Information processing system and information processing method

Abstract

To provide an information processing system and an information processing method that can improve convenience.SOLUTION: An information processing system according to an embodiment comprises a determination unit. The determination unit determines details of cooling operation of a refrigerator on the basis of a first determination element that is a determination element using state information indicating the state of the refrigerator, and including the state information in a fixed time in the past, and a second determination element calculated on the basis of the state information in a plurality of the fixed times in the past. The state information includes information indicating a door opening time of the refrigerator.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] FIELD An embodiment of the present invention relates to an information processing system and an information processing method. [Background technology]

[0002] Refrigerators that control cooling operation based on instructions from a server are known. Information processing systems related to such refrigerators are expected to improve convenience. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2019-143953 A Summary of the Invention [Problem to be solved by the invention]

[0004] An object of the present invention is to provide an information processing system and an information processing method that can improve convenience. [Means for solving the problem]

[0005] The information processing system according to the embodiment includes a determination unit. The determination unit is a determination element using status information indicating a status of a refrigerator, It is a continuous time A first determination element including the state information for a certain period of time; At least a certain time in the past multiple One and a second determination element calculated based on the status information for a fixed period of time, the status information including information indicating a door open time of the refrigerator. [Brief description of the drawings]

[0006] [Figure 1] FIG. 1 is a diagram showing an overall configuration of a refrigerator system according to an embodiment. [Diagram 2]FIG. 1 is a front view showing a schematic configuration of a refrigerator according to an embodiment. [Diagram 3] FIG. 2 is a block diagram showing a functional configuration of the refrigerator according to the embodiment. [Figure 4] FIG. 2 is a block diagram showing a functional configuration of a server according to the embodiment. [Diagram 5] 4A to 4C are diagrams for explaining estimation of a lifestyle pattern according to an embodiment. [Figure 6] FIG. 4 is a functional block diagram based on the processing of an operation plan generating unit according to the embodiment. [Figure 7] FIG. 4 is an explanatory diagram of creating a cooling mode according to the embodiment. [Figure 8] 5A to 5C are diagrams showing a specific example of data adjustment processing according to the embodiment. [Figure 9] 11 is a flowchart showing a flow of a prediction process in an operation plan generating unit of the embodiment. [Figure 10] FIG. 4 is a diagram for explaining a pre-cooling operation determination in the embodiment. [Figure 11] 5 is a diagram for explaining eco-driving determination according to the embodiment; FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, an information processing system and an information processing method according to an embodiment will be described with reference to the drawings. In the following description, the same reference numerals are used for configurations having the same or similar functions. Then, duplicated descriptions of those configurations may be omitted. In this application, "based on XX" means "based on at least XX" and may include cases where the configuration is based on another element in addition to XX. Furthermore, "based on XX" is not limited to cases where XX is directly used, but may also include cases where the configuration is based on XX that has been subjected to calculation or processing. In this application, "XX or YY" is not limited to either one of XX and YY, but may include both XX and YY. This also applies when there are three or more selective elements. XX and YY are any element (for example, any information).

[0008] In this application, "obtain" is not limited to actively obtaining information by sending a transmission request, but may also include passively receiving information transmitted from another device. Also, "obtain" is not limited to directly obtaining target information (information to be obtained) from outside, but may also include generating and obtaining target information by performing calculations or processing on information obtained from outside.

[0009] (Embodiment) <1. Overall configuration of home appliance management system> FIG. 1 is a diagram showing the overall configuration of a home appliance management system 1 according to an embodiment. The home appliance management system 1 includes, for example, a refrigerator 100, a server 200, and a terminal device 300. The server 200 is an example of an "information processing system." However, the "information processing system" is not limited to the above example and may be realized by the control device 160 of the refrigerator 100, or may be realized by the server 200 and the control device 160 of the refrigerator 100. The network NW described later may be, for example, the Internet, a cellular network, a Wi-Fi network, a Low Power Wide Area (LPWA), a Wide Area Network (WAN), a Local Area Network (LAN), or other public lines or dedicated lines, depending on the situation.

[0010] The refrigerator 100 is installed in the residence of a user U. The refrigerator 100 is connected to a network NW via, for example, a wireless router WR and a modem M installed in the residence of the user U. The refrigerator 100 can communicate with a server 200 or a terminal device 300 via the network NW.

[0011] The server 200 is a management server that manages the refrigerator 100. The server 200 is composed of one or more server devices (e.g., cloud servers). The server 200 is capable of communicating with the refrigerator 100 or the terminal device 300 via the network NW. The server 200 may include an information processing unit that performs edge computing or fog computing, such as an information processing unit included in a router in the network NW. The server 200 is not limited to a cloud server, and may be a computer in the residence of the user U, a home router, or the like.

[0012] The terminal device 300 is a terminal device used by a user U of the refrigerator 100. The terminal device 300 is, for example, a mobile terminal device such as a smartphone or a tablet terminal device. However, the terminal device 300 is not limited to a mobile terminal device, and may be a personal computer or a voice dialogue device such as a smart speaker. The terminal device 300 has, for example, a display device 301 including a display screen 301a capable of displaying various information, and an input device 302 capable of receiving input from the user U. The input device 302 is, for example, a touch panel provided on top of the display screen 301a of the display device 301. The input device 302 may include a camera, a microphone, and the like provided in the terminal device 300.

[0013] An application program P is installed in the terminal device 300, and the functions described below are supported. The application program P is an application program for managing the refrigerator 100. Hereinafter, application software that is started by executing the application program P is referred to as a "home appliance management application APP."

[0014] <2. Refrigerator> Next, the refrigerator 100 will be described in detail. 2 is a front view showing a schematic configuration of the refrigerator 100. The refrigerator 100 includes, for example, a housing 10 and a plurality of doors 20.

[0015] The housing 10 has thermal insulation properties and is formed in a rectangular box shape. A plurality of storage compartments 30 are provided inside the housing 10. The plurality of storage compartments 30 include, for example, a refrigerator compartment 31, a chilled compartment 31A, a vegetable compartment 32, an ice-making compartment 33, a small freezer compartment 34, and a main freezer compartment 35. The refrigerator compartment 31 and the vegetable compartment 32 are storage compartments in a chilled temperature range (for example, a temperature range of 1 to 4°C). The chilled compartment 31A is a storage compartment in a chilled temperature range (for example, a temperature range of -1°C to +1°C). The ice-making compartment 33, the small freezer compartment 34, and the main freezer compartment 35 are storage compartments in a freezer temperature range (for example, a temperature range of -10 to -20°C).

[0016] The above-mentioned refrigerator compartment 31, chilled compartment 31A, vegetable compartment 32, ice-making compartment 33, small freezer compartment 34, and main freezer compartment 35 are each an example of a "storage section". The chilled compartment 31A is an example of a "special storage section". The "special storage section" is not limited to the chilled compartment 31A, and may be a partial compartment cooled to a partial temperature zone (approximately -4°C to -2°C) or a temperature-switchable compartment in which the temperature can be switched between a plurality of temperature zones (for example, a refrigerated temperature zone and a freezer temperature zone). In the following, when the refrigerator compartment 31, chilled compartment 31A, and vegetable compartment 32 are not distinguished from each other, they may be referred to as "storage compartment 30R". In the following, when the ice-making compartment 33, small freezer compartment 34, and main freezer compartment 35 are not distinguished from each other, they may be referred to as "storage compartment 30F".

[0017] The openings of the multiple storage compartments 30 are closed openably and closably by multiple doors 20. The multiple doors 20 include left and right refrigerator compartment doors 21A, 21B that close the opening of the refrigerator compartment 31, a vegetable compartment door 22 that closes the opening of the vegetable compartment 32, an ice making compartment door 23 that closes the opening of the ice making compartment 33, a small freezer compartment door 24 that closes the opening of the small freezer compartment 34, and a main freezer compartment door 25 that closes the opening of the main freezer compartment 35. Hereinafter, when the left and right refrigerator compartment doors 21A, 21B are not distinguished from each other, they will be referred to as "refrigerator compartment doors 21."

[0018] 3 is a block diagram showing the functional configuration of the refrigerator 100. The refrigerator 100 includes, for example, a door open / close detection sensor 110, a temperature sensor 120, a cooling unit 130, an operation unit 140, a communication unit 150, a control device 160, and a storage unit 190.

[0019] <2.1 Door opening / closing detection sensor> Door opening / closing detection sensor 110 is a sensor that detects the opening and closing of door 20. Door opening / closing detection sensor 110 includes, for example, refrigerator compartment door sensor 111 that detects the opening and closing of refrigerator compartment door 21, vegetable compartment door sensor 112 that detects the opening and closing of vegetable compartment door 22, ice compartment door sensor 113 that detects the opening and closing of ice compartment door 23, small freezer compartment door sensor 114 that detects the opening and closing of small freezer compartment door 24, and main freezer compartment door sensor 115 that detects the opening and closing of main freezer compartment door 25. The detection results of door opening / closing detection sensor 110 are output to control device 160.

[0020] <2.2 Temperature sensor> Temperature sensor 120 is a temperature sensor that detects the temperature of storage compartment 30 (e.g., the air temperature inside storage compartment 30). Temperature sensor 120 includes, for example, refrigerator compartment temperature sensor 121 that detects the temperature of refrigerator compartment 31 (refrigerator compartment temperature), chilled compartment temperature sensor 122 that detects the temperature of chilled compartment 31A (chilled compartment temperature), and main freezer compartment temperature sensor 123 that detects the temperature of main freezer compartment 35 (freezer compartment temperature). The detection result of temperature sensor 120 is output to control device 160.

[0021] <2.3 Cooling section> The cooling unit 130 is a device that cools the multiple storage chambers 30. The cooling unit 130 includes, for example, a first cooler 131, a second cooler 132, a compressor 133, a three-way valve 134, a first blower 135, and a second blower 136.

[0022] The first cooler 131 is disposed corresponding to the storage compartments 30R (refrigerating compartment 31, chilled compartment 31A, and vegetable compartment 32) in the refrigeration temperature range. The second cooler 132 is disposed corresponding to the storage compartments 30F (ice-making compartment 33, small freezer compartment 34, and main freezer compartment 35) in the freezing temperature range. The compressor 133 supplies a refrigerant to the first cooler 131 and the second cooler 132.

[0023] The three-way valve 134 is switched between a first state in which the refrigerant compressed by the compressor 133 is supplied to the first cooler 131, and a second state in which the refrigerant compressed by the compressor 133 is supplied to the second cooler 132. The first blower 135 supplies the cold air cooled by the first cooler 131 to the storage compartment 30R (the refrigerator compartment 31, the chilled compartment 31A, and the vegetable compartment 32) in the refrigeration temperature range. The second blower 136 supplies the cold air cooled by the second cooler 132 to the storage compartment 30F (the ice-making compartment 33, the small freezer compartment 34, and the main freezer compartment 35) in the freezing temperature range.

[0024] <2.5 Control section> The operation unit 140 is an operation unit capable of accepting operations of the user U on the refrigerator 100. The operation unit 140 includes, for example, one or more buttons provided on the surface of the door 20 or the inner surface of the housing 10. The user U can set various cooling control modes, which will be described later, as control modes of the refrigerator 100 by operating the operation unit 140. In this application, "setting a control mode" means turning a control mode to an ON state. Instead of / in addition to the terminal device 300, the operation unit 140 may be capable of accepting an operation of the user U to set (i.e., turn to an ON state) a learning control mode, which will be described later.

[0025] <2.6 Communications Department> The communication unit 150 is, for example, a wireless communication module. The communication unit 150 is capable of communicating with the server 200 via a wireless router WR and a modem M disposed in the user U's residence.

[0026] <2.7 Control device> The control device 160 comprehensively controls the entire refrigerator 100. The control device 160 has a control command acquisition unit 161, a control unit 162, a state management unit 163, and a transmission unit 164. These functional units are realized by one or more hardware processors such as a CPU (Central Processing Unit) mounted on the refrigerator 100 executing programs. However, some or all of these functional units may be realized by hardware such as an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), or an FPGA (Field Programmable Gate Array), or may be realized by a combination of software and hardware.

[0027] The control command acquisition unit 161 acquires a control command related to the cooling operation of the refrigerator 100 from the server 200. In this embodiment, when the learning control mode is set, the control command acquisition unit 161 acquires a control command related to the cooling operation of the refrigerator 100 generated by the server 200 from the server 200. The control command is, for example, an operation command for a special operation that reduces the power consumption of the refrigerator 100. In this embodiment, the control command is a control command that designates one of a plurality of operation modes (cooling modes). The plurality of operation modes include, for example, normal operation, eco operation, and pre-cooling operation. Details of each of these operation modes will be described in the description of the server 200.

[0028] The control unit 162 controls the cooling unit 130 to cool each storage chamber 30. For example, the control unit 162 controls the cooling unit 130 based on the set temperature (target temperature) of each storage chamber 30 and the detection result of the temperature sensor 120. For example, the control unit 162 controls the compressor 133, the first fan 135, and the second fan 136 included in the cooling unit 130 by feedback control such as PID (Proportional-Integral-Differential) control based on the difference between the set temperature (target temperature) of each storage chamber 30 and the temperature detected by the temperature sensor 120.

[0029] In this embodiment, when a learning control mode described later is set, the control unit 162 controls the cooling unit 130 based on a control command (a control command from the server 200) acquired by the control command acquisition unit 161. That is, the control unit 162 executes normal operation, eco operation, or pre-cooling operation instructed by the control command.

[0030] The status management unit 163 stores information about the status of the refrigerator 100 (hereinafter referred to as "refrigerator information") in the storage unit 190. The refrigerator information includes, for example, learning status information 191 used to generate a control command for the refrigerator 100 in the server 200, and execution result information 192 indicating the execution result of the operation of the refrigerator 100.

[0031] The learning status information 191 is information indicating the status of the refrigerator 100. The learning status information 191 includes, for example, door opening / closing information 191a indicating the detection result of the door opening / closing detection sensor 110, and inside temperature information 191b indicating the detection result of the temperature sensor 120. The door opening / closing information 191a includes information regarding the door opening / closing for each predetermined unit time (for example, one hour). For example, the door opening / closing information 191a includes information indicating the number of times the door is opened or the door open time for each predetermined unit time. The "door open time" is the total time that the door 20 is in an open state. The inside temperature information 191b includes information regarding the temperature of the storage chamber 30 for each predetermined unit time (for example, one hour). For example, the inside temperature information 191b includes information indicating the average value of the deviation of the temperature sensor 120 from the set temperature (target temperature) of the storage chamber 30.

[0032] The execution result information 192 is information that indicates the type of operation mode that the refrigerator 100 actually executed in a time period in which the operation mode was instructed by a control command from the server 200. The execution result information 192 is information that indicates the type of operation mode that the refrigerator 100 actually executed in each predetermined unit time.

[0033] The transmission unit 164 communicates with the server 200 via the communication unit 150, and transmits the learning state information 191 and the execution result information 192 to the server 200. For example, the transmission unit 164 transmits the learning state information 191 and the execution result information 192 to the server 200 at a predetermined period.

[0034] <2.8 Storage section> The storage unit 190 is a functional unit that stores various information. The storage unit 190 is realized by a combination of a RAM (Random Access Memory), a ROM (Read Only Memory), an EEPROM (Electrically Erasable Programmable ROM), an SSD (Solid State Drive), etc. The storage unit 190 stores learning state information 191 and execution result information 192.

[0035] <3. Server> Next, the server 200 will be described in detail. 4 is a block diagram showing a functional configuration of the server 200. The server 200 includes, for example, an information acquisition unit 210, an operation plan generation unit 220, a control command transmission unit 230, a display information transmission unit 240, and a storage unit 290.

[0036] The information acquisition unit 210, the operation plan generation unit 220, the control command transmission unit 230, and the display information transmission unit 240 are realized by one or more hardware processors such as a CPU mounted on the server 200 executing a program. However, some or all of these functional units may be realized by hardware such as an ASIC, a PLD, or an FPGA, or may be realized by a combination of software and hardware. These functional units may be provided separately in multiple server devices. Furthermore, one or more of these functional units may be provided in the control device 160 of the refrigerator 100 or the home appliance management application APP of the terminal device 300 instead of the server 200.

[0037] <3.1 Information acquisition section> The information acquiring unit 210 acquires status information indicating the status of the refrigerator 100 transmitted from the refrigerator 100 at a predetermined period, for example, and stores the information in the storage unit 290 as part of the status information 291. The acquired status information includes door open / close information 191a indicating the detection result of the door open / close detection sensor 110 of the refrigerator 100, and inside temperature information 191b indicating the detection result of the temperature sensor 120.

[0038] <3.2 Operation plan generation unit> The operation plan generating unit 220 analyzes the lifestyle pattern (the usage pattern of the refrigerator 100) of the user U based on the usage state of the refrigerator 100 obtained based on the status information, and generates an operation plan for the refrigerator 100 according to the lifestyle pattern of the user U. In other words, the operation plan generating unit 220 is a learning function unit that learns the lifestyle pattern of the user U. In this application, "learning" is not limited to machine learning using a neural network or the like, but broadly means updating past decisions based on new information. Generating an operation plan for the refrigerator 100 is an example of "determining the details of the cooling operation of the refrigerator 100." The operation plan generating unit 220 is an example of a "decision unit."

[0039] In this embodiment, the operation plan generating unit 220 generates an operation plan for the next same day of the week based on, for example, past state information for the same day of the week directly or indirectly included in the state information 291 or the averaging information 292 described later. For example, the operation plan generating unit 220 generates an operation plan for the next same day of the week based on state information for the same day of the week for the past two weeks included in the state information 291. For example, the operation plan generating unit 220 generates an operation plan for the next Monday based on state information for the previous and two Mondays before last. Furthermore, in this embodiment, the operation plan generating unit 220 generates an operation plan for the next same day of the week and the same time based on state information for the same day of the week and the same time for the past two weeks included in the state information 291. For example, the operation plan generating unit 220 generates an operation plan for the next Monday from 10:00 a.m. to 11:00 a.m. based on state information for the previous and two Mondays before last. The same applies to Tuesday to Sunday.

[0040] In this embodiment, the operation plan of the refrigerator 100 is a plan that specifies a time period during which the refrigerator 100 performs a normal operation and a time period during which the refrigerator 100 performs a special operation. The special operation is an operation that reduces the power consumption of the refrigerator 100. In this embodiment, the special operation includes an eco-operation (first special operation) and a pre-cooling operation (second special operation). In the following, an example will be described in which the eco-operation is performed based on the number of times the door is opened and closed. Alternatively / in addition to this, the eco-operation may be performed based on the door open time.

[0041] Here, when an operation plan for the refrigerator 100 is simply generated based on the status information for the same day of the week for the past two weeks, if the actions of the user U on the same day of the week for the past two weeks are different, the accuracy of the operation plan for the refrigerator 100 may decrease. Therefore, the operation plan generating unit 220 of this embodiment performs the following process.

[0042] In the present embodiment, the operation plan generating unit 220 generates an operation plan for the refrigerator 100 based on a first judgment element, which is a judgment element using status information indicating a status of the refrigerator 100 and includes status information for a certain period of time in the past, and a second judgment element calculated based on status information for a plurality of certain periods of time in the past.

[0043] For example, the first judgment element includes status information of a first hour, which is a fixed time in the past, and status information of a second hour, which is a fixed time in the past before the first hour. The second judgment element includes status information of a third hour, which is a fixed time in the past before the second hour, as at least a part of the status information of the multiple fixed times. The second judgment element may include status information of a fourth hour, which is a fixed time in the past before the third hour, as at least a part of the status information of the multiple fixed times. In the following, a predetermined unit time (e.g., one hour) corresponds to an example of a "fixed time".

[0044] In this embodiment, the second time is the same time on the same day of the week one week ago compared to the first time. The third time is the same time on the same day of the week one week ago compared to the second time. The fourth time is the same time on the same day of the week one week ago compared to the third time. For example, status information between 10:00 a.m. and 11:00 a.m. on Monday one week ago is an example of "status information for the first time". Status information between 10:00 a.m. and 11:00 a.m. on Monday two weeks ago is an example of "status information for the second time". Status information between 10:00 a.m. and 11:00 a.m. on Monday three weeks ago is an example of "status information for the third time". Status information between 10:00 a.m. and 11:00 a.m. on Monday four weeks ago is an example of "status information for the fourth time".

[0045] In this embodiment, the second judgment element is information obtained by performing a predetermined averaging process on status information for a plurality of past fixed periods of time. For example, the second judgment element is information obtained by sequentially averaging status information for a plurality of past fixed periods of time based on a predetermined averaging process. Also, the second judgment element is information obtained by weighting and averaging status information for a plurality of past fixed periods of time so that the older the status information is, the smaller the influence it has on the second judgment element. These contents will be described in detail below.

[0046] In this embodiment, the operation plan generating unit 220 sets the state information of the predetermined unit time one week ago as the first hour state information, and sets the state information of the predetermined unit time two weeks ago as the second hour state information. The "predetermined unit time" is, for example, one hour. The state information of the first hour and the state information of the second hour are included in the first judgment element.

[0047] The operation plan generating unit 220 sets information calculated by performing a predetermined averaging process on the state information for a predetermined unit time on the same day of the week three weeks or earlier as the second judgment element. In this embodiment, the operation plan generating unit 220 analyzes the lifestyle pattern of the user U based on the first judgment element and the second judgment element, and generates an operation plan for the refrigerator 100 according to the lifestyle pattern of the user U.

[0048] In this embodiment, the status information for a predetermined unit time one week ago, the status information for a predetermined unit time two weeks ago, and the status information for a predetermined unit time three weeks ago are stored in the storage unit 290 as status information 291. On the other hand, the status information for four weeks ago or earlier is reflected in the averaged information 292 and then deleted from the status information 291.

[0049] The estimation of a lifestyle pattern will be described using the calendar shown in Fig. 5. The operation plan generating unit 220 estimates a lifestyle pattern for a given unit time on April 30 (Saturday) as follows. (1) Extract status information for a specified unit time on April 23rd, which is a Saturday one week ago, and status information for a specified unit time on April 16th, which is a Saturday two weeks ago, and set the status information one week ago and the status information two weeks ago as first judgment elements P1 and P2. (2) Status information for a specified unit time on Saturdays three weeks prior or earlier, such as April 9th, April 2nd, March 26th, March 19th, ..., is averaged by a specified averaging process, and this average value is set as the second judgment element Q (in this embodiment, this status information is sequentially averaged in advance and stored in the memory unit 290 as averaged information 292). (3) A lifestyle pattern for a given unit time on Saturday, April 30th is estimated based on the first judgment elements P1 and P2 (status information on April 23rd and April 16th) and the second judgment element Q (the average value of status information on Saturdays from April 9th, April 2nd, March 26th, March 19th, ..., which are the Saturdays from three weeks ago). The same is true for each time slot from Monday to Saturday.

[0050] In this embodiment, when the status information at the first time and the status information at the second time satisfy a predetermined relationship, the operation plan generating unit 220 generates an operation plan for the refrigerator 100 based on the first judgment element regardless of the content of the second judgment element. "Satisfying the predetermined relationship" refers to, for example, a case where a judgment result using the status information at the first time is the same as a judgment result using the status information at the second time.

[0051] On the other hand, when the state information at the first time and the state information at the second time do not satisfy the above-mentioned predetermined relationship, the operation plan generating unit 220 determines the content of the cooling operation based on the second judgment element. "The predetermined relationship is not satisfied" means, for example, that the judgment result using the state information at the first time differs from the judgment result using the state information at the second time.

[0052] In addition, when one of the status information at the first time and the status information at the second time does not exist (for example, when it cannot be acquired due to a communication failure), the operation plan generating unit 220 generates an operation plan for the refrigerator 100 based on the second determination element regardless of the content of the other of the status information at the first time and the status information at the second time.

[0053] <3.2-1 Configuration of the operation plan generation unit> 6 is a functional block diagram based on the processing of the operation plan generating unit 220. As shown in FIG. 6, the operation plan generating unit 220 has a pre-cooling operation determining unit 221, an eco-operation determining unit 222, and a normal operation determining unit 223.

[0054] The pre-cooling operation determination unit 221 estimates the lifestyle pattern of the user U using, for example, inside temperature information 191b as state information, and determines whether or not to perform pre-cooling operation in each time zone (each predetermined unit time). The eco-driving determination unit 222 estimates the lifestyle pattern of the user U using, for example, door opening / closing information 191a as state information, and determines whether or not to perform eco-driving in each time zone (each predetermined unit time). The normal operation determination unit 223 estimates the lifestyle pattern of the user U using the estimation results of the pre-cooling operation determination unit 221 and the eco-driving determination unit 222, and determines whether or not to perform normal operation in each time zone (each predetermined unit time).

[0055] The pre-cooling operation is an operation in which, when a large temperature rise (temperature rise exceeding a threshold) is expected in the storage compartment 30, the temperature of the storage compartment 30 is lowered in advance (so-called cooling is performed) to cut the peak of the temperature rise in the storage compartment 30, suppress a decrease in the cooling efficiency (COP: Coefficient Of Performance), and reduce the power consumption of the refrigerator 100. For convenience of explanation, the temperature rise in the storage compartment 30 that is the target of the pre-cooling operation is referred to as a "temperature rise exceeding a threshold" below. For example, the pre-cooling operation sets the set temperature (target temperature) of the specific storage compartment 30 lower than that of normal operation for a predetermined unit time in which it is estimated that a temperature rise exceeding the threshold will occur in the specific storage compartment 30, at the predetermined unit time and the predetermined unit time immediately before that, thereby lowering the temperature of the specific storage compartment 30 in advance. For example, the pre-cooling operation increases the operating frequency of the compressor 133, the rotation speed of the first fan 135, or the rotation speed of the second fan 136 by lowering the set temperature of the storage compartment 30 by 1°C or 2°C compared to normal operation.

[0056] The eco-operation is an operation for reducing power consumption of the refrigerator 100 by raising the set temperature (target temperature) of the storage compartment 30 compared to the normal operation during a time period when the number of times the door 20 is estimated to be low (for example, less than six times) and suppressing the operation of the cooling unit 130. For example, the eco-operation raises the set temperature of the storage compartment 30 by 1° C. or 2° C. compared to the normal operation, thereby lowering the operating frequency of the compressor 133, the rotation speed of the first fan 135, or the rotation speed of the second fan 136.

[0057] The normal operation is a basic operation of the refrigerator 100. For example, the normal operation is an operation that is set when learning is not performed by the operation plan generating unit 220. For example, the normal operation is an operation that is premised on the refrigerator 100 being used by the user U (for example, the door 20 being opened and closed). In other words, the normal operation is an operation in which a relatively low set temperature (target temperature) is set so that the temperature of the storage chamber 30 can be kept below a certain level even when the door 20 is opened and closed.

[0058] (Calculation of average data) In this embodiment, the pre-cooling operation determination unit 221 and the eco-driving determination unit 222 analyze the lifestyle pattern of the user U. As described above, in this embodiment, the lifestyle pattern is analyzed using averaged status information for a predetermined unit time one week ago and a predetermined unit time two weeks ago, as well as status information for a predetermined unit time on the same day of the week three weeks ago or earlier. The status information for a predetermined unit time on the same day of the week three weeks ago or earlier is calculated by a sequential averaging process. The calculation of the average value by this sequential averaging process will be described. The sequential averaging process is an example of a "predetermined averaging process".

[0059] The average value Xn of n pieces of data x1, x2, x3, . . . xn is calculated as shown in the following (Equation 1).

[0060]

number

[0061] Here, when new data xn+1 is added, the new average value Xn+1 can be calculated as shown in the following (Equation 2).

[0062]

number

[0063] From the above formula, the new average value Xn+1 can be calculated from the old average value Xn up to the previous time and the data to be added xn+1. If the calculated new average value is stored as the old average value, then when the next data to be added is obtained, the new average value can be calculated from the stored old average value and the next data to be added.

[0064] In this embodiment, the average value (old average value Xn) of the status information for a predetermined unit time three weeks or earlier is stored as averaging information 292 in the storage unit 290. When data xn+1 of a predetermined unit time three weeks earlier is acquired, a new average value (new average value Xn+1) of the status information for a predetermined unit time three weeks or earlier is calculated based on the average value (old average value Xn) of the status information for the predetermined unit time three weeks or earlier up to that point and the currently acquired data xn+1 of the predetermined unit time three weeks earlier. In addition, this new average value (new average value Xn+1) of the status information for a predetermined unit time three weeks or earlier is stored in the storage unit 290 as the old average value Xn to be used in the next calculation.

[0065] In this embodiment, the average value of the status information for a predetermined unit time up to three weeks ago is calculated by sequential averaging processing. Therefore, it is not necessary to store all of the huge amount of past data, and the burden on the storage capacity of the server 200 can be reduced.

[0066] Furthermore, the sequential averaging process is not limited to the above example, and may be a process in which status information for a plurality of past predetermined unit times is weighted and averaged so that the older the status information, the smaller the influence on the averaged data. This weights the time axis so that the further back in time the status information is, the smaller the contribution. For example, if a lifestyle pattern changes due to moving, the contribution of past information becomes smaller, and data that emphasizes the current lifestyle pattern (most recent lifestyle pattern) can be obtained.

[0067] An example of such an averaging process is a process in which the old average value Xn and the data xn of the predetermined unit time period three weeks ago that was acquired this time are simply averaged, without multiplying the old average value Xn by n in the above-mentioned (Equation 2). Such an averaging process is calculated as shown in the following (Equation 3).

[0068]

number

[0069] A specific example of the averaging process described in the following operation modes is an example in which the sequential averaging process is performed by the process of (Equation 3). Note that the example of the averaging process is not limited to the above example. For example, as an example of weighting so that the older the status information is, the smaller the influence on the averaged data, the older average value Xn in (Equation 2) above may be multiplied by a coefficient less than 1. The averaging process may use a moving average or the like instead of the sequential averaging process described above.

[0070] (Determining the driving mode) In this embodiment, the operating mode is determined as follows based on the judgment result using the status information from one week ago and the status information from two weeks ago (judgment result using the first judgment element) and the judgment result using the average value of the status information from three weeks ago or earlier (judgment result using the second judgment element).

[0071] (1) If the judgment result using the status information from one week ago is the same as the judgment result using the status information from two weeks ago, no judgment is made regarding the average value of the status information from three weeks ago or earlier, and the operating mode is determined based on the judgment result using the status information from one week ago and the judgment result using the status information from two weeks ago. (2) If the judgment result using the status information from one week ago differs from the judgment result using the status information from two weeks ago, the operating mode is determined based on the judgment result using the average value of the status information from three weeks ago or earlier. (3) If either the status information from one week ago or the status information from two weeks ago is not available, the operating mode is determined based on the judgment result using the average value of the status information from three weeks ago or earlier, regardless of the content of the other one of the status information from one week ago or the status information from two weeks ago.

[0072] For example, as shown in FIG. 7, the operation mode for the period from 10:00 am to 11:00 am on Saturday, April 30th is created as follows. (0) Based on the status information (data D3) from 10:00 am to 11:00 am on April 9th, which is a Saturday three weeks ago, and the old average value (data D4) reflecting the status information from 10:00 am to 11:00 am on April 2nd (Saturday), four weeks ago, data D5 of a new average value of the status information from 10:00 am to 11:00 am on any Saturday before April 9th, three weeks ago, is calculated and stored in the averaging information 292 of the storage unit 290. Note that this process may be performed simultaneously with or after the following (1) and (2). (1) Status information (data D1) from 10:00 am to 11:00 am on April 23rd, which is one Saturday from the previous week, is obtained from the status information 291 in the storage unit 290. (2) Status information (data D2) from 10:00 am to 11:00 am on April 16th, which is two weeks ago on Saturday, is obtained from status information 291 in storage unit 290. (3) A comparison is made as to whether the judgment result using the data D1 (whether the number of times the door is opened and closed is less than the threshold value of six) is the same as the judgment result using the data D2 (whether the number of times the door is opened and closed is less than the threshold value of six). In this example, the judgment result using the data D1 is that the number of times the door is opened and closed is less than the threshold value. The judgment result using the data D2 is that the number of times the door is opened and closed is equal to or greater than the threshold value. For this reason, the judgment result using the data D1 is different from the judgment result using the data D2. (4) If the judgment result using the data D1 is different from the judgment result using the data D2, data D5 of a new average value of the status information from 10:00 a.m. to 11:00 a.m. on a Saturday before April 9, three weeks ago, is obtained from the averaging information 292 of the storage unit 290. Then, a judgment result (D6) of the operation mode is generated based on the judgment result using the new average value data D5. (4') On the other hand, if the judgment result using data D1 and the judgment result using data D2 are the same, the new average value data D5 is not obtained from the averaging information 292 of the memory unit 290, but an operating mode judgment result (D6) is generated based on the judgment result using data D1 and the judgment result using data D2, which are the same.

[0073] In this example, the number of times the door was opened and closed at 10:00 a.m. on April 23, which is a Saturday one week ago, was 3 times, which is less than 6 times. The number of times the door was opened and closed at 10:00 a.m. on April 16, which is a Saturday two weeks ago, was 6 times, which is more than 6 times. The average number of times the door was opened and closed at 10:00 a.m. on Saturdays three weeks ago (new average value Xn+1) is calculated from the number of times the door was opened and closed at 10:00 a.m. on April 9, which is a Saturday three weeks ago, and the average value at that time, and the value is 5 times, which is less than 6 times. In this case, it is estimated that the number of times the door was opened and closed from 10:00 a.m. to 11:00 a.m. on April 30 (Saturday) will be less than 6 times. Therefore, eco mode will be used from 10:00 a.m. to 11:00 a.m. on April 30 (Saturday).

[0074] (Data Adjustment) When calculating the average value of status information for a predetermined unit time up to three weeks ago, if the status information transmitted from refrigerator 100 is used as is, it may contain elements that are not attributable to the usage of user U. For example, information on the internal temperature may be a special temperature depending on the internal control state of refrigerator 100. In this embodiment, if it is determined based on the internal control state of refrigerator 100 that the status information contains elements that are not attributable to the usage of user U, the status information data is excluded from the information for determining the lifestyle pattern (the first determination element or the second determination element). Control states that contain elements that are not attributable to the usage of user U are, for example, the defrost mode and the defrost mode described below.

[0075] The defrost mode is a control mode in which the temperature of the first cooler 131 or the second cooler 132 is increased when a predetermined condition is satisfied, and frost adhering to the first cooler 131 or the second cooler 132 is melted. The defrost mode includes pre-cooling for cooling the storage section in advance, energizing a defrost heater (not shown) (or circulating air by the first blower 135), and control for restoring the temperature of the cooling compartment, the temperature of which has risen, to a set temperature range. The defrost mode is a control mode that is executed based on, for example, a sensor value provided in the refrigerator 100, rather than a setting by the user U.

[0076] The "thawing mode" control mode is a control mode that promotes the thawing of food in chilled compartment 31A by raising the chilled compartment temperature compared to normal operation. In the "thawing mode" control mode, the set temperature of chilled compartment 31A (or the set temperature of refrigerator compartment 31) is set high for a predetermined time (e.g., 60 minutes). In the "thawing mode" control mode, the chilled compartment temperature falls within a certain temperature range with an average temperature of, for example, 1.5°C.

[0077] Fig. 8 shows a specific example of data adjustment processing. This example shows internal temperature data (data stream ST1) sent from the refrigerator 100 between 5:00 a.m. and 10:00 a.m., internal temperature data after adjustment based on the state of the control mode (data stream ST2), an average value of the old internal temperature data (data stream ST3), and an average value of the new internal temperature data (data stream ST4). In Fig. 8, ΔR_Ave and ΔF_Ave are internal temperature data, and in the temperature data when the defrost mode is set, the defrost flag is set to "1" corresponding to the time when the defrost mode is set.

[0078] In the example of Fig. 8, the defrost flag is "1" for data between 7:00 a.m. and 8:00 a.m. among the inside temperature data (data stream ST1) sent from the refrigerator 100. For this reason, it is determined that the data between 7:00 a.m. and 8:00 a.m. includes elements that are not attributable to the usage of the user U, and in the adjusted inside temperature data (data stream ST2), the inside temperature data ΔR_Ave and ΔF_Ave are replaced with no data (None).

[0079] A new average value of the inside storage temperature data (data stream ST4) is calculated from this adjusted inside storage temperature data (data stream ST2) and the average value of the inside storage temperature data up to that point (data stream ST3).

[0080] Between 5:00 a.m. and 6:00 a.m. and between 9:00 a.m. and 10:00 a.m., the inside temperature data (data stream ST1) sent from the refrigerator 100 is reflected in the previous average value (data stream ST3) to obtain a new average value (data stream ST4), so the average value of the old inside temperature data (data stream ST3) and the average value of the new inside temperature data (data stream ST4) are different values. In contrast, between 7:00 a.m. and 8:00 a.m., the defrost flag is "1", so the inside temperature data (data stream ST1) sent from the refrigerator 100 is adjusted to no data (None) (data stream ST2). Therefore, the average value of the old inside temperature data (data stream ST3) and the average value of the new inside temperature data (data stream ST4) are the same value.

[0081] The internal control state is a cooling mode that can be set by the user U, and similar adjustments may be made for quick freezing and quick ice making modes, which involve rapid temperature changes. In this example, the data is converted using a flag, but it is also possible to transmit data defined as "no data" at the time of transmission from the refrigerator, or to transmit average data (for example, 0).

[0082] <3.2-2 Processing flow in the operation plan generation unit> 9 is a flowchart showing the flow of the lifestyle pattern prediction process performed by the operation plan generating unit 220. The lifestyle pattern prediction process is performed, for example, at 12:00 on the day before the relevant day.

[0083] (Step S1) The pre-cooling operation determination unit 221 acquires, as state information, from the storage unit 290 for each predetermined unit time, the inside temperature data from one week ago, the inside temperature data from two weeks ago, and the inside temperature data from three weeks ago.

[0084] (Step S2) The pre-cooling operation determination unit 221 checks the status flag of the inside temperature data from three weeks ago. If the status flag indicates that the data is in the defrost mode or the thaw mode, the pre-cooling operation determination unit 221 excludes the data and performs data adjustment.

[0085] (Step S3) The pre-cooling operation determination unit 221 reads out from the memory unit 290 the average value of the in-fridge temperature data from three weeks ago or earlier (old average value Xn), and calculates the average value of the in-fridge temperature data from three weeks ago or earlier (new average value Xn+1) from the in-fridge temperature data from three weeks ago acquired in step S1 and the average value of the in-fridge temperature data from four weeks ago or earlier read from the memory unit 290 (old average value Xn).

[0086] (Step S4) The pre-cooling operation determination unit 221 stores the calculated average value of the inside temperature data three weeks or earlier (new average value Xn+1) in the storage unit 290 so as to become the old average value Xn for the next time.

[0087] (Step S5) The pre-cooling operation determination unit 221 determines whether or not a temperature rise equal to or greater than a threshold has occurred for each of the average values ​​of the inside storage temperature data one week ago, the inside storage temperature data two weeks ago, and the inside storage temperature data three weeks ago or earlier.

[0088] (Step S6) The pre-cooling operation determination unit 221 determines the pre-cooling operation execution time based on the results of the judgment of the in-compartment temperature data from one week ago, the results of the judgment of the in-compartment temperature data from two weeks ago, and, if necessary, the results of the judgment of the average value of the in-compartment temperature data from three weeks ago or earlier.

[0089] Fig. 10 is a diagram for explaining the pre-cooling operation judgment. In Fig. 10, in case Ca1 and case Ca2, the judgment result of the inside temperature data one week ago and the judgment result of the inside temperature data two weeks ago both show a temperature change of more than the threshold. In this case, the pre-cooling operation is performed regardless of the average value of the inside temperature data three weeks ago or earlier (for example, no judgment is made using the average value).

[0090] In cases Ca3 to Ca6, the judgment results of the inside temperature data from one week ago and the judgment results from two weeks ago are different. In these cases, if the judgment result of the average inside temperature data from three weeks ago or earlier shows a temperature change of more than the threshold (cases Ca3 and Ca4), pre-cooling operation is performed. If the judgment result of the average inside temperature data from three weeks ago or earlier shows no temperature change of more than the threshold (cases Ca5 and Ca6), pre-cooling operation is not performed.

[0091] In cases Ca7 and Ca8, the judgment results of the internal temperature data from one week ago and the judgment results of the internal temperature data from two weeks ago show no temperature change above the threshold. In this case, pre-cooling operation is not performed regardless of the average value of the internal temperature data from three weeks ago or earlier (for example, no judgment is made using the average value).

[0092] (Step S7) The eco-driving determination unit 222 acquires, as state information, from the storage unit 290 for each predetermined unit time, door opening / closing count data from one week ago, door opening / closing count data from two weeks ago, and door opening / closing count data from three weeks ago.

[0093] (Step S8) The eco-driving determination unit 222 reads out from the memory unit 290 the average value of the door opening and closing count data from three weeks ago or earlier (old average value Xn), and calculates the average value of the door opening and closing count data from three weeks ago or earlier (new average value Xn+1) from the door opening and closing count data from three weeks ago acquired in step S7 and the average value of the door opening and closing count data from four weeks ago or earlier read from the memory unit 290 (old average value Xn).

[0094] (Step S9) The eco-driving determination unit 222 stores the calculated average value (new average value Xn+1) of the door opening and closing frequency data from three weeks or earlier in the storage unit 290 so that it becomes the old average value Xn for the next time.

[0095] (Step S10) The eco-driving determination unit 222 determines whether the average value of the door opening and closing frequency data one week ago, the door opening and closing frequency data two weeks ago, and the door opening and closing frequency data three weeks ago or earlier is less than six times.

[0096] (Step S11) The eco-driving determination unit 222 performs eco-driving based on the results of the determination of the door opening and closing count data from one week ago, the results of the determination of the door opening and closing count data from two weeks ago, and, if necessary, the average value of the door opening and closing count data from three weeks ago or earlier.

[0097] Fig. 11 is a diagram for explaining eco-driving judgment. In Fig. 11, in case Cb1 and case Cb2, the judgment result of the door opening and closing count data from one week ago and the judgment result of the door opening and closing count data from two weeks ago are both less than 6 times. In this case, eco-driving is performed regardless of the average value of the door opening and closing count data from three weeks ago or earlier (for example, judgment is not performed using the average value).

[0098] In cases Cb3 to Cb6, the determination result of the door opening and closing count data from one week ago is different from the determination result from two weeks ago. In this case, if the determination result of the average of the door opening and closing count data from three weeks ago or earlier is less than six times (cases Cb3 and Cb4), eco-driving is performed. On the other hand, if the determination result of the average of the door opening and closing count data from three weeks ago or earlier is six times or more (cases Cb5 and Cb6), eco-driving is not performed.

[0099] In cases Cb7 and Cb8, the determination result of the door opening and closing count data from one week ago and the determination result of the door opening and closing count data from two weeks ago are both 6 or more. In this case, eco-driving is not performed regardless of the average value of the door opening and closing count data from three weeks ago or earlier (for example, no determination is made using the average value).

[0100] (Step S12) The normal operation determination unit 223 sets a time excluding the time during which it has been determined in step S6 that the pre-cooling operation will be performed and the time during which it has been determined in step S11 that the eco-operation will be performed, as a normal operation implementation period.

[0101] <3.3 Control command transmission unit> 4, the control command transmitting unit 230 transmits a control command corresponding to the operation plan generated by the operation plan generating unit 220 to the refrigerator 100. For example, the control command transmitting unit 230 transmits a control command for the next predetermined unit time to the refrigerator 100 every predetermined unit time (for example, every hour). In this embodiment, the control command includes any one of an execution command for normal operation, an execution command for eco-operation, or an execution command for pre-cooling operation.

[0102] <3.4 Display information transmission unit> The display information transmission unit 240 generates information to be displayed on the display screen 301a of the terminal device 300 (hereinafter referred to as "display information"), and transmits the generated display information to the terminal device 300. The display information includes information indicating the execution result of the operation of the refrigerator 100 (for example, the execution result for each predetermined unit time) generated based on the execution time of the pre-cooling operation or the eco operation.

[0103] <3.5 Storage section> The storage unit 290 is realized by a combination of RAM, ROM, EEPROM, HDD (Hard Disk Drive), SSD, etc. The storage unit 290 stores status information 291 and averaged information 292. The status information 291 is information indicating the status of the refrigerator 100, such as door open / close information and inside temperature information. The averaged information 292 is information obtained by averaging data of status information such as door open / close information and inside temperature information.

[0104] <4. Advantages> In this embodiment, the refrigerator includes a determination unit (pre-cooling operation determination unit 221 and eco-operation determination unit 222) that determines the content of the cooling operation of the refrigerator 100 based on first determination elements P1 and P2 including state information for a certain period of time in the past, and a second determination element Q calculated based on state information for a plurality of certain periods of time in the past, which are determination elements using state information indicating the state of the refrigerator 100. With this configuration, it is possible to suppress the influence of temporary changes in the lifestyle pattern due to holidays and other days off, and to set a cooling mode according to the lifestyle pattern of the user U. This improves the convenience of the user U.

[0105] In this embodiment, the first determination elements P1 and P2 include state information for a first time, which is a certain time in the past, and state information for a second time, which is a certain time in the past before the time 1. With this configuration, by using information for a plurality of certain times, the lifestyle pattern of the user U can be analyzed with high accuracy.

[0106] In this embodiment, the second determination element Q includes, as at least a part of the state information for the plurality of fixed time periods, state information for a third time period, which is a fixed time period prior to the second time period. With this configuration, it is possible to analyze the lifestyle pattern of the user U by reflecting past state information that is not included in the first determination element.

[0107] In this embodiment, the second time is the same time on the same day of the week one week ago compared to the first time, and the third time is the same time on the same day of the week one week ago compared to the second time. With this configuration, by using the time information related to the same day of the week, it is possible to analyze the user's lifestyle pattern for each day of the week.

[0108] In this embodiment, the second determination element Q includes, as at least a part of the state information for the plurality of fixed time periods, state information for a fourth time period, which is a fixed time period prior to the third time period. With this configuration, it is possible to analyze the lifestyle pattern of the user U by reflecting a plurality of past state information items not included in the first determination element.

[0109] In this embodiment, the determination units (pre-cooling operation determination unit 221 and eco-operation determination unit 222) determine the content of the cooling operation based on the first determination element regardless of the content of the second determination element when the state information at the first time and the state information at the second time satisfy a predetermined relationship. With this configuration, when the state information at the first time and the state information at the second time satisfy a predetermined relationship, the determination process regarding the second determination element can be omitted. This can reduce the information processing load on the determination units.

[0110] In this embodiment, when the state information at the first time and the second time do not satisfy a predetermined relationship, the determination units (pre-cooling operation determination unit 221 and eco-operation determination unit 222) determine the content of the cooling operation based on the second judgment element Q. With this configuration, even if the state information at the first time and the state information at the second time differ due to a temporary change in lifestyle pattern due to a public holiday or day off, the content of the cooling operation can be accurately determined based on the second judgment element Q.

[0111] In this embodiment, when one of the status information for the first hour and the status information for the second hour does not exist, the determination units (pre-cooling operation determination unit 221 and eco-operation determination unit 222) determine the content of the cooling operation based on the second judgment element Q, regardless of the content of the other of the status information for the first hour and the status information for the second hour. According to such a configuration, when the status information for the first hour or the status information for the second hour cannot be obtained due to poor communication in the network, the content of the cooling operation can be determined based on the second judgment element Q, thereby improving reliability.

[0112] In this embodiment, the determination unit (the pre-cooling operation determination unit 221 and the eco-driving determination unit 222) determines the content of the cooling operation based on the first determination element with priority over the second determination element. For example, in the above-mentioned embodiment, the determination unit performs a determination using the first determination element before a determination using the second determination element, and performs a determination using the second determination element when a determination using the first determination element is not possible. This reduces the processing load on the determination unit, and makes it easier to reflect the latest information, making it easier to deal with a case where a change in lifestyle pattern occurs due to moving, etc. Note that determining the content of the cooling operation based on the first determination element with priority over the second determination element is not limited to the above example, and the determination result of the first determination element may be weighted so that the determination result of the first determination element is prioritized over the second determination element.

[0113] In this embodiment, the second judgment element Q is obtained by performing a predetermined averaging process on the status information for a plurality of past fixed periods of time. With this configuration, by performing a predetermined averaging process on the status information for a plurality of past fixed periods of time, the status information for a plurality of past fixed periods of time can be stored or handled as a single piece of information.

[0114] In this embodiment, the second judgment element Q is obtained by sequentially averaging a plurality of pieces of past state information for a certain period of time. With this configuration, it is not necessary to store all of the plurality of pieces of past state information, and the required storage capacity can be reduced.

[0115] In this embodiment, the second judgment element Q is obtained by averaging a plurality of pieces of past status information for a certain period of time, weighting the information so that the older the status information is, the smaller the influence of the weighting. With this configuration, the most recent information is more likely to be reflected, and it is easier to deal with cases where a change in lifestyle pattern occurs due to moving, etc.

[0116] In this embodiment, the status information obtained while the refrigerator 100 is executing a predetermined control is not included, or its influence is reduced, in the first determination factors P1, P2 or the second determination factor Q. With this configuration, it is possible to estimate the lifestyle pattern of the user U by excluding factors that are not attributable to the usage of the user U.

[0117] Although one embodiment has been described above, the embodiment is not limited to the above example. For example, the user U's life pattern for each day of the week is fixed, but the life pattern differs when there are holidays or days off. Therefore, the life pattern may be estimated by incorporating calendar elements and taking into account holidays and days off.

[0118] According to at least one of the embodiments described above, convenience can be improved by determining the content of the cooling operation based on a first judgment element including status information for a certain period of time in the past and a second judgment element calculated based on status information for multiple certain periods of time in the past.

[0119] Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents described in the claims, as well as in the scope and spirit of the invention.

[0120] (Additional Note) The information processing system and the information processing method according to the embodiment may be configured as follows. (1) The information processing system is a determination unit that determines details of a cooling operation of the refrigerator based on a first determination element using status information indicating a status of a refrigerator, the first determination element including the status information for a certain period of time in the past and a second determination element calculated based on the status information for a plurality of the certain periods of time in the past; It is advisable to prepare the following. (2) In the information processing system according to (1) above, The first determination element may include the status information for a first time, which is the certain time in the past, and the status information for a second time, which is the certain time in the past that is earlier than the first time. (3) In the information processing system according to (2) above, The second determination element may include, as at least a portion of the status information for the plurality of fixed periods of time, the status information for a third period of time, which is the fixed period of time prior to the second period of time. (4) In the information processing system according to (3) above, The second time is the same time on the same day one week ago compared to the first time, The third time may be the same time and on the same day of the week one week prior to the second time. (5) In the information processing system according to (3) above, The second determination element may include, as at least a portion of the status information for the plurality of fixed periods of time, the status information for a fourth period of time, which is the fixed period of time prior to the third period of time. (6) In the information processing system according to (2) above, When the status information at the first time and the status information at the second time satisfy a predetermined relationship, the determination unit may determine the content of the cooling operation based on the first judgment element, regardless of the content of the second judgment element. (7) In the information processing system according to (6) above, When the state information at the first time and the state information at the second time do not satisfy the predetermined relationship, the decision unit may decide content of the cooling operation based on the second determination element. (8) In the information processing system according to (2) above, When one of the status information for the first time and the status information for the second time does not exist, the determination unit may determine the content of the cooling operation based on the second judgment element, regardless of the content of the other of the status information for the first time and the status information for the second time. (9) In the information processing system according to (1) above, The determination unit may determine the content of the cooling operation based on the first determination element with priority over the second determination element. (10) In the information processing system according to (1) above, The second determination element may be information obtained by performing a predetermined averaging process on the state information for a plurality of past periods of time. (11) In the information processing system according to (1) above, The second determination element may be information obtained by successively averaging the status information for a plurality of past periods of time based on a predetermined averaging process. (12) In the information processing system according to (1) above, The second judgment element may be information obtained by weighting and averaging the status information for a plurality of past fixed periods of time such that the older the status information is, the smaller its influence on the second judgment element. (13) In the information processing system according to (1) above, The status information obtained while the refrigerator is executing a predetermined control may not be included in the first judgment element or the second judgment element, or may be included with a reduced influence. (14) In the information processing system according to (13) above, The predetermined control may be a defrost control for defrosting a cooler of the refrigerator. (15) In the information processing system according to (13) above, The predetermined control may be cooling control that involves changing a set temperature of a storage compartment of the refrigerator. (12) The information processing method is The computer a determination element using status information indicating a status of a refrigerator, the determination being based on a first determination element including the status information for a certain period of time in the past and a second determination element calculated based on the status information for a plurality of periods of time in the past, It may be advisable to include the following: [Explanation of symbols]

[0121] 200: Server, 210: Information acquisition unit, 220: Operation plan generation unit, 221: Pre-cooling operation determination unit, 222: Eco-operation determination unit, 223: Normal operation determination unit, 290: Storage unit

Claims

1. a determination unit that determines details of a cooling operation of the refrigerator based on a first determination element, the first determination element being a determination element using status information indicating a status of a refrigerator, the first determination element including the status information for a certain period of time that is a continuous period of time in the past, and a second determination element calculated based on the status information for at least a plurality of certain periods of time prior to the certain period of time in the past; Equipped with The state information includes information indicating a door-open time of the refrigerator. Information processing system.

2. The determination unit, When only one of the first judgment element and the second judgment element is used, the first judgment element is used. The information processing system according to claim 1 .

3. The first determination element includes the state information of a first time, which is a past continuous time, and the state information of a second time, which is a past continuous time prior to the first time, The determination unit is When one of the status information at the first time and the status information at the second time does not exist, the content of the cooling operation is determined based on the second determination element regardless of the content of the other of the status information at the first time and the status information at the second time. The information processing system according to claim 1 .

4. The state information obtained while the refrigerator is executing a predetermined control is not included in the first judgment element or the second judgment element, or is included with a reduced influence. The information processing system according to any one of claims 1 to 3.

5. The computer determining details of a cooling operation of the refrigerator based on a first judgment element using status information indicating a status of the refrigerator, the first judgment element including the status information for a certain period of time which is a continuous period of time in the past, and a second judgment element calculated based on the status information for at least a plurality of certain periods of time prior to the certain period of time in the past; Including, The state information includes information indicating a door-open time of the refrigerator. Information processing methods.

Images