Methods, systems, storage media, and electronic devices for testing the accuracy of sensors

Abstract

This application provides a method, system, storage medium, and electronic device for testing sensor accuracy, relating to the field of sensor testing technology. The technical solution provided in this application achieves efficient testing of sensor accuracy by constructing a test scenario that matches the target deployment scenario and analyzing the sensor's monitoring area and monitoring method within that scenario. By acquiring scenario information and constructing the test scenario, consistency between the test environment and the actual application environment is ensured. By determining overlapping monitoring areas and analyzing the correlation between the monitoring methods of the target sensors, a test mechanism based on mutual verification between sensors is established. The accuracy test result is determined by analyzing the absolute accuracy difference between the target monitoring results. This test method based on overlapping monitoring areas avoids the problem of needing to test each sensor individually in traditional methods, significantly improving the testing efficiency of sensor networks.

Description

Technical Field

[0001] This application relates to the field of sensor testing technology, specifically to a sensor accuracy testing method, system, storage medium, and electronic device. Background Technology

[0002] As crucial devices for acquiring physical information, the accuracy of sensors directly impacts the precision of the acquired data. In practical applications, to ensure the reliability of monitoring data, the accuracy of sensors needs to be tested and calibrated regularly. Currently, the application of large-scale sensor networks is becoming increasingly widespread. These systems, composed of multiple sensors, are widely used in fields such as industrial monitoring, environmental monitoring, and intelligent transportation. In a sensor network, the accuracy of each sensor affects the overall monitoring performance of the network.

[0003] In related technologies, sensor accuracy testing methods often rely on dedicated testing equipment to test each sensor individually. This method requires a one-to-one connection between the sensor and the dedicated testing equipment, and the accuracy test must be completed under specific testing conditions. However, for sensor networks composed of a large number of sensors, this testing method is difficult to meet the actual needs of rapid and efficient testing of sensor networks. Summary of the Invention

[0004] This application provides a method, system, storage medium, and electronic device for testing the accuracy of a sensor, which can improve the testing efficiency of the sensor.

[0005] In a first aspect, this application provides a method for testing the accuracy of a sensor, the method comprising:

[0006] Acquire scene information from multiple sensors in a target delivery scenario, and construct a test scenario simulating the target delivery scenario based on the scene information;

[0007] Obtain the monitoring method and monitoring area of ​​each sensor in the test scenario, and determine the overlapping monitoring area in the monitoring area;

[0008] When the monitoring methods of multiple target sensors corresponding to the overlapping monitoring area are related, the target monitoring results of each target sensor in the overlapping monitoring area are obtained;

[0009] The accuracy test result of the target sensor is determined based on the absolute accuracy difference between the monitoring results of each target.

[0010] By adopting the above technical solution, a test scenario matching the target deployment scenario was built. Within this scenario, the sensor's monitoring area and monitoring method were analyzed, achieving efficient testing of sensor accuracy. First, by acquiring scenario information and building the test scenario, consistency between the test environment and the actual application environment was ensured, improving the reliability of the test results. Second, by determining the overlapping monitoring area and analyzing the correlation between the monitoring methods of the target sensors, a test mechanism based on mutual verification between sensors was established, enabling accuracy testing without the need for dedicated testing equipment. Finally, the accuracy test result was determined by analyzing the absolute accuracy difference between the target monitoring results, achieving an accurate assessment of the sensor's accuracy status. This test method based on overlapping monitoring areas avoids the problem of needing to test each sensor individually in traditional methods, significantly improving the testing efficiency of sensor networks.

[0011] Optionally, determining the accuracy test result of the target sensor based on the absolute accuracy difference between the target monitoring results includes:

[0012] Calculate the absolute accuracy difference between the monitoring results of each target;

[0013] If the absolute accuracy difference is less than a preset accuracy threshold, then the target sensor whose absolute accuracy difference is less than the preset accuracy threshold is identified as the first target sensor, and the accuracy test result corresponding to the first target sensor is marked as a test result that meets the accuracy requirements.

[0014] If the absolute accuracy difference is greater than or equal to a preset accuracy threshold, the target sensor whose absolute accuracy difference is greater than or equal to the preset accuracy threshold is determined as the second target sensor, and the standard monitoring result of the sensor detection device in the overlapping monitoring area is obtained. The second target sensor is calibrated according to the standard monitoring result and the target monitoring result corresponding to the second target sensor.

[0015] Optionally, if the absolute accuracy difference is greater than or equal to a preset accuracy threshold, then the target sensor whose absolute accuracy difference is greater than or equal to the preset accuracy threshold is determined as the second target sensor, and the standard monitoring result of the sensor detection device in the overlapping monitoring area is obtained. The second target sensor is then calibrated based on the standard monitoring result and the target monitoring result corresponding to the second target sensor, including:

[0016] If the absolute accuracy difference is greater than or equal to a preset accuracy threshold, then the target sensor whose absolute accuracy difference is greater than or equal to the preset accuracy threshold is determined as the second target sensor.

[0017] Several station locations are set within the overlapping monitoring area, and the test object is controlled to move along the station locations;

[0018] Acquire the location information of the sensor detection device at the station location, and organize the location information into standard monitoring results;

[0019] Based on the standard monitoring results and the target monitoring results corresponding to the second target sensor, the correction coefficients at each of the station locations are calculated.

[0020] The correction coefficients are arranged into a correction coefficient sequence according to the order of the station locations, and the second target sensor is linearly calibrated according to the correction coefficient sequence.

[0021] Optionally, after calculating the absolute accuracy difference between the monitoring results of each target, the method further includes:

[0022] Obtain the minimum accuracy requirements for the sensor;

[0023] Obtain the environmental characteristics of the test scenario, and determine the scenario type to which the environmental characteristics belong in a pre-established list of scenario types;

[0024] The preset accuracy threshold is obtained by multiplying the scene adjustment coefficient corresponding to the scene type with the minimum accuracy requirement. The scene adjustment coefficient is used to characterize the degree of attenuation of sensor accuracy in different scene types.

[0025] Optionally, the association relationship includes the same type association relationship and the similar type association relationship. When the monitoring methods of multiple target sensors corresponding to the overlapping monitoring area are associated, obtaining the target monitoring results of each target sensor in the overlapping monitoring area includes:

[0026] When the monitoring methods of multiple target sensors corresponding to the overlapping monitoring area have the same type of correlation, the first monitoring index corresponding to the same type of correlation is determined, and the target monitoring result of each target sensor corresponding to the first monitoring index in the overlapping monitoring area is obtained.

[0027] or,

[0028] When the monitoring methods of multiple target sensors corresponding to the overlapping monitoring area have similar type associations, the first monitoring result and the second monitoring result of each target sensor in the overlapping monitoring area are obtained. A second monitoring index is determined in the first monitoring result or the second monitoring result according to the similar type association, and the first monitoring result or the second monitoring result is converted into a target monitoring result according to the second monitoring index.

[0029] Optionally, after obtaining the monitoring method and monitoring area of ​​each sensor in the test scenario, and determining the overlapping monitoring area in the monitoring area, the method further includes:

[0030] The activation and deactivation conditions and change conditions of each sensor in the test scenario are obtained. The activation and deactivation conditions include conditions based on preset time scheduling, triggering conditions based on real-time environmental variables in the test scenario, and conditions based on linkage drive signals received from other devices.

[0031] Construct a test time axis and determine the real-time conditions corresponding to each discrete time point on the test time axis;

[0032] When the real-time conditions meet the opening / closing conditions or the changing conditions, the effective monitoring status of each sensor at different discrete time points is determined, and the dynamic monitoring area corresponding to each discrete time point is determined based on the effective monitoring status.

[0033] At the same discrete time point, geometric intersection is performed on at least two of the dynamic monitoring areas to obtain an instantaneously overlapping monitoring area;

[0034] The overlapping monitoring areas under the same time sequence are adjusted based on the instantaneous overlapping monitoring areas.

[0035] Optionally, after obtaining the monitoring method and monitoring area of ​​each sensor in the test scenario, and determining the overlapping monitoring area in the monitoring area, the method further includes:

[0036] Calculate the area ratio of the overlapping monitoring area to the corresponding monitoring area;

[0037] If the area ratio is less than a preset ratio, then the overlapping monitoring areas with an area ratio less than the preset ratio are removed.

[0038] Secondly, this application provides a sensor accuracy testing system, the system comprising:

[0039] The scene construction module is used to acquire scene information from multiple sensors in the target deployment scene, and to build a test scene simulating the target deployment scene based on the scene information;

[0040] The region determination module is used to obtain the monitoring method and monitoring area of ​​each sensor in the test scenario, and to determine the overlapping monitoring areas in the monitoring areas.

[0041] The testing module is used to acquire the target monitoring results of each target sensor in the overlapping monitoring area when there is a correlation between the monitoring methods of multiple target sensors corresponding to the overlapping monitoring area;

[0042] The result output module is used to determine the accuracy test result of the target sensor based on the absolute accuracy difference between the monitoring results of each target.

[0043] Thirdly, this application provides a computer storage medium storing a plurality of instructions adapted for loading by a processor and executing any of the methods described above.

[0044] Fourthly, this application provides an electronic device including a processor, a memory, and a transceiver, wherein the memory is used to store instructions, the transceiver is used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform any of the methods described above.

[0045] In summary, the beneficial effects of the technical solution of this application include:

[0046] By adopting the above technical solution, a test scenario matching the target deployment scenario was built. Within this scenario, the sensor's monitoring area and monitoring method were analyzed, achieving efficient testing of sensor accuracy. First, by acquiring scenario information and building the test scenario, consistency between the test environment and the actual application environment was ensured, improving the reliability of the test results. Second, by determining the overlapping monitoring area and analyzing the correlation between the monitoring methods of the target sensors, a test mechanism based on mutual verification between sensors was established, enabling accuracy testing without the need for dedicated testing equipment. Finally, the accuracy test result was determined by analyzing the absolute accuracy difference between the target monitoring results, achieving an accurate assessment of the sensor's accuracy status. This test method based on overlapping monitoring areas avoids the problem of needing to test each sensor individually in traditional methods, significantly improving the testing efficiency of sensor networks. Attached Figure Description

[0047] Figure 1 This is a schematic flowchart of a sensor accuracy testing method according to an embodiment of this application;

[0048] Figure 2 This is a schematic diagram of the structure of a sensor accuracy testing system according to an embodiment of this application;

[0049] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0050] Explanation of reference numerals in the attached drawings: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. Detailed Implementation

[0051] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0052] In the description of the embodiments of this application, words such as "illustrative," "for example," or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "illustrative," "for example," or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Rather, the use of words such as "illustrative," "for example," or "for example" is intended to present the relevant concepts in a specific manner.

[0053] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0054] Please see Figure 1 This is a flowchart illustrating a sensor accuracy testing method provided in an embodiment of this application. This method can be implemented using a computer program, a microcontroller, or run on a sensor accuracy testing system based on the von Neumann architecture. The computer program can be integrated into the application or run as a standalone utility application. The specific steps of the sensor accuracy testing method are described in detail below.

[0055] S101: Acquire scene information from multiple sensors in the target delivery scenario, and build a test scenario simulating the target delivery scenario based on the scene information;

[0056] The target deployment scenario refers to the actual working environment in which the sensor is applied; it can be understood as the actual location where the sensor is ultimately deployed and put into use. These scenarios typically have specific spatial layouts, environmental conditions, and business requirements, under which the sensor needs to perform its intended monitoring functions.

[0057] The test scenario refers to a simulated test environment built based on the characteristic information of the target deployment scenario. It can be understood as a standardized scenario constructed in a laboratory or under controlled conditions for testing sensor accuracy. This test scenario simulates various working conditions that sensors may encounter in practical applications by reproducing key elements of the target deployment scenario, such as spatial dimensions, environmental parameters, and obstacle distribution.

[0058] Acquire scene information from multiple sensors in the target delivery scenario, and build a test scenario simulating the target delivery scenario based on the scene information;

[0059] In practice, the first step is to acquire scene information from multiple sensors within the target deployment scenario. This scene information primarily includes spatial structural parameters, environmental parameters, signal transmission influencing factors, and sensor deployment information. Spatial structural parameters mainly reflect the physical characteristics and architectural features of the target deployment scenario; environmental parameters reflect the changing patterns and distribution characteristics of various environmental factors within the scenario; signal transmission influencing factors include various interference sources and transmission medium characteristics that may affect signal transmission quality; and sensor deployment information details the sensor installation methods and monitoring area divisions. The acquisition of this scene information requires specialized measurement equipment and standardized acquisition procedures to ensure the integrity and accuracy of the collected data.

[0060] It is important to note that the monitoring area of ​​the sensor in this application must have a clearly defined geometric boundary and be mathematically describable and calculable. It is not a vague coverage area with uneven signal strength, but rather a space that can be precisely defined as a fan-shaped, cone-shaped, or polygonal shape. For example, LiDAR sensors and vision sensors (cameras) are the most typical applications of this application. Two LiDARs are deployed in a scene, with their fan-shaped scanning areas partially overlapping. This overlapping area can be precisely calculated through geometric operations. A test object is placed within the overlapping area, and both LiDARs generate point cloud data about that object. By comparing the consistency of the two point cloud data in the world coordinate system, the "absolute accuracy difference" can be calculated, thus efficiently completing the accuracy test. Similarly, the detection area of ​​a vision sensor scanning radar is typically also a fan-shaped or cone-shaped space defined by the horizontal scanning angle, vertical scanning angle, and maximum detection distance, with a clearly defined geometric boundary.

[0061] After acquiring the scene information, a test scenario simulating the target deployment scenario needs to be constructed based on this information. The construction process for the test scenario first requires building a physical environment that matches the target deployment scenario in terms of spatial size and structure, ensuring consistency in spatial structural characteristics. Secondly, an environmental parameter control system needs to be configured, using professional environmental simulation equipment to precisely control various environmental parameters, ensuring their variation range and distribution characteristics are consistent with the target deployment scenario. Thirdly, the signal transmission environment needs to be simulated, by appropriately arranging various signal transmission-related facilities to ensure that the signal transmission characteristics in the test scenario match those of the target deployment scenario. Finally, according to the acquired sensor deployment information, the sensor installation locations and monitoring areas are rigorously reproduced in the test scenario to ensure consistency between the test conditions and the actual application environment.

[0062] S102: Obtain the monitoring method and monitoring area of ​​each sensor in the test scenario, and determine the overlapping monitoring area in the monitoring area;

[0063] The monitoring method refers to the specific detection technology used by the sensor when detecting a target. It can be understood as the technical principle and implementation method by which the sensor collects information from the monitored target. Each monitoring method has its specific physical characteristics and technical features, which determine the sensor's detection accuracy, detection range, and applicable conditions. For example, for indoor positioning sensors, the monitoring method could be based on Bluetooth signal strength positioning technology, calculating the target position by measuring the signal attenuation; or it could be based on infrared radiation detection positioning technology, determining the target's spatial location by receiving infrared signals. For temperature sensors, the monitoring method could be based on thermal imaging principles, obtaining temperature information by measuring the distribution of infrared energy radiated from the object's surface. The monitoring area refers to the sensor's effective detection range, that is, the spatial range within which the sensor can achieve its intended monitoring function. This range is affected by the sensor's installation location, monitoring method, and actual detection capabilities.

[0064] The overlapping monitoring area refers to the spatial range in a test scenario where the monitoring areas of two or more sensors intersect. It can be understood as the area where multiple sensors can simultaneously and effectively monitor the same spatial region. The monitoring data within these areas can come from different sensors, and there is a correlation between the monitoring methods of these sensors, making their monitoring results comparable or convertible.

[0065] In practical implementation, it is necessary to first obtain the monitoring methods and monitoring area information of each sensor in the test scenario. Since the monitoring methods employed by different sensors determine their signal acquisition and processing technical characteristics, it is necessary to clearly record and analyze the monitoring methods of each sensor, including its signal acquisition principle, data processing methods, and other technical features. Simultaneously, it is necessary to obtain the monitoring area information of each sensor. By analyzing parameters such as the sensor's installation location, detection angle, and effective operating distance, the actual monitoring coverage range of each sensor can be determined.

[0066] After obtaining the above information, it is necessary to determine the overlapping monitoring area in the test scenario. This process first requires spatially mapping the monitoring areas of each sensor in the test scenario to form a region coverage map. By analyzing the intersection of these region coverage maps, the spatial areas covered by multiple sensors simultaneously can be identified, i.e., the overlapping monitoring areas.

[0067] Based on the above embodiments, as an optional implementation, after step S102, the overlapping monitoring area needs to be adjusted through the following steps:

[0068] The activation and deactivation conditions and change conditions of each sensor in the test scenario are obtained. The activation and deactivation conditions include conditions based on preset time scheduling, triggering conditions based on real-time environmental variables in the test scenario, and conditions based on linkage drive signals received from other devices.

[0069] Construct a test time axis and determine the real-time conditions corresponding to each discrete time point on the test time axis;

[0070] When the real-time conditions meet the opening / closing conditions or the changing conditions, the effective monitoring status of each sensor at different discrete time points is determined, and the dynamic monitoring area corresponding to each discrete time point is determined based on the effective monitoring status.

[0071] At the same discrete time point, geometric intersection is performed on at least two of the dynamic monitoring areas to obtain an instantaneously overlapping monitoring area;

[0072] The overlapping monitoring areas under the same time sequence are adjusted based on the instantaneous overlapping monitoring areas.

[0073] In this embodiment, to achieve accurate testing and effective calibration of sensor accuracy, it is necessary to fully consider the dynamic characteristics of the sensor in the actual application environment. Since the operating state and monitoring performance of the sensor change with environmental conditions and time, it is first necessary to obtain two key parameters: the on / off conditions and the changing conditions of each sensor under the test scenario.

[0074] The activation and deactivation conditions define the sensor's monitoring behavior from non-existence to activation or vice versa. These conditions may be pre-set, such as conditions based on a preset time schedule; they may be a passive response to changes in the external environment, such as triggering conditions based on real-time environmental variables in the test scenario; or they may be the result of collaborative work between different units within the system, such as conditions based on linkage drive signals received from other devices. Meanwhile, the changing conditions describe the transitions in the sensor's performance parameters or monitoring modes during operation.

[0075] In practice, a test timeline is constructed, and the real-time conditions corresponding to each discrete time point on the timeline are determined, discretizing the continuous test process into a series of ordered time snapshots. At each discrete time point, the system captures a set of real-time conditions, which constitute the complete state of the test scenario at that instant. The system performs a judgment at each discrete time point. When the real-time conditions satisfy the on / off conditions or the change conditions, the effective monitoring state of each sensor at different discrete time points is determined. The sensor behavior rules are combined with the instantaneous state of the real scene. If the real-time conditions at a certain moment trigger the on / off or change conditions of a sensor, the system updates the effective monitoring state of that sensor. Subsequently, the system determines the dynamic monitoring area corresponding to each discrete time point based on the effective monitoring state.

[0076] Once the dynamic monitoring area of ​​each sensor at the same discrete time point is determined, precise overlap analysis can be performed. By geometrically intersecting at least two of the dynamic monitoring areas at the same discrete time point, an instantaneous overlapping monitoring area is obtained. This instantaneous overlapping monitoring area represents the unique common space in which multiple sensors can effectively monitor simultaneously at that specific moment.

[0077] Finally, the outcome of the entire process is reflected in the adjustment of the overlapping monitoring regions under the same time sequence based on the instantaneous overlapping monitoring regions. This essentially replaces a single, fixed concept of overlapping regions with a time series consisting of continuous instantaneous overlapping monitoring regions.

[0078] This dynamic analysis method, based on on / off conditions and changing conditions, can more accurately reflect the sensor's operating status in real-world application environments, avoiding testing when the sensor is in an ineffective monitoring state. By dynamically adjusting the overlapping monitoring area, it ensures that accuracy testing is always conducted within the effective monitoring range, improving the reliability of test results. This method can adapt to dynamic changes in environmental conditions, making accuracy testing and calibration processes more closely resemble real-world application scenarios.

[0079] Based on the above embodiments, as an optional implementation, after step S102, the overlapping monitoring area needs to be adjusted through the following steps:

[0080] Calculate the area ratio of the overlapping monitoring area to the corresponding monitoring area;

[0081] If the area ratio is less than the preset ratio, then the overlapping monitoring areas with an area ratio less than the preset ratio will be removed.

[0082] In this embodiment, to ensure the effectiveness and representativeness of the overlapping monitoring areas, it is necessary to screen the overlapping monitoring areas. By calculating the area ratio of the overlapping monitoring areas to their corresponding monitoring areas, the importance of the overlapping monitoring areas within the overall monitoring range can be assessed. This calculation process requires first obtaining the area value of each overlapping monitoring area and the area value of its corresponding sensor monitoring area, and then obtaining the area ratio through the ratio of the two.

[0083] Calculating the area proportion is crucial for evaluating the actual monitoring value of overlapping monitoring areas. When the area proportion of the overlapping monitoring area is small compared to the corresponding monitoring area, it indicates that the overlapping area accounts for a small proportion of the overall monitoring range, and the representativeness and reliability of its monitoring data may not meet the requirements of accuracy testing. Therefore, a preset proportion needs to be set as a screening criterion. When the area proportion is less than this preset proportion, the overlapping monitoring area should be removed from subsequent accuracy testing.

[0084] By setting area proportion thresholds and filtering accordingly, overlapping monitoring areas that are too small or have little monitoring significance can be effectively removed. This filtering mechanism not only improves the efficiency of accuracy testing but also avoids invalid testing in atypical areas.

[0085] S103: When the monitoring methods of multiple target sensors corresponding to the overlapping monitoring area are related, obtain the target monitoring results of each target sensor in the overlapping monitoring area;

[0086] The correlation refers to the rules for mutual conversion or comparison of monitoring data between different sensors. It can be understood as the logical correspondence between data collected by different sensors on the same monitoring object.

[0087] Among them, the target monitoring result refers to the actual monitoring data obtained by the target sensor under test in the overlapping monitoring area, which can be understood as the measurement value of the monitored object by the target sensor in the overlapping monitoring area.

[0088] In this embodiment, to effectively evaluate and calibrate the accuracy of the target sensors, it is necessary to first determine whether there is a correlation between the monitoring methods of multiple target sensors within the overlapping monitoring area. Only when there is a correlation between the monitoring methods of these target sensors can their monitoring results be comparable or convertible, and only then can the acquired monitoring data be used for subsequent accuracy evaluation.

[0089] In practice, the first step is to analyze the monitoring methods of each target sensor within the overlapping monitoring area to determine if there are data conversion rules or comparison standards between them. Once a correlation is confirmed, the system begins collecting the target monitoring results from each target sensor within the overlapping monitoring area. These target monitoring results represent the actual measurement values ​​of the monitored objects by the target sensors within the overlapping monitoring area, reflecting the actual working status and measurement performance of the sensors.

[0090] Based on the above embodiments, as an optional implementation method, the association relationship includes the same type association relationship and the similar type association relationship. The method of obtaining the target monitoring result according to different association relationships in S103 can be specifically implemented through the following steps S201 or S202.

[0091] S201: When the monitoring methods of multiple target sensors corresponding to the overlapping monitoring area have the same type of correlation, determine the first monitoring index corresponding to the same type of correlation, and obtain the target monitoring results of each target sensor corresponding to the first monitoring index in the overlapping monitoring area.

[0092] In this embodiment, it is necessary to further analyze the correlation between the monitoring methods of target sensors within the overlapping monitoring area. When multiple target sensors have the same type of correlation in their monitoring methods, it means that the monitoring data of these sensors can be directly compared without data conversion or mapping. In this case, it is necessary to determine the first monitoring index corresponding to the same type of correlation, which is a physical quantity or state parameter jointly monitored by these sensors.

[0093] After determining the primary monitoring indicator, the system will acquire the target monitoring results of each target sensor for that indicator within the overlapping monitoring area. Since these sensors have the same type of correlation, their acquired monitoring results share the same measurement standards and data formats, and can be directly used for subsequent accuracy assessment and comparative analysis.

[0094] S202: When the monitoring methods of multiple target sensors corresponding to the overlapping monitoring area have similar type correlation, the first monitoring result and the second monitoring result of each target sensor in the overlapping monitoring area are obtained. The second monitoring index is determined in the first monitoring result or the second monitoring result according to the similar type correlation, and the first monitoring result or the second monitoring result is converted into the target monitoring result according to the second monitoring index.

[0095] In this embodiment, when multiple target sensors within an overlapping monitoring area have similar types of relationships, although these sensors employ different monitoring methods and principles, they can obtain the same type of monitoring information through appropriate data processing. For example, one sensor directly monitors target location information, while another sensor indirectly obtains location information by processing infrared thermal imaging data. In this case, it is necessary to uniformly convert and process the data obtained from different monitoring methods.

[0096] In practice, the first step is to acquire the first and second monitoring results from each target sensor within the overlapping monitoring area. These results are derived from raw data from different monitoring methods. Then, a second monitoring index is determined based on similarity type correlations. This index serves as a unified standard for conversion and comparison between different monitoring results. For example, location information can be used as the second monitoring index. By establishing conversion rules from infrared thermal imaging data to location information, different forms of monitoring results can be uniformly converted into comparable target monitoring results.

[0097] S104: Determine the accuracy test results of the target sensors based on the absolute accuracy difference between the monitoring results of each target.

[0098] In this embodiment, the target monitoring results of each target sensor within the overlapping monitoring area are first compared pairwise, and the absolute difference between the monitoring results of each pair of sensors is calculated. These absolute accuracy differences reflect the degree of consistency in measurement between different sensors within the same monitoring area. The smaller the difference, the closer the measurement accuracy between the sensors; conversely, a larger difference indicates a larger accuracy deviation. By analyzing the distribution characteristics of these absolute accuracy differences, such as the mean and variance of the differences, the system ultimately obtains the accuracy test results of the target sensors.

[0099] Based on the above embodiments, as an optional implementation method, step S104 specifically includes S301-S303.

[0100] S301: Calculate the absolute accuracy difference between the monitoring results of each target;

[0101] In practice, the first step is to number and pair all target sensors within the overlapping monitoring area, combining these sensors into multiple sensor pairs. For each sensor pair, the system acquires its respective target monitoring results and calculates the absolute accuracy difference between them using a specific calculation method. This calculation process requires selecting an appropriate difference calculation method based on the type of monitoring data to ensure that the calculation results accurately reflect the accuracy differences between the sensors.

[0102] During the calculation process, the system samples and calculates the target monitoring results of each sensor pair multiple times to eliminate the influence of environmental factors and random errors. Each sampling yields an absolute accuracy difference, and the statistical distribution characteristics of these differences can comprehensively reflect the accuracy differences between the sensor pairs.

[0103] S302: If the absolute accuracy difference is less than the preset accuracy threshold, then the target sensor whose absolute accuracy difference is less than the preset accuracy threshold is determined as the first target sensor, and the accuracy test result corresponding to the first target sensor is marked as the test result that meets the accuracy requirements.

[0104] In this embodiment, to improve the efficiency of sensor accuracy testing, this solution innovatively utilizes the monitoring results of multiple sensors within an overlapping monitoring area for mutual verification. The core idea of ​​this method is that when the monitoring results of multiple sensors in the same overlapping area are small in difference, i.e., when the absolute accuracy difference is small, these sensors are very likely to have good monitoring accuracy, thus eliminating the need for further verification through specialized sensor testing equipment and significantly improving the efficiency of accuracy testing.

[0105] In practice, the system first acquires the absolute accuracy difference between each pair of sensors and compares these differences with a preset accuracy threshold. When all the absolute accuracy differences calculated for a sensor paired with other sensors are less than the preset accuracy threshold, that sensor is identified as the first target sensor. This method is based on an important practical experience: within the same overlapping monitoring area, if the monitoring results of multiple sensors are highly consistent, then these sensors are likely all in normal working condition and have good monitoring accuracy. This avoids the need to use specialized testing equipment to test each sensor individually, saving both time and resources.

[0106] For sensors identified as the primary target sensors, the system marks their corresponding accuracy test results as meeting the accuracy requirements. This method, based on mutual verification of overlapping regions, not only significantly improves the efficiency of accuracy testing but also offers strong real-time performance and cost-effectiveness. Compared to traditional methods that require specialized testing equipment for individual testing, this solution can quickly identify sensors that meet the accuracy requirements, allowing the system to concentrate limited testing resources on sensors that may have accuracy issues.

[0107] Optionally, the preset precision threshold can be determined in the following way:

[0108] Obtain the minimum accuracy requirements for the sensor;

[0109] Obtain the environmental characteristics of the test scenario, and determine the scenario type to which the environmental characteristics belong in a pre-established list of scenario types;

[0110] The preset accuracy threshold is obtained by multiplying the scene adjustment coefficient corresponding to the scene type with the minimum accuracy requirement. The scene adjustment coefficient is used to characterize the degree of attenuation of sensor accuracy in different scene types.

[0111] In this embodiment, to ensure the rationality and practicality of the preset accuracy threshold, it is necessary to dynamically adjust it based on the actual test scenario, after obtaining the minimum accuracy requirement of the sensor. This adjustment mechanism is designed to address the differences in sensor accuracy requirements across different scenarios; adaptive adjustment based on the scenario allows the preset accuracy threshold to better meet the needs of actual applications.

[0112] In practical implementation,

[0113] First, determine the minimum accuracy requirement for the sensor. This minimum accuracy requirement can be determined based on the sensor's specifications or set according to actual application needs, serving as a benchmark value for evaluating the sensor's accuracy performance. Next, acquire the environmental characteristics of the test scenario. These environmental characteristics are a comprehensive description of the test scenario, including but not limited to multiple environmental parameters such as temperature range, humidity range, light intensity, density of obstructions, spatial structure features, and electromagnetic environment. The acquisition of these environmental parameters can be accomplished using specialized environmental monitoring equipment or through on-site surveys.

[0114] Within a pre-established list of scene types, feature matching is performed based on acquired environmental characteristics to determine the scene type of the current test scenario. The scene type list is a systematically organized scene classification system covering various typical scenarios where the sensor may be applied. For different scene types, the system sets corresponding scene adjustment coefficients, which quantify the degree of accuracy degradation of the sensor under specific scene types. The determination of the scene adjustment coefficients is based on extensive experimental data and practical application experience, fully considering the impact of various environmental factors on sensor accuracy.

[0115] By multiplying the scene adjustment factor by the sensor's minimum accuracy requirement, a preset accuracy threshold applicable to the current test scenario is obtained. Different scenario types may have different requirements for sensor accuracy. For example, higher accuracy standards are required in some critical monitoring scenarios, while accuracy requirements can be appropriately relaxed in general monitoring scenarios.

[0116] S303: If the absolute accuracy difference is greater than or equal to the preset accuracy threshold, the target sensor with the absolute accuracy difference greater than or equal to the preset accuracy threshold is determined as the second target sensor, and the standard monitoring result of the sensor detection device in the overlapping monitoring area is obtained. The second target sensor is calibrated according to the standard monitoring result and the target monitoring result corresponding to the second target sensor.

[0117] In this embodiment, when the absolute accuracy difference of certain sensors is found to be greater than or equal to a preset accuracy threshold, it indicates that the monitoring accuracy of these sensors may have problems and further accuracy verification and calibration are required. In this case, these sensors are identified as second target sensors, and standard monitoring results are obtained by introducing sensor detection equipment, thereby achieving accurate calibration of these sensors.

[0118] In practice, the system first identifies sensors whose absolute accuracy difference is greater than or equal to a preset accuracy threshold and designates them as the second target sensor. This approach is based on the consideration that when the monitoring results of a sensor differ significantly from those of other sensors in the overlapping monitoring area, it indicates that the monitoring accuracy of that sensor may have drifted or that other anomalies exist. Subsequently, the system deploys sensor detection equipment in the overlapping monitoring area to obtain highly reliable standard monitoring results. Using these standard monitoring results as a calibration benchmark, the system compares them with the target monitoring results of the second target sensor, calculates the actual error value, and calibrates the accuracy of the second target sensor accordingly.

[0119] Based on the above embodiments, as an optional implementation method, step S303 further includes S401-S405.

[0120] S401: If the absolute accuracy difference is greater than or equal to the preset accuracy threshold, then the target sensor whose absolute accuracy difference is greater than or equal to the preset accuracy threshold is determined as the second target sensor.

[0121] In practice, after obtaining the absolute accuracy differences between sensors, the system compares these differences with a preset accuracy threshold. When it finds that the absolute accuracy difference calculated by pairing a sensor with other sensors is greater than or equal to the preset accuracy threshold, the system identifies that sensor as the second target sensor.

[0122] S402: Set up several station locations within the overlapping monitoring area and control the test object to move along the station locations;

[0123] In practice, the system first determines the number and density of monitoring stations based on the geometric characteristics and area of ​​the overlapping monitoring region. When dividing the monitoring area into grid cells, the overlapping monitoring region is divided into several grid cells, and a station location is set within each grid cell. For special areas, such as areas where sensor sensitivity may change or areas significantly affected by environmental factors, the station deployment can be appropriately increased. The system assigns a unique identifier to each station location and records its precise spatial coordinates.

[0124] After the site deployment is completed, the system controls the test object to move according to the pre-planned movement path. The design of the movement path needs to consider both testing efficiency and completeness, and typically uses the shortest path planning algorithm to ensure that the test object can reach each site location sequentially via the optimal path. During the movement of the test object, the system will control its stay at each site location for a sufficient amount of time to ensure that each sensor can acquire stable monitoring data.

[0125] S403: Acquire the location information of the sensor detection device at the site location and organize the location information into standard monitoring results;

[0126] In practice, the system controls sensor detection equipment to accurately measure the location of each station. A station location refers to a pre-defined test point within the overlapping monitoring area, and each station has its fixed spatial coordinates. Location information includes the specific coordinate values ​​of the station in a Cartesian coordinate system. To ensure the reliability of the measurement results, the system performs multiple repeated measurements on each station to eliminate the influence of random errors.

[0127] Organizing the measured location information into standard monitoring results refers to the standard-format dataset formed after the raw measurement data has been normalized. The standard monitoring results include standard coordinate values ​​for each station, which will serve as benchmark data for evaluating the accuracy of other sensors. The organization process includes necessary data processing steps such as data format standardization and coordinate system transformation to ensure that all data conforms to the system's preset standard format.

[0128] S404: Calculate the correction coefficient at each station location based on the standard monitoring results and the target monitoring results corresponding to the second target sensor;

[0129] In this embodiment, to achieve accurate calibration of the second target sensor, a correction coefficient needs to be calculated based on the difference between the standard monitoring results and the target monitoring results. The correction coefficient reflects the degree of accuracy deviation of the second target sensor at each station location.

[0130] In practice, the system first acquires the standard monitoring result measured by the sensor detection device and the target monitoring result corresponding to the second target sensor. At each station location, the correction coefficient for that location is calculated by comparing the difference between the two monitoring results. The correction coefficient is calculated by dividing the standard monitoring result by the target monitoring result; this coefficient reflects the correction required for the measurement value of the second target sensor at that station location to achieve the standard accuracy. In this way, the correction coefficients for all station locations within the overlapping monitoring area can be obtained.

[0131] S405: Arrange the correction coefficients into a correction coefficient sequence according to the station locations, and perform linear calibration on the second target sensor according to the correction coefficient sequence.

[0132] In this embodiment, to perform systematic accuracy calibration of the second target sensor, the correction coefficients need to be arranged in an orderly manner and calibrated. The correction coefficient refers to the ratio of the standard monitoring result to the target monitoring result at each station location, used to characterize the degree of accuracy deviation of the sensor at that location.

[0133] In practice, the correction coefficients corresponding to each station location are first arranged in order of station location to form a correction coefficient sequence. Here, the station location order refers to the sequential order in which the test object passes through each preset station as it moves within the overlapping monitoring area. The correction coefficient sequence is a set of correction coefficient data arranged in this order.

[0134] Based on the obtained correction coefficient sequence, the system performs linear calibration on the second target sensor. Linear calibration refers to using the correction coefficients of two adjacent station locations in the correction coefficient sequence, calculating the correction coefficient at any location between these two stations through linear interpolation, and then using this correction coefficient to correct the sensor's monitoring results. This linear calibration method can achieve continuous correction of the sensor's monitoring results, making the calibrated monitoring results closer to the standard monitoring results.

[0135] The following are system embodiments of this application, which can be used to execute the method embodiments of this application. For details not disclosed in the system embodiments of this application, please refer to the method embodiments of the application.

[0136] Please see Figure 2 This illustration shows a schematic diagram of a sensor accuracy testing system provided in an exemplary embodiment of this application. The system can be implemented entirely or partially through software, hardware, or a combination of both. The sensor accuracy testing system includes:

[0137] The scene construction module is used to acquire scene information from multiple sensors in the target deployment scene, and build a test scene that simulates the target deployment scene based on the scene information;

[0138] The region determination module is used to obtain the monitoring method and monitoring area of ​​each sensor in the test scenario, and to determine the overlapping monitoring areas in the monitoring area.

[0139] The testing module is used to obtain the target monitoring results of each target sensor in the overlapping monitoring area when there is a correlation between the monitoring methods of multiple target sensors corresponding to the overlapping monitoring area.

[0140] The results output module is used to determine the accuracy test results of the target sensors based on the absolute accuracy difference between the monitoring results of each target.

[0141] Based on the above embodiments, as an optional embodiment, the region determination module is further configured to acquire the activation / deactivation conditions and change conditions of each sensor in the test scenario. The activation / deactivation conditions include conditions based on a preset time schedule, triggering conditions based on real-time environmental variables in the test scenario, and conditions based on linkage drive signals received from other devices. A test time axis is constructed, and the real-time conditions corresponding to each discrete time point on the test time axis are determined. When the real-time conditions satisfy the activation / deactivation conditions or the change conditions, the effective monitoring state of each sensor at different discrete time points is determined, and the dynamic monitoring region corresponding to each discrete time point is determined based on the effective monitoring state. At the same discrete time point, at least two dynamic monitoring regions are geometrically intersected to obtain an instantaneously overlapping monitoring region. The overlapping monitoring regions under the same time sequence are adjusted based on the instantaneously overlapping monitoring regions.

[0142] Based on the above embodiments, as an optional embodiment, the region determination module is also used to calculate the area ratio of the overlapping monitoring region to the corresponding monitoring region; if the area ratio is less than a preset ratio, the overlapping monitoring region with an area ratio less than the preset ratio is removed.

[0143] Based on the above embodiments, as an optional embodiment, the test module is further configured to determine the first monitoring index corresponding to the same type of association when the monitoring methods of multiple target sensors corresponding to the overlapping monitoring area have the same type of association, and obtain the target monitoring result corresponding to the first monitoring index of each target sensor in the overlapping monitoring area; or, when the monitoring methods of multiple target sensors corresponding to the overlapping monitoring area have similar type of association, obtain the first monitoring result and the second monitoring result of each target sensor in the overlapping monitoring area, determine the second monitoring index based on the similar type of association in the first monitoring result or the second monitoring result, and convert the first monitoring result or the second monitoring result into the target monitoring result based on the second monitoring index.

[0144] Based on the above embodiments, as an optional embodiment, the result output module is further used to calculate the absolute accuracy difference between the monitoring results of each target; if the absolute accuracy difference is less than a preset accuracy threshold, the target sensor with an absolute accuracy difference less than the preset accuracy threshold is identified as the first target sensor, and the accuracy test result corresponding to the first target sensor is marked as a test result that meets the accuracy requirements; if the absolute accuracy difference is greater than or equal to the preset accuracy threshold, the target sensor with an absolute accuracy difference greater than or equal to the preset accuracy threshold is identified as the second target sensor, and the standard monitoring result of the sensor detection device in the overlapping monitoring area is obtained, and the second target sensor is calibrated according to the standard monitoring result and the target monitoring result corresponding to the second target sensor.

[0145] Based on the above embodiments, as an optional embodiment, the result output module is further configured to: if the absolute accuracy difference is greater than or equal to a preset accuracy threshold, determine the target sensor whose absolute accuracy difference is greater than or equal to the preset accuracy threshold as the second target sensor; set several station locations within the overlapping monitoring area and control the test object to move along the station locations; acquire the position information of the sensor detection device at the station locations and organize the position information into standard monitoring results; calculate the correction coefficient at each station location based on the standard monitoring results and the target monitoring results corresponding to the second target sensor; arrange the correction coefficients in the order of the station locations into a correction coefficient sequence, and perform linear calibration on the second target sensor according to the correction coefficient sequence.

[0146] Based on the above embodiments, as an optional embodiment, the result output module is also used to obtain the minimum accuracy requirement of the sensor; obtain the environmental features of the test scene, and determine the scene type to which the environmental features belong in a pre-established scene type list; calculate the product of the scene adjustment coefficient corresponding to the scene type and the minimum accuracy requirement to obtain a preset accuracy threshold, wherein the scene adjustment coefficient is used to characterize the degree of attenuation of sensor accuracy in different scene types.

[0147] This application also provides a computer storage medium that can store multiple instructions. The instructions are adapted to be loaded and executed by a processor to perform the accuracy testing method for a sensor as described in the above embodiments. For details of the execution process, please refer to the specific description of the embodiments, which will not be repeated here.

[0148] Please see Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 3 As shown, the electronic device 300 may include: at least one processor 301, at least one network interface 304, user interface 303, memory 305, and at least one communication bus 302.

[0149] The communication bus 302 is used to enable communication between these components.

[0150] The user interface 303 may include a display screen and a camera.

[0151] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0152] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 305, and by calling data stored in memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0153] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. Figure 3 As shown, the memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a sensor accuracy testing method.

[0154] exist Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 301 can be used to call an application program stored in the memory 305 for a sensor accuracy testing method. When executed by one or more processors, the electronic device executes one or more methods as described in the above embodiments.

[0155] An electronic device readable storage medium stores instructions that, when executed by one or more processors, cause the electronic device to perform one or more methods as described in the above embodiments.

[0156] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0157] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0158] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some service interfaces; indirect couplings or communication connections between apparatuses or units may be electrical or other forms.

[0159] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0160] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0161] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0162] The above are merely exemplary embodiments of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of other embodiments of this disclosure upon considering the specification and the disclosure of practical truths. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure.

Claims

1. A method of testing the accuracy of a sensor, characterized by, The method comprises: obtaining scene information of a plurality of sensors in a target delivery scene, and building a test scene simulating the target delivery scene according to the scene information; obtaining a monitoring mode and a monitoring area of each of the sensors in the test scene, and determining an overlapping monitoring area in the monitoring area; when the monitoring modes of a plurality of target sensors corresponding to the overlapping monitoring area have a correlation, obtaining target monitoring results of each of the target sensors in the overlapping monitoring area; determining precision test results of the target sensors according to absolute precision difference values between the target monitoring results; the determining of the precision test results of the target sensors according to the absolute precision difference values between the target monitoring results comprises: calculating the absolute precision difference values between the target monitoring results; if the absolute precision difference value is less than a preset precision threshold, determining a target sensor with the absolute precision difference value less than the preset precision threshold as a first target sensor, and marking a precision test result corresponding to the first target sensor as a test result meeting a precision requirement; if the absolute precision difference value is greater than or equal to the preset precision threshold, determining a target sensor with the absolute precision difference value greater than or equal to the preset precision threshold as a second target sensor, and obtaining a standard monitoring result of a sensor detection device in the overlapping monitoring area, and calibrating the second target sensor according to the standard monitoring result and a target monitoring result corresponding to the second target sensor.

2. The method of claim 1, wherein, if the absolute precision difference value is greater than or equal to the preset precision threshold, determining a target sensor with the absolute precision difference value greater than or equal to the preset precision threshold as a second target sensor, and obtaining a standard monitoring result of a sensor detection device in the overlapping monitoring area, and calibrating the second target sensor according to the standard monitoring result and a target monitoring result corresponding to the second target sensor, comprises: if the absolute precision difference value is greater than or equal to the preset precision threshold, determining a target sensor with the absolute precision difference value greater than or equal to the preset precision threshold as a second target sensor; setting a plurality of site positions in the overlapping monitoring area, and controlling a test object to move along the site positions; obtaining position information of a sensor detection device at the site positions, and arranging the position information into a standard monitoring result; calculating a correction coefficient at each of the site positions according to the standard monitoring result and a target monitoring result corresponding to the second target sensor; arranging the correction coefficient into a correction coefficient sequence according to an order of the site positions, and linearly calibrating the second target sensor according to the correction coefficient sequence.

3. The method of claim 1, wherein, after the calculating of the absolute precision difference values between the target monitoring results, the method further comprises: obtaining a minimum precision requirement of a sensor; obtaining an environmental feature of the test scene, and determining a scene type to which the environmental feature belongs in a pre-established scene type list; The product of the scene adjustment coefficient corresponding to the scene type and the minimum precision requirement is calculated to obtain a preset precision threshold, and the scene adjustment coefficient is used to represent the attenuation degree of sensor precision in different scene types.

4. The method of claim 1, wherein, The association relationship includes a same-type association relationship and a similar-type association relationship, and when the monitoring modes of the multiple target sensors corresponding to the overlapping monitoring area have an association relationship, the target monitoring results of each of the target sensors in the overlapping monitoring area are obtained, including: When the monitoring modes of the multiple target sensors corresponding to the overlapping monitoring area have a same-type association relationship, a first monitoring index corresponding to the same-type association relationship is determined, and the target monitoring results of each of the target sensors in the overlapping monitoring area corresponding to the first monitoring index are obtained. Or, When the monitoring modes of the multiple target sensors corresponding to the overlapping monitoring area have a similar-type association relationship, the first monitoring result and the second monitoring result of each of the target sensors in the overlapping monitoring area are obtained, a second monitoring index is determined in the first monitoring result or the second monitoring result according to the similar-type association relationship, and the first monitoring result or the second monitoring result is converted into a target monitoring result according to the second monitoring index.

5. The method of claim 1, wherein, After the monitoring modes and the monitoring areas of each of the sensors in the test scene are obtained and the overlapping monitoring areas in the monitoring areas are determined, the following steps are further included: The on-off conditions and the change conditions of each of the sensors in the test scene are obtained, the on-off conditions include a condition based on a preset time schedule, a trigger condition based on a real-time environmental variable in the test scene, and a condition based on a linkage driving signal received from other devices; A test time axis is constructed to determine real-time conditions corresponding to each discrete time point on the test time axis; When the real-time conditions meet the on-off conditions or the change conditions, the effective monitoring states of each of the sensors corresponding to different discrete time points are determined, and the dynamic monitoring areas corresponding to each of the discrete time points are determined according to the effective monitoring states; At the same discrete time point, at least two dynamic monitoring areas are geometrically intersected to obtain an instantaneous overlapping monitoring area; The overlapping monitoring areas under the same time sequence are adjusted based on the instantaneous overlapping monitoring area.

6. The method of claim 1, wherein, After the monitoring modes and the monitoring areas of each of the sensors in the test scene are obtained and the overlapping monitoring areas in the monitoring areas are determined, the following steps are further included: The area proportion of the overlapping monitoring area to the corresponding monitoring area is calculated; If the area proportion is less than a preset proportion, the overlapping monitoring area with the area proportion less than the preset proportion is removed.

7. A precision testing system for a sensor, characterized by, The system includes: A scene construction module is configured to obtain scene information of multiple sensors in a target delivery scene, and to build a test scene simulating the target delivery scene according to the scene information; A region determination module is configured to obtain the monitoring modes and the monitoring areas of each of the sensors in the test scene, and to determine the overlapping monitoring areas in the monitoring areas. The test module is configured to acquire target monitoring results of the target sensors in the overlapping monitoring area when the monitoring manners of the target sensors corresponding to the overlapping monitoring area have a correlation relationship. The result output module is configured to determine the accuracy test result of the target sensors according to the absolute accuracy difference between the target monitoring results. The determination of the accuracy test result of the target sensors according to the absolute accuracy difference between the target monitoring results includes: calculating the absolute accuracy difference between the target monitoring results; if the absolute accuracy difference is less than a preset accuracy threshold, determining the target sensor with the absolute accuracy difference less than the preset accuracy threshold as a first target sensor, and marking the accuracy test result corresponding to the first target sensor as a test result meeting the accuracy requirement; if the absolute accuracy difference is greater than or equal to the preset accuracy threshold, determining the target sensor with the absolute accuracy difference greater than or equal to the preset accuracy threshold as a second target sensor, acquiring a standard monitoring result of the sensor detection device in the overlapping monitoring area, and calibrating the second target sensor according to the standard monitoring result and the target monitoring result corresponding to the second target sensor.

8. A computer storage medium, characterized in that The computer storage medium stores a plurality of instructions, which are suitable for being loaded and executed by the processor to perform the method in any one of claims 1-6.

9. An electronic device, comprising: The electronic device includes a processor, a memory, and a transceiver. The memory is configured to store instructions. The transceiver is configured to communicate with other devices. The processor is configured to execute the instructions stored in the memory to enable the electronic device to perform the method in any one of claims 1-6.

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