Electromagnetic field intensity monitoring method and system

Abstract

The invention relates to an electromagnetic field intensity monitoring method and system. The method comprises the following steps: acquiring first field intensity data corresponding to a plurality of pre-inspection directions at a preset position in a to-be-inspected area; determining a monitoring interference type of the to-be-inspected area according to direction difference characteristics among the first field intensity data; and under the condition that the monitoring interference category represents that the to-be-inspected area is a strong interference area, determining a target inspection direction based on the first field intensity data in the plurality of pre-inspection directions, determining an inspection route corresponding to the to-be-inspected area according to the target inspection direction, and obtaining second field intensity data of the to-be-inspected area according to the inspection route and a preset inspection interval. By adopting the method, the monitoring accuracy can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of electromagnetic field strength monitoring, and in particular to an electromagnetic field strength monitoring method and system. Background Art

[0002] With the advent of 5G (5 th The rapid development of fifth-generation (5G) technology has significantly increased the number and density of 5G base stations. The rapid development and popularization of 5G technology has brought tremendous convenience to society. However, the high-density deployment of 5G base stations and the complex electromagnetic environment have also brought new challenges to electromagnetic radiation safety.

[0003] In related technologies, a method for monitoring the electromagnetic field strength in an area to be inspected is to use a drone equipped with a field strength monitoring instrument to obtain electromagnetic field strength data corresponding to multiple inspection points in the area to be inspected along a preset route.

[0004] However, the accuracy of the above-mentioned electromagnetic field strength monitoring method is low. Summary of the Invention

[0005] Based on this, it is necessary to provide an electromagnetic field strength monitoring method and system that can improve accuracy in response to the above technical problems.

[0006] In a first aspect, the present application provides a method for monitoring electromagnetic field strength, comprising:

[0007] Acquire first field strength data corresponding to a plurality of pre-inspection directions at a preset position in the area to be inspected;

[0008] Determine the monitoring interference category of the area to be inspected based on the directional difference characteristics between the first field strength data;

[0009] When the monitoring interference category characterizes that the area to be inspected is a strong interference area, the target inspection direction is determined based on the first field strength data in multiple pre-inspection directions, the inspection route corresponding to the area to be inspected is determined according to the target inspection direction, and the second field strength data of the area to be inspected is obtained according to the inspection route and the preset inspection interval.

[0010] In one embodiment, obtaining first field strength data corresponding to a plurality of pre-inspection directions at a preset position in the area to be inspected includes:

[0011] Take photos of the area to be inspected at a preset location to obtain an image of the area;

[0012] Analyze the number of obstacles based on the regional image and determine the number of targets corresponding to the area to be inspected;

[0013] Determine a target direction interval corresponding to the target quantity, wherein the target quantity and the target direction interval are negatively correlated;

[0014] The first field strength data are obtained at intervals in the target direction.

[0015] In one embodiment, determining the target direction interval corresponding to the number of targets includes:

[0016] When the target number is greater than or equal to a first number threshold, determining the first direction interval as the target direction interval;

[0017] When the number of targets is less than the first number threshold and the number of targets is greater than or equal to the second number threshold, determining the second direction interval as the target direction interval;

[0018] When the number of targets is less than a second number threshold, determining the third direction interval as the target direction interval;

[0019] The first direction interval is smaller than the second direction interval, and the second direction interval is smaller than the third direction interval.

[0020] In one embodiment, the first field strength data includes field intensity and electromagnetic radiation frequency;

[0021] According to the directional difference characteristics between the first field strength data, the monitoring interference category of the area to be inspected is determined, including:

[0022] According to the absolute variance corresponding to each field intensity and the absolute variance corresponding to each electromagnetic radiation frequency, the discrete data of the field intensity information is obtained;

[0023] According to the absolute variance corresponding to each signal noise, signal noise discrete data is obtained, and each signal noise corresponds to each first field strength data;

[0024] According to the discrete data of field intensity information and the discrete data of signal noise, the monitoring interference characterization data of the area to be inspected is obtained;

[0025] The monitoring interference category is determined based on the monitoring interference characterization data and the preset monitoring interference characterization threshold.

[0026] In one embodiment, obtaining monitoring interference characterization data of the area to be inspected based on the discrete data of field intensity information and the discrete data of signal noise includes:

[0027] Obtaining field strength direction difference data according to the field strength information discrete data and a preset field strength information discrete threshold;

[0028] Obtaining signal-noise difference data according to the signal-noise discrete data and a preset signal-noise discrete threshold;

[0029] The monitoring interference characterization data is obtained by performing weighted summation processing on the field intensity direction difference data and the signal-noise difference data.

[0030] In one embodiment, determining the monitoring interference category based on the monitoring interference characterization data and a preset monitoring interference characterization threshold includes:

[0031] When the monitoring interference characterization data is greater than the monitoring interference characterization threshold, the strong interference area is determined as a monitoring interference category;

[0032] When the monitoring interference characterization data is less than or equal to the monitoring interference characterization threshold, the weak interference area is determined as a monitoring interference category.

[0033] In one embodiment, determining a target inspection direction based on first field strength data in multiple pre-inspection directions includes:

[0034] For each pre-check direction, obtaining a change fluctuation value of the first field intensity data corresponding to the pre-check direction in the time domain dimension;

[0035] Determine the pre-check direction corresponding to the change fluctuation value with the smallest median value among the change fluctuation values ​​as the candidate direction;

[0036] Determine the target inspection direction based on the candidate directions.

[0037] In one embodiment, the method further comprises:

[0038] The inspection interval is determined according to the change fluctuation value corresponding to the candidate direction, wherein the inspection interval is negatively correlated with the change fluctuation value corresponding to the candidate direction.

[0039] In one embodiment, the first field strength data includes the field strength within a preset time period and the electromagnetic radiation frequency within a preset time period;

[0040] Obtaining the change fluctuation value of the first field strength data corresponding to the pre-check direction in the time domain dimension, including:

[0041] Determining discrete field strength time domain data according to a plurality of field strength peaks in the field strength within a preset time period;

[0042] Determining frequency time domain discrete data based on a plurality of frequency peaks in the electromagnetic radiation frequency within a preset time period;

[0043] Determining noise time-domain discrete data according to a plurality of noise peaks in the signal noise within a preset time length, wherein each signal noise corresponds to each first field intensity data;

[0044] A weighted summation process is performed on the field intensity time domain discrete data, the frequency time domain discrete data and the noise time domain discrete data to obtain a change fluctuation value corresponding to the pre-detection direction.

[0045] In a second aspect, the present application also provides an electromagnetic field strength monitoring system, comprising: a patrol device and a processor, wherein the patrol device is equipped with a field strength monitoring instrument, wherein:

[0046] The processor is configured to:

[0047] Acquire first field strength data corresponding to a plurality of pre-inspection directions respectively at a preset position of the inspection device in the area to be inspected;

[0048] Determine the monitoring interference category of the area to be inspected based on the directional difference characteristics between the first field strength data. If the monitoring interference category indicates that the area to be inspected is a strong interference area, determine the target inspection direction based on the first field strength data in multiple pre-inspection directions, and determine the inspection route corresponding to the area to be inspected according to the target inspection direction.

[0049] The inspection equipment is controlled to obtain the second field strength data of the area to be inspected according to the inspection route and the preset inspection interval.

[0050] The above-mentioned electromagnetic field strength monitoring method and system obtains first field strength data corresponding to multiple pre-inspection directions at preset positions in the area to be inspected; determines the monitoring interference category of the area to be inspected based on the directional difference characteristics between each first field strength data; when the monitoring interference category characterizes that the area to be inspected is a strong interference area, determines the target inspection direction based on the first field strength data in multiple pre-inspection directions, determines the inspection route corresponding to the area to be inspected according to the target inspection direction, and obtains second field strength data of the area to be inspected according to the inspection route and the preset inspection interval. In this way, in the case of high-density deployment of 5G base stations, due to the complex environment, the field strength of the electromagnetic radiation field is highly dynamic and uncertain. This embodiment first obtains the first field strength data for multiple pre-inspection directions to analyze the field strength differences between different pre-inspection directions to determine whether the interference of the electromagnetic radiation field in the area to be inspected is strong interference. When the area to be inspected is a strong interference area, the direction with less interference is selected as the target inspection direction based on the first field strength data in multiple pre-inspection directions, so as to plan the inspection route, so that the second field strength data obtained along the inspection route can accurately reflect the distribution of the electromagnetic radiation field in the area to be inspected, thereby improving the accuracy of monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1A diagram showing an application environment of an electromagnetic field intensity monitoring method according to an embodiment;

[0053] Figure 2 1 is a flow chart of an electromagnetic field intensity monitoring method according to an embodiment;

[0054] Figure 3 1 is a flow chart of steps for obtaining first field strength data in one embodiment;

[0055] Figure 4 A flowchart of the steps of determining a monitoring interference category in one embodiment is shown;

[0056] Figure 5 A schematic flow chart of the steps for obtaining monitoring interference characterization data in one embodiment;

[0057] Figure 6 A schematic diagram of a flow chart of steps for determining a target inspection direction in one embodiment;

[0058] Figure 7 is a structural block diagram of an electromagnetic field intensity monitoring device in one embodiment;

[0059] Figure 8 is a diagram of the internal structure of a computer device in one embodiment;

[0060] Figure 9 FIG. 4 is a diagram showing the internal structure of a computer device in another embodiment. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0062] It should be noted that the terms "first", "second", etc. used in this application may be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "including" and "having" used in this application and any variations thereof are intended to cover non-exclusive inclusions. The term "plurality" used in this application refers to two or more. The term "and / or" used in this application refers to one of the solutions or any combination of multiple solutions.

[0063] The electromagnetic field intensity monitoring method provided in the embodiment of the present application can be applied to Figure 1In the electromagnetic field strength monitoring system shown. The electromagnetic field strength monitoring system includes a processor 102 and a patrol device 104, and the processor 102 is communicatively connected to the patrol device 104. The patrol device 104 is equipped with a field strength monitoring instrument for obtaining field strength data of the electromagnetic radiation field. The patrol device 104 can be implemented based on a drone or a low-altitude aircraft. Exemplarily, the processor 102 can be a processor in a terminal device, and the processor 102 is connected to the communication module in the patrol device 104 through the communication module of the computer device; another exemplary embodiment, the processor 102 can also be a processor in a server, and the processor 102 is connected to the communication module in the patrol device 104 through the communication module of the server. In other application environments of the present application, the processor 102 is integrated with the patrol device 104. Exemplarily, the processor 102 can serve as a central processor in the patrol device 104, or it can be a dedicated processor in the patrol device 104 specifically used to perform electromagnetic field strength monitoring. Exemplarily, the processor 102 can be a field programmable processor.

[0064] In an exemplary embodiment, Figure 2 As shown, a method for monitoring electromagnetic field strength is provided, which is applied to Figure 1 The electromagnetic field intensity monitoring system in FIG. 1 is taken as an example to illustrate the method, which includes the following steps 202 to 206. Among them:

[0065] Step 202: acquiring first field strength data corresponding to a plurality of pre-inspection directions at a preset position in the area to be inspected.

[0066] The area where the electromagnetic radiation of the base station needs to be monitored is divided into multiple smaller inspection areas, and the electromagnetic field strength of the base station is monitored in each inspection area to obtain field strength data.

[0067] The preset position is any position within the area to be inspected, used to allow the inspection equipment to enter the area to be inspected and assess the area. For example, the preset position may be a position on the boundary of the area to be inspected, or another example, the preset position may be the center of the area to be inspected. For example, the preset position may be a position that is 10% of the maximum length of the travel area after the inspection equipment enters the boundary of the area to be inspected.

[0068] The first field strength data refers to the field strength data obtained by the field strength monitoring instrument at the preset position. The pre-inspection direction refers to the direction of the inspection device relative to the base station. For example, the inspection device is oriented toward the first boundary of the area as the starting direction, and the inspection device is rotated at intervals of the preset direction until the inspection device is oriented toward the second boundary of the area, wherein the first boundary and the second boundary are two opposite boundaries in the area to be inspected. For example, the preset direction interval is 30°, that is, the inspection device obtains the field strength data corresponding to the direction every 30° rotation at the preset position as the first field strength data corresponding to the direction. For example, the inspection device remains stationary and the field strength monitoring instrument is rotatable.

[0069] Step 204 : determining the monitoring interference category of the area to be inspected based on the directional difference characteristics between the first field strength data.

[0070] The difference characteristics between the pre-inspection directions are determined based on the first field strength data to determine the monitoring interference category of the area to be inspected.

[0071] Since the field strength of the electromagnetic radiation field is directional in space, there are differences in the field strength information in different directions. In particular, when 5G base stations are deployed at a high density, the monitoring of the electromagnetic field strength will be affected by obstructions in the base station and the terrain. It may also be affected by the reflection, refraction, and scattering of electromagnetic waves in the base station space, resulting in differences in various directions. This embodiment uses the first field strength data corresponding to multiple pre-inspection directions to analyze the directional difference characteristics between each pre-inspection direction to determine the distribution of the electromagnetic radiation field in the area to be inspected, so as to formulate inspection routes and strategies suitable for the area to be inspected.

[0072] The monitoring interference categories are divided into strong interference areas and weak interference areas. If the difference between the first field strength data in each pre-inspection direction is large, the area to be inspected is considered a strong interference area. If the difference between the first field strength data in each pre-inspection direction is small, the area to be inspected is considered a weak interference area.

[0073] Step 206, when the monitoring interference category indicates that the area to be inspected is a strong interference area, the target inspection direction is determined based on the first field strength data in multiple pre-inspection directions, the inspection route corresponding to the area to be inspected is determined according to the target inspection direction, and the second field strength data of the area to be inspected is obtained according to the inspection route and the preset inspection interval.

[0074] Among them, when the area to be inspected is a strong interference area, it means that there may be multiple interference sources in the area to be inspected, which causes the electromagnetic radiation field intensity in the area to fluctuate violently, and the electromagnetic radiation field intensity direction difference characteristics are obvious. At this time, based on the first field intensity data in multiple pre-inspection directions, the direction with less interference is selected as the target inspection direction, and the inspection route is formulated along this direction, which can more accurately obtain the true characteristics of the electromagnetic field strength in the area to be inspected.

[0075] The second field strength data refers to the field strength data obtained by the inspection equipment during inspections along the inspection route. The terms "first" and "second" in the first and second field strength data are used to distinguish field strength data obtained by the inspection equipment based on different requirements and do not limit the data type or content.

[0076] In one possible implementation, when the monitored interference category indicates that the area to be inspected is a weak interference area, an inspection route is determined along a preset inspection direction, and second field strength data for the area to be inspected is acquired according to the inspection route and the preset inspection interval. For example, the preset inspection direction is toward the next area to be inspected.

[0077] In the above-mentioned electromagnetic field strength monitoring method, first field strength data corresponding to multiple pre-inspection directions are obtained at preset positions in the area to be inspected; the monitoring interference category of the area to be inspected is determined based on the directional difference characteristics between each first field strength data; when the monitoring interference category characterizes that the area to be inspected is a strong interference area, the target inspection direction is determined based on the first field strength data in multiple pre-inspection directions, the inspection route corresponding to the area to be inspected is determined according to the target inspection direction, and the second field strength data of the area to be inspected is obtained according to the inspection route and the preset inspection interval. In this way, in the case of high-density deployment of 5G base stations, due to the complex environment, the field strength of the electromagnetic radiation field is highly dynamic and uncertain. This embodiment first obtains the first field strength data for multiple pre-inspection directions to analyze the field strength differences between different pre-inspection directions to determine whether the interference of the electromagnetic radiation field in the area to be inspected is strong interference. When the area to be inspected is a strong interference area, the direction with less interference is selected as the target inspection direction based on the first field strength data in multiple pre-inspection directions, so as to plan the inspection route, so that the second field strength data obtained along the inspection route can accurately reflect the distribution of the electromagnetic radiation field in the area to be inspected, thereby improving the accuracy of monitoring.

[0078] In the embodiments of this application, the implementation process and beneficial effects of the provided electromagnetic field strength monitoring method are illustrated using a 5G base station scenario as an example. It is understandable that the electromagnetic field strength monitoring method provided in this embodiment can be applied not only to the electromagnetic field strength monitoring scenario of a 5G base station, but also to the field strength monitoring scenario of other electromagnetic field radiation sources, such as high-voltage transformer stations and converter stations.

[0079] In an exemplary embodiment, based on Figure 2 The embodiment shown in the figure provides an electromagnetic field strength monitoring method which involves a process of obtaining first field strength data corresponding to a plurality of pre-inspection directions at a preset position in the area to be inspected. Figure 3 , the process includes steps 302 to 308, wherein:

[0080] Step 302: Take a picture of the area to be inspected at a preset position to obtain an image of the area.

[0081] For example, the inspection device is equipped with an image acquisition unit. At a preset position, the inspection device acquires an area image corresponding to the area to be inspected through the image acquisition unit.

[0082] Step 304 : Analyze the number of obstacles based on the regional image to determine the number of targets corresponding to the area to be inspected.

[0083] The obstacles refer to objects in the area to be detected that may affect the propagation of electromagnetic waves. For example, the obstacles include houses, towers, and mountains.

[0084] For example, the process of analyzing the number of obstacles based on regional images can be carried out through pre-training or using an open source image processing model that can identify predetermined targets. There is no limitation on the architecture of the image processing model, such as a neural network model. Of course, other forms can also be used, which will not be repeated here.

[0085] Step 306: Determine the target direction interval corresponding to the target quantity, wherein the target quantity and the target direction interval are negatively correlated.

[0086] Among them, the more obstacles there are in the area to be detected, the greater the possibility and degree of interference with the electromagnetic radiation field of the base station. Therefore, in this embodiment, the more targets there are and the smaller the target direction interval is, the more first field strength data that can be used for subsequent analysis. At the same time, the smaller the interval between multiple pre-inspection directions used to determine the target patrol direction, the more reliable the determined target patrol direction.

[0087] In one possible embodiment, the process of determining the target direction interval corresponding to the target number includes: when the target number is greater than or equal to a first number threshold, determining the first direction interval as the target direction interval; when the target number is less than the first number threshold and the target number is greater than or equal to a second number threshold, determining the second direction interval as the target direction interval; when the target number is less than the second number threshold, determining the third direction interval as the target direction interval; wherein the first direction interval is smaller than the second direction interval, and the second direction interval is smaller than the third direction interval.

[0088] The first quantity threshold and the second quantity threshold are determined based on a preset quantity. For example, the first quantity threshold is 1.5 times the preset quantity, and the second quantity threshold is 1.25 times the preset quantity.

[0089] Exemplarily, the preset number is determined by using regional images corresponding to several different types of sample areas as sample images, calculating the number of obstacles in each sample image, and taking the average of the number of obstacles in each sample image as the preset number. The sample areas are areas corresponding to possible base station locations, and the size of the sample areas is consistent or similar to the size of the area to be inspected, thereby improving the reliability of the preset number.

[0090] Exemplarily, the first direction interval is 30°, the second direction interval is 90°, and the third direction interval is 90°.

[0091] Step 308: Acquire first field strength data according to target direction intervals.

[0092] Wherein, each pre-inspection direction is determined according to the target direction interval, and corresponding first field strength data is obtained in each pre-inspection direction.

[0093] In one possible embodiment, when the inspection equipment takes pictures at a preset position, the height from the ground is relatively high, so that the acquired area image can accurately reflect the actual situation in the area to be inspected and avoid being blocked by obstacles; after acquiring the area image, the inspection equipment descends to a certain height and acquires each first field strength data at intervals in the target direction to monitor the near-ground field strength.

[0094] In one possible implementation, the system rotates multiple times at target direction intervals, acquiring multiple field intensity data sets in each pre-check direction. For example, the system rotates multiple times at target direction intervals to acquire a field intensity data set in the first pre-check direction, then to the second pre-check direction, then to the last pre-check direction, then rotates in the opposite direction to acquire a field intensity data set in each pre-check direction. This means that the first field intensity data set corresponding to each pre-check direction includes field intensity data sets acquired at multiple time intervals.

[0095] In a possible implementation, each time the inspection device rotates to a pre-inspection direction, it stays in the pre-inspection direction for a preset time. That is, the first field strength data is the field strength data obtained by the inspection device monitoring the pre-inspection direction at a preset position for a preset time.

[0096] In the electromagnetic field strength monitoring method provided in the above embodiment, a photograph of the area to be inspected is taken at a preset location to obtain an area image; an obstacle count analysis is performed based on the area image to determine the number of targets corresponding to the area to be inspected; target direction intervals corresponding to the target number are determined, wherein the target number and target direction intervals are negatively correlated; and first field strength data are obtained according to the target direction intervals. In this way, the intervals between each pre-inspection direction are negatively correlated with the number of obstacles in the area to be inspected, so that the greater the number of obstacles in the area to be inspected, the smaller the intervals between first field strength data are obtained. The directional difference characteristics obtained based on these first field strength data can more comprehensively reflect the field strength distribution in the area to be inspected.

[0097] In an exemplary implementation, based on Figure 2 The embodiment shown in the figure provides an electromagnetic field intensity monitoring method that involves determining the monitoring interference category of the area to be inspected based on the directional difference characteristics between each first field intensity data. In this embodiment, the first field intensity data includes field intensity, electromagnetic radiation frequency and signal noise. Please refer to Figure 4 The process of determining the monitoring interference category of the area to be inspected based on the directional difference characteristics between the first field strength data includes:

[0098] Step 402: Obtain discrete data of field intensity information according to the absolute variance corresponding to each field intensity and the absolute variance corresponding to each electromagnetic radiation frequency.

[0099] Exemplarily, the absolute variance corresponding to the field intensity in each pre-detection direction is used as the discrete quantity of the field intensity, and the absolute variance corresponding to the electromagnetic radiation frequency in each pre-detection direction is used as the discrete quantity of the electromagnetic radiation frequency; the mean of the discrete quantity of the field intensity and the discrete quantity of the electromagnetic radiation frequency is used as the discrete data of the field intensity information.

[0100] Step 404: Obtain signal noise discrete data according to the absolute variance corresponding to each signal noise.

[0101] Wherein, each signal noise corresponds to each first field strength data. Exemplarily, the absolute variance of the signal noise in each pre-detection direction is used as the signal noise discrete data.

[0102] Step 406 : Obtain monitoring interference characterization data of the area to be inspected based on the field intensity information discrete data and the signal noise discrete data.

[0103] Among them, the discrete data of the field strength information represents the discrete differences in the field strength information in different pre-detection directions. The larger the discrete data of the field strength information, the stronger the discrete difference. The discrete data of the signal noise represents the discrete differences in the interference of the detection information in different pre-detection directions. The larger the discrete amount of the signal noise, the stronger the discrete difference.

[0104] In one possible implementation, please refer to Figure 5 The process of obtaining monitoring interference characterization data of the area to be inspected based on the discrete data of field intensity information and the discrete data of signal noise includes steps 502 to 506, wherein:

[0105] Step 502: Obtain field intensity direction difference data according to the field intensity information discrete data and a preset field intensity information discrete threshold.

[0106] Exemplarily, the ratio of the discrete field strength information data to a preset discrete field strength information threshold is determined as the field strength directional difference data. The discrete field strength information threshold is a pre-set threshold. Directional difference features determined after performing a predetermined pre-check in a number of open areas are obtained in advance. The mean discrete field strength information value corresponding to each area is calculated, and the discrete field strength information threshold is set as the product of the mean discrete field strength information value and a field strength discrete offset coefficient. The field strength discrete offset coefficient is selected within the interval [1.4, 1.8].

[0107] Step 504 : Obtain signal-noise difference data according to the signal-noise discrete data and a preset signal-noise discrete threshold.

[0108] Exemplarily, the ratio of the signal-noise discrete data to a preset signal-noise discrete threshold is determined as the signal-noise difference data. The signal-noise discrete threshold is a pre-set threshold. Directional difference features are determined by performing a predetermined pre-inspection action in a number of open areas, and the mean signal-noise discrete value corresponding to each area is calculated. The signal-noise discrete threshold is set to the product of the mean signal-noise discrete value and a signal-noise discrete coefficient, where the signal-noise discrete coefficient is selected within the interval [1.5, 2].

[0109] Step 506 : Perform weighted summation processing based on the field intensity direction difference data and the signal-to-noise difference data to obtain monitoring interference characterization data.

[0110] The weight of the field intensity direction difference data is greater than the weight of the signal-noise difference data. For example, the weight of the field intensity direction difference data is 0.55, and the weight of the signal-noise difference data is 0.45.

[0111] Step 408 : Determine the monitoring interference category based on the monitoring interference characterization data and a preset monitoring interference characterization threshold.

[0112] In one possible implementation, the process of determining the monitoring interference category based on the monitoring interference characterization data and a preset monitoring interference characterization threshold includes: when the monitoring interference characterization data is greater than the monitoring interference characterization threshold, determining the strong interference area as the monitoring interference category; when the monitoring interference characterization data is less than or equal to the monitoring interference characterization threshold, determining the weak interference area as the monitoring interference category.

[0113] In actual situations, electromagnetic radiation propagation is directional in space. In particular, the number of terminals interacting with the base station in a single area is different, and the obstructions and terrain in the area are different. This causes electromagnetic waves to reflect, refract, and scatter differently in different directions within the area, which interferes with the detection signal, resulting in differences in detection results in different directions and affecting detection accuracy. Considering that the field intensity of the electromagnetic radiation field has dynamic changing characteristics and that signal noise directly affects the accuracy and stability of the field intensity information, this embodiment uses discrete data of field intensity information and discrete data of signal noise to respectively reflect the distribution characteristics of field intensity fluctuations and noise interference in the area to be inspected. Monitoring interference characterization data is calculated from two dimensions to facilitate the subsequent division of monitoring interference categories in the area, improve the accuracy and reliability of electromagnetic radiation monitoring, and effectively ensure the safety of the electromagnetic radiation field.

[0114] In an exemplary embodiment, based on Figure 2 The embodiment shown in the figure provides an electromagnetic field intensity monitoring method which involves a process of determining a target inspection direction based on first field intensity data in multiple pre-inspection directions. Figure 6 , the process includes steps 602 to 606, wherein:

[0115] Step 602: For each pre-check direction, obtain a change fluctuation value of first field intensity data corresponding to the pre-check direction in the time domain dimension.

[0116] In one possible implementation, the first field strength data includes field strength within a preset time period and electromagnetic radiation frequency within a preset time period; correspondingly, the process of obtaining a change fluctuation value of the first field strength data corresponding to the pre-inspection direction in the time domain dimension includes:

[0117] Step A1: determining discrete field intensity time domain data according to a plurality of field intensity peaks in a preset time period.

[0118] Exemplarily, a field intensity variation curve is constructed with time as the horizontal axis and field intensity as the vertical axis, and the absolute variance of each peak in the curve is determined as field intensity time-domain discrete data.

[0119] Step A2: determining frequency time-domain discrete data according to a plurality of frequency peaks in the electromagnetic radiation frequency within a preset time period.

[0120] Exemplarily, with time as the horizontal axis and the electromagnetic radiation frequency as the vertical axis, a frequency variation curve is constructed, and the absolute variance of each peak in the curve is determined as frequency-time domain discrete data.

[0121] Step A3: determining noise time-domain discrete data according to a plurality of noise peaks in the signal noise within a preset time period, wherein each signal noise corresponds to each first field intensity data.

[0122] Exemplarily, with time as the horizontal axis and signal noise as the vertical axis, a directional signal-noise variation curve is constructed, and the absolute variance of each peak in the curve is determined as noise time-domain discrete data.

[0123] Step A4: performing weighted summation processing on the field intensity time-domain discrete data, the frequency time-domain discrete data, and the noise time-domain discrete data to obtain a change fluctuation value corresponding to the pre-detection direction.

[0124] Exemplarily, the weight corresponding to the field intensity time-domain discrete data and the weight corresponding to the frequency time-domain discrete data are both smaller than the weight corresponding to the noise time-domain discrete data. For example, the weight of the field intensity time-domain discrete data is 0.3, the weight of the frequency time-domain discrete data is 0.3, and the weight of the noise time-domain discrete data is 0.4.

[0125] Exemplarily, the manner of constructing the field intensity variation curve, the frequency variation curve, and the signal-to-noise variation curve in steps A1 to A3 is not limited, and MATLAB or other simulation tools may be used.

[0126] Step 604: Determine the pre-check direction corresponding to the change fluctuation value with the smallest median value among the change fluctuation values ​​as a candidate direction.

[0127] Step 606: Determine the target inspection direction based on the candidate directions.

[0128] Among them, the pre-inspection direction with the smallest change fluctuation value can be considered as the direction with less interference, and it is determined as the candidate direction. Based on the candidate direction, the target inspection direction is determined for monitoring, which can more accurately obtain the true characteristics of the field strength.

[0129] In a possible implementation, the candidate direction is directly used as the target inspection direction.

[0130] In a possible implementation, a target inspection direction is determined based on the candidate directions and the position of the next area to be inspected.

[0131] In an exemplary embodiment, based on Figure 6 The embodiment shown in the figure further provides an electromagnetic field intensity monitoring method, which further includes: determining a patrol interval based on the change fluctuation value corresponding to the candidate direction, wherein the patrol interval is negatively correlated with the change fluctuation value corresponding to the candidate direction.

[0132] The fluctuation value corresponding to the candidate direction is the minimum fluctuation value among the fluctuation values ​​corresponding to the pre-check directions. The inspection interval is determined based on the minimum fluctuation value among the pre-check directions. When the minimum fluctuation value is large, a relatively small inspection interval is set, meaning a relatively large number of inspection points are used. When the minimum fluctuation value is small, a relatively large inspection interval is set, meaning a relatively small number of inspection points are used. In other words, there is a positive correlation between the number of inspection points and the fluctuation value corresponding to the candidate direction.

[0133] Exemplarily, if the change fluctuation value corresponding to the candidate direction is greater than the first fluctuation threshold, the first interval is determined as the patrol interval; if the change fluctuation value corresponding to the candidate direction is less than or equal to the first fluctuation threshold and greater than the second fluctuation threshold, the second interval is determined as the patrol interval; if the change fluctuation value corresponding to the candidate direction is less than or equal to the second fluctuation threshold, the third interval is determined as the patrol interval.

[0134] Wherein, the first fluctuation threshold is greater than the second fluctuation threshold. Exemplarily, the first fluctuation threshold and the second fluctuation threshold are determined based on a preset fluctuation value. Exemplarily, the first fluctuation threshold is 1.35 times the preset fluctuation value, and the second fluctuation threshold is 1.15 times the preset fluctuation value. Exemplarily, the method for determining the preset fluctuation value includes: pre-acquiring directional difference characteristics determined after performing predetermined pre-inspection actions in a number of open areas, determining the change fluctuation value in each direction, solving the mean of each change fluctuation value, setting the preset fluctuation value to be the product of the mean of the change fluctuation value and the precision coefficient, and the precision coefficient is selected within the interval [1.3, 1.6].

[0135] Exemplarily, the first interval is smaller than the second interval, and the second interval is smaller than the third interval. Correspondingly, the number of inspection points corresponding to the first interval is greater than the number of inspection points corresponding to the second interval, and the number of inspection points corresponding to the second interval is greater than the number of inspection points corresponding to the third interval.

[0136] For example, the number of inspection points corresponding to the first interval is the value rounded to 1.6 times the preset number of inspection points, the number of inspection points corresponding to the second interval is the value rounded to 1.45 times the preset number of inspection points, and the number of inspection points corresponding to the third interval is the value rounded to 1.3 times the preset number of inspection points.

[0137] The number of preset inspection points is determined based on the maximum width of the area to be inspected. For example, a checkpoint is typically set at every baseline monitoring interval, which is between 30 and 80 meters. In practice, the baseline monitoring interval is set to 40, and the preset number is one-third of the ratio of the maximum width to the baseline monitoring interval, to ensure that the monitored data is representative of the entire area.

[0138] In this embodiment, after determining the target inspection direction, the inspection interval is adaptively adjusted according to the change fluctuation value corresponding to the candidate direction to obtain comprehensive field strength information as much as possible, thereby improving the accuracy, comprehensiveness and reliability of the second field strength data.

[0139] In an exemplary embodiment, the provided electromagnetic field strength monitoring method further includes determining whether the area to be inspected meets the standard based on the second field strength data of the area to be inspected. The method includes: obtaining the field strength and electromagnetic radiation frequency of each inspection point in the second field strength data; calculating the mean field strength and mean electromagnetic radiation frequency corresponding to each inspection point; if the mean field strength at the inspection point is within the standard field strength range and the mean electromagnetic radiation frequency is within the standard electromagnetic radiation frequency range, the inspection and early warning module determines that the field strength in the area meets the standard; if the mean field strength at the inspection point is not within the standard field strength range and / or the mean electromagnetic radiation frequency is not within the standard electromagnetic radiation frequency range, the inspection and early warning module determines that the field strength in the area does not meet the standard.

[0140] Among them, the standard field strength range and the standard electromagnetic radiation frequency range are predetermined by technical personnel in this field. For example, the electromagnetic radiation frequency range and field strength range of different areas under normal operation of the base station can be predetermined, and the average electromagnetic radiation frequency range and the average field strength range can be solved. The average electromagnetic radiation frequency range is set as the standard electromagnetic radiation frequency range, and the average field strength range is set as the standard field strength range.

[0141] In one possible embodiment, the provided electromagnetic field strength monitoring method further includes: if the inspection and warning module determines that the field strength in the area does not meet the standard, sending an early warning signal. In this embodiment, the early warning signal can be sent to the monitoring terminal to alert the monitoring personnel, which will not be repeated here.

[0142] In an exemplary embodiment, a method for monitoring electromagnetic field strength is provided, wherein the method is applied to Figure 1 The electromagnetic field intensity monitoring system in the embodiment is described as an example, including the following steps S1 to S2.

[0143] Step S1: Take a picture of the area to be inspected at a preset position to obtain an image of the area.

[0144] Step S2: Analyze the number of obstacles based on the area image to determine the number of targets corresponding to the area to be inspected.

[0145] Step S3: determining a target direction interval corresponding to the target quantity, wherein the target quantity and the target direction interval are in a negative correlation.

[0146] Optionally, when the target number is greater than or equal to a first number threshold, the first direction interval is determined as the target direction interval; when the target number is less than the first number threshold and the target number is greater than or equal to a second number threshold, the second direction interval is determined as the target direction interval; when the target number is less than the second number threshold, the third direction interval is determined as the target direction interval; wherein the first direction interval is smaller than the second direction interval, and the second direction interval is smaller than the third direction interval.

[0147] Step S4: acquiring first field strength data corresponding to each pre-detection direction according to the target direction interval. The first field strength data includes field strength and electromagnetic radiation frequency.

[0148] Step S5: Obtaining discrete data of field intensity information according to the absolute variance corresponding to each field intensity and the absolute variance corresponding to each electromagnetic radiation frequency.

[0149] Step S6: Obtain signal noise discrete data according to the absolute variance corresponding to each signal noise, wherein each signal noise corresponds to each first field intensity data.

[0150] Step S7: obtaining monitoring interference characterization data of the area to be inspected based on the field intensity information discrete data and the signal noise discrete data.

[0151] Optionally, field strength direction difference data is obtained based on the field strength information discrete data and a preset field strength information discrete threshold; signal-noise difference data is obtained based on the signal-noise discrete data and a preset signal-noise discrete threshold; and monitoring interference characterization data is obtained by performing weighted summation processing on the field strength direction difference data and the signal-noise difference data.

[0152] Step S8: When the monitoring interference characterization data is greater than the monitoring interference characterization threshold, the strong interference area is determined as a monitoring interference category.

[0153] Step S9: When the monitoring interference characterization data is less than or equal to the monitoring interference characterization threshold, the weak interference area is determined as a monitoring interference category.

[0154] Step S10, when the monitoring interference category indicates that the area to be inspected is a strong interference area, for each pre-inspection direction, obtain the change fluctuation value of the first field strength data corresponding to the pre-inspection direction in the time domain dimension; determine the pre-inspection direction corresponding to the change fluctuation value with the smallest median value among the change fluctuation values ​​as the candidate direction; and determine the target inspection direction based on the candidate direction.

[0155] Optionally, the first field strength data includes the field strength within a preset time length and the electromagnetic radiation frequency within a preset time length; the process of obtaining the change fluctuation value of the first field strength data corresponding to the pre-inspection direction in the time domain dimension includes: determining the field strength time domain discrete data based on multiple field strength peaks in the field strength within the preset time length; determining the frequency time domain discrete data based on multiple frequency peaks in the electromagnetic radiation frequency within the preset time length; determining the noise time domain discrete data based on multiple noise peaks in the signal noise within the preset time length, wherein each signal noise corresponds to each first field strength data; performing weighted summation processing on the field strength time domain discrete data, the frequency time domain discrete data and the noise time domain discrete data to obtain the change fluctuation value corresponding to the pre-inspection direction.

[0156] Step S11 : determining a patrol interval according to the change fluctuation value corresponding to the candidate direction, wherein the patrol interval is negatively correlated with the change fluctuation value corresponding to the candidate direction.

[0157] Step S12: determining an inspection route corresponding to the area to be inspected according to the target inspection direction, and acquiring second field strength data of the area to be inspected according to the inspection route and inspection interval.

[0158] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily performed in sequence in the order indicated by the arrows. Unless clearly stated herein, the execution of these steps is not strictly limited in order, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of the steps or stages in other steps or other steps. It is understandable that the various steps in different embodiments can be freely combined as needed, and the various non-contradictory schemes formed by the combination all fall within the scope of protection of this application.

[0159] It should be understood that the term "based on" as used herein is used to describe one or more factors that influence a determination, and does not exclude other factors that may influence the determination. For example, the phrase "determine A based on B" means that the determination of A may be based entirely or at least partially on factor B. In other words, B is a factor that influences the determination of A, but does not exclude the determination of A being based on C as well.

[0160] Based on the same inventive concept, the present application also provides an electromagnetic field strength monitoring device for implementing the aforementioned electromagnetic field strength monitoring method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more of the following embodiments of the electromagnetic field strength monitoring device can be found in the above-mentioned limitations of the electromagnetic field strength monitoring method and will not be further elaborated here.

[0161] In an exemplary embodiment, Figure 7 As shown, an electromagnetic field intensity monitoring device is provided, including: a pre-inspection data acquisition module 702, an interference category determination module 704 and a patrol execution module 706, wherein:

[0162] A pre-inspection data acquisition module 702 is configured to acquire first field strength data corresponding to a plurality of pre-inspection directions at a preset position in the area to be inspected;

[0163] An interference category determination module 704 is configured to determine a monitoring interference category of the area to be inspected based on directional difference characteristics between the first field strength data;

[0164] The inspection execution module 706 is used to determine the target inspection direction based on the first field strength data in the multiple pre-inspection directions when the monitoring interference category characterizes that the area to be inspected is a strong interference area, determine the inspection route corresponding to the area to be inspected according to the target inspection direction, and obtain the second field strength data of the area to be inspected according to the inspection route and the preset inspection interval.

[0165] In an exemplary embodiment, the pre-inspection data acquisition module 702 is used to take a picture of the area to be inspected at the preset position to obtain an area image; perform obstacle quantity analysis based on the area image to determine the number of targets corresponding to the area to be inspected; determine the target direction interval corresponding to the target number, wherein the target number and the target direction interval are negatively correlated; and obtain each of the first field strength data according to the target direction interval.

[0166] In an exemplary embodiment, the pre-inspection data acquisition module 702 is used to determine the first direction interval as the target direction interval when the target number is greater than or equal to the first number threshold; determine the second direction interval as the target direction interval when the target number is less than the first number threshold and the target number is greater than or equal to the second number threshold; determine the third direction interval as the target direction interval when the target number is less than the second number threshold; wherein the first direction interval is smaller than the second direction interval, and the second direction interval is smaller than the third direction interval.

[0167] In an exemplary embodiment, the first field strength data includes field strength intensity and electromagnetic radiation frequency; the interference category determination module 704 is used to obtain field strength information discrete data based on the absolute variance corresponding to each field strength intensity and the absolute variance corresponding to each electromagnetic radiation frequency; obtain signal noise discrete data based on the absolute variance corresponding to each signal noise, and each signal noise corresponds to each first field strength data respectively; obtain monitoring interference characterization data of the area to be inspected based on the field strength information discrete data and the signal noise discrete data; determine the monitoring interference category based on the monitoring interference characterization data and a preset monitoring interference characterization threshold.

[0168] In an exemplary embodiment, the interference category determination module 704 is used to obtain field strength direction difference data based on the field strength information discrete data and a preset field strength information discrete threshold; obtain signal-noise difference data based on the signal-noise discrete data and a preset signal-noise discrete threshold; and perform weighted summation processing on the field strength direction difference data and the signal-noise difference data to obtain the monitoring interference characterization data.

[0169] In an exemplary embodiment, the inspection execution module 706 is used to determine the strong interference area as the monitoring interference category when the monitoring interference characterization data is greater than the monitoring interference characterization threshold; and to determine the weak interference area as the monitoring interference category when the monitoring interference characterization data is less than or equal to the monitoring interference characterization threshold.

[0170] In an exemplary embodiment, the interference category determination module 704 is used to obtain, for each pre-inspection direction, a change fluctuation value of the first field strength data corresponding to the pre-inspection direction in the time domain dimension; determine the pre-inspection direction corresponding to the change fluctuation value with the smallest median value among the change fluctuation values ​​as a candidate direction; and determine the target inspection direction based on the candidate direction.

[0171] In an exemplary embodiment, the inspection execution module 706 is configured to determine the inspection interval according to the change fluctuation value corresponding to the candidate direction, wherein the inspection interval is negatively correlated with the change fluctuation value corresponding to the candidate direction.

[0172] In an exemplary embodiment, the first field strength data includes the field strength intensity within a preset time length and the electromagnetic radiation frequency within a preset time length; the inspection execution module 706 is used to determine the field strength time domain discrete data based on the multiple field strength peaks in the field strength within the preset time length; determine the frequency time domain discrete data based on the multiple frequency peaks in the electromagnetic radiation frequency within the preset time length; determine the noise time domain discrete data based on the multiple noise peaks in the signal noise within the preset time length, wherein each of the signal noises corresponds to each of the first field strength data respectively; weighted summation processing is performed on the field strength time domain discrete data, the frequency time domain discrete data and the noise time domain discrete data to obtain the change fluctuation value corresponding to the pre-inspection direction.

[0173] Each module in the above-mentioned electromagnetic field intensity monitoring device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of the processor of the computer device in hardware form, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0174] In an exemplary embodiment, Figure 1 As shown, an electromagnetic field strength monitoring system is provided, including a patrol device and a processor, wherein the patrol device is equipped with a field strength monitoring instrument, wherein the processor is configured to: obtain first field strength data corresponding to multiple pre-inspection directions at a preset position in the area to be inspected by the patrol device; determine the monitoring interference category of the area to be inspected according to the directional difference characteristics between each of the first field strength data; when the monitoring interference category characterizes that the area to be inspected is a strong interference area, determine the target patrol direction based on the first field strength data in the multiple pre-inspection directions, and determine the patrol route corresponding to the area to be inspected according to the target patrol direction; control the patrol device to obtain second field strength data of the area to be inspected according to the patrol route and the preset patrol interval.

[0175] In an exemplary embodiment, the inspection device is equipped with an image acquisition module; the processor is configured to: take a picture of the area to be inspected at the preset position by the inspection device to obtain an area image, analyze the number of obstacles based on the area image, and determine the number of targets corresponding to the area to be inspected; determine the target direction interval corresponding to the target number, wherein the target number and the target direction interval are negatively correlated; and obtain each of the first field strength data according to the target direction interval.

[0176] In an exemplary embodiment, the processor is configured to: determine the first direction interval as the target direction interval when the target number is greater than or equal to the first number threshold; determine the second direction interval as the target direction interval when the target number is less than the first number threshold and the target number is greater than or equal to the second number threshold; determine the third direction interval as the target direction interval when the target number is less than the second number threshold; wherein the first direction interval is smaller than the second direction interval, and the second direction interval is smaller than the third direction interval.

[0177] In an exemplary embodiment, the first field strength data includes field strength intensity and electromagnetic radiation frequency; the processor is configured to: obtain field strength information discrete data based on the absolute variance corresponding to each field strength intensity and the absolute variance corresponding to each electromagnetic radiation frequency; obtain signal noise discrete data based on the absolute variance corresponding to each signal noise, and each signal noise corresponds to each first field strength data respectively; obtain monitoring interference characterization data of the area to be inspected based on the field strength information discrete data and the signal noise discrete data; determine the monitoring interference category based on the monitoring interference characterization data and a preset monitoring interference characterization threshold.

[0178] In an exemplary embodiment, the processor is configured to: obtain field strength direction difference data based on the field strength information discrete data and a preset field strength information discrete threshold; obtain signal-noise difference data based on the signal-noise discrete data and a preset signal-noise discrete threshold; and perform weighted summation processing on the field strength direction difference data and the signal-noise difference data to obtain the monitoring interference characterization data.

[0179] In an exemplary embodiment, the processor is configured to: determine the strong interference area as the monitoring interference category when the monitoring interference characterization data is greater than the monitoring interference characterization threshold; and determine the weak interference area as the monitoring interference category when the monitoring interference characterization data is less than or equal to the monitoring interference characterization threshold.

[0180] In an exemplary embodiment, the processor is configured to: for each pre-inspection direction, obtain the change fluctuation value of the first field strength data corresponding to the pre-inspection direction in the time domain dimension; determine the pre-inspection direction corresponding to the change fluctuation value with the smallest median value among the change fluctuation values ​​as a candidate direction; and determine the target inspection direction based on the candidate direction.

[0181] In an exemplary embodiment, the processor is configured to determine the patrol interval according to the change fluctuation value corresponding to the candidate direction, wherein the patrol interval is negatively correlated with the change fluctuation value corresponding to the candidate direction.

[0182] In an exemplary embodiment, the first field strength data includes the field strength intensity within a preset time length and the electromagnetic radiation frequency within a preset time length; the processor is configured to: determine the field strength time domain discrete data based on the multiple field strength peaks in the field strength intensity within the preset time length; determine the frequency time domain discrete data based on the multiple frequency peaks in the electromagnetic radiation frequency within the preset time length; determine the noise time domain discrete data based on the multiple noise peaks in the signal noise within the preset time length, wherein each of the signal noises corresponds to each of the first field strength data respectively; perform weighted summation processing on the field strength time domain discrete data, the frequency time domain discrete data and the noise time domain discrete data to obtain the change fluctuation value corresponding to the pre-inspection direction.

[0183] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 8 As shown. The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, memory and input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data required for performing electromagnetic field strength monitoring. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, an electromagnetic field strength monitoring method is implemented.

[0184] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 9As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless means. The wireless means can be implemented via Wi-Fi, a mobile cellular network, near-field communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for monitoring electromagnetic field strength. The display unit of the computer device is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0185] Those skilled in the art will understand that Figure 8 Or the structure shown in 9 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0186] In one embodiment, an inspection device is also provided, including a field strength monitoring instrument, an image acquisition unit, a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0187] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0188] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0189] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0190] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0191] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0192] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for monitoring electromagnetic field strength, characterized in that: The method comprises: Acquire first field strength data corresponding to a plurality of pre-inspection directions at a preset position in the area to be inspected; determining a monitoring interference category of the area to be inspected based on directional difference characteristics between the first field strength data; When the monitoring interference category characterizes that the area to be inspected is a strong interference area, the target inspection direction is determined based on the first field strength data in the multiple pre-inspection directions, the inspection route corresponding to the area to be inspected is determined according to the target inspection direction, and the second field strength data of the area to be inspected is obtained according to the inspection route and the preset inspection interval.

2. The method according to claim 1, characterized in that The obtaining of first field strength data corresponding to a plurality of pre-inspection directions at a preset position in the area to be inspected includes: Taking a picture of the area to be inspected at the preset position to obtain an image of the area; Analyze the number of obstacles based on the area image to determine the number of targets corresponding to the area to be inspected; Determining a target direction interval corresponding to the target quantity, wherein the target quantity and the target direction interval are negatively correlated; The first field strength data are acquired according to the target direction intervals.

3. The method according to claim 2, characterized in that The determining of the target direction interval corresponding to the number of targets includes: When the target quantity is greater than or equal to a first quantity threshold, determining the first direction interval as the target direction interval; When the target number is less than the first number threshold and the target number is greater than or equal to the second number threshold, determining the second direction interval as the target direction interval; When the target quantity is less than the second quantity threshold, determining the third direction interval as the target direction interval; The first direction interval is smaller than the second direction interval, and the second direction interval is smaller than the third direction interval.

4. The method according to claim 1, wherein The first field strength data includes field intensity and electromagnetic radiation frequency; The determining, based on the directional difference characteristics between the first field strength data, the monitoring interference category of the area to be inspected includes: Obtaining discrete data of field intensity information according to the absolute variance corresponding to each of the field intensities and the absolute variance corresponding to each of the electromagnetic radiation frequencies; Obtaining signal noise discrete data according to the absolute variance corresponding to each signal noise, wherein each signal noise corresponds to each first field strength data; Obtaining monitoring interference characterization data of the area to be inspected according to the field intensity information discrete data and the signal noise discrete data; The monitoring interference category is determined according to the monitoring interference characterization data and a preset monitoring interference characterization threshold.

5. The method according to claim 4, characterized in that The obtaining, according to the field intensity information discrete data and the signal noise discrete data, monitoring interference characterization data of the area to be inspected includes: Obtaining field intensity direction difference data according to the field intensity information discrete data and a preset field intensity information discrete threshold; Obtaining signal-noise difference data according to the signal-noise discrete data and a preset signal-noise discrete threshold; The monitoring interference characterization data is obtained by performing weighted summation processing on the field intensity direction difference data and the signal-to-noise difference data.

6. The method according to claim 4, characterized in that The determining the monitoring interference category according to the monitoring interference characterization data and a preset monitoring interference characterization threshold includes: In a case where the monitoring interference characterization data is greater than the monitoring interference characterization threshold, determining the strong interference area as the monitoring interference category; When the monitoring interference characterization data is less than or equal to the monitoring interference characterization threshold, the weak interference area is determined as the monitoring interference category.

7. The method according to claim 1, characterized in that The determining of the target inspection direction based on the first field strength data in the multiple pre-inspection directions includes: For each pre-check direction, obtaining a change fluctuation value of the first field intensity data corresponding to the pre-check direction in the time domain dimension; Determine the pre-check direction corresponding to the change fluctuation value with the smallest median value among the change fluctuation values ​​as the candidate direction; The target inspection direction is determined based on the candidate directions.

8. The method according to claim 7, characterized in that The method further comprises: The inspection interval is determined according to the change fluctuation value corresponding to the candidate direction, wherein the inspection interval is negatively correlated with the change fluctuation value corresponding to the candidate direction.

9. The method according to claim 7, characterized in that The first field strength data includes the field intensity within a preset time period and the electromagnetic radiation frequency within a preset time period; The obtaining of a change fluctuation value of the first field intensity data corresponding to the pre-check direction in the time domain dimension includes: Determining field intensity time-domain discrete data according to a plurality of field intensity peaks in the field intensity within the preset time length; Determining frequency time-domain discrete data according to a plurality of frequency peaks in the electromagnetic radiation frequency within the preset time length; Determining noise time-domain discrete data according to a plurality of noise peaks in the signal noise within a preset time length, wherein each of the signal noises corresponds to each of the first field intensity data; A weighted summation process is performed on the field intensity time-domain discrete data, the frequency time-domain discrete data, and the noise time-domain discrete data to obtain a change fluctuation value corresponding to the pre-detection direction.

10. An electromagnetic field intensity monitoring system, characterized in that: The system includes a patrol device and a processor, wherein the patrol device is equipped with a field strength monitoring instrument, wherein: The processor is configured to: Acquiring first field strength data corresponding to a plurality of pre-inspection directions respectively at a preset position of the inspection device in the area to be inspected; Determining a monitoring interference category of the area to be inspected based on directional difference characteristics between each of the first field strength data; if the monitoring interference category indicates that the area to be inspected is a strong interference area, determining a target inspection direction based on the first field strength data in the multiple pre-inspection directions, and determining an inspection route corresponding to the area to be inspected according to the target inspection direction; The inspection device is controlled to obtain second field strength data of the area to be inspected according to the inspection route and a preset inspection interval.

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