Dynamic adaptive data monitoring method

Abstract

The application discloses a kind of dynamic self-adapting data monitoring methods, comprising: receiving the corresponding multiple detection data that multiple detection sensors arranged in different positions of building periodically upload;After receiving the detection data, the environmental parameter information around multiple detection sensors is obtained;Match the preset determination value of the data detected by the detection sensor under the current environmental parameter information;When at least one of multiple detection data exceeds the preset determination value, send early warning information to the preset project personnel.The dynamic self-adapting data monitoring method provided by the application also considers the environmental factors of the area where the construction project is located when judging the risk of the data detected by the detection sensor, and dynamically adjusts the judgment strategy in real time according to the environmental factors.

Description

Technical Field

[0001] This invention belongs to the field of building inspection data processing technology, and specifically relates to a dynamic adaptive data monitoring method. Background Technology

[0002] Traditionally, construction projects require manual risk monitoring to ensure safety. However, with advancements in science and technology and increasing digitalization, risk monitoring in construction projects is gradually shifting towards automated monitoring using automated detection equipment and cloud platforms. This involves placing sensors at various locations within the building, such as vibration, tilt, or pressure sensors, to collect relevant data. This data is then uploaded to a cloud platform for automated processing and analysis to identify potential risks. This significantly reduces labor costs and provides more timely and effective risk identification.

[0003] The materials used in buildings exhibit varying properties such as vibration and hardness under different environments, resulting in different parameters detected by automated inspection equipment. However, existing digital monitoring methods rely on cloud platforms to directly process and analyze the data from these automated inspection devices. Consequently, the risk identification results based on this data by the cloud platform are not accurate enough. Summary of the Invention

[0004] This invention provides a dynamic adaptive data monitoring method to solve the aforementioned technical problems, specifically employing the following technical solution:

[0005] A dynamic adaptive data monitoring method includes the following steps:

[0006] It receives periodic uploads of multiple detection data from multiple detection sensors installed at different locations in the building;

[0007] After receiving the detection data, environmental parameter information around the multiple detection sensors is acquired;

[0008] Match the data detected by the detection sensor with a preset judgment value under the current environmental parameter information;

[0009] When at least one of the multiple detection data exceeds the preset judgment value, a warning message is sent to the preset project personnel.

[0010] Furthermore, the detection data uploaded by the detection sensor contains a unique identification code of the detection sensor;

[0011] The specific method for obtaining environmental parameters around the multiple detection sensors is as follows:

[0012] Extract the unique device code carried by one of the multiple detection data uploaded by the detection sensor;

[0013] The preset position information for the detection sensor is obtained based on the unique device code;

[0014] Based on the location information, the environmental parameter information of the area where the building is located at the current time is obtained from an external weather information system.

[0015] Furthermore, after obtaining the environmental parameter information, the dynamic adaptive data monitoring method further includes:

[0016] Based on the environmental parameter information, multiple corrected environmental parameter information corresponding to multiple detection sensors located at different locations within the building is obtained;

[0017] The specific method for matching the data monitored by the detection sensor with the environmental parameter information to the preset judgment value under the current environmental parameter information is as follows:

[0018] By matching multiple corrected environmental parameter information, the preset judgment value corresponding to the data monitored by multiple detection sensors under the corresponding corrected environmental parameter information is obtained;

[0019] When at least one of the multiple detection data exceeds its corresponding preset judgment value, a warning message is sent to the preset project personnel.

[0020] Furthermore, the specific method for obtaining multiple corrected environmental parameter information corresponding to multiple detection sensors based on environmental parameter information is as follows:

[0021] The environmental parameter information corresponding to the detection sensor is obtained by correcting the environmental parameter information based on the distance between the detection sensor and the edge of the building.

[0022] Furthermore, the multiple detection sensors are divided into multiple associated device groups, and each associated device group contains more than three detection sensors. The level of the warning information is comprehensively determined based on the range of the detection data exceeding the preset judgment value, the total number of exceeding values, and the number of exceeding values ​​in each group.

[0023] Furthermore, each of the associated device groups has a corresponding weight level, and the level of the warning information is comprehensively determined based on the exceeding range of the detection data that exceeds the preset judgment value, the total number of exceeding, the number of exceeding in groups, and the weight level.

[0024] Furthermore, after sending the warning information to the mobile devices of the project personnel, the system periodically receives the location information sent by the mobile devices of the project personnel within a preset time period, and compares the location information with the location of the building to determine whether the project personnel have reached the location of the building within the preset time period.

[0025] Furthermore, project personnel arrived at the building, verified the issues, and then uploaded a processing report.

[0026] Furthermore, when the warning information level reaches a preset level, the warning information is simultaneously sent to preset project personnel and management personnel.

[0027] Furthermore, the specific method for obtaining the environmental parameters around the detection sensor is as follows:

[0028] The environmental parameter information is obtained in real time from public environmental sensors installed at the edge of the building.

[0029] The advantage of this invention lies in the provision of a dynamic adaptive data monitoring method that, when assessing the risk of data detected by sensors, also considers environmental factors of the building project's location and dynamically adjusts the assessment strategy in real time based on these environmental factors. This significantly improves the accuracy of risk identification. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a schematic diagram of a dynamic adaptive data monitoring method according to the present invention. Detailed Implementation

[0032] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0033] like Figure 1This application illustrates a dynamic adaptive data monitoring method for real-time monitoring of building projects. It is understood that building data monitoring includes, but is not limited to, detecting vibration data using vibration sensors, tilt data using tilt sensors, and force data using pressure sensors. At least one of these sensors can be selected for data detection based on the specific needs of the building project. By placing multiple sensors at different locations within the building, the detection data is periodically transmitted to a cloud server via wired or wireless means. The cloud server then processes this detection data accordingly.

[0034] It is understood that the type of detection sensor can be selected and arranged according to the specific items to be detected, and this application does not impose any restrictions on it.

[0035] Specifically, the dynamic adaptive data monitoring method of this application includes the following steps: S1: Receiving multiple detection data periodically uploaded by multiple detection sensors installed at different locations on the building. S2: After receiving the detection data, acquiring environmental parameter information around the multiple detection sensors. S3: Matching the data detected by the detection sensors with a preset judgment value under the current environmental parameter information. S4: Sending a warning message to preset project personnel when at least one of the multiple detection data exceeds the preset judgment value. Through the above steps, the dynamic adaptive data monitoring method of this application, when judging the risk of the data detected by the detection sensors, also considers the environmental factors of the area where the building project is located, and dynamically adjusts the judgment strategy in real time according to the environmental factors.

[0036] The steps described above are explained in detail below.

[0037] For step S1: Receive the corresponding multiple detection data periodically uploaded by multiple detection sensors set at different locations in the building.

[0038] Understandably, building projects are generally large in scale and require multiple detection sensors to be installed in various locations on the building for data monitoring.

[0039] For step S2: After receiving the detection data, acquire environmental parameter information around multiple detection sensors.

[0040] Environmental parameters can include, but are not limited to, temperature and humidity information, and can be set according to actual needs.

[0041] It's understandable that environmental sensors, such as temperature or humidity sensors, could be integrated into each detection sensor to detect ambient conditions like temperature and humidity around that sensor. However, this approach requires a separate environmental sensor for each detection sensor, increasing the cost of the sensors and consequently raising the overall cost of the data monitoring solution.

[0042] As an optional implementation, a common environmental sensor can be installed on or near the building surface. The environmental parameter information obtained from this common environmental sensor can then be used as the environmental parameter information for each individual detection sensor. In this way, regardless of the number of detection sensors installed for the building project, only one common environmental sensor is needed to collect environmental information.

[0043] To further reduce data monitoring costs and eliminate the need for public environmental sensors, as an alternative implementation, the detection data uploaded by the sensors includes a unique identification code for each sensor. The specific method for obtaining environmental parameters around multiple sensors is as follows:

[0044] Extract the unique device code carried by one of the multiple detection data uploaded by the detection sensor.

[0045] The location information preset for the detection sensor is obtained based on the unique device code. Understandably, during the initial setup of the detection sensors, each sensor is configured, such as which building project it belongs to, the project's location, and so on. Thus, by extracting the unique device code from the detection data, it's possible to determine which detection sensor sent the data, and thereby obtain its corresponding location information.

[0046] The environmental parameter information for the area where the building is located at the current time is obtained from an external weather information system based on the location information. It is understood that an external weather information system is a system capable of obtaining environmental information at different times across the country in real time. This system can be a public website or a specific, more precise, and professional weather information provider; this invention does not impose any limitations on this.

[0047] In this way, environmental parameter information can be obtained in real time simply by observing the project's location, eliminating the need to install any environmental monitoring equipment at the construction site. This also avoids information errors caused by malfunctions in environmental monitoring equipment.

[0048] For step S3: Match the preset judgment value of the data detected by the detection sensor under the current environmental parameter information.

[0049] The fact that the data detected by the sensors are within a reasonable range indicates that the current state of the building project is relatively normal. Therefore, determining a scientifically sound preset threshold as the criterion for judging whether the monitoring data is abnormal is crucial. It is understandable that even if the building itself remains unchanged, the detection data from these sensors will vary depending on the environment, such as different temperatures and humidity levels. This is due to the influence of environmental factors on the building's materials. Therefore, it is inappropriate to use the same preset threshold as the basis for assessing the risk of the detection data from the sensors without considering the building's current environment.

[0050] In this application, to make the risk assessment of the detection data detected by the detection sensor more scientific and reasonable, a preset judgment value is matched with the current environmental parameter information, and then this preset judgment value is used as the criterion for judging whether the detection data is abnormal. Different preset judgment values ​​correspond to different environmental parameter information.

[0051] As a preferred embodiment, after obtaining the environmental parameter information, the dynamic adaptive data monitoring method further includes: obtaining multiple corrected environmental parameter information corresponding to multiple detection sensors located at different locations within the building based on the environmental parameter information.

[0052] Furthermore, the specific method for matching the data monitored by the detection sensors to the preset judgment value under the current environmental parameter information is as follows: Multiple preset judgment values ​​are obtained by matching the data monitored by multiple detection sensors to the corresponding preset environmental parameter information. When at least one of the multiple detection data exceeds its corresponding preset judgment value, a warning message is sent to the designated project personnel.

[0053] It's understandable that whether environmental parameters near a building are collected through public environmental sensors or matched with location information, the resulting environmental parameters are those of the environment outside the building. However, most of the sensors are located in different positions inside the building. Therefore, the environment near each sensor differs from the environment outside the building.

[0054] To address this issue, this application, after obtaining environmental parameter information, further calculates the actual environmental parameter information for each detection sensor, i.e., corrected environmental parameter information. This allows for the calculation of a corresponding corrected environmental parameter information for each detection sensor. Then, based on these corrected environmental parameter information, different preset judgment values ​​are matched. When determining whether the detection data detected by a particular detection sensor is abnormal, the detection data is compared with the preset judgment value corresponding to that sensor. This makes the comparison results more accurate.

[0055] As a preferred embodiment, the specific method for obtaining multiple corrected environmental parameter information corresponding to multiple detection sensors based on environmental parameter information is as follows: the environmental parameter information is corrected based on the distance of the detection sensor from the edge of the building to obtain the corrected environmental parameter information corresponding to the detection sensor.

[0056] It is understandable that the shallower the detection sensor is installed within a building, the closer its surrounding environment is to the external atmospheric environment. Conversely, the deeper the sensor is installed, the greater the difference between its surrounding environment and the external atmospheric environment. Therefore, the corrected environmental parameters of the detection sensor and the relationship between these environmental parameters are directly related to the depth at which the sensor is installed. Consequently, the corrected environmental parameters of the detection sensor can be calculated using both environmental parameters and distance information. Here, the distance between the detection sensor and the edge of the building refers to the closest distance between the sensor and the building's wall that meets the atmospheric environment.

[0057] It is understandable that the relationship between the corrected environmental parameters of the detection sensors and the environmental parameters is not only related to the depth of the sensor installation, but also to the structural characteristics of the building itself. For example, two detection sensors may be installed at the same distance within a building, but the wall structures of the building between the two sensors and the external environment may differ, resulting in different environments around the two sensors. Therefore, to further improve the accuracy of the calculated corrected environmental parameters, as another optional implementation method, a specific method for obtaining multiple corrected environmental parameters corresponding to multiple detection sensors based on the environmental parameters can also be as follows:

[0058] A 3D model is obtained by performing 3D modeling on the building.

[0059] Mark the position of each detection sensor in the 3D model.

[0060] The acquired environmental parameter information is used as the boundary parameters of the building's 3D model. Based on the boundary parameters and the position of the detection sensor in the 3D model, the corrected environmental parameter information corresponding to the detection sensor located inside the building is automatically calculated.

[0061] The above steps, through computer simulation, can directly simulate and calculate the corrected environmental parameters for each detection sensor based on the 3D model, the location of the detection sensor, and environmental parameter information.

[0062] For step S4: When at least one of the multiple detection data exceeds the preset judgment value, a warning message is sent to the preset project personnel.

[0063] In this application, multiple detection sensors are divided into multiple associated device groups, each containing three or more detection sensors. The warning information level is determined comprehensively based on the proportion of detection data exceeding a preset judgment value, the total number of exceeding values, and the number of exceeding values ​​in a group. Here, the proportion of exceeding values ​​refers to the percentage of detection data exceeding the preset judgment value, the total number of exceeding values ​​refers to the total number of detection sensors exceeding the preset judgment value, and the number of exceeding values ​​in a group refers to the total number of detection sensors belonging to the same associated device group that exceed the preset judgment value.

[0064] It's understandable that a building might have distinct, highly interconnected parts. In practice, the building can be divided according to these connections. Detection sensors placed within the same interconnected area can be grouped as a single interconnected device.

[0065] Understandably, assuming two sensors exhibit anomalies, their importance differs depending on whether they belong to the same associated device group or different groups. The presence of two anomalous sensors within the same associated device group indicates a significant associated risk in that area. Therefore, the risk of two anomalous sensors within a single associated device group is higher than the risk of one anomalous sensor in each of two different associated device groups. Consequently, when determining the level of warning information, considering both the total number of exceedances and the number of exceedances within a group as independent factors leads to more accurate results.

[0066] The following example illustrates the specific method used in this application to comprehensively determine the warning information level by considering the number of out-of-range detection data, the total number of out-of-range data points, and the number of out-of-range data points in groups. The out-of-range limit of 10% is scored as 2 points, the out-of-range limit of 20% as 4 points, the total number of out-of-range data points of 2 is 10 points, the total number of out-of-range data points of 3 is 20 points, the number of out-of-range data points in groups of 2 is 15 points, and the number of out-of-range data points in groups of 3 is 25 points. Assuming three detection sensors are out of range, all exceeding the limit by 5%, and two of them belong to the same associated device group, the total score would be 3*10 + 20 + 15 = 65. The risk level is then determined based on this 65-point score. It is understood that the specific numerical settings, calculation methods, and risk level classification methods can be adjusted as needed.

[0067] As another preferred implementation, each associated device group has a corresponding weight level, and the level of the warning information is determined by comprehensively considering the out-of-range of the detection data that exceeds the preset judgment value, the total number of out-of-range data, the number of out-of-range data in each group, and the weight level.

[0068] It is understandable that different groups of associated devices have different levels of importance. In this implementation, the weight of the associated device group is also considered as a calculation factor.

[0069] Suppose there are three associated device groups, with group A having a weight of 2, group B a weight of 3, and group C a weight of 4. Continuing the previous example, suppose three sensors are out of range, all exceeding the limit by 5%, and two of them belong to associated device group B. The total score would then be 3*10 + 20 + 2*15 = 80. Finally, the risk level is determined based on this 80-point score.

[0070] In a preferred implementation, after sending the warning information to the mobile devices of pre-selected project personnel, the system periodically receives location information from these devices within a preset time period. This location information is then compared with the building's location to determine if the project personnel have arrived at the building within the preset time. Upon arrival at the building, the project personnel verify the issue and upload a processing report. Preferably, when the warning information level reaches a preset level, the warning information is simultaneously sent to both pre-selected project personnel and management personnel.

[0071] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the above embodiments do not limit the present invention in any way, and all technical solutions obtained by equivalent substitution or equivalent transformation fall within the protection scope of the present invention.

Claims

1. A dynamic adaptive data monitoring method, characterized in that, Includes the following steps: It receives periodic uploads of multiple detection data from multiple detection sensors installed at different locations in the building; After receiving the detection data, environmental parameter information around the multiple detection sensors is acquired, including temperature information and humidity information. Match the data detected by the detection sensor with a preset judgment value under the current environmental parameter information; When at least one of the multiple detection data exceeds the preset judgment value, a warning message is sent to the preset project personnel; After obtaining the environmental parameter information, the dynamic adaptive data monitoring method further includes: Based on the environmental parameter information, multiple corrected environmental parameter information corresponding to multiple detection sensors located at different locations within the building is obtained; The specific method for matching the preset judgment value of the data detected by the detection sensor under the current environmental parameter information is as follows: By matching multiple corrected environmental parameter information, the preset judgment value corresponding to the data monitored by multiple detection sensors under the corresponding corrected environmental parameter information is obtained; When at least one of the multiple detection data exceeds its corresponding preset judgment value, a warning message is sent to the preset project personnel.

2. The dynamic adaptive data monitoring method according to claim 1, characterized in that, The detection data uploaded by the detection sensor contains the unique identification code of the detection sensor; The specific method for obtaining environmental parameters around the multiple detection sensors is as follows: Extract the unique identification code carried by one of the multiple detection data uploaded by the detection sensor; The preset position information for the detection sensor is obtained based on the unique identification code; Based on the location information, the environmental parameter information of the area where the building is located at the current time is obtained from an external weather information system.

3. The dynamic adaptive data monitoring method according to claim 1, characterized in that, The specific method for obtaining multiple corrected environmental parameter information corresponding to multiple detection sensors based on environmental parameter information is as follows: The environmental parameter information corresponding to the detection sensor is obtained by correcting the environmental parameter information based on the distance between the detection sensor and the edge of the building.

4. The dynamic adaptive data monitoring method according to claim 1, characterized in that, The multiple detection sensors are divided into multiple associated device groups, and each associated device group contains more than three detection sensors. The level of the warning information is determined by comprehensively considering the range of detection data exceeding the preset judgment value, the total number of exceeding data, and the number of exceeding data in each group.

5. The dynamic adaptive data monitoring method according to claim 4, characterized in that, Each of the associated device groups has a corresponding weight level. The level of the warning information is determined by comprehensively considering the exceedance range of the detection data that exceeds the preset judgment value, the total number of exceedances, the number of exceedances in each group, and the weight level.

6. The dynamic adaptive data monitoring method according to claim 1, characterized in that, After the warning information is sent to the mobile devices of the project personnel, the system periodically receives the location information sent by the mobile devices of the project personnel within a preset time period, and compares the location information with the location of the building to determine whether the project personnel have reached the location of the building within the preset time period.

7. The dynamic adaptive data monitoring method according to claim 6, characterized in that, After the project team arrives at the building, verifies the issues, and uploads a processing report, they will receive a report.

8. The dynamic adaptive data monitoring method according to claim 6, characterized in that, When the warning information level reaches the preset level, the warning information will be sent to the preset project personnel and management personnel at the same time.

9. The dynamic adaptive data monitoring method according to claim 1, characterized in that, The specific method for obtaining the environmental parameters around the detection sensor is as follows: obtain the environmental parameter information acquired in real time by a public environmental sensor installed at the edge of the building.

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