Data processing method and device, air conditioning system, storage medium and program product

Abstract

The invention provides a data processing method and device, an air conditioning system, a storage medium and a computer program product, and the method comprises the steps that engineering data collected by data collection equipment of the air conditioning system are received, and the engineering data are transmitted through at least one communication protocol; according to a preset standard data model, performing data standardization processing on the engineering data to obtain standard format data corresponding to the engineering data; and providing a data query service based on the standard format data. According to the method and the device, the engineering data can be subjected to standardization processing, format differences of different protocol data are eliminated, the standardization degree of the engineering data is improved, the storage complexity can be reduced, the problems of repeated development of query interfaces, complex query logic and the like caused by non-uniform data formats can be avoided, the data processing complexity is reduced, and the data processing efficiency is improved. The resource consumption and the cost are reduced, and the use experience of a user is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of air conditioners, and in particular to a data processing method and device, an air conditioning system, a storage medium, and a computer program product. BACKGROUND

[0002] Air conditioners have become one of the indispensable devices in daily life and play an important role in life. Air conditioning systems such as central air conditioning systems have been widely used in various large buildings and public places, and usually use cloud platforms to monitor, statistically analyze, and visualize engineering data of central air conditioning systems in real time. Since a central air conditioning system includes various devices, the number and types of various devices are different, and different suppliers and different projects use different protocols. Data acquisition devices may use multiple communication methods such as Modbus and http to transmit collected engineering data to a cloud platform, so that engineering data has problems such as non-uniform protocols, inconsistent data formats, and low standardization, and separate development of parsing and query functions for different protocols is required, which increases the complexity of data processing, resource consumption, and cost. SUMMARY

[0003] The present disclosure provides a data processing method and device, an air conditioning system, a storage medium, and a computer program product, which can convert engineering data into standard format data and provide data query services based on the standard format data.

[0004] According to a first aspect of the present disclosure, a data processing method is provided, comprising: receiving engineering data collected by a data acquisition device of an air conditioning system, wherein the engineering data is transmitted using at least one communication protocol; performing data standardization processing on the engineering data according to a preset standard data model to obtain standard format data corresponding to the engineering data; and providing a data query service based on the standard format data.

[0005] Optionally, the standard data model includes standard fields, and the data standardization processing on the engineering data according to the preset standard data model to obtain the standard format data corresponding to the engineering data includes: determining a communication protocol type corresponding to the engineering data, and obtaining a field mapping strategy corresponding to the communication protocol type; determining a standard field corresponding to an original field in the engineering data using the field mapping strategy, and setting a field value of the corresponding standard field according to a field value of the original field; and generating the standard format data based on the standard field and the field value of the standard field.

[0006] Optionally, the generating the standard format data based on the standard field and the field value of the standard field comprises: encapsulating the standard field and the field value of the standard field according to a data format of the standard data model to obtain the standard format data; and the data format of the standard data model comprises a JSON format.

[0007] Optionally, the standard field comprises a data type field and a unit field, and the method further comprises: determining the data type field and the unit field corresponding to the original field by using the field mapping strategy; performing data type conversion processing on the field value of the original field according to a first field value of the data type field corresponding to the original field, so that the data type of the converted field value of the original field conforms to the data type represented by the first field value; and performing unit conversion processing on the field value of the original field according to a second field value of the unit field corresponding to the original field, so that the unit of the converted field value of the original field conforms to the unit represented by the second field value.

[0008] Optionally, the data query service comprises a real-time data query service and a historical data query service, and the providing the data query service based on the standard format data comprises: caching the standard format data in a cache area and storing the standard format data in a first database; providing the real-time data query service through a first query interface corresponding to the cache area, and providing the historical data query service through a second query interface corresponding to the first database.

[0009] Optionally, determining statistical data corresponding to a preset statistical parameter according to the standard format data stored in the first database, and storing the statistical data in a second database; and providing a statistical data query service through a third query interface corresponding to the second database.

[0010] Optionally, the determining the statistical data corresponding to the preset statistical parameter according to the standard format data stored in the first database comprises: obtaining a data set of the statistical parameter within a unit time length according to the standard format data stored in the first database; sampling the data set based on a sampling interval time length to obtain a statistical parameter sampling value; and calculating the statistical data according to the statistical parameter sampling value and the sampling interval time length.

[0011] Optionally, the statistical parameter comprises at least one of a refrigeration capacity, an energy consumption parameter, and an energy efficiency parameter.

[0012] Optionally, determining expired standard format data in the cache area according to a cache time of the standard format data in the cache area and a preset cache time threshold; and deleting the expired standard format data in the cache area.

[0013] Optionally, the communication protocol comprises a Modbus communication protocol, and the engineering data collected by the data collection device of the air conditioning system comprises: determining, according to a preset device configuration table, device address information of a Modbus slave station that needs to be accessed; controlling a Modbus master station to access the Modbus slave station according to the device address information, so as to obtain the engineering data collected by the Modbus slave station in a Modbus communication protocol format, wherein the Modbus slave station comprises a data collection device supporting the Modbus protocol.

[0014] Optionally, before the data standardization processing of the engineering data according to the preset standard data model, the method comprises: converting, by a Modbus parser, the engineering data in the Modbus communication protocol format into engineering data in a preset format.

[0015] Optionally, the communication protocol comprises at least one of an HTTP protocol and an IoT protocol, and the engineering data collected by the data collection device of the air conditioning system comprises: receiving, by a message middleware, the engineering data collected by the data collection device.

[0016] Optionally, the air conditioning system comprises a central air conditioning system, the data collection device comprises at least one of a sensor, a metering device and a controller, and the engineering data comprises at least one of running state data, fault data and control data.

[0017] According to a second aspect of the present disclosure, a data processing apparatus is provided, comprising: a data receiving module configured to receive engineering data collected by a data collection device of an air conditioning system, wherein the engineering data is transmitted in at least one communication protocol; a standardization processing module configured to perform data standardization processing on the engineering data according to a preset standard data model, to obtain standard format data corresponding to the engineering data; and a data service module configured to provide data query services based on the standard format data.

[0018] According to a third aspect of the present disclosure, a data processing apparatus is provided, comprising: a memory; and a processor coupled to the memory, the processor being configured to execute a method as described above based on instructions stored in the memory.

[0019] According to a fourth aspect of the present disclosure, an air conditioning system is provided, comprising a data processing apparatus as described above.

[0020] According to a fifth aspect of the present disclosure, a computer readable storage medium is provided, the computer readable storage medium storing computer instructions, the instructions being executed by a processor to implement a method as described above.

[0021] According to a sixth aspect of the present disclosure, a computer program product is provided, which stores computer instructions, which, when executed by a processor, implement the method as described above.

[0022] The data processing method, device, air conditioning system, storage medium and computer program product of the present disclosure can convert engineering data transmitted through multiple communication protocols into data with a standard format according to a standard data model, provide data query services based on the standard format data, can standardize engineering data, eliminate format differences of different protocol data, improve the standardization degree of engineering data, reduce the complexity of storage, and reduce resource consumption and cost; can provide a fusion mechanism of extensible communication protocols, support the addition of new communication protocol data; can avoid problems such as repeated development of query interfaces and complex query logic caused by non-uniform data formats, reduce the complexity of data processing, reduce resource consumption and cost, and improve user experience. BRIEF DESCRIPTION OF DRAWINGS

[0023] The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description of embodiments of the present disclosure taken in conjunction with the accompanying drawings. The accompanying drawings provide illustrations of embodiments of the present disclosure and constitute a part of the specification. The drawings illustrate embodiments of the present disclosure and, together with the description, serve to explain the present disclosure. The present disclosure is not limited by the drawings. The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description of embodiments of the present disclosure taken in conjunction with the accompanying drawings. The accompanying drawings provide illustrations of embodiments of the present disclosure and constitute a part of the specification. The drawings illustrate embodiments of the present disclosure and, together with the description, serve to explain the present disclosure. The present disclosure is not limited by the drawings. The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description of embodiments of the present disclosure taken in conjunction with the accompanying drawings. The accompanying drawings provide illustrations of embodiments of the present disclosure and constitute a part of the specification. The drawings illustrate embodiments of the present disclosure and, together with the description, serve to explain the present disclosure. The present disclosure is not limited by the drawings. The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description of embodiments of the present disclosure taken in conjunction with the accompanying drawings. The accompanying drawings provide illustrations of embodiments of the present disclosure and constitute a part of the specification. The drawings illustrate embodiments of the present disclosure and, together with the description, serve to explain the present disclosure. The present disclosure is not limited by the drawings. The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description of embodiments of the present disclosure taken in conjunction with the accompanying drawings. The accompanying drawings provide illustrations of embodiments of the present disclosure and constitute a part of the specification. The drawings illustrate embodiments of the present disclosure and, together with the description, serve to explain the present disclosure. The present disclosure is not limited by the drawings. The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description of embodiments of the present disclosure taken in conjunction with the accompanying drawings. The accompanying drawings provide illustrations of embodiments of the present disclosure and constitute a part of the specification. The drawings illustrate embodiments of the present disclosure and, together with the description, serve to explain the present disclosure. The present disclosure is not limited by the drawings. The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description of embodiments of the present disclosure taken in conjunction with the accompanying drawings. The accompanying drawings provide illustrations of embodiments of the present disclosure and constitute a part of the specification. The drawings illustrate embodiments of the present disclosure and, together with the description, serve to explain the present disclosure. The present disclosure is not limited by the drawings. The above and other objects, features and advantages of the present disclosure will become more apparent from the following detailed description of embodiments of the present disclosure taken in conjunction with the accompanying drawings. The accompanying drawings provide illustrations of embodiments of the present disclosure and constitute a part of the specification. The drawings illustrate embodiments of the present disclosure and, together with the description, serve to explain the present disclosure. The present disclosure is not limited by the drawings.

[0024] Figure 1 Flowchart of some embodiments of the data processing method according to the present disclosure;

[0025] Figure 2 Schematic diagram of accessing Modbus slave station in some embodiments of the data processing method according to the present disclosure;

[0026] Figure 3 Schematic diagram of obtaining chiller data in some embodiments of the data processing method according to the present disclosure;

[0027] Figure 4 Flowchart of obtaining standard format data in some embodiments of the data processing method according to the present disclosure;

[0028] Figure 5 Flowchart of providing data query services in some embodiments of the data processing method according to the present disclosure;

[0029] Figure 6This is a schematic diagram of the process for providing statistical data query services in some embodiments of the data processing method according to this disclosure;

[0030] Figure 7 This is a schematic diagram of the architecture for engineering data acquisition, fusion, and transmission in some embodiments of the data processing method according to this disclosure;

[0031] Figure 8 This is a schematic diagram of modules according to some embodiments of the data processing apparatus of this disclosure;

[0032] Figure 9 This is a schematic diagram of a standardized processing module in some embodiments of the data processing apparatus according to the present disclosure;

[0033] Figure 10 This is a schematic diagram of a data service module according to some embodiments of the data processing apparatus of this disclosure;

[0034] Figure 11 This is a schematic diagram of modules according to other embodiments of the data processing apparatus according to the present disclosure. Detailed Implementation

[0035] Exemplary embodiments of the present disclosure will be described below with reference to the accompanying drawings. For clarity and brevity, not all features of the embodiments are described in the specification. However, it should be understood that many implementation-specific settings must be made in carrying out the embodiments to achieve the developer's specific goals, such as complying with constraints related to the device and business, and these constraints may vary depending on the implementation. Furthermore, it should be understood that while development work can be very complex and time-consuming, such development work is merely a routine task for those skilled in the art who benefit from the present disclosure.

[0036] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of this disclosure.

[0037] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of this disclosure are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0038] It should also be understood that in the embodiments disclosed herein, "a plurality of" may refer to two or more, and "at least one" may refer to one, two or more.

[0039] It should also be understood that any component, data or structure mentioned in the embodiments of this disclosure can generally be understood as one or more unless expressly defined or given to the contrary in the context.

[0040] Furthermore, the term "and / or" in this disclosure is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this disclosure generally indicates that the preceding and following related objects have an "or" relationship.

[0041] It should also be understood that the description of the various embodiments in this disclosure emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0042] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0043] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this disclosure or its application or use.

[0044] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0045] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0046] Furthermore, to avoid obscuring this disclosure with unnecessary detail, only processing steps and / or apparatus structures closely related to at least the solutions according to this disclosure are shown in the accompanying drawings, while other details less relevant to this disclosure are omitted. It should also be noted that similar reference numerals and letters in the drawings indicate similar items, and therefore once an item is defined in one drawing, it need not be discussed again in subsequent drawings.

[0047] Figure 1 This is a flowchart illustrating some embodiments of the data processing method according to this disclosure, such as... Figure 1 As shown:

[0048] Step S101: Receive engineering data collected by the data acquisition device of the air conditioning system, wherein the engineering data is transmitted using at least one communication protocol.

[0049] Air conditioning systems can be of various types, such as central air conditioning systems. Central air conditioning systems include computer room systems, chiller / heater systems, hot water systems, and multi-split systems. Data acquisition equipment for air conditioning systems can include various devices such as sensors, metering devices, and controllers. For example, sensors include temperature sensors, pressure sensors, and humidity sensors; metering devices include electricity meters and flow meters; and controllers include DDC (Direct Digital Controller) supporting the Modbus protocol and IoT gateways supporting the HTTP (Hypertext Transfer Protocol) protocol.

[0050] Engineering data refers to data generated throughout the entire process of an air conditioning system (including construction, adaptation, operation and maintenance phases). Engineering data includes various types of data such as operational status data, fault data, and control data. Data acquisition equipment can collect various engineering data such as operational status data, fault data, and control data from central air conditioning systems. One or more communication protocols can be used when transmitting engineering data, including Modbus, HTTP, and IoT (Internet of Things) protocols.

[0051] Step S102: Based on the preset standard data model, perform data standardization processing on the engineering data to obtain standard format data corresponding to the engineering data.

[0052] Step S103: Provide data query services based on standard format data.

[0053] Based on the data processing method disclosed herein, engineering data transmitted through multiple communication protocols can be fused and processed. According to a standard data model, engineering data transmitted through multiple communication protocols is converted into data with a standard format. Data query services are provided based on this standard format data. This standardization process eliminates format differences between different protocols, improves the standardization of engineering data, reduces storage complexity, and decreases resource consumption and costs. It also provides a scalable communication protocol fusion mechanism, supporting the addition of data from new communication protocols. Providing data query services based on standard format data avoids problems such as redundant development of query interfaces and complex query logic caused by inconsistent data formats, reducing data processing complexity, resource consumption, and costs, and improving data processing accuracy.

[0054] In some embodiments, the Modbus protocol is an industrial-grade serial communication protocol. When the data acquisition device transmits engineering data using the Modbus communication protocol, the Modbus data service can be used to receive the engineering data acquired by the data acquisition device. For the Modbus data service, a Modbus master station and a Modbus slave station can be configured. The Modbus master station is the device that actively initiates data requests, and the Modbus slave station is the device that passively responds to requests. Each Modbus slave station has a unique slave station address. Modbus slave stations include data acquisition devices that support the Modbus protocol, such as DDCs (Data Centers) that support the Modbus protocol.

[0055] Based on a preset device configuration table, the device address information of the Modbus slave station to be accessed can be determined; the Modbus master station can then access the Modbus slave station according to the device address information to obtain engineering data transmitted using the Modbus communication protocol format collected by the Modbus slave station.

[0056] Based on the device configuration table, the required Modbus slave station can be determined, and engineering data can be collected on demand. This reduces communication load and storage pressure, and improves the efficiency and accuracy of collecting engineering data transmitted using the Modbus communication protocol format.

[0057] like Figure 2 As shown, based on the type of engineering data and data acquisition rules, the various Modbus slave stations from Modbus slave station 1 to Modbus slave station N are configured to collect engineering data from different devices. Each Modbus slave station can correspond to one or more data acquisition points. Different types of data can be distributed to multiple Modbus slave stations, and each Modbus slave station uses a unique device address.

[0058] A device configuration table can be pre-configured for the air conditioning system in the cloud platform. This table includes information such as the device addresses of the Modbus slave stations to be accessed. By identifying the Modbus slave stations to be accessed, the type and type of engineering data to be collected can be determined. Based on the device configuration table, data requests can be submitted. The scheduling module then uses the device configuration table to determine that the required Modbus slave stations are Modbus slave station 1 and Modbus slave station 3. The device address information of Modbus slave station 1 and Modbus slave station 3 is sent to the Modbus master station. The master station then accesses Modbus slave station 1 and Modbus slave station 3 based on their device address information to obtain the engineering data transmitted using the Modbus communication protocol format from Modbus slave station 1 and Modbus slave station 3.

[0059] The device configuration table can also include the register address range of the Modbus slave stations that need to be accessed. The scheduling module can send the device address information and register address range of Modbus slave station 1 and Modbus slave station 3 to the Modbus master station, and control the Modbus master station to access Modbus slave station 1 and Modbus slave station 3 according to the device address information and register address range of Modbus slave station 1 and Modbus slave station 3, and obtain the engineering data in the Modbus communication protocol format stored in the corresponding registers of Modbus slave station 1 and Modbus slave station 3.

[0060] For example, for projects requiring different numbers of chiller units, the chiller unit data can be obtained solely from the addresses of the equipment needed for the project. Figure 3 As shown, when configuring 4 chiller units, it is necessary to collect relevant data from chiller units 1-4; when configuring 8 chiller units, it is necessary to collect relevant data from chiller units 1-8; and when configuring 16 chiller units, it is necessary to collect relevant data from chiller units 1-16.

[0061] Based on the type of engineering data and data acquisition rules, the device address of Modbus slave station A is configured as device address 1 to collect relevant data from chiller units 1-4; the device address of Modbus slave station B is configured as device address 2 to collect relevant data from chiller units 5-8; the device address of Modbus slave station C is configured as device address 3 to collect relevant data from chiller units 9-12; the device address of Modbus slave station D is configured as device address 4 to collect relevant data from chiller units 13-16; and the device address of Modbus slave station E is configured as device address 5 to collect relevant data from chiller units 17-20.

[0062] With 4 chiller units configured, the device address information of the Modbus slave station to be accessed is determined to be device address 1 according to the equipment configuration table; the Modbus master station is controlled to access Modbus slave station A according to device address 1 to obtain relevant data from chiller units 1-4. With 8 chiller units configured, the device address information of the Modbus slave stations to be accessed is determined to be device address 1 and device address 2 according to the equipment configuration table; the Modbus master station is controlled to access Modbus slave stations A and Modbus slave station B according to device address 1 and device address 2. The system accesses Modbus slave station B to obtain relevant data for chiller units 1-8. With 16 chiller units configured, the device addresses of the Modbus slave stations to be accessed are determined according to the equipment configuration table as device address 1, device address 2, device address 3, and device address 4. The Modbus master station is then controlled to access Modbus slave stations A, B, C, and D based on device addresses 1, 2, 3, and 4 to obtain relevant data for chiller units 1-16.

[0063] In some embodiments, before standardizing the engineering data according to a preset standard data model, a Modbus parser is used to convert the engineering data using the Modbus communication protocol format into engineering data with a preset format. Various Modbus parsers can be used, and the preset format can be JSON-like or other formats. Engineering data in HTTP protocol format, IoT protocol format, and other formats are similar to the standard data model format and do not require parsing.

[0064] By using a Modbus parser to pre-convert engineering data in Modbus communication protocol format to a preset format, the problems of unreadable, difficult-to-understand, and inability to be directly converted engineering data in Modbus communication protocol format are solved. Invalid data can be eliminated in advance, improving the accuracy and stability of data processing.

[0065] Engineering data using the Modbus communication protocol is in binary or hexadecimal format. After being parsed by a Modbus parser, it can be converted into understandable engineering data with a preset format. For example, engineering data using the Modbus communication protocol format is: 01 03 04 00 FA 01 2C 79 84; using a Modbus parser to convert this Modbus communication protocol format engineering data into JSON-like format engineering data is as follows:

[0066] { "device_id": "modbus_01",

[0067] "timestamp": "2025-04-24T10:00:00Z",

[0068] "data": {

[0069] Temperature: 25.0

[0070] "humidity": 30.0

[0071] },

[0072] "unit": {

[0073] "temperature": "°C",

[0074] "humidity": "%RH"}

[0075] }

[0076] In some embodiments, when the communication protocol includes HTTP, IoT, etc., various methods can be used to receive engineering data collected by the data acquisition device of the air conditioning system. For example, message middleware can be used to receive engineering data collected by the data acquisition device. Receiving engineering data using protocols such as HTTP and IoT through message middleware allows for asynchronous data reception, improving the concurrency capability of multi-protocol data reception and enhancing the stability of data reception.

[0077] MQTT (Message Queuing Telemetry Transport) is an IoT protocol that can use the MQTT Broker (Message Queuing Telemetry Transport Broker) to receive engineering data in MQTT protocol format collected by data acquisition devices; it can also use the HTTP API of the message middleware to receive engineering data in HTTP protocol format collected by data acquisition devices.

[0078] Figure 4 This is a schematic diagram of a process for obtaining standard format data according to some embodiments of the data processing method of this disclosure. The standard data model includes standard fields, such as... Figure 4 As shown:

[0079] Step S401: Determine the communication protocol type corresponding to the engineering data and obtain the field mapping strategy corresponding to the communication protocol type.

[0080] Different field mapping strategies can be set for different communication protocols. These strategies include the mapping relationship between the original fields in the engineering data and the standard fields in the standard data model, as well as the field mapping methods.

[0081] Step S402: Using a field mapping strategy, determine the standard field corresponding to the original field in the engineering data, and set the field value of the corresponding standard field according to the field value of the original field.

[0082] Step S403: Generate standard format data based on the standard fields and their values.

[0083] By obtaining the standard fields corresponding to the original fields of different protocols, and setting the field values ​​of the corresponding standard fields according to the field values ​​of the original fields, standard format data is generated. This solves the problem that the original fields of different protocols have similar meanings but large differences in format, ensuring accurate mapping between the original fields and the standard fields, guaranteeing the consistency of data semantics, and improving the reliability of data processing.

[0084] There are several methods for generating standard-formatted data. For example, standard fields and their values ​​can be encapsulated according to the data format of a standard data model to obtain standard-formatted data. The data format of a standard data model includes JSON format.

[0085] By encapsulating standard fields and their values, standard JSON format data is obtained, reducing the logical complexity of data processing, lowering system development and maintenance costs, and avoiding parsing errors caused by inconsistent data structures. This enhances data compatibility and universality, improves cross-system data compatibility, and allows for parsing by multiple languages ​​and systems, avoiding data interoperability issues caused by format incompatibility.

[0086] Standard fields in a standard data model include data type fields and unit fields, and field mapping strategies in different protocols may also include the correspondence between the data type fields and unit fields corresponding to the original fields.

[0087] Using a field mapping strategy, determine the data type field and unit field corresponding to the original field; based on the first field value of the data type field in the standard data model, ensure that the data type of the converted field value conforms to the data type represented by the first field value; based on the second field value of the unit field corresponding to the original field, perform unit conversion processing on the field value of the original field, ensuring that the unit of the converted field value conforms to the unit represented by the second field value.

[0088] By converting the data type and unit values ​​of the original fields, data calculation errors caused by inconsistencies in data type and unit values ​​across different protocols can be avoided. This ensures data calculation accuracy, eliminates biases in data presentation and analysis, and improves the quality of data analysis.

[0089] In some embodiments, the data format of the standard data model can be JSON (JavaScript Object Notation), etc. Engineering data from various communication protocols can be parsed and converted to generate standardized JSON data. Standard fields in the standard data model include project number, equipment number, timestamp, location number, numerical value, data type, and unit. One or more standard fields in the standard data model can have their values ​​pre-set; for example, data type and unit values ​​can be pre-set.

[0090] For example, a standard data model in JSON format is shown below:

[0091] {

[0092] “project_id”: ,

[0093] “device_id”: ,

[0094] "time_stamp": ,

[0095] “point_code”: ,

[0096] “value”: ,

[0097] "value_type": float,

[0098] "unit": "℃"

[0099] }

[0100] Standard fields include project_id, device_id, time_stamp, point_code, value, data type, and unit. The first field value of the data type field, "float", can be pre-set, and the second field value of the unit field, "℃", can be pre-set.

[0101] Several methods can be used to determine the communication protocol type and field mapping strategy corresponding to the engineering data to ensure that the engineering data can be correctly converted into standard format data. For example, for engineering data transmitted using the Modbus communication protocol, the received engineering data can be determined by identifying the port receiving the engineering data (such as port 502), or by parsing the data frame structure (the data frame includes start characters, CRC checksums, etc.) and register address format, etc.

[0102] For engineering data transmitted using the HTTP protocol, the received engineering data can be determined by analyzing the HTTP request headers and data structures. For engineering data transmitted using the MQTT / CoAP (Constrained Application Protocol) protocol, the received engineering data can be determined by analyzing the protocol headers or by determining the UDP / TCP port on which the engineering data is received.

[0103] Field mapping strategies corresponding to various communication protocols can be pre-set and stored, and the field mapping strategy can be determined based on the communication protocol type corresponding to the engineering data. For example, when the communication protocol type corresponding to the engineering data is Modbus, the field mapping strategy corresponding to Modbus is obtained; when the communication protocol type corresponding to the engineering data is HTTP, the field mapping strategy corresponding to HTTP is obtained, and so on.

[0104] Field mapping strategies can be used to determine the standard fields corresponding to the original fields in engineering data, mapping the original fields to the standard fields required by the standard data model. For example, the correspondence between some original fields and the mapped standard fields is shown in Table 1 below, depending on different field mapping strategies:

[0105] Table 1 - Correspondence between original fields and mapped standard fields

[0106] Inconsistent data type definitions for the same data across different protocols, or errors in manual configuration, can lead to inconsistent data types in the original fields. A field mapping strategy can be used to determine the data type field and unit field corresponding to the original field. Based on the first field value of the data type field corresponding to the original field, the data type of the original field is converted. Similarly, based on the second field value of the unit field corresponding to the original field, the unit of the original field is converted.

[0107] For example, the correction table for the original field values ​​is shown in Table 2 below:

[0108] Table 2 - Correction Comparison Table of Original Field Values

[0109] As shown in Table 2, using a field mapping strategy, the data type field corresponding to the original field 1 is determined in the standard data model. The first field value of this data type field is "float", the field value of the original field 1 is "12.5", and the data type of the field value of the original field 1 is "str". Various methods can be used to perform data type conversion on the field value "12.5" of the original field 1 based on the first field value "float" of the data type field corresponding to the original field 1, correcting the "str" ​​type "12.5" to "float" 12.5, so that the data type of the field value 12.5 of the original field 1 conforms to the float data type represented by the first field value.

[0110] Using a field mapping strategy, determine the data type field corresponding to the original field 2 in the standard data model. The first field value of this data type field is "bool", the field value of the original field 2 is "1", and the data type of the field value of the original field 2 is "int". Various methods can be used to perform data type conversion on the field value "1" of the original field 2 based on the first field value "bool" of the data type field corresponding to the original field 2. This will correct the "int" type field value "1" of the original field 2 to the "bool" type "true", making the data type of the field value "True" of the original field 2 conform to the bool data type represented by the first field value.

[0111] The table below shows the unit conversion for the original field values:

[0112] Table 3 - Unit Conversion Reference Table for Original Field Values

[0113] Using a field mapping strategy, a unit field corresponding to the original field 3 is determined in the standard data model. The second field value of this unit field is "kPa", the field value of the original field 3 is "10", and the unit of the original field 3 is "Bar". Various methods can be used to convert the unit value of the original field 3 based on the second field value "kPa" of the unit field corresponding to the original field 3, converting the original field value "10" to "1000" so that the unit of the converted field value "1000" conforms to the unit kPa represented by the second field value.

[0114] Using a field mapping strategy, a unit field corresponding to the original field 4 is determined in the standard data model. The second field value of this unit field is "m³ / h", the field value of the original field 4 is "1000", and the unit of the original field 4 is "L / s". Various methods can be used to convert the unit value of the original field 4 based on the second field value "m³ / h" of the unit field corresponding to the original field 4, converting the original field value "1000" to "3600" so that the unit of the converted field value "3600" conforms to the unit m³ / h represented by the second field value.

[0115] Based on the data format of the standard data model, raw data from different protocols can be encapsulated into standard format data conforming to the standard data model, achieving data semantic alignment and format mapping, and providing consistent data parsing and processing. For example, the obtained standard format data in JSON format is shown below:

[0116] {

[0117] “project_id”: 123456,

[0118] “device_id”: “dev_a”,

[0119] "time_stamp": "2025-02-02T10:00:00Z"

[0120] "point_code": "chilled_water_temp_in",

[0121] “value”: 10.2,

[0122] "value_type": float,

[0123] "unit": "℃"

[0124] }

[0125] Figure 5 This is a schematic diagram of the process for providing a data query service according to some embodiments of the data processing method of this disclosure, such as... Figure 5 As shown:

[0126] Step S501: Cache the standard format data in the cache area and store it in the first database.

[0127] It can perform real-time data caching of standard format data, caching the latest one or several standard format data in the cache area; it can use multiple databases to store standard format data, the first database can be multiple non-relational databases such as MongoDB or multiple relational databases, and it can store all historical standard format data actually obtained through the database.

[0128] In step S502, a real-time data query service is provided through the first query interface corresponding to the cache area, and a historical data query service is provided through the second query interface corresponding to the first database.

[0129] The first query interface provides the front end with real-time query, monitoring, and display functions based on standard format data; the second query interface provides the front end with historical query, monitoring, and display functions based on standard format data.

[0130] By caching and storing standard format data in a database, real-time and historical data query services can be provided separately. Using a cache to provide real-time query services, the high memory read and write speed of the cache can solve the problem of real-time data query latency. Using a database to store historical data can leverage the persistent storage characteristics of the database to ensure that historical data is not lost. The database's indexing mechanism can ensure efficient retrieval of large-scale historical data and achieve reasonable allocation of query resources.

[0131] Based on the caching time of standard format data in the cache and the preset caching duration threshold, expired standard format data in the cache is determined and deleted from the cache.

[0132] By determining and deleting expired standard format data based on the caching time and caching duration threshold, cache memory space can be freed up, preventing invalid data from occupying the cache and preventing new standard format data from being stored in the cache, thus ensuring the stability of real-time query services. By automatically cleaning up expired data, no manual intervention is required for cache management, reducing operation and maintenance costs and ensuring the timeliness of real-time query results.

[0133] For example, when caching standard format data in the cache, the caching time of the standard format data is recorded; the caching duration threshold is preset to 5 minutes, 10 minutes, etc.; expired standard format data in the cache can be determined periodically based on the caching time of the standard format data in the cache and the caching duration threshold; when it is determined that the caching duration of the standard format data in the cache exceeds the caching duration threshold, this standard format data is determined to be expired standard format data and deleted from the cache.

[0134] Figure 6This is a schematic diagram of the process for providing statistical data query services according to some embodiments of the data processing method of this disclosure, such as... Figure 6 As shown:

[0135] Step S601: Based on the standard format data stored in the first database, determine the statistical data corresponding to the preset statistical parameters and store it in the second database. The second database can be multiple databases; the first database and the second database can be the same database or different databases.

[0136] Step S602: Provide statistical data query services through the third query interface corresponding to the second database.

[0137] By identifying statistical data corresponding to statistical parameters and providing statistical data query services, a pre-storage strategy can be provided. Statistical data for statistical parameters can be calculated and stored in advance based on standard format data, avoiding the need for the front end to calculate historical data in real time when statistical analysis is required. This allows for direct acquisition of statistical results, avoiding issues such as display lag and calculation delays caused by real-time calculations, significantly improving front-end loading speed and reducing application development difficulty.

[0138] Statistical parameters can be of various types, including cooling capacity, energy consumption parameters, and energy efficiency parameters. Energy consumption parameters can be the cumulative power of the equipment, while energy efficiency parameters can be the ratio of cooling capacity to energy consumption. Multiple methods can be used to determine the statistical data corresponding to these parameters, providing a data pre-storage mechanism. Key indicators such as cooling capacity, energy consumption parameters, and energy efficiency parameters can be used as statistical parameters, and aggregation processing can be performed on these parameters to avoid real-time calculation pressure.

[0139] Based on the standard format data stored in the first database, a dataset of statistical parameters within a unit time period is obtained; the dataset is sampled based on the sampling interval to obtain sampled values ​​of statistical parameters; and statistical data are calculated based on the sampled values ​​of statistical parameters and the sampling interval.

[0140] By sampling the dataset based on the sampling interval, statistical parameter sample values ​​are obtained and statistical data are calculated. Sampling can balance calculation accuracy and efficiency, reduce the amount of computation and system resource consumption, and reflect the data change trend through sample values, thus ensuring the reliability of statistical data.

[0141] For example, the statistical parameter is (instantaneous) cooling capacity, and the unit of time can be one day, etc.; based on the standard format data stored in the first database, a dataset of cooling capacity within one day is obtained; the sampling interval is ΔT (ΔT≤300) seconds, for example, ΔT is 60 seconds; the dataset is sampled based on ΔT, that is, one data point is obtained from the dataset every 60 seconds, and 1440 statistical parameter sample values ​​can be obtained within the dataset. Various methods can be used to calculate statistical data based on the statistical parameter sample values ​​and the sampling interval.

[0142] For example, the cumulative cooling capacity per ΔT is calculated as follows:

[0143] (1-1);

[0144] The instantaneous cooling capacity in formula (1-1) is the sampled value of the statistical parameter. By adding up the cumulative cooling capacity of each ΔT within a time period of 1 hour, 2 hours, etc., the cumulative cooling capacity within a time period of 1 hour, 2 hours, etc. can be obtained as the statistical data corresponding to the cooling capacity and stored in the second database. Based on the same method, statistical data such as energy consumption parameters and energy efficiency parameters can be obtained and stored. The statistical data can be displayed on the front end through the third query interface, or further calculations can be performed based on the statistical data, such as calculating the statistical data such as cooling capacity, energy consumption parameters, and energy efficiency parameters within a month or a year.

[0145] In some embodiments, the data processing method of this disclosure can be applied to a central air conditioning system, and the engineering data acquisition, fusion, and transmission architecture corresponding to the data processing method of this disclosure is as follows: Figure 7 As shown, the data processing method disclosed herein can realize the collection, adaptation, standardization conversion, storage, and provision of data query services for multi-protocol data. Figure 7 The data access layer, protocol parsing / adaptation layer, data encapsulation layer, and application interface layer are all logical concepts and can be deployed using various methods.

[0146] The multi-protocol data source, namely the field perception layer, is responsible for collecting and acquiring various engineering data of the central air conditioning system, converting them into digital signals for transmission, and reporting them to the data access layer. The field perception layer is equipped with data acquisition devices for the air conditioning system, including controllers and other data acquisition devices. Controllers may include DDCs that support the Modbus protocol, and other data acquisition devices include sensors, metering devices, smart devices, etc. that support the IoT protocol.

[0147] The data access layer is configured with Modbus data service and message middleware such as MQTT Broker and HTTP API. Modbus data service has on-demand collection and dynamic point mechanism, which can collect project data on demand according to the effective points involved in the project and report it to the protocol parsing / adaptation layer. Message middleware such as MQTT Broker and HTTP API are responsible for the transmission and distribution of project data and report the project data to the protocol parsing / adaptation layer.

[0148] The protocol parsing / adaptation layer is equipped with a Modbus parser. Engineering data transmitted using the Modbus protocol is parsed by the Modbus parser and then subjected to data standardization processing. Engineering data transmitted using the IoT protocol is in a format similar to the standard data model and does not require parsing; it can be directly subjected to data standardization processing. Data standardization processing includes various processes such as data source identification processing, field mapping processing, field type conversion processing, and unit conversion processing.

[0149] The data encapsulation layer encapsulates the data processed by the protocol parsing / adaptation layer into standard format data conforming to the standard data model format, ensuring consistency in the format of engineering data transmitted using various protocols. The data storage layer includes a real-time data cache, a historical data storage database (first database), and an aggregated statistics database (second database), which can respectively meet the storage needs for real-time monitoring, historical data storage, and statistical analysis based on standard format data. The application interface layer provides standardized data query service interfaces, supporting data display and application on the cloud platform frontend. These data query service interfaces include a real-time data API (first query interface), a historical data API (second query interface), and an aggregated statistics API (third query interface).

[0150] In some embodiments, such as Figure 8 As shown, this disclosure provides a data processing device, which includes a data receiving module 801, a standardization processing module 802, and a data service module 803, etc.

[0151] The data receiving module 801 receives engineering data collected by the data acquisition device of the air conditioning system, wherein the engineering data is transmitted using at least one communication protocol; the standardization processing module 802 performs data standardization processing on the engineering data according to a preset standard data model to obtain standard format data corresponding to the engineering data; and the data service module 803 provides data query services based on the standard format data.

[0152] The communication protocol includes the Modbus communication protocol. The data receiving module 801 determines the device address information of the Modbus slave station to be accessed according to the preset device configuration table. The data receiving module 801 controls the Modbus master station to access the Modbus slave station according to the device address information, in order to obtain engineering data collected by the Modbus slave station using the Modbus communication protocol format. The Modbus slave station includes a data acquisition device that supports the Modbus protocol.

[0153] Before performing data standardization processing on the engineering data according to the preset standard data model, the data receiving module 801 uses a Modbus parser to convert the engineering data using the Modbus communication protocol format into engineering data with a preset format.

[0154] The communication protocol includes at least one of the HTTP protocol and the IoT protocol. The data receiving module 801 uses message middleware to receive engineering data collected by the data acquisition device.

[0155] In some embodiments, such as Figure 9 As shown, the standardization processing module includes a data source identification unit 8021, a field mapping unit 8022, a data encapsulation unit 8023, a field type correction unit 8024, and a unit conversion unit 8025.

[0156] The data source identification unit 8021 determines the communication protocol type corresponding to the engineering data and obtains the field mapping strategy corresponding to the communication protocol type; the field mapping unit 8022 uses the field mapping strategy to determine the standard field corresponding to the original field in the engineering data, and sets the field value of the corresponding standard field according to the field value of the original field; the data encapsulation unit 8023 generates standard format data based on the standard field and the field value of the standard field.

[0157] The data encapsulation unit 8023 encapsulates standard fields and their values ​​according to the data format of the standard data model to obtain standard format data. The data format of the standard data model includes JSON format, etc.

[0158] The field type correction unit 8024 uses a field mapping strategy to determine the unit field corresponding to the original field; the field type correction unit 8024 performs data type conversion processing on the field value of the original field according to the first field value of the data type field corresponding to the original field, so that the data type of the converted field value of the original field conforms to the data type represented by the first field value.

[0159] The unit conversion unit 8025 uses a field mapping strategy to determine the unit field corresponding to the original field. Based on the second field value of the unit field corresponding to the original field, the unit conversion unit 8025 performs unit conversion processing on the field value of the original field so that the unit of the converted field value of the original field conforms to the unit represented by the second field value.

[0160] In some embodiments, such as Figure 10 As shown, the data service module includes a data storage unit 8031, a service provision unit 8032, and a statistical data unit 8033, etc.

[0161] The data storage unit 8031 ​​caches standard format data in a cache area and stores it in a first database; the service providing unit 8032 provides real-time data query services through a first query interface corresponding to the cache area, and provides historical data query services through a second query interface corresponding to the first database.

[0162] The data storage unit 8031 ​​determines the expired standard format data in the cache based on the cache time of the standard format data in the cache and the preset cache duration threshold; the data storage unit 8031 ​​deletes the expired standard format data in the cache.

[0163] The statistical data unit 8033 determines the statistical data corresponding to the preset statistical parameters based on the standard format data stored in the first database, and stores it in the second database; the service providing unit 8032 provides statistical data query services through the third query interface corresponding to the second database.

[0164] The statistical data unit 8033 obtains a dataset of statistical parameters within a unit time period based on the standard format data stored in the first database; the statistical data unit 8033 samples the dataset based on the sampling interval time to obtain the sampled values ​​of the statistical parameters; the statistical data unit 8033 calculates the statistical data based on the sampled values ​​of the statistical parameters and the sampling interval time.

[0165] Figure 11 This is a schematic diagram of modules according to other embodiments of the data processing apparatus of this disclosure. For example... Figure 11 As shown, the data processing device may include a memory 1101, a processor 1102, a communication interface 1103, and a bus 1104. The memory 1101 is used to store instructions, and the processor 1102 is coupled to the memory 1101. The processor 1102 is configured to execute the above-described data processing method based on the instructions stored in the memory 1101.

[0166] The memory 1101 can be a high-speed RAM, non-volatile memory, or a memory array. The memory 1101 may also be divided into blocks, and these blocks can be combined into virtual volumes according to certain rules. The processor 1102 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the data processing methods of this disclosure.

[0167] In some embodiments, this disclosure provides an air conditioning system, including the data processing device as described in any of the above embodiments, wherein the air conditioning system may be a central air conditioning system, etc.

[0168] In some embodiments, this disclosure provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the data processing methods as described in any of the foregoing embodiments.

[0169] Computer-readable storage media may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples (not an exhaustive list) of readable storage media may include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0170] Embodiments of this disclosure may also be computer program products, including computer program instructions that, when executed by a processor, cause the processor to perform the steps in the methods according to various embodiments of this disclosure described in the "Exemplary Methods" section above.

[0171] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.

[0172] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0173] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0174] It should also be noted that in the apparatus, devices, and methods of this disclosure, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions to this disclosure.

[0175] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0176] The above description has been given for illustrative and descriptive purposes. Furthermore, this description is not intended to limit the embodiments of this disclosure to the forms disclosed herein. Although several exemplary aspects and embodiments have been discussed above, those skilled in the art will understand that the above embodiments are illustrative only and do not limit the scope of this disclosure. Those skilled in the art will understand that the above embodiments can be combined, modified, or replaced without departing from the scope and spirit of this disclosure.

Claims

1. A data processing method, comprising: The system receives engineering data collected by the data acquisition device of the air conditioning system, wherein the engineering data is transmitted using at least one communication protocol. Based on a preset standard data model, the engineering data is standardized to obtain standard format data corresponding to the engineering data. Provide data query services based on the standard format data.

2. The method as described in claim 1, wherein, The standard data model includes standard fields. The step of standardizing the engineering data according to the preset standard data model to obtain standard format data corresponding to the engineering data includes: Determine the communication protocol type corresponding to the engineering data, and obtain the field mapping strategy corresponding to the communication protocol type; Using the field mapping strategy, standard fields corresponding to the original fields in the engineering data are determined, and the field values ​​of the corresponding standard fields are set according to the field values ​​of the original fields; The standard format data is generated based on the standard fields and their values.

3. The method as described in claim 2, wherein, The process of generating the standard format data based on the standard fields and their values ​​includes: Based on the data format of the standard data model, the standard fields and their values ​​are encapsulated to obtain the standard format data. The data format of the standard data model includes JSON format.

4. The method of claim 2, wherein, The standard fields include data type fields and unit fields, and the method further includes: Using the field mapping strategy, determine the data type field and unit field corresponding to the original field; Based on the first field value of the data type field corresponding to the original field, the field value of the original field is converted to a data type so that the data type of the converted field value conforms to the data type represented by the first field value. Based on the second field value of the unit field corresponding to the original field, the field value of the original field is converted to a unit, so that the unit of the converted field value conforms to the unit represented by the second field value.

5. The method of claim 1, wherein, The data query service includes real-time data query service and historical data query service, and the data query service based on the standard format data includes: The standard format data is cached in the cache area and stored in the first database; The real-time data query service is provided through a first query interface corresponding to the cache area, and the historical data query service is provided through a second query interface corresponding to the first database.

6. The method of claim 5, further comprising: Based on the standard format data stored in the first database, determine the statistical data corresponding to the preset statistical parameters and store them in the second database; Statistical data query services are provided through a third query interface corresponding to the second database.

7. The method of claim 6, wherein, The step of determining the statistical data corresponding to the preset statistical parameters based on the standard format data stored in the first database includes: Based on the standard format data stored in the first database, obtain the dataset of the statistical parameters within a unit time period; The dataset is sampled based on the sampling interval to obtain the sampled values ​​of statistical parameters; The statistical data is calculated based on the sampled values ​​of the statistical parameters and the sampling interval duration.

8. The method of claim 6, wherein, The statistical parameters include at least one of the following: cooling capacity, energy consumption parameters, and energy efficiency parameters.

9. The method of claim 5, comprising: Based on the caching time of the standard format data in the cache area and the preset caching duration threshold, the expired standard format data in the cache area is determined; Delete the expired standard format data from the cache.

10. The method of claim 1, wherein, The communication protocol includes the Modbus communication protocol, and the engineering data collected by the data acquisition device of the air conditioning system includes: Based on the preset device configuration table, determine the device address information of the Modbus slave station that needs to be accessed; The Modbus master station controls the Modbus slave station to access the Modbus slave station based on the device address information, in order to obtain engineering data collected by the Modbus slave station using the Modbus communication protocol format. The Modbus slave station includes a data acquisition device that supports the Modbus protocol.

11. The method of claim 10, wherein, Before performing data standardization processing on the engineering data according to a preset standard data model, the following steps are included: Using a Modbus parser, the engineering data using the Modbus communication protocol format is converted into engineering data with a preset format.

12. The method of claim 1, wherein, The communication protocol includes at least one of the HTTP protocol and the IoT protocol, and the engineering data collected by the data acquisition device of the air conditioning system includes: The system uses a message middleware to receive engineering data collected by the data acquisition device.

13. The method as claimed in any one of claims 1 to 12, wherein, The air conditioning system includes a central air conditioning system; The data acquisition device includes at least one of a sensor, a measuring device, and a controller; The engineering data includes at least one of the following: operating status data, fault data, and control data.

14. A data processing apparatus, comprising: A data receiving module is used to receive engineering data collected by the data acquisition device of the air conditioning system, wherein the engineering data is transmitted using at least one communication protocol; The standardization processing module is used to perform data standardization processing on the engineering data according to a preset standard data model to obtain standard format data corresponding to the engineering data. The data service module is used to provide data query services based on the standard format data.

15. A data processing apparatus, comprising: Memory; and a processor coupled to the memory, the processor being configured to perform the method as described in any one of claims 1 to 13 based on instructions stored in the memory.

16. An air conditioning system, comprising: The data processing apparatus as described in claim 14 or 15.

17. A computer-readable storage medium storing computer instructions that, when executed by a processor, implement the steps of the method as claimed in any one of claims 1 to 13.

18. A computer program product comprising a computer program that, when executed by a processor, implements the steps of the method according to any one of claims 1 to 13.

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