JP7671328B2 - Information processing system and information processing method - Google Patents

Description

Embodiments of the present invention relate to an information processing system and an information processing method.

Refrigerators are known that control cooling operation based on instructions from a server. Information processing systems related to such refrigerators are expected to improve convenience.

JP 2019-143953 A

The problem that the present invention aims to solve is to provide an information processing system and an information processing method that can improve convenience.

An information processing system according to an embodiment includes a determination unit. The determination unit determines details of a cooling operation of the refrigerator based on a first determination element, which is a determination element using status information indicating a status of the refrigerator, 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. The status information includes information indicating a door-open time of the refrigerator.

FIG. 1 is a diagram showing an overall configuration of a refrigerator system according to an embodiment. FIG. 1 is a front view showing a schematic configuration of a refrigerator according to an embodiment. FIG. 2 is a block diagram showing a functional configuration of the refrigerator according to the embodiment. FIG. 2 is a block diagram showing a functional configuration of a server according to the embodiment. 4A to 4C are diagrams for explaining estimation of a lifestyle pattern according to an embodiment. FIG. 4 is a functional block diagram based on the processing of an operation plan generating unit according to the embodiment. FIG. 4 is an explanatory diagram of creating a cooling mode according to the embodiment. 5A to 5C are diagrams showing a specific example of data adjustment processing according to the embodiment. 11 is a flowchart showing a flow of a prediction process in an operation plan generating unit of the embodiment. FIG. 4 is a diagram for explaining a pre-cooling operation determination in the embodiment. 5 is a diagram for explaining eco-driving determination according to the embodiment; FIG.

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

In this application, "acquire" is not limited to active acquisition by sending a transmission request, but may also include acquisition by passively receiving information transmitted from another device. Furthermore, "acquire" is not limited to direct acquisition of target information (information to be acquired) from outside, but may also include acquisition of target information by generating it through calculation or processing of information acquired from outside.

(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.

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

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.

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.

An application program P is installed on 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, the application software that is started by executing the application program P is referred to as the "appliance management app APP."

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.

The housing 10 is insulated and 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 the chilled temperature range (for example, a temperature range of 1 to 4°C). The chilled compartment 31A is a storage compartment in the 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 the freezer temperature range (for example, a temperature range of -10 to -20°C).

Each of 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 is 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, but 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 multiple 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 differentiated, 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 differentiated, they may be referred to as "storage compartment 30F".

The openings of the multiple storage compartments 30 are closed by multiple doors 20 in an openable and closable manner. 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."

Figure 3 is a block diagram showing the functional configuration of the refrigerator 100. The refrigerator 100 has, for example, a door opening/closing 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 memory unit 190.

<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, a refrigerator compartment door sensor 111 that detects the opening and closing of refrigerator compartment door 21, a vegetable compartment door sensor 112 that detects the opening and closing of vegetable compartment door 22, an ice compartment door sensor 113 that detects the opening and closing of ice compartment door 23, a small freezer compartment door sensor 114 that detects the opening and closing of small freezer compartment door 24, and a 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.

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

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.

The first cooler 131 is arranged to correspond to the storage compartment 30R (refrigerator compartment 31, chilled compartment 31A, and vegetable compartment 32) in the refrigeration temperature range. The second cooler 132 is arranged to correspond to the storage compartment 30F (ice-making compartment 33, small freezer compartment 34, and main freezer compartment 35) in the freezing temperature range. The compressor 133 supplies refrigerant to the first cooler 131 and the second cooler 132.

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 (refrigerator compartment 31, chilled compartment 31A, and 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 (ice-making compartment 33, small freezer compartment 34, and main freezer compartment 35) in the freezing temperature range.

2.5 Operation unit
The operation unit 140 is an operation unit capable of accepting an operation 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. 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, instead of/in addition to the terminal device 300.

<2.6 Communication section>
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 installed in the user U's residence.

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 cooperation between software and hardware.

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 specifies 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 explanation of the server 200.

The control unit 162 controls the cooling unit 130 to cool each storage chamber 30 using the cooling unit 130. 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, first fan 135, and second fan 136 included in the cooling unit 130 using 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.

In this embodiment, when a learning control mode, which will be 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 as instructed by the control command.

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 control commands for the refrigerator 100 in the server 200, and execution result information 192 indicating the execution results of the operation of the refrigerator 100.

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 internal 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, 1 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 internal temperature information 191b includes information regarding the temperature of the storage chamber 30 for each predetermined unit time (for example, 1 hour). For example, the internal 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.

The execution result information 192 is information indicating the type of operation mode actually executed by the refrigerator 100 during the time period when the operation mode was instructed by the control command from the server 200. The execution result information 192 is information indicating the type of operation mode actually executed by the refrigerator 100 for each specified unit time.

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 interval.

2.8 Storage Unit
The storage unit 190 is a functional unit that stores various information. The storage unit 190 is realized by a combination of a random access memory (RAM), a read only memory (ROM), an electrically erasable programmable ROM (EEPROM), a solid state drive (SSD), etc. The storage unit 190 stores learning state information 191 and execution result information 192.

<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.

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, PLD, or 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 app APP of the terminal device 300 instead of the server 200.

<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.

<3.2 Operation plan generation unit>
The operation plan generating unit 220 analyzes the lifestyle pattern of the user U (the usage pattern of the refrigerator 100) 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 determination contents based on new information. Generating an operation plan for the refrigerator 100 is an example of "determining the contents of the cooling operation of the refrigerator 100". The operation plan generating unit 220 is an example of a "determination unit".

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.

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

Here, when generating an operation plan for the refrigerator 100 simply based on the status information for the same day of the week for the past two weeks, if the behavior of the user U on the same day of the week for the past two weeks is 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.

In this 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 the 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 multiple certain periods of time in the past.

For example, the first judgment element includes status information of a first time, which is a fixed time in the past, and status information of a second time, which is a fixed time in the past prior to the first time. The second judgment element includes status information of a third time, which is a fixed time in the past prior to the second time, 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 time, which is a fixed time in the past prior to the third time, 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".

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 AM and 11:00 AM on Monday one week ago is an example of "status information for the first time". Status information between 10:00 AM and 11:00 AM on Monday two weeks ago is an example of "status information for the second time". Status information between 10:00 AM and 11:00 AM on Monday three weeks ago is an example of "status information for the third time". Status information between 10:00 AM and 11:00 AM on Monday four weeks ago is an example of "status information for the fourth time".

In this embodiment, the second judgment element is information obtained by performing a predetermined averaging process on status information for multiple past fixed periods of time. For example, the second judgment element is information obtained by sequentially averaging status information for multiple past fixed periods of time based on a predetermined averaging process. In addition, the second judgment element is information obtained by weighting and averaging status information for multiple past fixed periods of time such that the older the status information is, the smaller its influence on the second judgment element. These details are explained below.

In this embodiment, the operation plan generating unit 220 sets the status information for a predetermined unit time one week ago as the first hour status information, and sets the status information for a predetermined unit time two weeks ago as the second hour status information. The "predetermined unit time" is, for example, one hour. The above-mentioned first hour status information and the above-mentioned second hour status information are included in the first determination element.

The operation plan generating unit 220 uses information calculated by performing a predetermined averaging process on the status 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.

In this embodiment, the status information for a specified unit time one week ago, the status information for a specified unit time two weeks ago, and the status information for a specified 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.

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 predetermined 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 the 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 April 30 (Saturday) is estimated based on the first determination elements P1 and P2 (status information on April 23 and April 16) and the second determination element Q (the average value of status information on April 9, April 2, March 26, March 19, ..., which are Saturdays from three weeks ago). The same applies to each time slot from Monday to Saturday.

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 a predetermined relationship" means, for example, when the judgment result using the status information at the first time and the judgment result using the status information at the second time are the same.

On the other hand, if the state information at the first time and the state information at the second time do not satisfy the above-mentioned specified relationship, the operation plan generating unit 220 determines the content of the cooling operation based on the second judgment element. "The specified 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.

In addition, when one of the first time status information and the second time status information does not exist (for example, when it cannot be obtained due to poor communication, etc.), the operation plan generation 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 first time status information and the second time status information.

<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.

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

In the pre-cooling operation, 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 the 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 the threshold". For example, in the pre-cooling 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, the set temperature (target temperature) of the specific storage compartment 30 is set lower than in normal operation for 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, in the pre-cooling operation, the set temperature of the storage compartment 30 is lowered by 1°C or 2°C compared to normal operation, thereby increasing the operating frequency of the compressor 133, the rotation speed of the first fan 135, or the rotation speed of the second fan 136.

Eco operation is an operation that reduces the power consumption of the refrigerator 100 by raising the set temperature (target temperature) of the storage compartment 30 compared to normal operation during a time period when the number of times the door 20 is estimated to be low (e.g., less than six times) and suppressing the operation of the cooling unit 130. For example, eco operation raises the set temperature of the storage compartment 30 by 1°C or 2°C compared to 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.

Normal operation is the basic operation of the refrigerator 100. For example, normal operation is an operation that is set when learning is not performed by the operation plan generation unit 220. For example, normal operation is an operation that assumes that the refrigerator 100 will be used by the user U (for example, the door 20 will be opened and closed). In other words, 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.

(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 the status information for a predetermined unit time one week ago and the status information for a predetermined unit time two weeks ago, as well as the averaged 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".

The average value Xn of n pieces of data x1, x2, x3, ... xn can be calculated as follows (Equation 1).

Now, if new data xn+1 is added, the new average value Xn+1 can be calculated as follows (Equation 2).

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 then 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.

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

In this embodiment, the average value of the status information for a specific unit time up to three weeks ago is calculated by sequential averaging processing. Therefore, there is no need to store all of the huge amount of past data, and the burden on the storage capacity of the server 200 can be reduced.

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

One example of this type of averaging process is to simply average the old average value Xn and the data xn for a given unit time period three weeks ago that was acquired this time, without multiplying the old average value Xn by n in the above (Equation 2). This type of averaging process can be calculated as shown in the following (Equation 3).

A specific example of the averaging process described in the following operation modes is an example in which sequential averaging 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 average data, the older the status information is, the older the average value Xn in (Equation 2) may be multiplied by a coefficient less than 1. The averaging process may use a moving average instead of the sequential averaging process described above.

(Determination of Operation Mode)
In this embodiment, the operating mode is determined 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) as follows.

(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 present, 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 of the status information from one week ago or the status information from two weeks ago.

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 status information 291 in storage unit 290.
(2) Status information (data D2) from 10:00 am to 11:00 am on April 16th, which is a Saturday two weeks ago, is obtained from status information 291 in storage unit 290.
(3) A comparison is made to see 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. Therefore, 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 the new average value of the status information from 10:00 a.m. to 11:00 a.m. on 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 the 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.

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

(Data Adjustment)
When calculating an 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 include factors that are not attributable to how user U uses it. For example, information regarding 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 includes factors that are not attributable to how user U uses it, that status information data is excluded from information for determining the lifestyle pattern (first determination element or second determination element). Control states that include factors that are not attributable to how user U uses it include, for example, the defrost mode and defrost mode described below.

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 to cool the storage section in advance, energizing a defrost heater (not shown) (or circulating air by the first blower 135), and control to restore the temperature of the cooling compartment, whose temperature has risen, to a set temperature range. The defrost mode is a control mode that is executed based on, for example, sensor values provided in the refrigerator 100, rather than settings by the user U.

The "thaw 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 "thaw 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 "thaw mode" control mode, the chilled compartment temperature falls within a certain temperature range with an average temperature of, for example, 1.5°C.

Figure 8 shows a specific example of data adjustment processing. This example shows the internal temperature data (data stream ST1) sent from the refrigerator 100 between 5:00 AM and 10:00 AM, the internal temperature data after adjustment based on the state of the control mode (data stream ST2), the average value of the old internal temperature data (data stream ST3), and the average value of the new internal temperature data (data stream ST4). In Figure 8, ΔR_Ave and ΔF_Ave are internal temperature data, and for 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.

In the example of FIG. 8, the defrost flag is set to "1" for the data between 7:00 AM and 8:00 AM among the internal temperature data (data stream ST1) sent from the refrigerator 100. For this reason, it is determined that the data between 7:00 AM and 8:00 AM contains elements that are not attributable to the usage of the user U, and in the internal temperature data after adjustment (data stream ST2), the internal temperature data ΔR_Ave and ΔF_Ave are replaced with no data (None).

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

Between 5:00 AM and 6:00 AM and between 9:00 AM and 10:00 AM, the internal 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 internal temperature data (data stream ST3) and the average value of the new internal temperature data (data stream ST4) are different values. In contrast, between 7:00 AM and 8:00 AM, the defrost flag is "1", so the internal 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 internal temperature data (data stream ST3) and the average value of the new internal temperature data (data stream ST4) are the same value.

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

<3.2-2 Processing flow in the operation plan generation unit>
9 is a flowchart showing the flow of a 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.

(Step S1) The pre-cooling operation determination unit 221 acquires, from the memory unit 290, the internal temperature data from one week ago, two weeks ago, and three weeks ago as status information for each specified unit time.

(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 from the defrost mode or thaw mode, the pre-cooling operation determination unit 221 excludes the data and adjusts the data.

(Step S3) The pre-cooling operation determination unit 221 reads out the average value of the in-fridge temperature data from three weeks ago or earlier (old average value Xn) from the memory unit 290, 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 out from the memory unit 290 (old average value Xn).

(Step S4) The pre-cooling operation determination unit 221 stores the calculated average value of the in-fridge temperature data from three weeks or earlier (new average value Xn+1) in the memory unit 290 so that it becomes the old average value Xn for the next time.

(Step S5) The pre-cooling operation decision unit 221 determines whether a temperature rise equal to or exceeds a threshold value has occurred for each of the average values of the in-cabinet temperature data from one week ago, the in-cabinet temperature data from two weeks ago, and the in-cabinet temperature data from three weeks ago or earlier.

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

Figure 10 is a diagram for explaining the pre-cooling operation judgment. In Figure 10, in cases Ca1 and Ca2, the judgment results of the in-fridge temperature data from one week ago and the judgment results of the in-fridge temperature data from two weeks ago both show a temperature change equal to or greater than the threshold. In this case, pre-cooling operation is performed regardless of the average value of the in-fridge temperature data from three weeks ago or earlier (for example, no judgment is made using the average value).

In cases Ca3 to Ca6, the judgment results of the in-fridge temperature data from one week ago are different from those from two weeks ago. In this case, if the judgment result of the average in-fridge temperature data from three weeks ago or earlier shows that there has been a temperature change of more than the threshold (cases Ca3 and Ca4), pre-cooling operation is performed. If the judgment result of the average in-fridge temperature data from three weeks ago or earlier shows that there has not been a temperature change of more than the threshold (cases Ca5 and Ca6), pre-cooling operation is not performed.

In cases Ca7 and Ca8, the judgment results of the in-cabinet temperature data from one week ago and the judgment results of the in-cabinet 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 in-cabinet temperature data from three weeks ago or earlier (for example, no judgment is made using the average value).

(Step S7) The eco-driving determination unit 222 acquires data on the number of door opening and closing operations from the memory unit 290 every predetermined unit time as status information, such as data on the number of door opening and closing operations from one week ago, two weeks ago, and three weeks ago.

(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 out from the memory unit 290 (old average value Xn).

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

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

(Step S11) The eco-driving decision 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 results of the determination of the average value of the door opening and closing count data from three weeks ago or earlier.

Figure 11 is a diagram for explaining eco-driving judgment. In Figure 11, in case Cb1 and case Cb2, the judgment results of the door opening and closing count data from one week ago and the door opening and closing count data from two weeks ago are both less than six 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).

In cases Cb3 to Cb6, the judgment result of the door opening and closing count data from one week ago is different from the judgment result from two weeks ago. In this case, if the judgment result of the average value 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 judgment result of the average value 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.

In cases Cb7 and Cb8, the determination results of the door opening and closing count data from one week ago and the door opening and closing count data from two weeks ago are both 6 or more times. 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).

(Step S12) The normal operation determination unit 223 sets the normal operation implementation period to the time excluding the time during which it was determined in step S6 that pre-cooling operation will be performed and the time during which it was determined in step S11 that eco-operation will be performed.

<3.3 Control command transmission unit>
4, the control command transmission unit 230 transmits a control command corresponding to the operation plan generated by the operation plan generation unit 220 to the refrigerator 100. For example, the control command transmission 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, and an execution command for pre-cooling operation.

<3.4 Display information transmission unit>
The display information transmitting 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 implementation time of the pre-cooling operation or the eco operation.

3.5 Storage Unit
The storage unit 290 is realized by a combination of a RAM, a ROM, an EEPROM, a HDD (Hard Disk Drive), an 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.

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 makes it possible to improve the convenience of the user U.

In this embodiment, the first judgment elements P1 and P2 include status information for a first time, which is a fixed time in the past, and status information for a second time, which is a fixed time in the past prior to the first time. With this configuration, the lifestyle patterns of the user U can be analyzed with high accuracy by using information from multiple fixed times.

In this embodiment, the second judgment element Q includes, as at least a portion of the status information for a plurality of fixed time periods, status 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 status information that is not included in the first judgment element.

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, the user's lifestyle patterns for each day of the week can be analyzed by using time information related to the same day of the week.

In this embodiment, the second judgment element Q includes, as at least a portion of the status information for multiple fixed periods of time, status information for a fourth time, which is a fixed period of time in the past prior to the third time. With this configuration, it is possible to analyze the lifestyle pattern of the user U by reflecting multiple past status information not included in the first judgment element.

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 judgment element regardless of the content of the second judgment 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 judgment element can be omitted. This can reduce the information processing burden on the determination units.

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 second judgment element Q when the status information for the first time and the second time do not satisfy a predetermined relationship. With this configuration, even if the status information for the first time and the status information for 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.

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

In this embodiment, the determination unit (pre-cooling operation determination unit 221 and eco-operation 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-described embodiment, the determination unit performs a determination using the first determination element before performing 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, makes it easier to reflect the most recent information, and makes it easier to deal with cases 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.

In this embodiment, the second judgment element Q is obtained by performing a predetermined averaging process on status information for multiple past fixed periods of time. With this configuration, by performing a predetermined averaging process on status information for multiple past fixed periods of time, it is possible to store or handle status information for multiple past fixed periods of time as a single piece of information.

In this embodiment, the second judgment element Q is obtained by sequentially averaging multiple pieces of past status information for a certain period of time. With this configuration, it is no longer necessary to store all of the multiple pieces of past status information, and the required storage capacity can be reduced.

In this embodiment, the second judgment element Q is obtained by averaging multiple pieces of status information from a certain period of time in the past, weighting them so that the older the status information, the less influence it has. With this configuration, it becomes easier to reflect the most recent information, making it easier to deal with cases where there are changes in lifestyle patterns due to moving, etc.

In this embodiment, the status information obtained while the refrigerator 100 is executing a predetermined control is not included in the first determination elements P1, P2 or the second determination element Q, or is included with a reduced influence. With this configuration, factors that are not attributable to the user U's usage can be excluded to estimate the user U's lifestyle pattern.

Although one embodiment has been described above, the embodiment is not limited to the above example. For example, the lifestyle pattern of user U is fixed for each day of the week, but the lifestyle pattern differs when there are public holidays or days off. Therefore, a calendar element may be incorporated to estimate the lifestyle pattern taking public holidays and days off into account.

According to at least one of the embodiments described above, the content of the cooling operation is determined based on a first determination element including status information for a certain period of time in the past, and a second determination element calculated based on status information for multiple certain periods of time in the past, thereby improving convenience.

Although several 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 gist of the invention. These embodiments and their modifications are within the scope of the invention and its equivalents as set forth in the claims, as well as the scope and gist of the invention.

(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 includes:
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),
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 a fixed period of time in the past that is prior to the second period of time.
(4) In the information processing system according to (3),
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 may be the same time 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 a fixed period of time in the past that is earlier than 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),
When the status information at the first time and the status 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),
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),
The second determination element may be information obtained by performing a predetermined averaging process on the status information for a plurality of past periods of time.
(11) In the information processing system according to (1),
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),
The second judgment element may be information obtained by weighting and averaging the status information for a number of past 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),
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),
The predetermined control may be a defrost control for defrosting a cooler of the refrigerator.
(15) In the information processing system according to (13),
The predetermined control may be cooling control that involves changing a set temperature of a storage compartment of the refrigerator.
(12) An information processing method includes:
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 the certain periods of time in the past;
It may be advisable to include the following:

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 (5)

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. The determination unit is
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 . the first determination element includes the status information of a first time period that is a past continuous time period, and the status information of a second time period that is a past continuous time period that is earlier than the first time period,
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 . 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 . 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