A data processing method and system for monitoring a conference room of a building

Abstract

The application relates to the technical field of building conference room monitoring, in particular to a data processing method and system for monitoring a building conference room, which comprises the following steps: obtaining a target conference information set of a target building; obtaining an estimated conference energy consumption data set according to the target conference information set; and controlling target conference equipment data corresponding to the target conference information set according to the estimated conference energy consumption data set and a target building key energy consumption set. It is known that, by distinguishing basic energy consumption, per capita energy consumption and introducing an energy consumption influence factor, the energy consumption prediction is more accurate than traditional methods. Meanwhile, by comparing the difference between the actual energy consumption of the building and the estimated energy consumption, two different regulation and control strategies are realized, greater energy-saving measures are taken when the overall energy consumption of the building exceeds the standard, and the per capita energy consumption and the second adjusted energy consumption can be calculated to allocate the energy consumption in the conference room of the target building, so that the effect of reasonably allocating energy and saving energy consumption is achieved.

Description

Technical Field

[0001] This invention relates to the field of building conference room monitoring technology, and in particular to a data processing method and system for monitoring building conference rooms. Background Technology

[0002] With the rapid development of the mobile internet, many smart buildings have emerged to meet the needs of modern construction. Smart building management systems need to aggregate data from various systems within the building and transmit it to a server. They also need to manage building energy consumption. However, current technologies typically only adjust or optimize the air conditioning systems of the entire building, especially since conference rooms are a significant source of energy waste. They fail to consider the usage of each conference room for optimization, making it impossible to rationally and accurately regulate building energy consumption. Therefore, accurately monitoring building energy consumption based on conference room usage and then rationally allocating energy across the entire building is a pressing issue that needs to be addressed. Summary of the Invention

[0003] To address the aforementioned technical problems, the present invention provides a data processing method for monitoring building conference rooms, the method comprising the following steps:

[0004] S100, Obtain the target meeting information set A = {A1, ..., A...} of the target building. i , ..., A m}, A i It is the i-th target meeting information of the target building, where i ranges from 1 to m, and m is the number of target meeting information of the target building;

[0005] S200, Based on A, obtain the estimated meeting energy consumption dataset B = {B1, ..., B1} corresponding to A. i , ..., B m}, B i It is A i Corresponding estimated meeting energy consumption data;

[0006] S300, obtain the actual energy consumption of the target building before each target meeting as the key energy consumption set G, so as to control the target meeting equipment data corresponding to the target meeting information set A according to the estimated meeting energy consumption dataset B and the key energy consumption set G.

[0007] Specifically, the target meeting information includes the target meeting ID, the target meeting room ID corresponding to the target meeting ID, the target meeting time period corresponding to the target meeting ID, the target meeting type corresponding to the target meeting ID, and the target number of participants corresponding to the target meeting ID.

[0008] Specifically, the target meeting ID is a unique identifier for the target meeting.

[0009] Specifically, the target meeting room ID is a unique identifier for the meeting room within the target building.

[0010] Specifically, step S200 also includes the following steps to determine B. i :

[0011] S201, Obtain A i ={A i1 A i2 A i3 A i4 A i5}, A i1 It is the target meeting ID in the i-th target meeting information, A i2 It is the target meeting room ID in the i-th target meeting information, A i3 A is the target meeting time period in the i-th target meeting information. i4 A is the target meeting type in the i-th target meeting information. i5 It represents the number of participants in the target meeting from the information of the i-th target meeting;

[0012] S202, according to A i , obtain B i Among them, B i The following conditions must be met:

[0013] B i =(E i1 +E i2 ×A i5 )×F i ×T i , of which E i1 Through A i2 The target meeting room's base energy consumption, E i2 It is the per capita energy consumption of the target meeting, F i Through A i4 The energy consumption impact factor of the defined target meeting, T i Through A i3 The duration of the meeting with the defined objectives.

[0014] Specifically, the method further includes the following steps to determine E. i2 :

[0015] Get A i2 The corresponding historical conference room uses the information set D = {D1, ..., D...} y , ..., D q}, D y This refers to the historical meeting room usage information for the y-th time, where y ranges from 1 to q, and q represents the number of times the historical meeting room has been used. y =(D y1D y2 ), where D y1 This is the actual energy consumption of the historical conference room during the yth session, D. y2 This represents the actual number of participants in the yth historical conference room.

[0016] when but D0 is the preset per capita energy consumption threshold;

[0017] when but α is the per capita energy consumption weight value and α∈[0,1].

[0018] Specifically, the S300 procedure also includes the following steps:

[0019] S301, obtain G = {G1, ..., G...} i , ..., G m}, G i It is A i The corresponding key energy consumption, wherein the key energy consumption is the target building energy consumption at the time before the preset time period corresponding to the target meeting ID;

[0020] S302, Obtain the estimated energy consumption set G corresponding to G. 0 ={G 0 1, ..., G 0 i , ..., G 0 m}, G 0 i It is G i The corresponding estimated energy consumption, wherein the estimated energy consumption is the energy consumption estimated in advance before the preset time period corresponding to the target meeting ID;

[0021] S303, when G i -G 0 i When > △G, according to B i Generate A i The corresponding first adjustment energy consumption K i According to K i Adjust the device usage status corresponding to the target meeting room ID in A, where △G is the preset energy consumption difference threshold;

[0022] S304, when G i -G 0 i When ≤△G, according to B i Generate A i The corresponding second adjustment energy consumption K 0 i According to K 0i Adjust the device usage status corresponding to the target meeting room ID in A.

[0023] Furthermore, in step S303, K i The following conditions must be met:

[0024]

[0025] Furthermore, in step S304, K 0 i The following conditions must be met:

[0026] V ig It is A i The average number of participants in the historical meeting information corresponding to the target meeting room ID, V imax It is A i The maximum number of participants in the historical meeting information corresponding to the target meeting room ID, V imin It is A i The minimum number of participants in the historical meeting information of the corresponding target meeting room ID.

[0027] This invention also provides a data processing system for monitoring building conference rooms. The system includes: a data acquisition module, a database storage unit, and a data processing server. The data acquisition module is used to collect target conference information from the target building. The database storage unit stores historical conference room usage information. The data processing server executes a computer program to perform the following steps:

[0028] S100, Obtain the target meeting information set A = {A1, ..., A...} of the target building. i , ..., A m}, A i It is the i-th target meeting information of the target building, where i ranges from 1 to m, and m is the number of target meeting information of the target building;

[0029] S200, Based on A, obtain the estimated meeting energy consumption dataset B = {B1, ..., B1} corresponding to A. i , ..., B m}, B i It is A i Corresponding estimated meeting energy consumption data;

[0030] S300, obtain the actual energy consumption of the target building before each target meeting as the key energy consumption set G, so as to control the target meeting equipment data corresponding to the target meeting information set A according to the estimated meeting energy consumption dataset B and the key energy consumption set G.

[0031] The present invention has at least the following beneficial effects: a data processing method for monitoring building conference rooms, the method comprising the following steps: S100, obtaining the target conference information set A = {A1, ..., A...} of the target building. i , ..., A m}, A i This refers to the i-th target meeting information in the target building, where i ranges from 1 to m, and m is the number of target meeting information in the target building; S200, based on A, obtain the estimated meeting energy consumption dataset B = {B1, ..., B...} corresponding to A. i , ..., B m}, B i It is A i The corresponding estimated meeting energy consumption data; S300, obtain the actual energy consumption of the target building before each target meeting as the key energy consumption set G, so as to control the target meeting equipment data corresponding to the target meeting information set A according to the estimated meeting energy consumption dataset B and the key energy consumption set G; it can be seen that by distinguishing between basic energy consumption and per capita energy consumption and introducing energy consumption influencing factors, the energy consumption prediction is more accurate than traditional methods; at the same time, by comparing the difference between the actual energy consumption of the building and the estimated energy consumption, two different control strategies are realized. When the overall energy consumption of the building exceeds the standard, more forceful energy-saving measures are taken, while more refined optimization measures are taken when it is normal, which reflects the advanced intelligence and flexibility of the system; it can also utilize historical data in the calculation of per capita energy consumption and the calculation of the second adjustment energy consumption, so as to allocate the energy consumption in the meeting room in the target building and achieve the effect of rational energy allocation and energy saving. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 A flowchart illustrating a data processing method for monitoring building conference rooms provided in Embodiment 1 of the present invention;

[0034] Figure 2 This is a schematic diagram of the structure of a data processing system for monitoring building conference rooms provided in Embodiment 2 of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0037] Example 1

[0038] like Figure 1 As shown in the figure, this embodiment provides a data processing method for monitoring building conference rooms, the method including the following steps:

[0039] S100, Obtain the target meeting information set A = {A1, ..., A...} of the target building. i , ..., A m}, A i It is the i-th target meeting information of the target building, where i ranges from 1 to m, and m is the number of target meeting information of the target building.

[0040] Specifically, the target meeting information includes the target meeting ID, the target meeting room ID corresponding to the target meeting ID, the target meeting time period corresponding to the target meeting ID, the target meeting type corresponding to the target meeting ID, and the target number of participants corresponding to the target meeting ID.

[0041] Furthermore, the target meeting ID is a unique identifier for the target meeting.

[0042] Furthermore, the target meeting room ID is a unique identifier for the meeting room within the target building.

[0043] Furthermore, the target meeting time is the predetermined time period of the target meeting.

[0044] Furthermore, the target meeting type is the meeting type of the target meeting.

[0045] Furthermore, the target number of attendees is the expected number of participants in the target meeting.

[0046] S200, Based on A, obtain the estimated meeting energy consumption dataset B = {B1, ..., B1} corresponding to A. i , ..., B m}, B i It is A i Corresponding estimated meeting energy consumption data.

[0047] In one specific embodiment, step S200 further includes the following step: determining B. i :

[0048] S201, Obtain A i ={A i1 A i2 A i3 A i4 A i5}, A i1 It is the target meeting ID in the i-th target meeting information, A i2 It is the target meeting room ID in the i-th target meeting information, A i3 A is the target meeting time period in the i-th target meeting information. i4 A is the target meeting type in the i-th target meeting information. i5 It represents the number of participants in the target meeting from the information of the i-th target meeting.

[0049] S202, according to A i , obtain B i Among them, B i The following conditions must be met:

[0050] B i =(E i1 +E i2 ×A i5 )×F i ×T i , of which E i1 Through A i2 The target meeting room's base energy consumption, E i2 It is the per capita energy consumption of the target meeting, F i Through A i4 The energy consumption impact factor of the defined target meeting, T i Through A i3 The duration of the meeting with the defined objectives.

[0051] Specifically, the method further includes the following steps to determine E. i1 :

[0052] Obtain the set of basic energy consumption information C = {C1, ..., C2} for the preset meeting rooms of the target building. j , ..., C n}, C j This refers to the preset basic energy consumption information of the j-th meeting room in the target building, where j ranges from 1 to n, and n is the number of preset basic energy consumption information entries for the j-th meeting room in the target building; it can be understood as: C j ={C j1 C j2 C j3}, C j1 It is the ID of the j-th meeting room in the target building, C j2 It is C j1 The corresponding base energy consumption, C j3 It is C j1 Corresponding conference room equipment information, C j3 ={C 1 j3 , ..., C x j3 , ..., C p j3}, C x j3 It is C j1 The corresponding meeting room device ID and the device attribute data corresponding to that meeting room device ID, where x ranges from 1 to x, and x is C. j1 The number of conference room device IDs in the corresponding conference room.

[0053] Find A from C. i2 With consistent C j At that time, C j2 As E i1 .

[0054] The above-mentioned data on the basic energy consumption of the target meeting room, the per capita energy consumption of the target meeting, the energy consumption influencing factors of the target meeting, and the duration of the target meeting are used to obtain the estimated meeting energy consumption data. In this way, the energy consumption of the meeting rooms in the target building can be allocated in a reasonable manner to achieve the effect of energy conservation.

[0055] Specifically, the method further includes the following steps to determine E. i2 :

[0056] Get A i2 The corresponding historical conference room uses the information set D = {D1, ..., D...} y , ..., D q}, D y This refers to the historical meeting room usage information for the y-th time, where y ranges from 1 to q, and q represents the number of times the historical meeting room has been used. y =(Dy1 D y2 ), where D y1 This is the actual energy consumption of the historical conference room during the yth session, D. y2 This represents the actual number of participants in the yth historical conference room.

[0057] when but D0 is the preset per capita energy consumption threshold;

[0058] when but α is the per capita energy consumption weight value and α∈[0,1].

[0059] Furthermore, D is sorted in chronological order from most recent to oldest. Those skilled in the art can set a preset per capita energy consumption threshold according to actual needs, which will not be elaborated here. For example, D0 can be calculated by statistically analyzing a large amount of historical data to obtain the average value or inflection point value.

[0060] Preferably, α meets the following conditions:

[0061] △T1 is the time interval between the usage time node corresponding to D1 and the current time node, △T q It is D q The time interval between the corresponding usage time node and the current time node.

[0062] The above method compares the historical meeting room usage information set with the threshold to determine the per capita energy consumption of the target meeting, and then predicts the meeting energy consumption data so as to allocate the energy consumption in the meeting rooms of the target building and achieve the effect of rational energy allocation and energy saving.

[0063] Specifically, the method further includes the following steps to determine F. i :

[0064] Get C j3 ={C 1 j3 , ..., C x j3 , ..., C p j3} and C j3 Dataset U of historical device usage in the corresponding meeting type j ={U j1 , ..., U jr , ..., U js}, U r It is the historical equipment usage data corresponding to the r-th meeting type in the j-th meeting room, where r ranges from 1 to s, and s is the number of meeting types.

[0065] Based on C j3 and U j Determine F 0 j , of which F 0 j The following conditions must be met:

[0066]

[0067] When F i Corresponding meeting room ID and F 0 j If the corresponding meeting room IDs match, determine F. i equals F 0 j .

[0068] Specifically, in the method, T i It is A i3 Divide the duration by 3600.

[0069] Based on historical equipment usage data and equipment attribute data, the energy consumption influencing factors of the target meeting are determined, and the meeting energy consumption data is then estimated to facilitate the allocation of energy consumption in the meeting rooms of the target building, thereby achieving the effect of rational energy allocation and energy conservation.

[0070] S300, obtain the actual energy consumption of the target building before each target meeting as the key energy consumption set G, so as to control the target meeting equipment data corresponding to the target meeting information set A according to the estimated meeting energy consumption dataset B and the key energy consumption set G.

[0071] In one specific embodiment, step S300 further includes the following steps:

[0072] S301, obtain G = {G1, ..., G...} i , ..., G m}, G i It is A i The corresponding key energy consumption, wherein the key energy consumption is the energy consumption of the target building at the time before the preset time period corresponding to the target meeting ID, can be understood as: the actual energy consumption of the target building at the time before the preset time period corresponding to the target meeting ID; wherein, those skilled in the art can set the preset time period according to actual needs, which will not be elaborated here. For example, the preset time period can be set to 15 minutes or 30 minutes before the meeting starts.

[0073] S302, Obtain the estimated energy consumption set G corresponding to G. 0 ={G 0 1, ..., G 0 i , ..., G 0 m}, G 0 i It is G i The corresponding estimated energy consumption, wherein the estimated energy consumption is the energy consumption estimated in advance before the preset time period corresponding to the target meeting ID, which can be understood as: the estimated energy consumption of the target building at that time before the preset time period corresponding to the target meeting ID.

[0074] S303, when G i -G 0 i When > △G, according to B i Generate A i The corresponding first adjustment energy consumption K i According to K i Adjust the equipment usage status corresponding to the target meeting room ID in A. △G is a preset energy consumption difference threshold. Those skilled in the art can set the preset energy consumption difference threshold according to actual needs, which will not be elaborated here. For example, the preset energy consumption difference threshold ΔG can be 5% of the building's average hourly energy consumption, or it can be dynamically adjusted according to different seasons or time periods. Where K... i The following conditions must be met:

[0075]

[0076] S304, when G i -G 0 i When ≤△G, according to B i Generate A i The corresponding second adjustment energy consumption K 0 i According to K 0 i Adjust the device usage status corresponding to the target meeting room ID in A, where K 0 i The following conditions must be met:

[0077] The mean of V imax It is A i The maximum number of participants in the historical meeting information corresponding to the target meeting room ID, V imin It is A i The minimum number of participants in the historical meeting information of the corresponding target meeting room ID.

[0078] This embodiment provides a data processing method for monitoring building conference rooms. The method includes the following steps: S100, obtaining the target conference information set A = {A1, ..., A...} of the target building. i , ..., A m}, A iThis refers to the i-th target meeting information in the target building, where i ranges from 1 to m, and m is the number of target meeting information in the target building; S200, based on A, obtain the estimated meeting energy consumption dataset B = {B1, ..., B...} corresponding to A. i , ..., B m}, B i It is A i The corresponding estimated meeting energy consumption data; S300, based on B and the target building's key energy consumption set G, controls the target meeting equipment data corresponding to A; it can be seen that by distinguishing between basic energy consumption and per capita energy consumption and introducing energy consumption influencing factors, energy consumption prediction is more accurate than traditional methods; at the same time, by comparing the difference between the building's actual energy consumption and the estimated energy consumption, two different control strategies are implemented: when the overall energy consumption of the building exceeds the standard, more forceful energy-saving measures are taken, while more refined optimization measures are taken when the building is normal, demonstrating the system's advanced intelligence and flexibility; it can also utilize historical data in the calculation of per capita energy consumption and the calculation of the second adjustment energy consumption, so as to allocate the energy consumption in the meeting rooms of the target building and achieve the effect of rational energy allocation and energy saving.

[0079] Example 2

[0080] like Figure 2 As shown in the figure, Embodiment 2 of the present invention provides a data processing system for monitoring building conference rooms. The system includes: a data acquisition module, a database storage, and a data processing server. The data acquisition module is used to collect target conference information sets of the target building, and the database storage stores historical conference room usage information sets.

[0081] Furthermore, the database storage also stores a dataset of historical device usage.

[0082] Specifically, the data processing server executes a computer program to perform the following steps:

[0083] S100, Obtain the target meeting information set A = {A1, ..., A...} of the target building. i , ..., A m}, A i It is the i-th target meeting information of the target building, where i ranges from 1 to m, and m is the number of target meeting information of the target building.

[0084] Specifically, the target meeting information includes the target meeting ID, the target meeting room ID corresponding to the target meeting ID, the target meeting time period corresponding to the target meeting ID, the target meeting type corresponding to the target meeting ID, and the target number of participants corresponding to the target meeting ID.

[0085] Furthermore, the target meeting ID is a unique identifier for the target meeting.

[0086] Furthermore, the target meeting room ID is a unique identifier for the meeting room within the target building.

[0087] Furthermore, the target meeting time is the predetermined time period of the target meeting.

[0088] Furthermore, the target meeting type is the meeting type of the target meeting.

[0089] Furthermore, the target number of attendees is the expected number of participants in the target meeting.

[0090] S200, Based on A, obtain the estimated meeting energy consumption dataset B = {B1, ..., B1} corresponding to A. i , ..., B m}, B i It is A i Corresponding estimated meeting energy consumption data.

[0091] In one specific embodiment, step S200 further includes the following step: determining B. i :

[0092] S201, Obtain A i ={A i1 A i2 A i3 A i4 A i5}, A i1 It is the target meeting ID in the i-th target meeting information, A i2 It is the target meeting room ID in the i-th target meeting information, A i3 A is the target meeting time period in the i-th target meeting information. i4 A is the target meeting type in the i-th target meeting information. i5 It represents the number of participants in the target meeting from the information of the i-th target meeting.

[0093] S202, according to A i , obtain B i Among them, B i The following conditions must be met:

[0094] B i =(E i1 +E i2 ×A i5 )×F i ×T i , of which E i1 Through A i2 The target meeting room's base energy consumption, E i2 It is the per capita energy consumption of the target meeting, F i Through A i4The energy consumption impact factor of the defined target meeting, T i Through A i3 The duration of the meeting with the defined objectives.

[0095] Specifically, the method further includes the following steps to determine E. i1 :

[0096] Obtain the set of basic energy consumption information C = {C1, ..., C2} for the preset meeting rooms of the target building. j , ..., C n}, C j This refers to the preset basic energy consumption information of the j-th meeting room in the target building, where j ranges from 1 to n, and n is the number of preset basic energy consumption information entries for the j-th meeting room in the target building; it can be understood as: C j ={C j1 C j2 C j3}, C j1 It is the ID of the j-th meeting room in the target building, C j2 It is C j1 The corresponding base energy consumption, C j3 It is C j1 Corresponding conference room equipment information, C j3 ={C 1 j3 , ..., C x j3 , ..., C p j3}, C x j3 It is C j1 The corresponding meeting room device ID and the device attribute data corresponding to that meeting room device ID, where x ranges from 1 to x, and x is C. j1 The number of conference room device IDs in the corresponding conference room.

[0097] Find A from C. i2 With consistent C j At that time, C j2 As E i1 .

[0098] The above-mentioned data on the basic energy consumption of the target meeting room, the per capita energy consumption of the target meeting, the energy consumption influencing factors of the target meeting, and the duration of the target meeting are used to obtain the estimated meeting energy consumption data. In this way, the energy consumption of the meeting rooms in the target building can be allocated in a reasonable manner to achieve the effect of energy conservation.

[0099] Specifically, the method further includes the following steps to determine E. i2 :

[0100] Get A i2 The corresponding historical conference room uses the information set D = {D1, ..., D...} y , ..., D q}, D y This refers to the historical meeting room usage information for the y-th time, where y ranges from 1 to q, and q represents the number of times the historical meeting room has been used. y =(D y1 D y2 ), where D y1 This is the actual energy consumption of the historical conference room during the yth session, D. y2 This represents the actual number of participants in the yth historical conference room.

[0101] when but D0 is the preset per capita energy consumption threshold;

[0102] when but α is the per capita energy consumption weight value and α∈[0,1].

[0103] Furthermore, D is sorted in chronological order from most recent to oldest. Those skilled in the art can set a preset per capita energy consumption threshold according to actual needs, which will not be elaborated here. For example, D0 can be calculated by statistically analyzing a large amount of historical data to obtain the average value or inflection point value.

[0104] Preferably, α meets the following conditions:

[0105] △T1 is the time interval between the usage time node corresponding to D1 and the current time node, △T q It is D q The time interval between the corresponding usage time node and the current time node.

[0106] The above method compares the historical meeting room usage information set with the threshold to determine the per capita energy consumption of the target meeting, and then predicts the meeting energy consumption data so as to allocate the energy consumption in the meeting rooms of the target building and achieve the effect of rational energy allocation and energy saving.

[0107] Specifically, the method further includes the following steps to determine F. i :

[0108] Get C j3 ={C 1 j3 , ..., C x j3 , ..., C p j3} and C j3 Dataset U of historical device usage in the corresponding meeting type j={U j1 , ..., U jr , ..., U js}, U r It is the historical equipment usage data corresponding to the r-th meeting type in the j-th meeting room, where r ranges from 1 to s, and s is the number of meeting types.

[0109] Based on C j3 and U j Determine F 0 j , of which F 0 j The following conditions must be met:

[0110]

[0111] When F i Corresponding meeting room ID and F 0 j If the corresponding meeting room IDs match, determine F. i equals F 0 j .

[0112] Specifically, in the method, T i It is A i3 Divide the duration by 3600.

[0113] Based on historical equipment usage data and equipment attribute data, the energy consumption influencing factors of the target meeting are determined, and the meeting energy consumption data is then estimated to facilitate the allocation of energy consumption in the meeting rooms of the target building, thereby achieving the effect of rational energy allocation and energy conservation.

[0114] S300, obtain the actual energy consumption of the target building before each target meeting as the key energy consumption set G, so as to control the target meeting equipment data corresponding to the target meeting information set A according to the estimated meeting energy consumption dataset B and the key energy consumption set G.

[0115] In one specific embodiment, step S300 further includes the following steps:

[0116] S301, obtain G = {G1, ..., G...} i , ..., G m}, G i It is A iThe corresponding key energy consumption, wherein the key energy consumption is the energy consumption of the target building at the time before the preset time period corresponding to the target meeting ID, can be understood as: the actual energy consumption of the target building at the time before the preset time period corresponding to the target meeting ID; wherein, those skilled in the art can set the preset time period according to actual needs, which will not be elaborated here. For example, the preset time period can be set to 15 minutes or 30 minutes before the meeting starts.

[0117] S302, Obtain the estimated energy consumption set G corresponding to G. 0 ={G 0 1, ..., G 0 i , ..., G 0 m}, G 0 i It is G i The corresponding estimated energy consumption, wherein the estimated energy consumption is the energy consumption estimated in advance before the preset time period corresponding to the target meeting ID, which can be understood as: the estimated energy consumption of the target building at that time before the preset time period corresponding to the target meeting ID.

[0118] S303, when G i -G 0 i When > △G, according to B i Generate A i The corresponding first adjustment energy consumption K i According to K i Adjust the equipment usage status corresponding to the target meeting room ID in A. △G is a preset energy consumption difference threshold. Those skilled in the art can set the preset energy consumption difference threshold according to actual needs, which will not be elaborated here. For example, the preset energy consumption difference threshold ΔG can be 5% of the building's average hourly energy consumption, or it can be dynamically adjusted according to different seasons or time periods. Where K... i The following conditions must be met:

[0119]

[0120] S304, when G i -G 0 i When ≤△G, according to B i Generate A i The corresponding second adjustment energy consumption K 0 i According to K 0 i Adjust the device usage status corresponding to the target meeting room ID in A, where K 0 i The following conditions must be met:

[0121] V ig It is A i The average number of participants in the historical meeting information corresponding to the target meeting room ID, V imax It is A i The maximum number of participants in the historical meeting information corresponding to the target meeting room ID, V imin It is A i The minimum number of participants in the historical meeting information of the corresponding target meeting room ID.

[0122] This second embodiment provides a data processing system for monitoring building conference rooms. The system includes a data acquisition module, a database storage unit, and a data processing server. The data acquisition module is used to collect target conference information from the target building. The database storage unit stores historical conference room usage information sets. The data processing server executes a computer program to perform the following steps: S100, obtaining the target conference information set A = {A1, ..., A...} from the target building. i , ..., A m}, A i This refers to the i-th target meeting information in the target building, where i ranges from 1 to m, and m is the number of target meeting information in the target building; S200, based on A, obtain the estimated meeting energy consumption dataset B = {B1, ..., B...} corresponding to A. i , ..., B m}, B i It is A i The corresponding estimated meeting energy consumption data; S300, obtain the actual energy consumption of the target building before each target meeting as the key energy consumption set G, so as to control the target meeting equipment data corresponding to the target meeting information set A according to the estimated meeting energy consumption dataset B and the key energy consumption set G; it can be seen that by distinguishing between basic energy consumption and per capita energy consumption and introducing energy consumption influencing factors, the energy consumption prediction is more accurate than traditional methods; at the same time, by comparing the difference between the actual energy consumption of the building and the estimated energy consumption, two different control strategies are realized. When the overall energy consumption of the building exceeds the standard, more forceful energy-saving measures are taken, while more refined optimization measures are taken when it is normal, which reflects the advanced intelligence and flexibility of the system; it can also utilize historical data in the calculation of per capita energy consumption and the calculation of the second adjustment energy consumption, so as to allocate the energy consumption in the meeting room in the target building and achieve the effect of rational energy allocation and energy saving.

[0123] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A data processing method for monitoring building conference rooms, characterized in that, The method includes the following steps: S100, Obtain the target meeting information set A = {A1, ..., A...} of the target building. i , ..., A m }, A i It is the i-th target meeting information of the target building, where i ranges from 1 to m, and m is the number of target meeting information of the target building; S200, Based on A, obtain the estimated meeting energy consumption dataset B = {B1, ..., B1} corresponding to A. i , ..., B m }, B i It is A i Corresponding estimated meeting energy consumption data; S300: Obtain the actual energy consumption of the target building before each target meeting as a key energy consumption set G, and control the target meeting equipment data corresponding to the target meeting information set A based on the estimated meeting energy consumption dataset B and the key energy consumption set G; step S300 also includes the following steps: S301, obtain G = {G1, ..., G...} i , ..., G m }, G i It is A i The corresponding key energy consumption, wherein the key energy consumption is the target building energy consumption at the time before the preset time period corresponding to the target meeting ID; S302, Obtain the estimated energy consumption set G corresponding to G. 0 ={G 0 1, ..., G 0 i , ..., G 0 m }, G 0 i It is G i The corresponding estimated energy consumption, wherein the estimated energy consumption is the energy consumption estimated in advance before the preset time period corresponding to the target meeting ID; S303, when G i -G 0 i When > △G, according to B i Generate A i The corresponding first adjustment energy consumption K i According to K i Adjust the device usage status corresponding to the target meeting room ID in A, where △G is the preset energy consumption difference threshold; where K i The following conditions must be met: ； S304, when G i -G 0 i When ≤△G, according to B i Generate A i The corresponding second adjustment energy consumption K 0 i According to K 0 i Adjust the device usage status corresponding to the target meeting room ID in A, where K 0 i The following conditions must be met: V ig It is A i The average number of participants in the historical meeting information corresponding to the target meeting room ID, V imax It is A i The maximum number of participants in the historical meeting information corresponding to the target meeting room ID, V imin It is A i The minimum number of participants in the historical meeting information of the corresponding target meeting room ID.

2. The data processing method for monitoring building conference rooms according to claim 1, characterized in that, The target meeting information includes the target meeting ID, the target meeting room ID corresponding to the target meeting ID, the target meeting time period corresponding to the target meeting ID, the target meeting type corresponding to the target meeting ID, and the target number of participants corresponding to the target meeting ID.

3. The data processing method for monitoring building conference rooms according to claim 2, characterized in that, The target meeting ID is a unique identifier for the target meeting.

4. The data processing method for monitoring building conference rooms according to claim 2, characterized in that, The target meeting room ID is a unique identifier for the meeting room within the target building.

5. The data processing method for monitoring building conference rooms according to claim 1, characterized in that, Step S200 also includes the following step to determine B. i : S201, Obtain A i ={A i1 A i2 A i3 A i4 A i5 }, A i1 It is the target meeting ID in the i-th target meeting information, A i2 It is the target meeting room ID in the i-th target meeting information, A i3 A is the target meeting time period in the i-th target meeting information. i4 A is the target meeting type in the i-th target meeting information. i5 It represents the number of participants in the target meeting from the information of the i-th target meeting; S202, according to A i , obtain B i Among them, B i The following conditions must be met: B i =(E i1 +E i2 ×A i5 )×F i ×T i , of which E i1 Through A i2 The target meeting room's base energy consumption, E i2 It is the per capita energy consumption of the target meeting, F i Through A i4 The energy consumption impact factor of the defined target meeting, T i Through A i3 The duration of the meeting with the defined objectives.

6. The data processing method for monitoring building conference rooms according to claim 5, characterized in that, The method further includes the following steps to determine E. i2 : Get A i2 The corresponding historical conference room uses the information set D = {D1, ..., D}. y , ..., D q }, D y This refers to the historical meeting room usage information for the y-th time, where y ranges from 1 to q, and q represents the number of times the historical meeting room has been used. y =(D y1 D y2 ), where D y1 This is the actual energy consumption of the historical conference room during the yth session, D. y2 This represents the actual number of participants in the yth historical conference room. when ,but D0 is the preset per capita energy consumption threshold; when ,but , It is the per capita energy consumption weight value and .

7. A data processing system for monitoring building conference rooms, characterized in that, The system includes: a data acquisition module, a database storage unit, and a data processing server. The data acquisition module is used to acquire target meeting information for the target building. The database storage unit stores historical meeting room usage information sets. The data processing server executes a computer program to perform the following steps: S100, Obtain the target meeting information set A = {A1, ..., A...} of the target building. i , ..., A m }, A i It is the i-th target meeting information of the target building, where i ranges from 1 to m, and m is the number of target meeting information of the target building; S200, Based on A, obtain the estimated meeting energy consumption dataset B = {B1, ..., B1} corresponding to A. i , ..., B m }, B i It is A i Corresponding estimated meeting energy consumption data; S300: Obtain the actual energy consumption of the target building before each target meeting as a key energy consumption set G. Based on the estimated meeting energy consumption dataset B and the key energy consumption set G, control the target meeting equipment data corresponding to the target meeting information set A. Step S300 also includes the following steps: S301, obtain G = {G1, ..., G...} i , ..., G m }, G i It is A i The corresponding key energy consumption, wherein the key energy consumption is the target building energy consumption at the time before the preset time period corresponding to the target meeting ID; S302, Obtain the estimated energy consumption set G corresponding to G. 0 ={G 0 1, ..., G 0 i , ..., G 0 m }, G 0 i It is G i The corresponding estimated energy consumption, wherein the estimated energy consumption is the energy consumption estimated in advance before the preset time period corresponding to the target meeting ID; S303, when G i -G 0 i When > △G, according to B i Generate A i The corresponding first adjustment energy consumption K i According to K i Adjust the device usage status corresponding to the target meeting room ID in A, where △G is the preset energy consumption difference threshold; where K i The following conditions must be met: ； S304, when G i -G 0 i When ≤△G, according to B i Generate A i The corresponding second adjustment energy consumption K 0 i According to K 0 i Adjust the device usage status corresponding to the target meeting room ID in A, where K 0 i The following conditions must be met: V ig It is A i The average number of participants in the historical meeting information corresponding to the target meeting room ID, V imax It is A i The maximum number of participants in the historical meeting information corresponding to the target meeting room ID, V imin It is A i The minimum number of participants in the historical meeting information of the corresponding target meeting room ID.

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