TWI852185B - Shopping mall energy saving control method and shopping mall energy saving control system - Google Patents

Abstract

The invention discloses a shopping mall energy saving control method and a shopping mall energy saving control system. The shopping mall energy saving control system can execute the shopping mall energy saving control method. The shopping mall energy saving control method can be executed by the processor, and the shopping mall energy saving control method can use the real-time number of people and the real-time energy consumption to calculate the predicted number of people and the predicted energy consumption through a machine learning algorithm. The energy saving control method can control the online application of the shopping mall when it is judged that the predicted number of people is greater than the preset number of people, and display a online shopping discount information on online application of the shopping mall, so as to guide consumers to change from shopping in the shopping mall to shopping online, thereby enabling the shopping mall to achieve energy saving effect.

Description

Shopping mall energy saving control method and shopping mall energy saving control system

The present invention relates to an energy-saving control method and an energy-saving control system, in particular to a shopping mall energy-saving control method and a shopping mall energy-saving control system.

In common shopping malls such as department stores and fresh food stores, the temperature settings of air-conditioning equipment are basically adjusted based on the past experience of relevant management personnel. Therefore, in practice, it often happens that there are too few consumers in the mall, but the temperature of the air-conditioning equipment is set very low, which leads to waste of electricity and makes consumers in the mall feel uncomfortable because the perceived temperature is too low. Conversely, in practice, it often happens that there are more and more consumers in the mall, but the temperature of the air-conditioning equipment is set too high, which leads to consumers in the mall feeling uncomfortable because the perceived temperature is too high. At the same time, if the relevant management personnel lower the set temperature of the air-conditioning equipment, the air-conditioning equipment will continue to run strongly for a while to make the temperature in the mall reach the relatively low temperature reset by the management personnel. When the air conditioning equipment is running vigorously, the power it consumes will be relatively high.

Therefore, how to effectively adjust the relevant air-conditioning equipment in the shopping mall to achieve energy saving is a problem faced by relevant managers.

The present invention discloses a shopping mall energy-saving control method and a shopping mall energy-saving control system, which are mainly used to improve the existing shopping malls where relevant management personnel can only adjust air-conditioning equipment and other related energy-consuming equipment based on their own experience, so that the shopping mall cannot achieve the effect of energy saving.

One embodiment of the present invention discloses a shopping mall energy-saving control method, which can be executed by a processor. The energy-saving control method includes: a receiving step, a first prediction step, a second prediction step, a first determination step and a query step. Receiving step: receiving a real-time number of people, a real-time environmental information and a real-time energy consumption respectively transmitted by a number detection module, an environment detection module and at least one energy consumption detection module; the real-time environmental information at least includes an indoor temperature data and an outdoor temperature data; the real-time number of people refers to the total number of people in the shopping mall in the past preset time period; the real-time energy consumption refers to the total energy consumption of all preset energy-consuming devices connected to the energy consumption detection module in the past preset time period; the preset time period is not less than 30 minutes; wherein the processor is connected to the number detection module, the environment detection module and the energy consumption detection module respectively. The first prediction step: input the real-time number of people and the real-time environmental information into a first machine learning model to calculate a predicted number of people; the first machine learning model is trained using multiple historical real-time number of people and multiple historical real-time environmental information. The second prediction step: input the real-time energy consumption and the predicted number of people into a second machine learning model to calculate a predicted energy consumption; the second machine learning model is trained using multiple historical real-time energy consumption and multiple historical real-time number of people. The first judgment step: judge whether the predicted number of people exceeds a preset number of people threshold. If it is determined that the predicted number of people exceeds the preset number of people threshold, execute the following steps. Online push step: Send an online push message to a server running a shopping mall online application, so that the shopping mall online application can continuously display a limited-time online shopping discount information in the future preset time period. Query step: Query a database for energy-consuming equipment control suggestion information using the predicted number of people and predicted energy consumption, and control a display interface to display the energy-consuming equipment control suggestion information; wherein, after the receiving step, the first prediction step, the second prediction step, the first judgment step and the query step are sequentially performed, or, after the receiving step, the first prediction step, the first judgment step, the second prediction step and the query step are sequentially performed.

In summary, the energy-saving control method and energy-saving control system of the shopping mall of the present invention, through the design of the receiving step, the first prediction step, the second prediction step, the first judgment step and the query step, allow relevant personnel to know how to set the preset energy-consuming equipment, thereby achieving the effect of saving energy and making the temperature in the shopping mall in a relatively comfortable state at the same time.

To further understand the features and technical contents of the present invention, please refer to the following detailed description and drawings of the present invention. However, such description and drawings are only used to illustrate the present invention and do not limit the scope of protection of the present invention.

100: Shopping mall energy saving control system

1: Processor

11: Predicted number of people

12: Predict energy consumption

13: Online push information

131: Limited time online shopping discount information

132: Deadline

14: Default number of people threshold

15: Default energy consumption threshold

2: Human detection module

21:Real-time number of people

3: Environmental detection module

31: Outdoor detector

311: Outdoor temperature data

312: Outdoor humidity data

32: Indoor detector

321: Indoor temperature data

322: Indoor humidity data

33: Real-time environmental information

4: Energy consumption detection module

41: Real-time energy consumption

5: Display device

51: Display interface

6: Input device

7: Parking space detection module

71: Number of parking spaces in the mall at the moment

8: Database

81: Recommended information on energy-consuming equipment control

9: Broadcasting device

91: Crowd reminder audio

92: Crowd guidance audio

200: Default energy-consuming equipment

300: Server

301: Online shopping application

S11, S12, S13, S14, S15, S16: Process steps

S15A, S17, S18, S19, S20, S21, S22: Process steps

Figure 1 is a block diagram of the first embodiment of the shopping mall energy saving control system of the present invention.

Figure 2 is a schematic diagram of one embodiment of the display interface in the first embodiment of the shopping mall energy saving control system of the present invention.

Figure 3 is a schematic diagram of the online shopping mall application in the first embodiment of the shopping mall energy saving control system of the present invention.

Figure 4 is a block diagram of the second embodiment of the shopping mall energy saving control system of the present invention.

Figure 5 is a schematic diagram of the process of the first embodiment of the shopping mall energy saving control method of the present invention.

Figure 6 is a flow chart of the second embodiment of the shopping mall energy saving control method of the present invention.

Figure 7 is a schematic diagram of the process of the third embodiment of the shopping mall energy saving control method of the present invention.

Figure 8 is a schematic diagram of the process of the fourth embodiment of the shopping mall energy saving control method of the present invention.

FIG9 is a schematic diagram of one embodiment of the display interface of the fourth embodiment of the shopping mall energy saving control method of the present invention.

Figure 10 is a schematic diagram of the process of the fifth embodiment of the shopping mall energy saving control method of the present invention.

In the following description, if it is indicated to refer to a specific figure or as shown in a specific figure, it is only used to emphasize that most of the relevant content mentioned in the subsequent description appears in the specific figure, but it does not limit the subsequent description to only refer to the specific figure.

Please refer to Figures 1 to 3 together. Figure 1 is a block diagram of the first embodiment of the shopping mall energy-saving control system of the present invention, Figure 2 is a schematic diagram of one embodiment of the display interface in the first embodiment of the shopping mall energy-saving control system of the present invention, and Figure 3 is a schematic diagram of the shopping mall online application in the first embodiment of the shopping mall energy-saving control system of the present invention. The shopping mall energy-saving control system 100 of the present invention includes: a processor 1, a human number detection module 2, an environment detection module 3, an energy consumption detection module 4 and a display device 5. The processor 1 can be connected to the human number detection module 2, the environment detection module 3, the energy consumption detection module 4 and the display device 5 by wireless or wired means. The processor 1 can be, for example, various microprocessors or various computers.

The crowd detection module 2 is used to detect the number of people in the shopping mall to generate a real-time number of people 21, and the crowd detection module 2 can transmit the real-time number of people 21 to the processor 1. The real-time number of people 21 refers to the total number of people in the shopping mall in the past preset time period. The preset time period is not less than 30 minutes.

The environment detection module 3 may include an outdoor detector 31 and at least one indoor detector 32. The outdoor detector 31 is used to detect the environment outside the shopping mall to generate at least an outdoor temperature data 311. The indoor detector 32 is used to detect the environment inside the shopping mall to generate at least an indoor temperature data 321. The environment detection module 3 can transmit a real-time environment information 33 to the processor 1, and the real-time environment information 33 at least includes indoor temperature data 321 and outdoor temperature data 311. The number of indoor detectors 32 included in the environment detection module 3 can be designed according to the area of the shopping mall, indoor space planning, etc. For example, if the shopping mall includes three floors, the environment detection module 3 may include at least three indoor detectors 32, and each floor is equipped with at least one indoor detector 32.

Since the perceived temperature is related to the temperature and humidity in the space, in a preferred embodiment, the outdoor detector 31 can also detect the environment outside the shopping mall and generate an outdoor humidity data 312, and the indoor detector 32 can also detect the environment inside the shopping mall and generate an indoor humidity data 322. The real-time environmental information 33 transmitted by the environmental detection module 3 to the processor 1 can include outdoor temperature data 311, outdoor humidity data 312, indoor temperature data 321 and indoor humidity data 322.

The energy consumption detection module 4 is connected to a plurality of preset energy-consuming devices 200 installed in the shopping mall, and the energy consumption detection module 4 can detect an energy consumption of each preset energy-consuming device 200, and the energy consumption detection module 4 can transmit a real-time energy consumption 41 to the processor 1. The real-time energy consumption 41 refers to the sum of the energy consumption of all preset energy-consuming devices 200 in the past preset time period. For example, the preset energy-consuming devices 200 can be air-conditioning equipment, lighting equipment, freezers, refrigerators, etc., various equipment that consumes electrical energy, and the real-time energy consumption 41 refers to the electrical energy consumed by the preset energy-consuming devices 200 (for example, measured in kilowatts).

In an embodiment where at least one of the preset energy-consuming devices 200 is an air-conditioning device, the preset time period may be 30 minutes, and the real-time number of people 21 refers to the total number of people in the previous 30 minutes, and the real-time energy consumption 41 refers to the total energy consumption corresponding to all the preset energy-consuming devices in the previous 30 minutes, and the real-time environmental information 33 includes at least the average outdoor temperature in the previous 30 minutes and the average indoor temperature in the previous 30 minutes.

In actual applications, the preset time segment can be adjusted based on the space of the actual shopping mall, the response time of each preset energy-consuming device 200 (such as air-conditioning equipment, lighting equipment, etc.). More specifically, the response time of air-conditioning equipment in common shopping malls is about 30 minutes, that is, after the shopping mall has just turned on the air-conditioning equipment, or just adjusted the temperature of the air-conditioning equipment, it will take about 30 minutes for the temperature in the shopping mall to reach the temperature set by the relevant personnel in the air-conditioning equipment.

The display device 5 can be various display screens. The processor 1 can control the display device 5 to display the display interface 51. The display interface 51 can be presented in the form of an application or a webpage, but is not limited thereto. The processor 1 can control the display interface 51 to display various data such as real-time energy consumption 41, real-time number of people 21, and real-time environmental information 33. In one specific embodiment, the energy consumption detection module 4 can also transmit the energy consumption corresponding to each preset energy consumption device 200 to the processor 1, and the processor 1 can control the display interface 51 to display the real-time energy consumption 41 and the energy consumption corresponding to each preset energy consumption device 200.

The processor 1 can use the real-time number of people 21 and the real-time environmental information 33 to calculate a predicted number of people 11 using a machine learning algorithm; the machine learning algorithm model used in the machine learning algorithm referred to herein can be trained using multiple historical real-time numbers of people 21 and multiple historical real-time environmental information 33.

The processor 1 can use the real-time energy consumption 41 and the predicted number of people 11 to calculate a predicted energy consumption 12 using a machine learning algorithm; the machine learning algorithm model used in the machine learning algorithm referred to herein can be trained using multiple historical real-time numbers of people 21 and multiple historical real-time energy consumption 41. The processor 1 can also control the display interface 51 to display the predicted number of people 11 and the predicted energy consumption 12.

When the processor 1 determines that the predicted number of people 11 exceeds a preset number of people threshold 14, it can send an online push information 13 to a server 300 running a shopping mall online application 301, so that the shopping mall online application 301 can continuously display a limited-time online shopping discount information 131 within a future preset time period, thereby prompting consumers to choose online shopping instead of shopping in the shopping mall within the future preset time period. The shopping mall online application 301 referred to here can be, for example, an application (Application, APP) running on a smart phone or a laptop, or a website that can be run on various browsers (web browser).

In one specific embodiment, the online push information 13 may include limited-time online shopping discount information 131 and a deadline 132. After receiving the online push information 13, the server 300 will start to let the mall online application 301 send out the limited-time online shopping discount information 131 until the deadline 132. The cut-off time 132 is the current time when the processor 1 determines that the predicted number of people 11 exceeds the preset number of people threshold of 14 o'clock, plus the preset time period; for example, assuming that the preset time period is 30 minutes, if the processor determines that the predicted number of people exceeds the preset number of people threshold at 12 o'clock, the cut-off time will be 12:30, and the server will basically make the mall online application display the limited-time online shopping discount information between 12 o'clock and 12:30, and consumers will basically not see the limited-time online shopping discount information on the mall online application after 12:31. Of course, in different embodiments, the processor 1 may not transmit the above-mentioned expiration time, and the server 300 automatically stops the mall online application 301 from displaying the limited-time online shopping discount information 131 after receiving the online push information 13 after a preset time period.

In one practical application, the shopping mall energy saving control system 100 further includes an input device 6, which is electrically connected to the processor 1, and the input device 6 is used to provide the user with input of limited-time online shopping discount information 131. For example, the input device 6 may include a keyboard, a mouse, a touch screen, etc.

As shown in Figures 2 and 3, for example, assuming that the maximum capacity of the mall is 12,000 people, the default threshold is 12,000 people, and the default time period is 30 minutes; if at 19:00 p.m., the real-time (total) number of people in the mall is 8,000 people, and the predicted number of people calculated by processor 1 is 12,000 people, it means that processor 1 predicts that at 19:30 p.m., the total number of people in the mall will reach 12,000 people. At this time, the processor 1 will send online push information 13 to the server 300, and the relevant consumers will be able to view the limited-time online shopping discount information 131 on the mall online application 301 between 19:00 and 19:30. In this way, consumers who might have entered the mall to consume between 19:00 and 19:30 can instead shop online directly instead of going to the mall to consume.

Based on the above assumption, if the total number of people in the mall is only 5,000 at 20:30 pm, and the predicted number of people calculated by processor 1 is 6,000, processor 1 will not send limited-time online shopping discount information 131 to server 300 because the predicted number of people (6,000) is less than the preset number of people threshold (12,000). In other words, consumers will only see the corresponding limited-time online shopping discount information 131 on the mall online application 301 when processor 1 determines that the number of people in the mall will be greater than the preset number of people threshold in the future preset time period.

In one embodiment, the processor 1 can send the online push information 13 to the server 300 while also transmitting the real-time number of people 21 and the predicted number of people 11 to the server 300, so that the online application 301 of the shopping mall can simultaneously display the limited-time online shopping discount information 131, the real-time number of people 21 and the predicted number of people 11, thereby making some consumers more willing to switch to online shopping.

As shown in FIG. 1 and FIG. 3 , in different embodiments, the shopping mall energy-saving control system 100 may further include a parking space detection module 7 for detecting the idle state of all parking spaces in the shopping mall to generate a real-time number of parking spaces 71 in the shopping mall. The real-time number of parking spaces 71 in the shopping mall refers to the total number of parking spaces that can still be used to park vehicles in the parking lot of the shopping mall. The parking space detection module 7 can send the real-time number of parking spaces 71 in the shopping mall to the processor 1 . When the processor 1 sends the online push information 13 to the server 300, it can also transmit the real-time number of parking spaces 71 of the mall to the server 300, so that the mall online application 301 can simultaneously display the limited-time online shopping discount information 131, the real-time number of people 21, the predicted number of people 11 and the real-time number of parking spaces 71 of the mall. In this way, consumers can not only see the real-time number of parking spaces 71 in a specific time period, but also the real-time number of parking spaces 71 in the mall. In addition to limited-time online shopping discount information 131, the real-time number of people in the mall 21, and the predicted number of people in the mall in the future preset time period 11, the real-time number of parking spaces in the mall 71 can also be seen. Consumers will find it relatively easy to change from going to the mall to online shopping because they want to avoid the crowds in the mall, the lack of parking spaces in the mall, and the limited-time discounts that are only available for online shopping. The way in which the mall online application 301 displays the real-time number of parking spaces in the mall 71 can be, for example, as shown in FIG. 3, displaying the remaining number of parking spaces and the total number of parking spaces at the same time, or it can also be displaying only the remaining number of parking spaces.

Through the above design, before the expected crowds in the mall in the future, some consumers who originally intended to go shopping in the mall can be encouraged to shop online instead. In this way, it will be possible to avoid the problem that the mall's overall energy consumption continues to rise due to the large crowds in the future. The related air-conditioning equipment must continue to operate strongly, thereby enabling the mall to achieve energy saving. Moreover, the above design does not simply encourage consumers not to go to the mall, but allows consumers to shop directly online. Therefore, for the mall operator, while saving the mall's energy consumption, it can still retain consumers' spending.

In different embodiments, the processor 1 can also send online push information 13 to the server 300 when it is determined that the predicted energy consumption 12 exceeds a preset energy consumption threshold 15. That is, when the processor 1 determines that the predicted number of people 11 exceeds the preset number of people threshold 14, or when it determines that the predicted energy consumption 12 exceeds the preset energy consumption threshold 15, it sends online push information 13 to the server 300.

Please refer to Figures 1 and 2 again. The processor 1 can also use the predicted number of people 11 and the predicted energy consumption 12 to query an energy-consuming equipment control suggestion information 81 in a database 8, and control the display interface 51 of the display device 5 to display the energy-consuming equipment control suggestion information 81. The database 8 referred to here can be, for example, present in the processor 1, or the database 8 can be stored in a server, industrial computer or other equipment connected to the processor 1, or the database 8 can be stored in a data storage device (such as a hard disk, memory) connected to the processor 1.

In practical applications, the database 8 may store a query table, each column of the query table may correspond to a population interval, and each row of the query table may correspond to an energy consumption interval. The processor 1 may first determine which column of the population interval in the query table the predicted population 11 is located in, and then determine which row of the energy consumption interval in the query table the predicted energy consumption 12 is located in. In this way, the corresponding energy-consuming equipment control recommendation information 81 may be queried in the query table.

As shown in the following table, for example, assuming that the predicted number of people and predicted energy consumption calculated by the processor are 7100 people and 7100KW respectively, the processor will query the following query table stored in the database with 7100 people and 7100KW, and will be able to obtain the energy-consuming equipment control recommendation information of "turn on all air-conditioning equipment and adjust the temperature of all air-conditioning equipment to 23.5 degrees".

It should be noted that since the space, number of people accommodated, tonnage of air-conditioning equipment, brand of air-conditioning equipment, placement of air-conditioning equipment, and energy consumption of air-conditioning equipment of each shopping mall are all different, in actual application, relevant technical personnel can design the above query table and its included population intervals, energy consumption sections, and energy-consuming equipment control recommendation information based on the actual conditions of different shopping malls.

It should be emphasized that the energy-consuming equipment control suggestion information in the above table is only for controlling the air-conditioning equipment in the shopping mall. In actual application, the energy-consuming equipment control suggestion information is not limited to providing control suggestions for air-conditioning equipment. For example, in different embodiments, some of the preset energy-consuming equipment 200 may also be direct lighting equipment and indirect lighting equipment in the shopping mall, and one of the energy-consuming equipment suggestion information may be, for example, "turn on all air-conditioning equipment, adjust the temperature of all air-conditioning equipment to 23 degrees, and turn off all indirect lighting equipment."

As shown in FIG. 2 , for example, the relevant management personnel of the shopping mall can view the energy-consuming equipment control suggestion information 81 corresponding to each floor of the shopping mall in the display interface 51, and the relevant management personnel of the shopping mall can refer to the energy-consuming equipment control suggestion information 81 corresponding to each floor displayed in the display interface 51 to adjust the air-conditioning equipment on each floor accordingly. The energy-consuming equipment control suggestion information 81 can be changed according to the number of preset energy-consuming equipment 200 in the shopping mall and the adjustable parameters.

In one embodiment, one of the energy-consuming device control recommendation information 81 may be to turn on all the default energy-consuming devices 200 in the shopping mall. When the processor 1 uses the predicted number of people 11 and the predicted energy consumption 12 to find out in the database 8 that the energy-consuming device control recommendation information 81 is to turn on all the default energy-consuming devices 200 in the shopping mall, the processor 1 may also send online push information 13 to the server 300. That is, assuming that the preset time period is 30 minutes, if the processor 1 determines that the mall must turn on all air conditioning equipment in the mall (preset energy-consuming equipment 200) after 30 minutes, the processor 1 will send online push information 13 to the server 300 to guide consumers who originally planned to go to the mall to shop to shop online, thereby avoiding the mall having to turn on all air conditioning equipment in the mall after 30 minutes. In this way, the mall can achieve energy saving.

In practical applications, each energy-consuming device control suggestion information 81 in the query table may correspond to a unique number, and the processor 1 may use the predicted number of people 11 and the predicted energy consumption 12 to find the energy-consuming device control suggestion information 81 in the database 8, and then determine whether the energy-consuming device control suggestion information 81 is a suggestion for the user to turn on all the preset energy-consuming devices 200 in the shopping mall by determining the unique number of the energy-consuming device control suggestion information 81.

It should be emphasized that through the design of energy-consuming equipment control suggestion information 81, the relevant management personnel of the shopping mall can better understand how to set the various energy-consuming equipment in the shopping mall to achieve energy-saving effects. In this way, the shopping mall can still achieve energy-saving effects while maintaining a comfortable temperature. In other words, when designing energy-consuming equipment control suggestions, the relevant personnel take energy saving as the design axis. Therefore, the energy-consuming equipment control suggestion information found in the database by the processor using the predicted number of people and predicted energy consumption will be the most (or relatively) energy-saving energy-consuming equipment control method when there is a predicted number of people in the shopping mall.

In various common shopping malls, relevant managers usually set the temperature of each air-conditioning device in the mall based on their past experience. Therefore, it is easy for the mall to be too cold when there are no people in the mall, but the temperature of the air-conditioning device is too low. Alternatively, in order to save electricity costs, the relevant managers keep the temperature of the air-conditioning device relatively high even when there are more and more people in the mall, which leads to the temperature of the entire mall being too high and consumers feel too hot. The energy-saving control system of the present invention can avoid the above-mentioned problems that are easy to occur in shopping malls that rely on the experience of relevant managers to control air-conditioning equipment by predicting the number of people, predicting energy consumption and energy-consuming equipment control suggestions.

Please refer to FIG. 4, which is a block diagram of the second embodiment of the shopping mall energy saving control system of the present invention. One difference between this embodiment and the above-mentioned embodiment is that the shopping mall energy saving control system 100 can also include at least one broadcasting device 9. The processor 1 is connected to the broadcasting device 9. When the processor 1 determines that the predicted number of people 11 exceeds the preset number of people threshold 14, it can control the broadcasting device 9 to send a crowd reminder audio message 91 to inform consumers in the shopping mall that there will be crowds in the shopping mall in the future preset time period. That is, if the processor 1 calculates that the number of people in the mall will exceed the preset number threshold 14 after 30 minutes (preset time period), then consumers in the mall will hear a reminder audio message such as "There will be a crowd in the mall in 30 minutes" from the broadcasting device 9 in the mall.

As described above, through the design of the above-mentioned broadcasting device 9, consumers in the mall can be informed that there may be crowds of people in the mall in the future preset time period, so that some consumers in the mall can complete their consumption as soon as possible and leave the mall, thereby avoiding the mall's related air conditioning equipment (preset energy-consuming equipment 200) from having to operate strongly in response to the crowds after the preset time period.

In one variation of the present embodiment, the shopping mall energy-saving control system 100 may include a plurality of people detection modules 2, a plurality of environment detection modules 3, and a plurality of broadcasting devices 9. Each floor of the shopping mall may be provided with at least one people detection module 2, at least one environment detection module 3, and at least one broadcasting device 9. When the processor 1 determines that the predicted number of people 11 on one floor exceeds the preset number of people threshold 14, it may control the broadcasting device 9 provided on the floor to send out a crowd reminder audio message 91 to inform consumers on the floor that there will be crowds on the floor in the future preset time period. For example, consumers in a shopping mall may hear the broadcasting device 9 send out a message such as "The 5th floor, home appliance floor, is expected to have a significant crowd in 30 minutes."

In another variation, the processor 1 may also control the broadcasting device 9 installed on one floor to send out a crowd guidance audio message 92 to guide consumers on the floor to move to other floors in the mall when it determines that the predicted number of people 11 on one floor exceeds the preset number of people threshold 14, so as to guide consumers on the floor to move to other floors in the mall. For example, consumers in the mall may hear the broadcasting device 9 send out audio messages such as "The 5th floor home appliance floor is expected to have a significant crowd in 30 minutes, and the 3rd floor atrium will have a lucky draw in 10 minutes."

Please refer to Figure 5, which shows a flowchart of the first embodiment of the shopping mall energy saving control method of the present invention. The shopping mall energy saving control method of the present invention can be executed by a processor, and the energy saving control method includes: A receiving step S11: receiving a real-time number of people, a real-time environmental information and a real-time energy consumption respectively transmitted by a number detection module, an environment detection module and at least one energy consumption detection module; a first prediction step S12: inputting the real-time number of people and the real-time environmental information into a first machine learning model to calculate a predicted number of people; the first machine learning model is trained using multiple historical real-time numbers of people and multiple historical real-time environmental information; a second prediction step S13: inputting the real-time energy consumption and Predict the number of people, input a second machine learning model to calculate a predicted energy consumption; the second machine learning model is trained using multiple historical real-time energy consumption and multiple historical real-time number of people; a first judgment step S14: judge whether the predicted number of people exceeds a preset number of people threshold; if it is determined that the predicted number of people exceeds the preset number of people threshold, execute the following steps: an online push step S15: send an online push information to a server running a shopping mall online application, so that the shopping mall online application can continuously display a limited-time online shopping discount information within a preset time period in the future.

In the first judgment step S14, if it is determined that the predicted number of people does not exceed the preset number of people, or after the online push step S15, the following steps are executed: A query step S16: using the predicted number of people and the predicted energy consumption, query a database for energy-consuming equipment control recommendation information, and control a display interface to display the energy-consuming equipment control recommendation information.

In the process diagram of this embodiment, after the first prediction step S13, the second prediction step S13 is executed first, and then the first judgment step S14 is executed, but it is not limited to this. In different embodiments, after the first prediction step S13, the first judgment step S14 may be executed first, and then the second prediction step S13 is executed.

For the description of the crowd detection module, environment detection module, energy consumption detection module, real-time crowd, real-time environment information, real-time energy consumption, predicted crowd, predicted energy consumption, preset crowd threshold, online shopping mall application, server, online push information, database, energy-consuming equipment control suggestion information, display interface, etc. described in this embodiment, please refer to the description of the aforementioned embodiment, and no further description will be given here.

In practical applications, various cloud computing service providers, such as Google ^® , Amazon Web Services, and IBM ^® , can be used to provide relevant machine learning model testing and verification services to find and train the first and second machine learning models that are suitable for calculating the predicted number of people and the predicted energy consumption. Of course, in practical applications, Python programming language can also be used in conjunction with databases such as Tensorflow, Sparkmlib, and Pybrain to find and train the first and second machine learning models that are suitable for calculating the predicted number of people and the predicted energy consumption.

In one of the variant embodiments, the online push step S15 further includes: sending the predicted number of people and the real-time number of people to the server, so that the online application of the shopping mall can display the predicted number of people, the real-time number of people and the limited-time online shopping discount information. In another variant embodiment, the online push step S15 can also include: sending the predicted number of people, the real-time number of people and the real-time number of parking spaces in a shopping mall (that is, the total number of parking spaces that can still be parked in the parking lot of the shopping mall) to the server, so that the online application of the shopping mall can display the predicted number of people, the real-time number of people, the limited-time online shopping discount information and the real-time number of parking spaces in the shopping mall. For the relevant effect description of the above two variant embodiments, please refer to the description of the aforementioned embodiment, which will not be repeated here.

As described above, the shopping mall energy saving control method of the present invention can automatically display limited-time online shopping discount information on the shopping mall online application when it is expected that there will be crowds in the shopping mall during the future preset time period through the design of receiving step, first prediction step, second prediction step, first judgment step, online push step and query step, so as to guide consumers who want to go to the shopping mall during the future preset time period to shop online instead, thereby avoiding the situation that the air conditioning equipment (preset energy-consuming equipment) must continue to operate strongly in the shopping mall during the future preset time period in order to cope with the crowds. In this way, the shopping mall can achieve the effect of energy saving.

Please refer to Figure 6, which is a schematic diagram of the process of the second embodiment of the shopping mall energy saving control method of the present invention. The biggest difference between this embodiment and the first embodiment is that one of the energy-consuming device control suggestion information can be to turn on all the preset energy-consuming devices in the shopping mall. After the query step S16, an information determination step S17 is also included: determining whether the energy-consuming equipment control suggestion information found in the database is to turn on all the preset energy-consuming equipment in the mall; if the energy-consuming equipment control suggestion information found is to turn on all the preset energy-consuming equipment in the mall, an online push step S15A is executed: sending online push information to the server running the mall online application, so that the mall online application can continue to display limited-time online shopping discount information in the future preset time period. If the energy-consuming equipment control suggestion information found is not to turn on all the preset energy-consuming equipment in the mall, the process ends.

Regarding the specific implementation method of how the processor determines whether the energy-consuming device control suggestion information found in the database is to turn on all the preset energy-consuming devices in the shopping mall, please refer to the description of the relevant paragraphs in the aforementioned shopping mall energy-saving control system, which will not be elaborated here.

Please refer to Figure 7, which shows a schematic diagram of the process of the third embodiment of the shopping mall energy saving control method of the present invention. The biggest difference between this embodiment and the aforementioned first embodiment is that: after the second prediction step S13, a second judgment step S18 can be included: judging whether the predicted energy consumption exceeds a preset energy consumption threshold; if it is determined that the predicted energy consumption exceeds the preset energy consumption threshold, the online push step S15 is executed.

It should be noted that in the diagram of this embodiment, the second judgment step S18 is performed between the first judgment step S14 and the query step S16, but it is not limited to this. The second judgment step S18 can be performed as long as it is located after the second prediction step S13. That is to say, in another variation embodiment, the second judgment step S18 can also be located between the second prediction step S13 and the first judgment step S14.

Please refer to Figure 8, which shows a schematic diagram of the process of the third embodiment of the shopping mall energy saving control method of the present invention. The biggest difference between this embodiment and the aforementioned first embodiment is that: after the first prediction step S12, it also includes a first display step S19: control the display interface to display the predicted number of people and the real-time number of people; after the second prediction step S13, it also includes a second display step S20: control the display interface to display the predicted energy consumption and the real-time energy consumption; in this way, the relevant personnel of the shopping mall will be able to view the predicted number of people, the real-time number of people, the predicted energy consumption and the real-time energy consumption on the display interface (as shown in Figure 2), so that better relevant countermeasures can be made.

Another difference between this embodiment and the first embodiment is that after a preset time period after executing the online push step S15, it further includes a third display step S21: controlling the display interface to display the real-time number of people currently transmitted by the number detection module, and making the display interface display the corresponding predicted number of people before executing the online push step S15, the online push information in the online push step, and the number of people using the discount. The number of people using the discount refers to the total number of people who consume using the discount corresponding to the online push information in the shopping mall online application from the time when the online push information starts to be displayed until the online push information is no longer displayed. The discount corresponding to the online push information referred to here may be, for example, a discount code, that is, when a user makes a purchase in the online application of the shopping mall, he must first enter the discount code before he can obtain the discount promoted in the online push information.

For example, as shown in FIG. 9, which is a schematic diagram of one embodiment of the display interface of the fourth embodiment of the shopping mall energy saving control method of the present invention, after the processor executes the third display step S21, the relevant personnel can view in the display interface 51 of the display device 5: the current time is 19:35, the current number of people in the shopping mall is 11,000, and the predicted number of people before the shopping guide (19:00) is 12,000. 500 people, 500 people who used online discount codes to shop between 19:00 and 19:30, and 19:00 limited-time online shopping discount information is "5% discount for using discount code 1130 between 19:00 and 19:30", etc. With this design, relevant personnel can know the effectiveness of the limited-time online shopping discount information issued between 19:00 and 19:30 from the display interface 51.

Please refer to Figure 10, which shows a schematic diagram of the process of the fourth embodiment of the shopping mall energy-saving control method of the present invention. The biggest difference between this embodiment and the aforementioned first embodiment is that: in the first judgment step S14, if it is determined that the predicted number of people exceeds the preset number of people threshold, a broadcasting step S22 is also executed: a broadcasting device in the shopping mall is controlled to issue a crowd reminder audio message to inform consumers in the shopping mall that the number of people in the shopping mall will reach the predicted number of people in the future preset time period. For the relevant description of the crowd reminder audio message, please refer to the description of the aforementioned energy-saving control system of the present invention, which will not be repeated here.

It should be noted that in the diagram of this embodiment, after the processor determines that the predicted number of people exceeds the preset number of people threshold, it first executes the online push step S15 and then executes the broadcast step S21, but the execution order of these two steps is not limited to this. In different embodiments, the order of the two steps can also be reversed, or the two steps can be executed synchronously.

In one variation of this embodiment, in the receiving step S11, the real-time number of people refers to the total number of people on each floor of the shopping mall in the past preset time period (see FIG9 ); the real-time energy consumption refers to the total energy consumption of the preset energy-consuming equipment on each floor of the shopping mall in the past preset time period (see FIG9 ); the indoor temperature data refers to the total energy consumption of the preset energy-consuming equipment on each floor of the shopping mall in the past preset time period. The average temperature and humidity of the floor (see Figure 9), and in the first judgment step S14, it is judged whether the predicted number of people on each floor of the mall exceeds the preset number of people threshold; if the processor determines that the predicted number of people on one floor of the mall exceeds the preset number of people threshold, then in the broadcasting step S21, the processor controls the broadcasting device set on the corresponding floor to send out crowd reminder information.

As mentioned above, in another variation, in the broadcasting step S21, instead of issuing crowd reminder information, an audio message of activities on other floors may be issued to inform consumers on the floor that crowds will appear in the future preset time period, and an activity will be held on other floors, so as to guide consumers to go to other floors in the future preset time period, so as to avoid the relevant air-conditioning equipment (preset energy-consuming equipment) on a single floor from having to operate continuously and strongly in the future preset time period in order to cope with the crowds, thereby achieving the effect of energy saving.

It should be noted that the different features of the various embodiments of the shopping mall energy-saving control method of the present invention can be combined with each other according to actual needs to form new embodiments.

Please refer to Figure 1 again. In one of the variant embodiments of the shopping mall energy saving control system of the present invention, the processor 1 of the shopping mall energy saving control system 100 can execute the above-mentioned shopping mall energy saving control method of the present invention.

In summary, the mall energy-saving control system and the mall energy-saving control method of the present invention can automatically conduct online shopping guidance when it is predicted that there will be crowds in the mall in the future predicted time period, so that the mall online application can display limited-time online shopping discount information, so that some consumers who want to go to the mall to shop can switch to online shopping, thereby avoiding the mall having to keep all energy-consuming equipment (such as air-conditioning equipment) running continuously and strongly in order to cope with the crowds after the future predicted time period. In this way, the mall energy saving effect can be achieved without losing the mall's turnover.

The above is only the best feasible embodiment of the present invention, and does not limit the patent scope of the present invention. Therefore, all equivalent technical changes made by using the contents of the specification and drawings of the present invention are included in the protection scope of the present invention.

S11, S12, S13, S14, S15, S16: Process steps

Claims (12)

A shopping mall energy-saving control method can be executed by a processor, the energy-saving control method comprising: a receiving step: receiving a real-time number of people, a real-time environmental information and a real-time energy consumption respectively transmitted by a number detection module, an environment detection module and at least one energy consumption detection module; the real-time environmental information at least comprises indoor temperature data and outdoor temperature data; the real-time number of people refers to the total number of people in the shopping mall within a preset time period in the past; the real-time energy consumption refers to the total number of people connected to the energy consumption detection module within the preset time period in the past; The total energy consumption of the preset energy-consuming equipment is not less than 30 minutes; wherein the processor is connected to the human number detection module, the environment detection module and the energy consumption detection module respectively; a first prediction step: inputting the real-time human number and the real-time environmental information into a first machine learning model to calculate a predicted human number; the first machine learning model is trained using multiple historical real-time human numbers and multiple historical real-time environmental information; a second prediction step: inputting the real-time energy consumption and the predicted human number into a first machine learning model; A second machine learning model is input to calculate a predicted energy consumption; the second machine learning model is trained using the multiple historical records of the real-time energy consumption and the multiple historical records of the real-time number of people; a first determination step: determining whether the predicted number of people exceeds a preset number of people threshold; if it is determined that the predicted number of people exceeds the preset number of people threshold, the following steps are executed: an online push step: sending an online push message to a server running a shopping mall online application, so that the shopping mall online application can be pushed within the preset time period in the future , continuously displaying a limited-time online shopping discount information; a query step: using the predicted number of people and the predicted energy consumption, querying a database for energy-consuming equipment control suggestion information, and controlling a display interface to display the energy-consuming equipment control suggestion information; wherein, after the receiving step, the first prediction step, the second prediction step, the first judgment step and the query step are sequentially performed, or, after the receiving step, the first prediction step, the first judgment step, the second prediction step and the query step are sequentially performed. As described in claim 1, the shopping mall energy saving control method, wherein, in the online push step, the online push information includes the limited-time online shopping discount information and a deadline, and after the server receives the online push information, the shopping mall online application will start to display the limited-time online shopping discount information until the deadline; the deadline is the time corresponding to the moment when the processor determines that the predicted number of people exceeds the preset number of people threshold plus the preset time segment. As described in claim 1, the shopping mall energy saving control method further includes a second judgment step after the second prediction step: judging whether the predicted energy consumption exceeds a preset energy consumption threshold; if it is determined that the predicted energy consumption exceeds the preset energy consumption threshold, the online push step is executed. The shopping mall energy saving control method as described in claim 1, wherein the preset time segment is 30 minutes, at least one of the preset energy-consuming devices is an air conditioning device, the real-time number of people refers to the total number of people in the shopping mall in the previous 30 minutes, the real-time energy consumption refers to the total energy consumption of all the preset energy-consuming devices in the shopping mall in the previous 30 minutes, and the real-time environmental information at least includes the average outdoor temperature in the previous 30 minutes and the average indoor temperature in the shopping mall in the previous 30 minutes. As described in claim 1, the shopping mall energy saving control method, wherein one of the energy-consuming equipment control suggestion information is to turn on all the preset energy-consuming equipment in the shopping mall; after the query step, it also includes an information judgment step: judging whether the energy-consuming equipment control suggestion information found in the database is to turn on all the preset energy-consuming equipment in the shopping mall; if it is determined that the energy-consuming equipment control suggestion information found in the database is to turn on all the preset energy-consuming equipment in the shopping mall, then sending the online push information to the server running the server, so that the shopping mall online application can continuously display the limited-time online shopping discount information in the preset time period in the future. The shopping mall energy saving control method as described in claim 1, wherein, after the first prediction step, it further comprises a first display step: controlling the display interface to display the predicted number of people and the real-time number of people; after the second prediction step, it further comprises a second display step: controlling the display interface to display the predicted energy consumption and the real-time energy consumption; after the preset time period after executing the online push step, it further comprises a third display step: controlling the display interface to display the number of people detected The module transmits the real-time number of people at the moment, and makes the display interface display the corresponding predicted number of people before executing the online push step, the online push information in the online push step, and the number of people using the discount; the number of people using the discount refers to the total number of people who consume using the discount corresponding to the online push information in the online application of the shopping mall from the time when the online push information starts to be displayed until the online push information is no longer displayed. As described in claim 1, the shopping mall energy saving control method, wherein, in the online push step, the predicted number of people is also sent to the server, so that the shopping mall online application can display the predicted number of people and the limited-time online shopping discount information. As described in claim 7, the shopping mall energy saving control method, wherein, in the online push step, the real-time number of people and the real-time number of parking spaces in the shopping mall are also sent to the server, so that the online application of the shopping mall can display the real-time number of people, the predicted number of people, the limited-time online shopping discount information and the real-time number of parking spaces in the shopping mall. As described in claim 1, in the shopping mall energy saving control method, before executing the online push step, a broadcasting step is also executed: a broadcasting device in the shopping mall is controlled to send out a crowd reminder audio message to inform consumers in the shopping mall that there will be crowds in the shopping mall in the future preset time period. As described in claim 9, the shopping mall energy saving control method, wherein, in the receiving step, the real-time number of people refers to the total number of people on each floor of the shopping mall in the past preset time period; the real-time energy consumption refers to the total energy consumption of the preset energy-consuming equipment on each floor of the shopping mall in the past preset time period; the indoor temperature data refers to the total energy consumption of the preset energy-consuming equipment on each floor of the shopping mall in the past preset time period; The average temperature of the floor; in the first judgment step, it is to judge whether the predicted number of people on each floor of the shopping mall exceeds the preset number of people threshold; if the processor determines that the predicted number of people on one floor of the shopping mall exceeds the preset number of people threshold, then in the broadcasting step, the processor controls the broadcasting device set on the corresponding floor to send out the crowd prompt information. As described in claim 1, the shopping mall energy saving control method, wherein, in the receiving step, the real-time number of people refers to the total number of people on each floor of the shopping mall in the past preset time period; the real-time energy consumption refers to the total energy consumption of the preset energy-consuming equipment on each floor of the shopping mall in the past preset time period; the indoor temperature data refers to the average temperature of each floor of the shopping mall in the past preset time period; in the first judgment step, In the judgment step, it is to judge whether the predicted number of people on each floor of the shopping mall exceeds the preset number of people threshold. If it is judged that the predicted number of people exceeds the preset number of people threshold, a broadcasting step is also executed: a broadcasting device installed on the corresponding floor is controlled to send out an audio message of activities on other floors to inform consumers on the corresponding floor that there will be a crowd in the preset time period in the future, and an activity will be held on other floors. A shopping mall energy saving control system, comprising: the processor of the shopping mall energy saving control method as described in any one of claims 1 to 11 and a display device, wherein the display device is electrically connected to the processor, and the processor can control the display device to display the display interface.

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