buildings 300 in which gas cylinders 301 are installed, a delivery management device 200 that manages the delivery of the gas cylinders 301, and terminals M1, M2, M3, and M4 that are owned by multiple delivery personnel who deliver the gas cylinders 301 to each building 300. The database (DB), multiple buildings 300 managed by the delivery management device 200, the delivery management device 200, and multiple terminals M1 to M4 are connected to each other via a network (N).

Database DB stores statistical information on weather and information on future weather forecasts, measured or collected by organizations such as government agencies, NGOs, and private companies. Database DB acquires statistical information on weather, such as temperature, rainfall, snowfall, and sunshine hours, at the location where building 300 is located, linking it to the measurement date and time, and provides the acquired information to the outside via network N. Terminals M1 to M4 each have a display device Ma that displays information. Display device Ma is, for example, an LCD display that can display information as an image. Terminals M1 to M4 display the information acquired via network N on display device Ma.

Next, the configuration of building 300 according to embodiment 1 will be described with reference to Figure 2. Figure 2 is a block diagram showing part of the configuration of building 300. Building 300 has gas cylinder 301, gas usage measuring device 302, and gas equipment (not shown) that uses gas fuel. Gas cylinder 301 supplies the gas fuel stored therein to gas equipment (not shown) such as heating equipment, hot water equipment, and gas cookers installed in building 300 via a pressure regulator (not shown) that reduces the gas fuel to a predetermined pressure.

The gas usage amount measuring device 302 has a flow rate measuring unit 302a, a timing unit 302c, a memory unit 302b, and an output unit 302d. The flow rate measuring unit 302a measures the flow rate of gas fuel supplied from the gas cylinder 301 to the gas equipment. The timing unit 302c measures the measurement date and time of the flow rate of gas fuel measured by the flow rate measuring unit 302a. The memory unit 302b stores the measurement results of the flow rate of gas fuel measured by the flow rate measuring unit 302a and information related to the measurement date and time.

The output unit 302d outputs information regarding the flow rate of gas fuel supplied from the gas cylinder 301 to the gas equipment via the network N. For example, the output unit 302d references information stored in the memory unit 302b and outputs information regarding the measurement results of the gas fuel flow rate by the flow rate measurement unit 302a and the measurement date and time via the network N. Also, for example, the output unit 302d outputs the total amount of gas used in a specified unit period via the network N for each unit period. The unit period may be, for example, one day, one week, or one month.

Configured in this manner, the gas usage measurement device 302 acquires information regarding the amount of gas supplied by the gas cylinder 301 to the gas equipment of the building 300, i.e., the amount of gas usage in the building 300, and outputs the acquired information via the network.

Next, the configuration of the delivery management device 200 according to embodiment 1 will be described with reference to Figure 3. Figure 3 is a block diagram showing part of the configuration of the delivery management device 200. The delivery management device 200 has an input unit 201, an output unit 202, a gas usage amount acquisition unit 204, a weather information acquisition unit 205, a gas usage amount prediction unit 206, an information generation unit 207, and a memory unit 203.

The input unit 201 is connected to the network N and an input device such as a keyboard or mouse, and various information is input thereto. The output unit 202 is connected to the network N and an output device such as an LCD display, and outputs various information. The gas usage amount acquisition unit 204 acquires information related to gas usage from the gas usage measurement devices 302 of each building 300 via the input unit 201 and the network N. For example, the gas usage amount acquisition unit 204 acquires the total gas usage amount for each building 300 in a unit period multiple times during a specified survey period (analysis period) that is sufficiently longer than the unit period. Specifically, the gas usage amount acquisition unit 204 acquires the weekly gas usage amount for each building 300 from the start date to the end date of the 10-month survey period.

The weather information acquisition unit 205 acquires statistical information about the weather in the location of the building 300, for which the gas usage acquisition unit 204 has acquired information about gas usage, from the database DB via the input unit 201 and the network N. For example, the weather information acquisition unit 205 acquires statistical information about the temperature at a representative point in the area where the building 300, for which the gas usage acquisition unit 204 has acquired information about gas usage, is located. Specifically, if the gas usage acquisition unit 204 acquires gas usage for a unit period for a specific building 300 multiple times during a specific survey period, the weather information acquisition unit 205 acquires the average temperature at a representative point in the administrative district for which the building 300 is located, for the same unit period during the survey period as the unit period for which the gas usage acquisition unit 204 acquired gas usage. Note that it is desirable that the unit period for which statistical information about gas usage and weather is acquired be adjacent to the unit periods before and after it. When multiple unit periods are set in this way, the total length of all unit periods is equal to the length of the survey period.

The gas usage prediction unit 206 predicts the gas usage of each building 300 for a predetermined future prediction period based on information relating to the gas usage of each building 300 acquired by the gas usage acquisition unit 204 and statistical information relating to the weather in the locations where these buildings 300 are located acquired by the weather information acquisition unit 205. Details of the gas usage prediction unit 206 will be described later.

The information generation unit 207 generates delivery management information for managing the delivery of new gas cylinders 301 to the building 300 based on the predictions made by the gas usage prediction unit and the information stored in the memory unit 203. Details of the information generation unit 207 will be described later.

The memory unit 203 stores information input from the input unit 201, information calculated by each unit of the delivery management device 200, and other information. The memory unit 203 has a building information memory unit 203a, a weather information memory unit 203b, and a delivery information memory unit 203c. The building information memory unit 203a stores information about each building 300 input from the input unit 201. For example, the building information memory unit 203a stores information about the gas usage of each building 300 acquired by the gas usage acquisition unit 204, the address of each building 300, location information for identifying the location of each building 300, information for identifying customers using the building 300, information about the characteristics of the building 300, and the like. The characteristics of the building 300 are, for example, the temperature elasticity with respect to the gas consumption of each building 300. Details of the temperature elasticity with respect to the gas consumption will be described later.

The weather information storage unit 203b stores statistical information about the weather in the location where each building 300 is located, acquired by the weather information acquisition unit 205. For example, the weather information storage unit 203b stores information about the temperature in the area where each building 300 is located, acquired by the weather information acquisition unit 205. The delivery information storage unit 203c stores information for managing the delivery of gas cylinders 301, such as delivery management information generated by the information generation unit 207 and information about past deliveries of gas cylinders 301.

Next, the hardware configuration of the delivery management device 200, the gas usage amount measuring device 302, and the terminals M1 to M4 will be described with reference to Figures 4 and 5. Figures 4 and 5 are diagrams showing an example of a portion of the hardware configuration of the delivery management device 200, the gas usage amount measuring device 302, and the terminals M1 to M4.
For example, as shown in FIG. 4, the delivery management device 200 has a processing circuit, which is dedicated hardware. The processing circuit may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination thereof. Also, as shown in FIG. 5, for example, the delivery management device 200 has a memory and a processor, and is configured so that the processor reads and executes programs stored in the memory. In this way, each function of the delivery management device 200 is realized by the dedicated hardware processing circuit or processor executing a program.

Similarly, the gas usage measurement device 302 and terminals M1 to M4 have dedicated hardware processing circuits or processors, and the functions of the gas usage measurement device 302 and terminals M1 to M4 are realized by the dedicated hardware processing circuits or processors executing programs.

Next, the delivery management processing performed by the delivery management device 200 will be described with reference to Figures 1, 3, and 6 to 9. Figure 6 is a flowchart showing the delivery management processing performed by the delivery management device 200 according to embodiment 1. The delivery management processing is processing to support the delivery work of the delivery personnel by generating delivery management information for managing the delivery of the gas cylinders 301 and transmitting the delivery management information to the terminals owned by each delivery personnel.

First, when the delivery management device 200 starts the delivery management process, it determines whether the gas usage acquisition unit 204 and the weather information acquisition unit 205 have acquired, for each building 300 under management, unit gas usage as information regarding gas usage over multiple different unit periods, and information regarding the temperature at the location where each building 300 is located over those unit periods as statistical information regarding the weather (step ST1).

The unit gas usage is the gas usage for each building 300 under management per unit period during the survey period. For example, if the unit periods p1, p2, ... pn are the periods divided into unit periods from the start date of the survey period, the delivery management device 200 acquires multiple unit gas usages u1, u2, ... un for each building 300, which are the gas usage for each building 300 during each unit period p1, p2, ... pn. In addition, in this process, the delivery management device 200 acquires information related to temperature, such as the average daily temperature in the area where each building 300 is located from the start date to the end date of the survey period.

If, in the processing of step ST1, information regarding unit gas usage and temperature for multiple different unit periods is obtained (YES in step ST1), the delivery management device 200 calculates the unit temperature using the gas usage prediction unit 206 based on the obtained information regarding temperature (step ST2). The unit temperature is the temperature during the unit period at the location of each building 300, and is the temperature during the unit period corresponding to the unit period for the obtained unit gas usage. For example, the delivery management device 200 obtains unit temperatures t1, t2, ... tn, which are the average temperatures at the location of each building 300 during each unit period p1, p2, ... pn for which the unit gas usage was obtained.

After processing step ST2, the delivery management device 200 performs, by the gas usage amount prediction unit 206, a simple regression analysis of the unit temperatures t1, t2, ..., tn acquired over multiple unit periods p1, p2, ..., pn for each building 300, with the unit temperatures t1, t2, ..., tn as explanatory variables and the unit gas usage amount as the response variable (step ST3). In this processing, the delivery management device 200 obtains the following regression equation, which is the result of the simple regression analysis of the unit temperature and the unit gas usage amount, with gas consumption amount u and temperature t.
u=m*t+k (1)

In order to ensure the reliability of the simple regression analysis, a sufficient number of unit temperatures and unit gas consumption volumes are required, so it is desirable that the survey period be sufficiently longer than the unit period. However, if the survey period is too long, there is a possibility that the characteristics of the building 300 being managed may change due to changes in the consumer's family structure or changes to the building's 300 gas equipment. For this reason, it is desirable that the survey period be at least six months but no more than three years. Furthermore, in areas with four seasons, it is desirable that the survey period be a period of approximately three seasons or more, for example, a period of nine months or more. More preferably, in areas with summer and winter, the survey period should be at least nine months but no more than one year, including summer and winter.

After processing step ST3, the delivery management device 200 calculates the total average gas usage U and the total average temperature for the survey period using the gas usage prediction unit 206 (step ST4). The total average gas usage U is the average value of the unit gas usage for the survey period. The total average gas usage U is expressed as follows using the unit gas usages u1, u2, ..., un obtained for unit periods p1, p2, ..., pn and the number of samples n:
U=(u1+u2+...+un)/n (2)

The total average temperature is the average value of the unit temperatures during the survey period. The total average temperature T is expressed as follows using the unit temperatures t1, t2, ..., tn calculated over the multiple unit periods p1, p2, ..., pn and the number of samples n:
T=(t1+t2+...tn)/n (3)
The total average temperature may be obtained directly from the database DB by the weather information acquisition unit 205, or may be calculated by the gas usage prediction unit 206 based on the temperature of each day in the survey period and the number of days in the survey period obtained from the database DB by the weather information acquisition unit 205. Furthermore, if the unit temperature is the average temperature in the unit period and the total length of all the unit periods is equal to the length of the survey period, the total average temperature is the average temperature in the survey period.

After processing step ST4, the delivery management device 200 uses the gas usage prediction unit 206 to calculate a characteristic value ε for each building 300 that is the management target, based on the total average gas usage during the survey period, the total average temperature, and the slope of the regression equation (step ST5). The characteristic value ε is the ratio of the rate of change in the gas consumption of the building 300 to the rate of change in the temperature of the location where the building 300 is located. In other words, the characteristic value ε is the temperature elasticity of the gas consumption of the building 300. The characteristic value ε is expressed as follows using the total average gas usage U during the survey period, the total average temperature T, and the slope m of the regression equation:
ε=(dU/U)/(dT/T)=(T/U)*(dU/dT)=(T/U)m
(4)
Here, dT/T is the rate of change of the temperature, and dU/U is the rate of change of the gas consumption.

For example, a building 300 with a characteristic value ε of ε<0 tends to increase its gas consumption as the temperature drops, while a building 300 with a characteristic value ε of 0<ε tends to decrease its gas consumption as the temperature drops. Furthermore, a building 300 with a characteristic value ε of |ε|<1 has a small rate of change in gas consumption relative to changes in temperature, while a building 300 with a characteristic value ε of 1<|ε| has a large rate of change in gas consumption relative to changes in temperature. In other words, a building 300 with a characteristic value ε of |ε|<1 has a low temperature elasticity of gas consumption, while a building 300 with a characteristic value ε of 1<|ε| has a high temperature elasticity of gas consumption. In other words, a building 300 with a characteristic value ε of |ε|<1 has inelastic gas consumption relative to temperature, while a building 300 with a characteristic value ε of 1<|ε| has an elastic gas consumption relative to temperature.

After processing step ST5, the delivery management device 200 extracts a specific building 300 from the multiple buildings 300 under management based on the characteristic value ε, the total average gas usage U, and the slope m of the regression equation using the gas usage prediction unit 206 (step ST6).
7 is a distribution diagram showing the distribution of buildings 300 in an area with the same statistical total average temperature T, with the horizontal axis representing the slope m of the regression equation and the vertical axis representing the total average gas usage U, in order to enable visual analysis of buildings 300 that are the subject of management based on the characteristic value ε, the total average gas usage U, and the slope m of the regression equation. In FIG. 7, line L1 indicates the line where the characteristic value ε is -1, line L0 indicates the line where the characteristic value ε is 0, and line L2 indicates the line where the characteristic value ε is 1.

Therefore, buildings 300 located in area A, which is the area below (to the left of) line L1, are buildings 300 whose characteristic value ε is ε < -1; buildings 300 located in area B, which is the area between lines L1 and L0, are buildings 300 whose characteristic value ε is 0 < ε < -1; buildings 300 located in area C, which is the area between lines L0 and L2, are buildings 300 whose characteristic value ε is 0 < ε < 1; and buildings 300 located in area D, which is the area below (to the right of) line L2, are buildings 300 whose characteristic value ε is 1 < ε. For example, in the processing of step ST6, the delivery management device 200 can classify the building 300 using the gas usage prediction unit 206 based on whether the characteristic value ε is ε<-1, ε=-1, -1<ε<0, ε=0, 0<ε<1, 1=ε, or 1<ε; whether the total average gas usage U is relatively high or low; and whether the absolute value |m| of the slope m of the regression equation is relatively large or small. Note that the determination of whether the total average gas usage U and the absolute value |m| of the slope m of the regression equation are relatively large or small may be based on the average value of the total average gas usage U and the absolute value |m| of the slope m of the regression equation in each of regions A to D, the median value, or some other criterion.

In addition, in Figure 7, line L3 indicates a straight line where the total average gas usage U is a predetermined first threshold U1, and line L4 indicates a straight line where the slope m of the regression equation is a predetermined second threshold m1. In the processing of step ST6, the delivery management device 200, using the gas usage prediction unit 206, extracts as specific buildings buildings 300 located in area A1, which is the area above line L3 in area A, and buildings 300 located in area B1, which is the area to the left of line L4 in area B. Buildings 300 located in area A1 are buildings 300 with a relatively large characteristic value ε and a relatively large total average gas usage U, while buildings 300 located in area B1 are buildings 300 with a relatively small characteristic value ε, a relatively large absolute value |m| of the slope m of the regression equation, and a relatively large total average gas usage U.

In general, gas consumption increases as the temperature drops. The specific buildings, which are buildings 300 located in area A1 and areas 300 located in area B1, are likely to experience a significant increase in gas consumption as the temperature drops, and are therefore buildings 300 that have a significant impact on the workload of delivery personnel when delivering gas cylinders 301. For this reason, managing specific buildings is important when managing the delivery of gas cylinders 301. Note that in Figure 7, the intersection of line L3 and line L1 is depicted as coinciding with the intersection of line L4 and line L1, but the first threshold U1 and second threshold m1 may be set so that these intersections do not coincide. After extracting specific buildings, the delivery management device 200 stores, for each building 300, the characteristic value ε of each building 300, the slope m of the regression equation, and information indicating whether the building is a specific building in the building information storage unit 203a.

After processing step ST6, the delivery management device 200 uses the weather information acquisition unit 205 to acquire temperature information, which is information related to temperatures during a specified prediction period (YES in step ST7). The prediction period may be, for example, the next week, the next month, the next quarter, or a specified period in the winter of the following year. The weather information acquisition unit 205 may, for example, acquire temperature information, which is a predicted value of the temperature during the prediction period, from the database DB, or the gas usage prediction unit 206 may acquire temperature information by predicting the temperature during the prediction period based on information about past weather acquired from the database DB.

After processing step ST7, the delivery management device 200 uses the gas usage prediction unit 206 to predict the gas usage of each specific building during the prediction period (step ST8). In this process, the gas usage prediction unit 206 predicts the gas usage of each specific building during the prediction period based on the information related to gas usage acquired by the gas usage acquisition unit 204 and the information related to weather acquired by the weather information acquisition unit 205. For example, the gas usage prediction unit 206 predicts the gas usage of each specific building based on the characteristic value ε of each specific building, the slope m of the regression equation, and the temperature information during the prediction period.

After processing step ST8, the delivery management device 200 generates delivery management information using the information generation unit 207 (step ST9). In this process, the information generation unit 207 generates delivery management information based on the prediction by the gas usage prediction unit 206. For example, the information generation unit 207 generates delivery management information based on the prediction by the gas usage prediction unit 206, including information on the number of replacements of gas cylinders 301 for each building 300 required during the prediction period. Also, for example, the information generation unit 207 generates delivery management information based on the prediction by the gas usage prediction unit 206, including information on the number of replacements of gas cylinders 301 for each building 300 required during the prediction period. Also, for example, the information generation unit 207 generates delivery management information based on the prediction by the gas usage prediction unit 206, including information on the delivery route along which delivery personnel will deliver gas cylinders 301 on each delivery date during the prediction period.

Furthermore, for example, the information generation unit 207 generates delivery management information including information classifying multiple buildings 300 into multiple groups based on the predictions made by the gas usage prediction unit 206 and the location information of each building 300 acquired from the building information storage unit 203a. Specifically, the information generation unit 207 generates delivery management information including information classifying multiple buildings 300 into multiple groups associated with each delivery person delivering the gas cylinders 301 based on the predictions made by the gas usage prediction unit 206 and the location information of each building 300 acquired from the building information storage unit 203a.

Figure 8 is a schematic diagram showing groups into which multiple buildings J10-J49, which are subject to management, are associated with each delivery person. For example, the delivery information storage unit 203c stores information (classification information) in advance that classifies buildings J10-J49 into groups R1, R2, R3, and R4, which are the multiple reference groups shown in Figure 8. For example, buildings J10-J19 are classified into group R1, buildings J20-J29 are classified into group R2, buildings J30-J39 are classified into group R3, and buildings J40-J49 are classified into group R4. Each group R1-R4 is associated with a delivery person, and gas cylinders 301 are delivered to buildings classified into one group by the same delivery person. Groups R1-R4 are separated by boundaries BN. The boundary BN is set based on, for example, roads W1, W2, W3, W4, W5, W6, W7, river K, railway tracks (not shown), administrative division boundaries (not shown), etc.

The reference groups R1 to R4 stored in the delivery information storage unit 203c may be, for example, information previously input from the input unit 201, or may be groups in which each delivery person delivered gas cylinders 301 in the past, such as during the previous prediction period.

For example, in the processing of step ST9, the information generation unit 207 references the information on the reference group stored in the delivery information storage unit 203c and predicts, for each group, the delivery time required to deliver the gas cylinder 301 during the prediction period. For example, the information generation unit 207 generates delivery management information for each group, including information indicating the delivery route of the gas cylinder 301 that passes through the buildings to which the gas cylinder 301 is delivered, and predicts the delivery time required to deliver the gas cylinder 301 along the delivery route. Furthermore, for example, the information generation unit 207 predicts the delivery time required to deliver the gas cylinder 301 based on one or a combination of the length of the generated delivery route, the number of buildings passed by the generated delivery route, the number of gas cylinders 301 to be replaced when delivery is made along the generated delivery route, and the predicted travel time when moving along the delivery route by a transport vehicle or the like for the delivery gas cylinder 301 and a specified means of transportation.

Once the delivery time is predicted, the information generation unit 207 compares the predicted delivery times between each group and reclassifies buildings J10 to J49 into new groups so as to minimize the difference in delivery time between each group.

Figure 9 is a schematic diagram showing the groups into which the information generation unit 207 has reclassified buildings J10 to J49. For example, if the information generation unit 207 determines that the delivery time required to deliver gas cylinder 301 to buildings in group R2 during the prediction period is longer than the delivery time required to deliver gas cylinder 301 to buildings in group R1 during the prediction period, it changes the boundary BN to set a new boundary BN' and reclassifies buildings J10 to J49 into new groups R1', R2', R3, and R4. For example, the information generation unit 207 adds buildings J28 and J29 included in group R2 to buildings J10 to J19 included in group R1 to create a new group R1', and removes buildings J28 and J29 included in group R2 from group R2 to create a new group R2'. This allows delivery management of gas cylinders 301 to be carried out so as to equalize the workload among delivery personnel making deliveries for each group R1', R2', R3, and R4.

When the information generation unit 207 classifies buildings J10 to J49 into new groups, it generates delivery management information for each newly classified group, including information indicating the delivery route of the gas cylinder 301.

If no information is acquired in the processing of step ST1 (NO in step ST1), or if no temperature information is acquired in the processing of step ST7 (NO in step ST7), the delivery management device 200 generates delivery management information (step ST9) without using the information generation unit 207 to predict gas usage or classify buildings into new groups. For example, in this process, the information generation unit 207 generates delivery management information based on the reference groups R1 to R4, including information on delivery routes that are not based on gas consumption predictions.

When the information generation unit 207 generates delivery management information in the processing of step ST9, the delivery management device 200 outputs (transmits) the delivery management information from the output unit 202 (step ST10). For example, the delivery management device 200 transmits delivery management information including information indicating that the buildings have been classified into a new group and information indicating the delivery route for each group to the terminal of the delivery person corresponding to each group among terminals M1 to M4. When terminals M1 to M4 receive the delivery management information, they display the received delivery management information on the display device Ma. For example, terminals M1 to M4 display on the display device Ma the delivery route for gas cylinders 301 for the group corresponding to the delivery person using the terminal.

In this way, the delivery management device 200 according to embodiment 1 predicts gas usage in the building 300 based on information related to temperature, and generates delivery management information for managing the delivery of the gas cylinder 301 based on the predicted gas usage, thereby enabling delivery management of the gas cylinder 301 in accordance with changes in gas usage in the building 300.

In addition, the delivery management device 200 according to embodiment 1 classifies multiple buildings 300 into multiple groups based on predicted gas usage, and can therefore manage delivery for each group according to gas usage based on predicted gas usage.

In addition, the delivery management device 200 according to embodiment 1 predicts the delivery time of the gas cylinders 301 for each group and classifies multiple buildings into new multiple groups so as to minimize the difference in delivery time between multiple groups, thereby leveling out the workload of delivery personnel, which changes in response to changes in gas usage.

Note that, although the delivery management device 200 according to embodiment 1 predicts gas usage in the building 300 based on information relating to temperature, this is not limited to this. The delivery management device may predict gas usage in the building based on weather-related information that correlates with gas usage; for example, the delivery management device may predict gas usage based on weather-related information such as rainfall, snowfall, and sunshine hours.

Furthermore, the delivery management device 200 according to embodiment 1 compares the predicted delivery times between each group and reclassifies buildings J10 to J49 into new groups so as to minimize the difference in delivery times between each group, but is not limited to this. The delivery management device may classify buildings into multiple groups so as to minimize the difference in the amount of delivery work between each group. For example, the delivery management device may generate information on the gas cylinder delivery routes for each group and classify the buildings into multiple groups so as to minimize the difference in the length of the delivery routes between each group, or may classify the buildings into multiple groups so as to minimize the difference in the length of travel time along the delivery route by a specified means of transportation between each group, or may classify the buildings into multiple groups so as to minimize the difference in the number of buildings passed by the delivery route between each group, or may classify the buildings into multiple groups so as to minimize the difference in the number of gas cylinders replaced when making deliveries along the delivery route between each group.

Note that this disclosure allows for modifications to any of the components of the embodiments, or for any of the components to be omitted.

200 Delivery management device 202 Output unit 204 Gas usage amount acquisition unit 205 Weather information acquisition unit 206 Gas usage amount prediction unit 207 Information generation unit 300 Building 301 Gas cylinder m Slopes of regression equation M1 to M4 Terminal T Total average temperature U Total average gas usage amount ε Characteristic value

Claims (9)

a gas usage amount acquiring unit that acquires information about gas usage amount from a gas cylinder installed in the building;
a weather information acquisition unit that acquires information about the weather in a location where the building is located;
a gas usage amount prediction unit that predicts gas usage in the building based on information about gas usage acquired by the gas usage amount acquisition unit and information about weather acquired by the weather information acquisition unit;
an information generating unit that generates delivery management information for managing delivery of new gas cylinders to the building based on the prediction by the gas usage prediction unit ,
The gas usage amount acquisition unit acquires the gas usage amount of the building for a unit period,
the meteorological information acquisition unit acquires the temperature for a unit period at a location where the building is located,
The gas usage amount prediction unit predicts the gas usage amount in the building by simple regression analysis of the temperatures and unit gas usage amounts acquired over a plurality of unit periods, with the temperatures in the unit periods acquired by the weather information acquisition unit as an explanatory variable and the unit gas usage amount, which is the gas usage amount in the unit periods acquired by the gas usage amount acquisition unit, as a response variable, and classifies the building based on the slope of the regression equation calculated by the simple regression analysis, the total average temperature, which is the average temperature over the analysis period in which the simple regression analysis is performed, and the total average gas usage amount, which is the average value of the plurality of unit gas usage amounts over the analysis period.
A delivery management device characterized by: a gas usage amount acquiring unit that acquires information about gas usage amount from a gas cylinder installed in the building;
a weather information acquisition unit that acquires information about the weather in a location where the building is located;
a gas usage amount prediction unit that predicts gas usage in the building based on information about gas usage acquired by the gas usage amount acquisition unit and information about weather acquired by the weather information acquisition unit;
an information generating unit that generates delivery management information for managing delivery of new gas cylinders to the building based on the prediction by the gas usage prediction unit,
the information generation unit acquires location information relating to locations of a plurality of buildings including the building, and generates delivery management information including information for classifying the plurality of buildings into a plurality of groups based on the location information;
the information generation unit generates, for each of the plurality of groups, delivery management information based on the location information, the delivery management information including information indicating a gas cylinder delivery route passing through buildings to which the gas cylinder is delivered;
the information generation unit predicts a delivery time required to deliver the gas cylinder along the delivery route, and generates information for classifying the plurality of buildings into the plurality of groups based on the delivery time;
The information generation unit acquires classification information including information on classification of the plurality of buildings into a plurality of reference groups, and classifies the plurality of buildings into the plurality of groups so as to reduce the difference in delivery time between the plurality of reference groups.
A delivery management device characterized by: The delivery management device according to claim 1 or 2 , wherein the weather information acquisition unit acquires information about the temperature of a location where the building is located. The delivery management device described in claim 1, characterized in that the information generation unit acquires location information regarding the locations of multiple buildings including the building, and generates delivery management information including information classifying the multiple buildings into multiple groups based on the location information. The delivery management device according to claim 4, characterized in that the information generation unit generates delivery management information for each of the plurality of groups based on the location information, the delivery management information including information indicating a gas cylinder delivery route passing through buildings to which the gas cylinder is delivered. The delivery management device according to claim 5, characterized in that the information generation unit predicts the delivery time required to deliver the gas cylinders along the delivery route, and generates information for classifying the plurality of buildings into the plurality of groups based on the delivery time. The delivery management device of claim 6, characterized in that the information generation unit acquires classification information including information on the classification of the multiple buildings into multiple reference groups, and classifies the multiple buildings into the multiple groups so as to reduce the difference in delivery time between the multiple reference groups. 6. The delivery management device according to claim 2 , further comprising an output unit that outputs delivery management information including the delivery route to a plurality of terminals associated with each of the plurality of groups. A delivery management method performed by a device including a gas usage amount acquisition unit, a weather information acquisition unit, a gas usage amount prediction unit, and an information generation unit,
a step in which the gas usage amount acquisition unit acquires information regarding gas usage amount from a gas cylinder installed in the building ;
a step in which the meteorological information acquisition unit acquires information about the weather in a location where the building is located;
a step in which the gas usage prediction unit predicts the gas usage in the building based on the information on gas usage acquired by the gas usage acquisition unit and the information on weather acquired by the weather information acquisition unit;
a step in which the information generation unit generates delivery management information for managing the delivery of new gas cylinders to the building based on the prediction by the gas usage prediction unit ;
The gas usage amount acquisition unit acquires the gas usage amount of the building for a unit period,
the meteorological information acquisition unit acquires the temperature for a unit period at a location where the building is located,
The gas usage amount prediction unit predicts the gas usage amount in the building by simple regression analysis of the temperatures and unit gas usage amounts acquired over a plurality of unit periods, with the temperatures in the unit periods acquired by the weather information acquisition unit as an explanatory variable and the unit gas usage amount, which is the gas usage amount in the unit periods acquired by the gas usage amount acquisition unit, as a response variable, and classifies the building based on the slope of the regression equation calculated by the simple regression analysis, the total average temperature, which is the average temperature over the analysis period in which the simple regression analysis is performed, and the total average gas usage amount, which is the average value of the plurality of unit gas usage amounts over the analysis period.
A delivery management method characterized by: