Elevator data request and response method

Abstract

The invention discloses an elevator data requesting and responding method. The elevator data requesting and responding method comprises the steps that S1, a requester encapsulates data content and data requirements into a data request according to a preset encapsulation format; s2, the requester sends the data request to the elevator; s3, the elevator analyzes the data request according to a preset packaging format to obtain data content and data requirements; s4, the elevator collects data according to the data content and the data requirements; s5, the elevator carries out integration processing on the collected data to obtain integrated data; and S6, the elevator packages the integrated data and the integration algorithm to obtain packaged data actually to be transmitted to the requester, and the packaged data is sent to the requester. According to the method, the elevator can provide the data meeting the requirement according to the specified data requirement of the requester, and the original data volume is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of elevators, and particularly to an elevator data request and response method. Background Art

[0002] In engineering practice, it is often necessary to send instructions to an elevator to have the elevator provide data that meets requirements, so as to obtain special information hidden in the data by analyzing the data provided by the elevator. Currently, various data generated during operation are usually pre-stored in the elevator in advance. When receiving an instruction to provide data, the elevator directly sends the stored data externally. Additionally, in some cases, it may be necessary for the elevator to provide data under specific circumstances (such as diagnostic operation data after an abnormality occurs). When an abnormal elevator receives a diagnostic operation instruction, it executes the diagnostic operation instruction, collects relevant diagnostic operation data, and then sends the collected diagnostic operation data externally.

[0003] In the above description, the diagnostic operation instruction of the elevator is directly provided to the elevator. However, in some cases, it may be specified that the elevator provide specific data under certain specified circumstances, but how the elevator meets these specified circumstances is not provided. Therefore, how the elevator provides data that meets requirements according to the specified data requirements becomes a technical problem to be solved.

[0004] Currently, when the elevator provides data externally, it usually directly sends the collected original data externally. However, in many cases, the amount of original data is very large, which brings difficulties to the collection, storage, and transmission of the original data. Therefore, how to reduce the amount of original data while retaining the valuable information in the original data becomes another technical problem to be solved. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides an elevator data request and response method, including:

[0006] Step S1, the requester encapsulates the data content and data requirements into a data request according to a preset encapsulation format;

[0007] Step S2, the requester sends the data request to the elevator;

[0008] Step S3, the elevator parses the data request according to the preset encapsulation format to obtain the data content and data requirements;

[0009] Step S4, the elevator collects data according to the data content and data requirements;

[0010] Step S5, the elevator performs an integration process on the collected data to obtain integrated data;

[0011] Step S6: The elevator packs the integrated data and the integrated algorithm to obtain the packed data actually to be transmitted to the requester, and sends it to the requester.

[0012] Preferably, in step S4, data is collected according to a first method.

[0013] The first method is: identifying the categories included in the data requirements, and collecting data separately according to different categories.

[0014] The categories include one or more of the following preset categories: Category 1, representing the specifications of data sampling and data format; Category 2, representing the influencing factors that only depend on the elevator; Category 3, representing the influencing factors that depend on the elevator user and / or the usage environment.

[0015] Preferably, for Category 2, in step S4, data is collected according to the following steps:

[0016] Step A1: Determine the first elevator state corresponding to when Category 2 is satisfied.

[0017] Step A2: Compare the state difference between the first elevator state and the second elevator state where the elevator is currently located.

[0018] Step A3: Determine the transition process from the second elevator state to the first elevator state according to the state difference.

[0019] Step A4: Determine the control instructions required to control the elevator to transition from the second elevator state to the first elevator state according to the transition process.

[0020] Step A5: Control the elevator using the control instructions so that the elevator finally transitions to the first elevator state.

[0021] Step A6: Collect data.

[0022] Preferably, for Category 3, step 4 evaluates whether the current elevator meets the Category 3 part of the data requirements. If it meets, data is collected immediately. If it does not meet, data is collected after the current elevator meets the Category 3 part of the data requirements, or another elevator that meets the Category 3 part of the data requirements is selected as the target for data collection.

[0023] Preferably, when the data requirements include Category 1, Category 2, and Category 3 at the same time, first wait for the current elevator to meet the Category 3 requirements, then control the current elevator to meet Category 2, and finally collect data according to the data requirements corresponding to Category 1.

[0024] Preferably, in step S4, it is determined whether relevant historical data is stored locally in the elevator according to the data content and data requirements. If so, the associated historical data is directly extracted. If not, data is collected according to the first method. And when there is historical data stored associatively multiple times, the historical data is maintained according to the data requirements and data content.

[0025] Preferably, for two pieces of historical data with the same data requirements except for the time range, if the time periods of the two pieces of historical data are adjacent or partially overlap, the two pieces of historical data are merged, the merged time period is determined, and the merged time period is used as the time period in the data requirements of the merged data.

[0026] Preferably, for two pieces of historical data with the same other data requirements except that the sampling precisions are different and the corresponding time periods overlap, the low-precision data corresponding to the overlapping period is deleted, and at the same time, the time period of the low-precision data is adjusted so that the adjusted time period corresponds to the remaining low-precision data.

[0027] Preferably, the step maintains the historical data in at least one of the following ways:

[0028] Method 1: Save the data collected in the most recent n times, where n is a positive integer preset to be greater than 1;

[0029] Method 2: Save the data collected in the most recent n times, where n is a positive integer preset to be greater than 1, and ensure that the total size of the historical data does not exceed the first threshold;

[0030] Method 3: Save the historical data whose requested frequency is higher than the threshold;

[0031] Method 4: Determine the priority according to the physical attribute bits of the data, and save the historical data with a priority higher than the threshold;

[0032] Method 5: Select the historical data to be saved according to the ratio of the occupied space of the data before integration to the occupied space of the data after integration.

[0033] Preferably, the method for the step S5 to perform integration processing on the collected data is: first classify the data according to a preset type, and then select a corresponding integration algorithm according to the type of the data to perform integration processing on the data;

[0034] The preset types include: the first type of data, indicating that the actual value of the data is only a finite number of discrete values; the second type of data, indicating that the actual value of the data is a continuous or discrete value that fluctuates up and down within a certain range centered on a certain value; the third type of data, indicating that the actual value of the data is a changing continuous or discrete value, and its actual value can be represented by a mathematical formula; the fourth type of data, indicating that the actual value of the data presents a certain statistical law and can be described by statistical means; the fifth type of data, indicating other situations where the data does not conform to the first, second, third, and fourth types.

[0035] Preferably, any of the following pairs of data is classified according to the preset type:

[0036] Method 1: First, determine the change characteristics of the data according to the physical properties represented by all possible data contents of the data, and then classify the data into the corresponding type according to the change characteristics of the data.

[0037] Method 2: Perform data analysis on each data content of the collected data respectively, discover the characteristics of the data, and then classify the data into the corresponding type according to the characteristics of the data; the characteristics of the data refer to the unique properties of each data type that are different from other types of data.

[0038] Preferably, the integration algorithms corresponding to the first type of data are: record the change moment when the data changes from the previous value to the current value and the current value of the change; the integration algorithms corresponding to the second type of data are: record the central value and the mathematical parameters used to describe the fluctuation situation; the integration algorithms corresponding to the third type of data are: determine the mathematical formula reflecting its change by means of curve fitting or physical meaning analysis, and record the mathematical formula and related parameter values; the integration algorithms corresponding to the fourth type of data are: find out the statistical law of the data and record the law and related parameter values; the integration algorithms corresponding to the fifth type of data are: do not process and directly record the data.

[0039] Preferably, the elevator data request and response method further includes:

[0040] Step S7, the requester extracts the integrated data and the integration algorithm;

[0041] Step S8, determine the meaning of each part in the integrated data according to the integration algorithm;

[0042] Step S9, analyze the internal data value according to the meaning of each part in the integrated data, and judge whether the data value meets the requirements of the requester's data request; if so, end, otherwise perform inverse integration on the integrated data to obtain the data before integration.

[0043] Compared with the prior art, the present invention enables an elevator to provide data that meets the requirements according to the specified data requirements of the requester, and reduces the amount of original data. Specific Embodiments

[0046] The following specific embodiments illustrate the implementation manners of the present invention. Those skilled in the art can fully understand other advantages and technical effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through different specific implementation manners. The details in this specification can also be applied based on different viewpoints, and various modifications or changes can be made without departing from the overall design concept of the invention. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other. The following exemplary embodiments of the present invention can be implemented in many different forms and should not be construed as being limited only to the specific embodiments described herein. It should be understood that these embodiments are provided to make the disclosure of the present invention complete and thorough, and to fully convey the technical solutions of these exemplary specific embodiments to those skilled in the art.

[0047] Embodiment 1

[0048] In order to obtain our understanding and management of elevators through the implementation of data analysis, we need to acquire specific elevator data. For example: Government regulatory departments usually require elevator manufacturers to provide them with specified elevator-related data (such as elevator operation-related data, production design data, etc.); for remote monitoring centers or property management centers that implement remote monitoring of elevators, they need to regularly or irregularly obtain the on-site operation data of elevators, maintenance data of vulnerable components, maintenance operation data of maintenance workers, etc. from the elevator site; for passengers, they may hope to use their smart terminals such as mobile phones to obtain relevant data such as the design, manufacture, maintenance, and operation of elevators, and understand information such as the reliability, failure rate, and next maintenance of elevators. All of these require the data provider to collect data that meets the needs of the data requester according to the data content of the requested data by the data requester (i.e., which data are needed, such as noise in the car, vibration, torque current of the drive motor, door opening and closing resistance, etc.) and the data requirements (such as the accuracy of the data, sampling period, the state in which the elevator needs to be, the position of the car, the load situation in the car, etc.), and provide it to the data requester in an appropriate manner.

[0049] This embodiment provides an elevator data request and response method, including:

[0050] Step S1, the requester encapsulates the data content and data requirements into a data request according to a preset encapsulation format;

[0051] Step S2, the requester sends the data request to the elevator;

[0052] Step S3: The elevator parses the data request according to a preset encapsulation format to obtain the data content and data requirements.

[0053] Step S4: The elevator collects data according to the data content and data requirements.

[0054] Step S5: The elevator integrates and processes the collected data to obtain integrated data.

[0055] Step S6: The elevator packs the integrated data and the integration algorithm to obtain the packed data actually to be transmitted to the requester, and sends it to the requester.

[0056] The following takes the following example to illustrate the data request and response method of the elevator:

[0057] The maintenance staff uses the maintenance mobile phone to request the required elevator operation data from the elevator. After the elevator completes data collection and processing, it uses the communication between the maintenance staff's mobile phone and the elevator to send the data to the maintenance mobile phone of the maintenance staff.

[0058] Execute Step S1: The requester encapsulates the data content and data requirements into a data request according to a preset encapsulation format. Specifically, the maintenance staff's mobile phone as the data requester encapsulates the data content and data requirements according to the preset encapsulation format, and then executes Step S2 to send the encapsulated data request to the elevator as the data provider. Here, for the encapsulation of the data content and data requirements, the preset encapsulation format is: after the start bit is the data content, the data content and data requirements are separated by a flag bit or a delimiter, and an end bit is set at the end of the data requirements. The data requirements adopt the flag bit method in the communication protocol combined with key-value pairs. For example: after the start bit is the data content, such as the aforementioned noise, vibration, torque current of the drive motor, door opening and closing resistance, etc. After the data content ends, a delimiter that separates the data content and the data requirements is set, and then the data requirements in the form of key-value pairs are as follows: data time range: 2024 / 06 / 18 00:00:00 - 2024 / 06 / 19 00:00:00, car load rate: 80%, car position: 15th floor, etc. At the end of the data requirements, an end bit is set.

[0059] Execute Step S3: After receiving the data request from the maintenance staff's mobile phone, the elevator parses the data request according to the preset encapsulation format to obtain the specific data content and data requirements. During parsing, mainly identify the start bit, delimiter, and end bit, then determine the data content segment and the data requirements segment, and then extract the specific data content and data requirements according to the format definition of the key-value pair, such as the noise, vibration, torque current of the drive motor, door opening and closing resistance, etc. in the data content, and the data time range in the data requirements: 2024 / 06 / 18 00:00:00 - 2024 / 06 / 19

[0060] 00:00:00, car load rate: 80%, car position: 15th floor, etc. After obtaining the specific data content and data requirements, it is possible to determine which data the requesting party actually needs under what elevator conditions and within what time range.

[0061] The following details step S4 on how the elevator collects data according to the data content and data requirements.

[0062] One way is that step S4 directly collects data according to the first method; the first method is: identify the categories included in the data requirements and collect data separately according to different categories;

[0063] The categories include one or more of the following preset categories:

[0064] Category 1, representing the specifications of data sampling and data format; such as: sampling period, accuracy, fixed-point or floating-point, word length, etc.;

[0065] Category 2, representing the influencing factors that only depend on the elevator, that is, these influencing factors will not be interfered by other external objects except the elevator, such as: the operating mode of the elevator, car position, running direction, operating conditions of equipment such as air conditioners and lighting devices in the car, the condition of the voice broadcast device in the car, the display status of the display device on the landing, etc.;

[0066] Category 3, representing the influencing factors that depend on the elevator users and / or the usage environment; such as: car load, wind pressure (i.e., the pressure generated by the wind in the waiting hall on the landing door), elevator user attributes (age, disabled people, robots, pets, wheelchairs, carrying large-volume items, etc.), environmental temperature and humidity, atmospheric pressure, etc.

[0067] For the processing of Category 1, just collect data according to the data requirements of this category.

[0068] For Category 2, step S4 collects data according to the following steps:

[0069] Step A1, determine the first elevator state corresponding to when Category 2 is satisfied;

[0070] Step A2, compare the state difference between the first elevator state and the second elevator state where the elevator is currently located;

[0071] Step A3, determine the transition process from the second elevator state to the first elevator state according to the state difference;

[0072] Step A4, determine the control instructions required to control the elevator to transition from the second elevator state to the first elevator state according to the transition process;

[0073] Step A5, control the elevator using control instructions so that the elevator finally transitions to the first elevator state;

[0074] Step A6, collect data.

[0075] For Category 3, in Step 4, evaluate whether the current elevator meets the Category 3 part of the data requirements. If it does, collect data immediately. If not, wait until the current elevator meets the Category 3 part of the data requirements and then collect data, or select another elevator that meets the Category 3 part of the data requirements as the target for data collection.

[0076] In engineering practice, data requirements often include all three of the above categories at the same time. Therefore, when the data requirements include Category 1, Category 2, and Category 3 at the same time, first wait for the current elevator to meet the Category 3 requirements, then control the current elevator to meet the Category 2 requirements, and finally collect data according to the data requirements corresponding to Category 1.

[0077] In Step S4, after collecting data, associate and store the collected data with the corresponding data content and data requirements.

[0078] Another way is that in Step S4, first judge whether there is relevant historical data stored locally in the elevator according to the data content and data requirements. If there is, directly extract the associated historical data. If not, collect data according to the first method mentioned above; and when there are multiple historical data stored in association, maintain the historical data according to the data requirements and data content. In order to facilitate determining whether the data actually required by this request has been saved in the historical data according to the data requirements, the data content and data requirements should be stored in association.

[0079] When there are multiple historical data stored, the historical data should also be maintained according to the data requirements and data content.

[0080] For example, for two historical data with the same data requirements except for the time range, if the time periods of the two historical data are adjacent or partially overlapping, merge the two historical data, determine the merged time period, and use the merged time period as the time period in the data requirements of the merged data.

[0081] For another example, for two pieces of historical data with the same other data requirements except for different sampling precisions and overlapping corresponding time periods (at the ends of the time periods), delete the low-precision data corresponding to the overlapping time periods, and at the same time adjust the time periods of the low-precision data so that the adjusted time periods correspond to the remaining low-precision data. That is to say, after obtaining new data each time, first determine the data requirements of the new data, then judge whether the new data and the historical data meet the maintenance conditions of the preset data requirements according to the specific content of the data requirements, and then perform corresponding data maintenance according to the judgment results.

[0082] To avoid historical data occupying too much storage space, at least one of the following methods can be used to limit the stored historical data:

[0083] Method 1: Save the data collected in the most recent n times, where n is a preset positive integer greater than 1;

[0084] Method 2: Save the data collected in the most recent n times, where n is a preset positive integer greater than 1, and ensure that the total size of the historical data does not exceed the first threshold;

[0085] Method 3: Save the historical data whose request frequency is higher than the threshold;

[0086] Method 4: Determine the priority according to the physical attribute bits of the data, and save the historical data with a priority higher than the threshold;

[0087] Method 5: Select the historical data to be saved according to the ratio of the occupied space of the data before integration to the occupied space of the data after integration.

[0088] Considering that historical data needs to be saved locally, in the case where government regulatory agencies require elevator enterprises (usually their data processing centers with large data servers) to provide elevator data, as the data provider, the data processing center has no difficulty in saving a large amount of historical data locally. However, saving a large amount of data at the elevator site (whether in the elevator control system or in the data transmission unit - DTU set at the elevator site) requires high costs or cannot be saved at all. Therefore, the above content should be considered as preferred.

[0089] In step S5, the method for integrating the collected data is: first classify the data according to the preset type, and then select the corresponding integration algorithm according to the type of the data to perform integration processing on the data;

[0090] The preset types include:

[0091] The first type of data indicates that the actual value of the data is only a finite number of discrete values; for example, for data representing certain switch states, the possible values may only be 1 and 0 representing on and off; for the floor where the elevator car is located, its actual value is also the number corresponding to all the floors where it can stop.

[0092] The second type of data indicates that the actual value of the data is a continuous or discrete value that fluctuates up and down within a certain range centered around a certain value; for example, the vibration level of the elevator car when it moves up and down in the hoistway under normal conditions.

[0093] The third type of data indicates that the actual value of the data is a changing continuous or discrete value, and its actual value can be represented by a mathematical formula; for example: the moving speed of the elevator car, the speed command for opening and closing the door, etc.

[0094] The fourth type of data indicates that the actual value of the data presents a certain statistical law and can be described by statistical means; for example: the time interval between when a certain elevator component is put into use and the first occurrence of a failure presents a specific distribution law (such as a Gaussian distribution or other distribution laws).

[0095] The fifth type of data indicates other situations where the data does not conform to the first, second, third, and fourth types.

[0096] After the provider completes the collection of elevator data, it is necessary to classify the collected elevator data. For classification, two methods can be adopted:

[0097] Method 1: First, determine the change characteristics of the data according to the physical attributes represented by all possible data contents of the data, and then classify it into the corresponding type according to the change characteristics of the data; in this way, the provider can directly classify the elevator data according to the data content corresponding to the elevator data to obtain the classification result. However, this method may lead to unreasonable classification because the elevator data with the same data content may present different characteristics under different data requirements.

[0098] Method 2: Conduct data analysis on each data content of the collected data respectively, discover the characteristics possessed by the data, and then classify it into the corresponding type according to the characteristics possessed by the data; the characteristics possessed by the data refer to the unique properties that each data type has and are different from other types of data. For example, the actual value of the data in the first type is a limited number of possible values determined by the physical attributes of the data content of the data. The same is true for other categories of data. This method directly analyzes the actual data, and the classification result is accurate but the processing load is relatively large due to data analysis.

[0099] After completing the classification of the collected elevator data, the elevator data of each category can be integrated and processed according to the characteristics of each category of data. The purpose is to compress the elevator data, thereby reducing the amount of data that actually needs to be sent from the provider to the requester, and then reducing the channel resources required for data transmission and reducing the communication cost by reducing the amount of data transmitted. The following gives the integration algorithms for the elevator data of each category:

[0100] The integration algorithm corresponding to the first category of data is: record the change time when the data changes from the previous value to the current value and the current value of the change; this can complete retaining all the intrinsic value that the elevator data of this category can reflect;

[0101] The integration algorithm corresponding to the second category of data is: record the central value and the mathematical parameters used to describe the fluctuating situation; such as variance, mean square deviation, standard deviation, etc., extreme values and their occurrence positions, etc.; the reason is that the value of the second category of data lies in its central value (usually the mean or median, mathematical expectation, etc.) and the fluctuating situation.

[0102] The integration algorithm corresponding to the third category of data is: determine the mathematical formula reflecting its change by means of curve fitting or physical meaning analysis, and record the mathematical formula and related parameter values; because the value of the third category of data lies in the magnitude of the data and its change law.

[0103] The integration algorithm corresponding to the fourth category of data is: find out the statistical law of the data and record the law and related parameter values; for example, when the presented law is a Gaussian distribution (i.e., a normal distribution), only the parameter values of the distribution need to be recorded, that is, the normal distribution and its parameters: mathematical expectation μ, variance σ2. Because the value of the fourth category of data lies in the relative magnitude of the data, that is, the law of the position distribution presented due to the relative magnitude of each data.

[0104] The integration algorithm corresponding to the fifth category of data is: do not process it and directly record the data. Because there is basically no effective integration algorithm that can significantly reduce the amount of integrated data while retaining all the data value.

[0105] After completing the integration and processing of the collected elevator data, step S6 is executed. The provider should package the integrated data and the integration algorithm in accordance with the format or protocol previously agreed upon with the requester, obtain the data actually to be transmitted to the requester, and send it to the requester.

[0106] Preferably, the elevator data request and response method further includes:

[0107] Step S7, the requester extracts the integrated data and the integration algorithm;

[0108] Step S8: Determine the meanings of the respective parts in the integrated data according to the integration algorithm;

[0109] Step S9: Analyze the inherent data value according to the meanings of the respective parts in the integrated data, and determine whether the data value meets the requirements of the data request of the requester (that is, obtain the expected data analysis value points from the integrated data); if so, end; otherwise, perform inverse integration on the integrated data (reverse application of the integration algorithm) to obtain the data before integration, so as to meet the requirements of the data request of the requester by analyzing the elevator data before integration.

[0110] The present invention has been described in detail through specific embodiments and examples above, but these do not constitute a limitation to the present invention. Without departing from the principle of the present invention, those skilled in the art can also make many deformations and improvements, which should also be regarded as the protection scope of the present invention.

Claims

1. An elevator data request and response method, characterized in that Including: Step S1, the requester encapsulates the data content and data requirements into a data request according to a preset encapsulation format; Step S2, the requester sends the data request to the elevator; Step S3, the elevator parses the data request according to the preset encapsulation format to obtain the data content and data requirements; Step S4, the elevator collects data according to the data content and data requirements; Step S5, the elevator integrates and processes the collected data to obtain integrated data; Step S6, the elevator packages the integrated data and the integration algorithm to obtain the packaged data actually to be transmitted to the requester, and sends it to the requester.

2. The elevator data request and response method according to claim 1, wherein The data in step S4 is collected by the first method; The first method is: identify the categories included in the data requirements, and collect data separately according to different categories; The categories include one or more of the following preset categories: Category 1, representing the specifications of data sampling and data format; Category 2, representing the influencing factors that only depend on the elevator; Category 3, representing the influencing factors that depend on the elevator user and / or usage environment.

3. The elevator data request and response method according to claim 2, wherein For Category 2, step S4 collects data according to the following steps: Step A1, determine the first elevator state corresponding to when Category 2 is satisfied; Step A2, compare the state difference between the first elevator state and the second elevator state where the elevator is currently located; Step A3, determine the transition process from the second elevator state to the first elevator state according to the state difference; Step A4, determine the control instruction required to control the elevator to transition from the second elevator state to the first elevator state according to the transition process; Step A5, use the control instruction to control the elevator so that the elevator finally transitions to the first elevator state; Step A6, collect data.

4. The elevator data request and response method according to claim 2, wherein For Category 3, step 4 evaluates whether the current elevator meets the Category 3 part in the data requirements. If it meets, data is collected immediately. If it does not meet, data is collected after the current elevator meets the Category 3 part in the data requirements, or another elevator that meets the Category 3 part in the data requirements is selected as the target for data collection.

5. The elevator data request and response method according to claim 2, characterized in that, When the data requirements include Category 1, Category 2, and Category 3 at the same time, first wait for the current elevator to meet the Category 3 in the data requirements, then control the current elevator to meet Category 2, and finally collect data according to the data requirements corresponding to Category 1.

6. The elevator data request and response method according to claim 2, wherein, Step S4 determines whether there is associated historical data stored locally in the elevator according to the data content and data requirements. If there is, directly extract the associated historical data. If not, collect data according to the first method; and when there are multiple associated historical data stored, maintain the historical data according to the data requirements and data content.

7. The elevator data request and response method according to claim 6, wherein For two historical data with the same data requirements except for the time range, if the time periods of these two historical data are adjacent or partially overlapping, the two historical data are merged, the merged time period is determined, and the merged time period is used as the time period in the data requirements of the merged data.

8. The elevator data request and response method according to claim 6, wherein For two pieces of historical data with the same data requirements except for different sampling precisions and overlapping corresponding time periods, delete the low-precision data corresponding to the overlapping period, and at the same time adjust the time period of the low-precision data so that the adjusted time period corresponds to the remaining low-precision data.

9. The elevator data request and response method according to claim 6, wherein, The above steps maintain the historical data in at least one of the following ways: Method 1: Save the data collected in the most recent n times, where n is a preset positive integer greater than 1; Method 2: Save the data collected in the most recent n times, where n is a preset positive integer greater than 1, and ensure that the total size of the historical data does not exceed the first threshold; Method 3: Save the historical data whose requested frequency is higher than the threshold; Method 4: Determine the priority according to the physical attribute bits of the data represented by the data, and save the historical data with a priority higher than the threshold; Method 5: Select the historical data to be saved according to the ratio of the occupied space of the data volume before integration to the data volume after integration.

10. The elevator data request and response method according to claim 1, characterized in that, The method for the step S5 to perform integration processing on the collected data is: first classify the data according to the preset type, and then select the corresponding integration algorithm according to the type of the data to perform integration processing on the data; The preset types include: the first type of data, indicating that the actual value of the data is only a finite number of discrete values; the second type of data, indicating that the actual value of the data is a continuous or discrete value that fluctuates up and down within a certain range centered on a certain value; the third type of data, indicating that the actual value of the data is a changing continuous or discrete value, and its actual value can be represented by a mathematical formula; the fourth type of data, indicating that the actual value of the data presents a certain statistical law and can be described by statistical means; the fifth type of data, indicating other situations where the data does not conform to the first, second, third, and fourth types.

11. The elevator data request and response method according to claim 10, wherein, Classify the data according to the preset type in any of the following ways: Method 1: First, determine the change characteristics of the data according to the physical attributes represented by all possible data contents of the data, and then classify the data into the corresponding type according to the change characteristics of the data; Method 2: Perform data analysis on the data of each data content collected, discover the characteristics possessed by the data, and then classify the data into the corresponding type according to the characteristics possessed by the data; the characteristics possessed by the data refer to the unique properties of each data type that are different from the data of other types.

12. The elevator data request and response method according to claim 10, characterized in that, The integration algorithm corresponding to the first type of data is: record the change moment when the data changes from the previous value to the current value and the current value of the change; the integration algorithm corresponding to the second type of data is: record the central value and the mathematical parameters used to describe the fluctuation situation; the integration algorithm corresponding to the third type of data is: determine the mathematical formula reflecting its change by means of curve fitting or physical meaning analysis, and record the mathematical formula and related parameter values; the integration algorithm corresponding to the fourth type of data is: find the statistical law of the data and record the law and related parameter values; the integration algorithm corresponding to the fifth type of data is: do not process and directly record the data.

13. The elevator data request and response method according to claim 1, wherein The elevator data request and response method further includes: Step S7, the requester extracts the integrated data and the integration algorithm; Step S8, determine the meaning of each part in the integrated data according to the integration algorithm; Step S9, analyze the internal data value according to the meaning of each part in the integrated data, and determine whether the data value meets the requirements of the data request of the requester; if so, end, otherwise perform inverse integration on the integrated data to obtain the data before integration.