Radiation risk information processing method and device

Abstract

The present application discloses a method and device for processing radiation risk information, the method comprising: obtaining an image of the surrounding environment, and establishing a 3D area model of the area to be detected based on the image of the surrounding environment; dividing the area to be detected into multiple partitions, and performing the following operations for each partition: randomly calibrating at least one first detection point; calculating the radius distance between each first detection point and the target object, and forming multiple sub-areas between at least one first detection point and the target object; determining the target detection point corresponding to the partition based on the radius distance and the multiple sub-areas; determining the radiation risk detection scheme corresponding to each partition based on the target detection point corresponding to each partition; and controlling the radiation detector to perform the detection operation based on the radiation risk detection scheme to obtain the detection result data set corresponding to each partition. The use of the present application is conducive to improving the intelligence and comprehensiveness of smart wearable devices.

Description

Technical Field

[0001] The present application relates to the technical field of smart wearable devices, and in particular to a method and device for processing radiation risk information. Background Art

[0002] Radiation that reaches a certain level is very harmful to human health, environmental ecology, etc., and will cause radiation risks. For example, long-term exposure to high-dose radiation environments will increase the risk of malignant tumors such as leukemia, thyroid cancer and lung cancer; radiation will also pollute soil, water sources, etc., affecting the balance of the ecosystem. Therefore, it is necessary to detect whether there are radiation risks in some areas.

[0003] Currently, users mainly record radiation detection information manually, and then enter it into a computer afterwards to further determine radiation risks. The data processing efficiency is low and there are cases of missed detections, resulting in a lack of comprehensiveness. Summary of the invention

[0004] The embodiments of the present application provide a method and device for processing radiation risk information, which can assist in radiation detection through smart wearable devices, thereby improving the intelligence and comprehensiveness of smart wearable devices.

[0005] In a first aspect, an embodiment of the present application provides a method for processing radiation risk information, which is applied to a smart wearable device, wherein the smart wearable device is communicatively connected to a radiation detector; the method comprises:

[0006] Acquire a surrounding environment image, and establish a 3D area model of the area to be detected based on the surrounding environment image;

[0007] Divide the area to be detected into multiple partitions, and perform the following operations for each partition:

[0008] Randomly calibrating at least one first detection point;

[0009] Calculating a radius distance between each of the first detection points and the target object, wherein a plurality of sub-areas are formed between the at least one first detection point and the target object;

[0010] Determining a target detection point corresponding to the partition according to the radius distance and the multiple sub-areas;

[0011] Determining a radiation risk detection scheme corresponding to each of the partitions according to the target detection points corresponding to each of the partitions;

[0012] According to the radiation risk detection scheme, the radiation detector is controlled to perform a detection operation to obtain a detection result data set corresponding to each partition.

[0013] In a second aspect, an embodiment of the present application provides a device for processing radiation risk information, which is applied to a smart wearable device, wherein the smart wearable device is communicatively connected to a radiation detector; the device comprises:

[0014] An acquisition unit, used for acquiring a surrounding environment image and establishing a 3D area model of the area to be detected according to the surrounding environment image;

[0015] An execution unit, used for dividing the area to be detected into a plurality of partitions, and performing the following operations for each of the partitions: randomly calibrating at least one first detection point; calculating the radius distance between each of the first detection points and the target object, wherein a plurality of sub-regions are formed between the at least one first detection point and the target object; determining the target detection point corresponding to the partition according to the radius distance and the plurality of sub-regions; determining the radiation risk detection scheme corresponding to each of the partitions according to the target detection point corresponding to each of the partitions;

[0016] The control unit is used to control the radiation detector to perform a detection operation according to the radiation risk detection scheme, and obtain a detection result data set corresponding to each partition.

[0017] In a third aspect, an embodiment of the present application provides a smart wearable device, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing some or all of the steps described in the first aspect of the embodiment of the present application.

[0018] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in the first aspect of the embodiment of the present application.

[0019] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0020] Implementing the embodiments of the present application has the following beneficial effects: acquiring an image of the surrounding environment, and establishing a 3D area model of the area to be detected based on the image of the surrounding environment; dividing the area to be detected into multiple partitions, and performing the following operations for each of the partitions: randomly calibrating at least one first detection point; calculating the radius distance between each of the first detection points and the target object, and forming multiple sub-areas between the at least one first detection point and the target object; determining the target detection point corresponding to the partition based on the radius distance and the multiple sub-areas; determining the radiation risk detection scheme corresponding to each of the partitions based on the target detection point corresponding to each of the partitions; and controlling the radiation detector to perform the detection operation based on the radiation risk detection scheme to obtain a detection result data set corresponding to each of the partitions. In this way, radiation detection can be assisted by smart wearable devices, which is conducive to improving the intelligence and comprehensiveness of smart wearable devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 It is a schematic diagram of the architecture of a radiation risk detection system provided in an embodiment of the present application;

[0023] Figure 2 It is a flowchart of a method for processing radiation risk information provided by an embodiment of the present application;

[0024] Figure 3 This is a schematic diagram of dividing a region to be detected provided in an embodiment of the present application;

[0025] Figure 4 This is a schematic diagram of dividing sub-areas corresponding to a partition provided in an embodiment of the present application;

[0026] Figure 5 is a structural schematic diagram of a smart wearable device provided in an embodiment of the present application;

[0027] Figure 6 It is a block diagram of the functional units of a radiation risk information processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0029] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but in a possible example also includes steps or units that are not listed, or in a possible example also includes other steps or units inherent to these processes, methods, products or devices.

[0030] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0031] See also Figure 1 , Figure 1 A schematic diagram of the architecture of a radiation risk detection system provided in an embodiment of the present application. The radiation risk detection system includes: a radiation detector and a smart wearable device.

[0032] Among them, the smart wearable device in the embodiment of the present application is a wearable device, for example, it can be smart glasses, smart watches, Bluetooth headsets, or smart bracelets, etc. The above are only examples and not exhaustive.

[0033] For example, if the smart wearable device is a smart watch, it can be worn on the user's wrist, arm, etc. The smart wearable device may include a vibration device, a display device, a current output device, a voice device, etc., and can provide voice playback, display, vibration, electric shock and other functions through the above-mentioned different devices. The above functions can be combined with single functions or multiple functions to remind the user of some information, for example, moving to a detection point to detect radiation risk information, etc., and the specific details are not limited here.

[0034] Among them, users can wear smart wearable devices, which can communicate with radiation detectors and can be used to control the radiation detectors to detect x / gamma rays, radiation dose rates, etc. in radioactive workplaces.

[0035] It should be noted that, in the present application, a plurality may refer to two or more than two, which will not be repeated later.

[0036] See also Figure 2 , Figure 2 : is a flow chart of a method for processing radiation risk information provided by an embodiment of the present application; applied to a smart wearable device, the method includes:

[0037] S201, acquiring a surrounding environment image, and establishing a 3D area model of the area to be detected according to the surrounding environment image.

[0038] Among them, the smart wearable device may include an intelligent radiation detection function and establish a communication connection with a dedicated radiation detector to obtain relevant detection data from the smart detector.

[0039] For example, if the smart wearable device is a smart watch, the user can be guided to quickly scan the surrounding environment image through the camera by moving the wrist, etc., to obtain the surrounding environment image, and establish a 3D area model of the area to be detected based on the surrounding environment image. The 3D area model includes at least one of the following: location information, category information, height information, etc., which are not limited here; the category information is used to indicate the land use in the surrounding environment, etc.

[0040] It should be noted that radiation risk information may include the area to be detected as described in step S201, as well as multiple partitions obtained by dividing the area to be detected, as well as the target detection point corresponding to each partition, the detection result data set corresponding to each partition, etc. The information related to radiation risk detection, radiation contamination remediation, etc. described in this application can be called radiation risk information, and will not be repeated later.

[0041] S202: Divide the area to be detected into a plurality of partitions, and perform the following operations for each partition: randomly calibrate at least one first detection point.

[0042] The above-mentioned area to be detected can be set by the user or the system can define the range according to the surrounding environment image, which is not limited here.

[0043] Among them, for each partition, the following can be performed: randomly calibrating at least one first detection point; calculating the radius distance between each of the first detection points and the target object, forming multiple sub-areas between the at least one first detection point and the target object; and determining the target detection point corresponding to the partition based on the radius distance and the multiple sub-areas.

[0044] In one possible example, the area to be inspected is divided into multiple partitions, and the method includes the following steps: dividing the area to be inspected into a first partition that is in a first height range and is used for farming, a second partition that is in a second height range and borders the first partition and is used for traffic, and a third partition that is in a third height and is used for landscape.

[0045] Among them, the above-mentioned first height range, second height range and third height range can be set by the user or by the system default, and are not limited here; taking into account the influence of the differences in spatial object categories such as the land use in some areas, or the uneven distribution of terrain height or the terrain with fluctuating heights (the corresponding area to be detected can be a basin surrounded by mountains), the terrain impacted by sea water at the seaside (the corresponding area to be detected can be a seaside area affected by radiation), then the radiation risk will also be distributed differently with the spatial object category, which is relatively complicated. Therefore, it can be considered to divide the area to be detected into multiple areas, each with different land use. For example, it can be divided into different height ranges: the first height range, the second height range and the third height range can be the same or different, and the land use in different height ranges is different.

[0046] like Figure 3 As shown in FIG. 1 , it is a schematic diagram of the division of the area to be detected. The smart wearable device can divide the area to be detected into a first subarea in a first height range and used for farming, a second subarea in a second height range bordering the first subarea and used for traffic, and a third subarea in a third height range and used for landscape. The third subarea can be as follows: Figure 3 As shown, bordering the Second Division.

[0047] It can be seen that in this example, taking into account the differentiated distribution of radiation risks with the categories of spatial objects, for some complex areas, such as areas to be inspected with multiple land uses, the area to be inspected can be adaptively divided into multiple partitions to achieve subsequent radiation risk detection and other operations for each area.

[0048] S203: Calculate the radius distance between each of the first detection points and the target object, wherein a plurality of sub-areas are formed between the at least one first detection point and the target object.

[0049] The target object may be a nuclear leakage source, or other radiation source to be detected, etc., which is not limited here.

[0050] For example, when any partition in the area to be detected includes a first detection point, the first detection point and the target object can be connected, and the radius distance between the first detection point and the target object can be calculated. By drawing a circle with the radius range, two area spaces within the partition range, namely two sub-areas, can be obtained.

[0051] For example, when a partition includes multiple first detection points, each first detection point and the target object can be connected, and the radius distance between each first detection point and the target object can be calculated. The radius distance can be different. Therefore, after connecting each first detection point and the target object, the partition can be divided into multiple sub-areas, and each sub-area corresponds to a different first detection point.

[0052] For example, Figure 4 As shown, it is a schematic diagram of the division of sub-areas corresponding to a partition. For any partition of the area to be detected, if the area to be detected includes two first detection points, as shown in the figure, the first detection points are identified by hollow points, and the target object (radiation source) is identified by solid points. Each first detection point and the target object can be connected, and a circle with a radius between the two can be drawn to obtain two circular areas shown by dotted lines. It can be seen that if one of the circular areas is in the partition, the entire circular area can be regarded as a sub-area, and the other circular area intersects with the partition, then the intersecting part can be regarded as a sub-area, and the area in the partition except the above two sub-areas can be regarded as a sub-area. In this way, any partition of the area to be detected can be divided into three sub-areas.

[0053] It should be noted that the division method of sub-areas is not limited in this application.

[0054] S204: Determine a target detection point corresponding to the partition according to the radius distance and the multiple sub-areas.

[0055] The above-mentioned target detection point can be understood as a finally determined detection point, at which the detection result data can be more accurately obtained through the radiation detector.

[0056] In a possible example, the target detection point corresponding to the partition is determined based on the radius distance and the multiple sub-areas. The above method may include the following steps: if the radius distance indicates that the multiple sub-areas corresponding to the partition are all located in the same radius range, then judging the change amplitude of the partition surface height based on the 3D area model; if the change amplitude of the partition surface height is greater than or equal to a preset threshold, setting the position greater than or equal to the preset threshold as a second detection point, and setting the second detection point and at least one of the first detection points as the target detection point; if the change amplitude of the partition surface height is less than the preset threshold, then setting the at least one of the first detection points as the target detection point within the partition.

[0057] Among them, the smart wearable device can draw a circle according to the radius distance to obtain an area range, so that the area range corresponding to each sub-area can be obtained.

[0058] Among them, the above-mentioned radius range can be set by the user or by the system default, and is not limited here; for example, the radius range can be used as a critical range. The radiation risk detected within the critical range may be consistent, and the radiation range detected outside the critical range is inconsistent. Therefore, a sub-area within the same radius range can be selected, that is, a sub-area within the radius range can be selected to determine the radiation risk.

[0059] Among them, if the area ranges corresponding to multiple sub-areas are all within the same radius, the change range of the partition surface height can be judged according to the height information in the 3D regional model, so as to further determine whether the radiation risks detected within the critical range are consistent.

[0060] Among them, the above-mentioned preset threshold can be set by the user or by the system default, and is not limited here; the preset threshold can refer to the minimum value or average value within a height range, and the preset threshold can be used to evaluate the change in the surface height of a partition or sub-partition.

[0061] Specifically, when the change range of the surface height of a partition is greater than or equal to a preset threshold, it may indicate that the change range of the surface height within the partition is large, and the radiation risk detected within the above critical range is inconsistent. Therefore, in order to reduce the impact of the differentiated distribution of radiation risks in complex areas with the spatial object categories, at least one second detection point may continue to be set or additionally set. The at least one second detection point may be randomly set at a position greater than or equal to the preset threshold, and the number may also be randomly set, for example, it may be 1 or 3 or 5, etc. In this way, the first detection point and the second detection point may be set as target detection points.

[0062] Furthermore, when the change in the surface height of the partition is less than the preset threshold, it indicates that the spatial object categories within the partition are less differentiated and the ground change trend is smaller, then the radiation risks detected within the above critical range are consistent, and its impact on the accuracy of radiation risk detection will be relatively small; therefore, the above at least one first detection point can be used as the target detection point.

[0063] It can be seen that in this example, when determining the target detection point, if multiple sub-areas are located in the same radius range, the differentiation of spatial object categories in the complex area can be reflected by the change in the surface height. When the differentiation is large, multiple detection points can be selected for different situations, and a second detection point can be added. At least one first detection point and (at least one) second detection point can be used as target detection points; when the differentiation is small, no additional detection points can be added, and at least one first detection point can be used as a target detection point. In this way, the influence of the differentiation of spatial object types in complex areas on radiation risk judgment can be overcome, which is conducive to improving the accuracy of radiation risk detection.

[0064] In a possible example, the above method may also include the following steps: if the radius distance indicates that some of the multiple sub-areas corresponding to the partition are located in the same radius range, and another part of the sub-areas are located in other radius ranges, then randomly setting a third detection point in each of the other radius ranges to obtain at least one third detection point; judging the variation amplitude of the surface height within the same other radius range according to the 3D area model; if the variation amplitude of the surface height within the same other radius range is greater than or equal to the preset threshold, then setting a fourth detection point for a position greater than or equal to the preset threshold, and setting the at least one first detection point, the at least one third detection point and the fourth detection point as the target detection point, or setting the at least one first detection point, the second detection point, the at least one third detection point and the fourth detection point as the target detection point.

[0065] Among them, when some sub-areas are located in the same radius range and the change range of the surface height of some sub-areas is greater than or equal to a preset threshold, at least one first detection point, a second detection point, at least one third detection point and a fourth detection point are set as target detection points.

[0066] Among them, when some sub-areas are located in the same radius range and the change range of the surface height of some sub-areas is less than a preset threshold, at least one first detection point, at least one third detection point and a fourth detection point are set as target detection points.

[0067] It can be seen that in this example, if some sub-areas are located in the same radius range and other sub-areas have different radius ranges, the third detection point or the fourth detection point can be reset; further, the differentiation of spatial object categories in complex areas can be reflected by the change range of the ground surface height. When the differentiation is large, multiple detection points can be selected for different situations, that is, an additional fourth detection point is added, and at least one first detection point, a second detection point, at least one third detection point and a fourth detection point are set as target detection points, or at least one first detection point, at least one third detection point and a fourth detection point are set as target detection points. In this way, the influence of the differentiation of spatial object types in complex areas on radiation risk determination can be overcome, which is conducive to improving the accuracy of radiation risk detection.

[0068] In a possible example, the above method may also include the following steps: if the change amplitude of the surface height within the same other radius range is less than the preset threshold, then setting the at least one first detection point and the at least one third detection point as the target detection point, or setting the at least one first detection point, the second detection point and the at least one third detection point as the target detection point.

[0069] It can be seen that in this example, if some sub-areas are located in the same radius range and other sub-areas have different radius ranges, the third detection point or the fourth detection point can be reset; when the differentiation is small, no additional detection points need to be added, that is, no fourth detection point needs to be added, and at least one third detection point and at least one first detection point, or at least one third detection point, a second detection point and at least one first detection point can be used as target detection points.

[0070] S205: Determine a radiation risk detection scheme corresponding to each partition according to the target detection point corresponding to each partition.

[0071] Among them, the radiation risk detection scheme is used to indicate the radiation detector used for radiation detection and the detection method corresponding to the radiation detector, etc.

[0072] The above detection result data may include at least one of the following: the type of radionuclide, the concentration of radionuclide, etc., which are not limited here.

[0073] S206. According to the radiation risk detection scheme, control the radiation detector to perform a detection operation to obtain a detection result data set corresponding to each partition.

[0074] Among them, the detection result data set is used to: determine the fixed minimum years according to the type of radioactive nuclides, and determine the chemical substance use plan according to the concentration. For example, it can be the type of chemical substances of fixed nuclides, the proportion relationship, the amount of chemical substances used per unit area, etc.

[0075] In one possible example, according to the radiation risk detection scheme, the radiation detector is controlled to perform a detection operation to obtain a detection result data set corresponding to each of the partitions. The method may include the following steps: generating a prompt instruction according to the target detection point corresponding to each of the partitions, the prompt instruction being used to prompt the user to move to the target detection point in the corresponding partition; when it is detected that the user has arrived at the target detection point, sending a detection instruction to the radiation detector to control the radiation detector to perform the detection operation, and acquiring the detection data of the radiation detector to obtain the detection result data set corresponding to each of the partitions.

[0076] For example, when conducting detection, the smart wearable device can prompt the user to reach the target detection point, and determine the specific radiation detector used for radiation detection and the detection method corresponding to the radiation detector based on the radiation risk detection plan, and prompt the user to select the radiation detector and detection method used for the partition radiation detection, or directly send a detection instruction to the radiation detector used for the partition radiation detection, and the detection instruction is used to control the radiation detector to realize radiation detection in the detection method.

[0077] Furthermore, the smart wearable device is communicatively connected with the radiation detector to synchronize the detection result data obtained by the radiation detector, and summarizes the detection result data of various radiation detectors corresponding to the partition to obtain a detection result data set, and each partition can correspond to a detection result data set.

[0078] The types of the radiation detectors mentioned above may include at least one of the following: a multifunctional radiation monitor, an underwater γ-spectrometer, a ground γ-spectrometer, etc., which are not limited here.

[0079] For example, for the same target detection point, the smart wearable device can control the radiation detector to simultaneously measure the nuclear radiation data on the surface and in the air; for example, nuclear radiation in the air usually exists in the form of α, β, and γ rays. For the detection of nuclear radiation in the air, environmental radiation monitoring instruments, such as multi-function radiation monitors, can be used to measure various types of radiation; for the detection of nuclear radiation in water, an underwater γ-spectrometer can be used to measure the γ rays in the water, and perform nuclide identification and quantitative analysis. In addition, a water sample collector can be used to collect water from the source and bring it back to the detection agency for specific analysis; for the detection of nuclear radiation in the soil, a ground γ-spectrometer can be used to measure the γ rays in the soil, and so on, without limitation here.

[0080] It can be seen that in this example, the smart wearable device can be connected to the radiation detector to achieve radiation detection for each partition and obtain a detection result data set corresponding to each partition.

[0081] In a possible example, the above method may also include the following steps: according to the detection result data sets corresponding to the first partition, the second partition and the third partition respectively, and the water flow impact terrain distribution characteristics constrained by the first height range, the second height range and the third height range respectively, determine the surface radiation contamination remediation strategies corresponding to the first partition, the second partition and the third partition respectively.

[0082] Among them, the above-mentioned surface radiation contamination remediation strategy can be used to carry out surface radiation contamination remediation for different partitions (first partition, second partition and third partition) to reduce radiation contamination.

[0083] The distribution characteristics of the water flow impact terrain respectively constrained by the first height range, the second height range and the third height range can be predicted based on the Geographic Information System (GIS) technology.

[0084] Optionally, the above 3D regional model may also include: soil type, terrain (slope information) and the like.

[0085] In a specific implementation, when determining the surface radiation contamination remediation strategies corresponding to the first partition, the second partition, and the third partition, respectively, the following steps may be included: the smart wearable device obtains the climate model in the area to be detected, and predicts the rainfall within a fixed minimum number of years based on the climate model; the rainfall, land use, soil type, terrain and other information in the 3D regional model are imported into the GIS software, and combined with a soil erosion model, such as the Revised Universal Soil Loss Equation (RUSLE) or the Soil and Water Assessment Tool (SWAT), the degree of land erosion by rainwater is quantitatively analyzed within a fixed minimum number of years to obtain a prediction result; the soil turning depth in the current treatment partition is obtained based on the prediction result; and the surface radiation contamination remediation strategy in different partitions (the first partition, the second partition, or the third partition) is determined based on the chemical substance use plan and the soil turning depth.

[0086] It can be seen that in this example, the smart wearable device can determine the surface radiation pollution remediation strategy corresponding to each partition based on the detection result data obtained from the radiation detection and the distribution characteristics of the water flow impact terrain affected by different height ranges in the area to be detected, so as to achieve surface radiation pollution remediation for different partitions in a differentiated manner.

[0087] It can be seen that the method for processing radiation risk information described in the embodiment of the present application obtains the surrounding environment image, and establishes a 3D area model of the area to be detected based on the surrounding environment image; divides the area to be detected into multiple partitions, and performs the following operations for each of the partitions: randomly calibrates at least one first detection point; calculates the radius distance between each of the first detection points and the target object, and forms multiple sub-areas between the at least one first detection point and the target object; determines the target detection point corresponding to the partition based on the radius distance and the multiple sub-areas; determines the radiation risk detection scheme corresponding to each partition based on the target detection point corresponding to each partition; according to the radiation risk detection scheme, controls the radiation detector to perform the detection operation, and obtains the detection result data set corresponding to each partition. In this way, radiation detection can be assisted by smart wearable devices, which is conducive to improving the intelligence and comprehensiveness of smart wearable devices.

[0088] In accordance with the above embodiment, please refer to Figure 5 , Figure 5 1 is a schematic diagram of the structure of a smart wearable device provided in an embodiment of the present application. As shown in the figure, the smart wearable device includes a processor, a memory, a communication interface, and one or more programs. The one or more programs are stored in the memory and configured to be executed by the processor. The program includes instructions for executing the following steps:

[0089] Acquire a surrounding environment image, and establish a 3D area model of the area to be detected based on the surrounding environment image;

[0090] Divide the area to be detected into multiple partitions, and perform the following operations for each partition:

[0091] Randomly calibrating at least one first detection point;

[0092] Calculating a radius distance between each of the first detection points and the target object, wherein a plurality of sub-areas are formed between the at least one first detection point and the target object;

[0093] Determining a target detection point corresponding to the partition according to the radius distance and the multiple sub-areas;

[0094] Determining a radiation risk detection scheme corresponding to each of the partitions according to the target detection points corresponding to each of the partitions;

[0095] According to the radiation risk detection scheme, the radiation detector is controlled to perform a detection operation to obtain a detection result data set corresponding to each partition.

[0096] In a possible example, in determining the target detection point corresponding to the partition according to the radius distance and the multiple sub-areas, the program includes instructions for performing the following steps:

[0097] If the radius distance indicates that the multiple sub-areas corresponding to the partition are all within the same radius range, determining the change range of the surface height of the partition according to the 3D area model;

[0098] If the variation of the subarea ground surface height is greater than or equal to a preset threshold, setting a position greater than or equal to the preset threshold as a second detection point, and setting the second detection point and at least one of the first detection points as the target detection point;

[0099] If the variation of the ground surface height of the partition is less than the preset threshold, the at least one first detection point is used as the target detection point in the partition.

[0100] In a possible example, the program further includes instructions for executing the following steps:

[0101] If some of the multiple sub-areas corresponding to the partition indicated by the radius distance are located in the same radius range, and another part of the sub-areas are located in other radius ranges, a third detection point is randomly set in each of the other radius ranges to obtain at least one third detection point;

[0102] Determining the change range of the ground surface height within the same other radius according to the 3D regional model;

[0103] If the change in the ground height within the same other radius is greater than or equal to the preset threshold, a fourth detection point is set for a position greater than or equal to the preset threshold, and at least one of the first detection points, at least one of the third detection points, and the fourth detection point are set as the target detection point, or at least one of the first detection points, the second detection point, at least one of the third detection points, and the fourth detection point are set as the target detection point.

[0104] In a possible example, the program further includes instructions for executing the following steps:

[0105] If the change in the ground height within the same other radius is less than the preset threshold, at least one of the first detection points and at least one of the third detection points are set as the target detection points, or at least one of the first detection points, the second detection point and the at least one third detection point are set as the target detection points.

[0106] In a possible example, in terms of controlling the radiation detector to perform a detection operation according to the radiation risk detection scheme to obtain a detection result data set corresponding to each partition, the program includes instructions for performing the following steps:

[0107] Generate a prompt instruction according to the target detection point corresponding to each partition, wherein the prompt instruction is used to prompt the user to move to the target detection point in the corresponding partition;

[0108] When it is detected that the user has arrived at the target detection point, a detection instruction is sent to the radiation detector to control the radiation detector to perform the detection operation, and the detection data of the radiation detector is acquired to obtain the detection result data set corresponding to each partition.

[0109] In a possible example, in terms of dividing the area to be detected into a plurality of partitions, the program includes instructions for executing the following steps:

[0110] The area to be inspected is divided into a first subarea at a first altitude range and used for farming, a second subarea bordering the first subarea at a second altitude range and used for traffic, and a third subarea at a third altitude and used for landscape.

[0111] In a possible example, the program further includes instructions for executing the following steps:

[0112] According to the detection result data sets corresponding to the first partition, the second partition and the third partition respectively, and the water flow impact terrain distribution characteristics constrained by the first height range, the second height range and the third height range respectively, the surface radiation contamination remediation strategies corresponding to the first partition, the second partition and the third partition respectively are determined.

[0113] It can be seen that the smart wearable device described in the embodiment of the present application obtains the surrounding environment image, and establishes a 3D area model of the area to be detected based on the surrounding environment image; divides the area to be detected into multiple partitions, and performs the following operations for each partition: randomly calibrates at least one first detection point; calculates the radius distance between each of the first detection points and the target object, and forms multiple sub-areas between the at least one first detection point and the target object; determines the target detection point corresponding to the partition based on the radius distance and the multiple sub-areas; determines the radiation risk detection scheme corresponding to each partition based on the target detection point corresponding to each partition; according to the radiation risk detection scheme, controls the radiation detector to perform the detection operation, and obtains the detection result data set corresponding to each partition. In this way, radiation detection can be assisted by smart wearable devices, which is conducive to improving the intelligence and comprehensiveness of smart wearable devices.

[0114] Figure 6 It is a functional unit composition block diagram of a radiation risk information processing device 600 involved in an embodiment of the present application, which is applied to a smart wearable device. The radiation risk information processing device 600 includes: an acquisition unit 601, an execution unit 602 and a control unit 603, wherein:

[0115] The acquisition unit 601 is used to acquire a surrounding environment image and establish a 3D area model of the area to be detected according to the surrounding environment image;

[0116] The execution unit 602 is used to divide the area to be detected into multiple partitions, and perform the following operations for each of the partitions: randomly calibrate at least one first detection point; calculate the radius distance between each of the first detection points and the target object, and form multiple sub-regions between the at least one first detection point and the target object; determine the target detection point corresponding to the partition according to the radius distance and the multiple sub-regions; determine the radiation risk detection scheme corresponding to each of the partitions according to the target detection point corresponding to each of the partitions;

[0117] The control unit 603 is used to control the radiation detector to perform a detection operation according to the radiation risk detection scheme, and obtain a detection result data set corresponding to each partition.

[0118] In a possible example, in determining the target detection point corresponding to the partition according to the radius distance and the multiple sub-areas, the execution unit 602 is specifically configured to:

[0119] If the radius distance indicates that the multiple sub-areas corresponding to the partition are all within the same radius range, determining the change range of the surface height of the partition according to the 3D area model;

[0120] If the variation of the subarea ground surface height is greater than or equal to a preset threshold, setting a position greater than or equal to the preset threshold as a second detection point, and setting the second detection point and at least one of the first detection points as the target detection point;

[0121] If the variation of the ground surface height of the partition is less than the preset threshold, the at least one first detection point is used as the target detection point in the partition.

[0122] In a possible example, the execution unit 602 is specifically used to:

[0123] If some of the multiple sub-areas corresponding to the partition indicated by the radius distance are located in the same radius range, and another part of the sub-areas are located in other radius ranges, a third detection point is randomly set in each of the other radius ranges to obtain at least one third detection point;

[0124] Determining the change range of the ground surface height within the same other radius according to the 3D regional model;

[0125] If the change in the ground height within the same other radius is greater than or equal to the preset threshold, a fourth detection point is set for a position greater than or equal to the preset threshold, and at least one of the first detection points, at least one of the third detection points, and the fourth detection point are set as the target detection point, or at least one of the first detection points, the second detection point, at least one of the third detection points, and the fourth detection point are set as the target detection point.

[0126] In a possible example, the execution unit 602 is specifically used to:

[0127] If the change in the ground height within the same other radius is less than the preset threshold, at least one of the first detection points and at least one of the third detection points are set as the target detection points, or at least one of the first detection points, the second detection point and the at least one third detection point are set as the target detection points.

[0128] In a possible example, in controlling the radiation detector to perform a detection operation according to the radiation risk detection scheme to obtain a detection result data set corresponding to each partition, the control unit 603 is specifically used to:

[0129] Generate a prompt instruction according to the target detection point corresponding to each partition, wherein the prompt instruction is used to prompt the user to move to the target detection point in the corresponding partition;

[0130] When it is detected that the user has arrived at the target detection point, a detection instruction is sent to the radiation detector to control the radiation detector to perform the detection operation, and the detection data of the radiation detector is acquired to obtain the detection result data set corresponding to each partition.

[0131] In a possible example, in terms of dividing the area to be detected into a plurality of partitions, the execution unit 602 is specifically configured to:

[0132] The area to be inspected is divided into a first subarea at a first altitude range and used for farming, a second subarea bordering the first subarea at a second altitude range and used for traffic, and a third subarea at a third altitude and used for landscape.

[0133] In a possible example, the execution unit 602 is further configured to:

[0134] According to the detection result data sets corresponding to the first partition, the second partition and the third partition respectively, and the water flow impact terrain distribution characteristics constrained by the first height range, the second height range and the third height range respectively, the surface radiation contamination remediation strategies corresponding to the first partition, the second partition and the third partition respectively are determined.

[0135] It can be seen that the radiation risk information processing device described in the embodiment of the present application obtains the surrounding environment image, and establishes a 3D area model of the area to be detected based on the surrounding environment image; divides the area to be detected into multiple partitions, and performs the following operations for each of the partitions: randomly calibrates at least one first detection point; calculates the radius distance between each of the first detection points and the target object, and forms multiple sub-areas between the at least one first detection point and the target object; determines the target detection point corresponding to the partition based on the radius distance and the multiple sub-areas; determines the radiation risk detection scheme corresponding to each partition based on the target detection point corresponding to each partition; according to the radiation risk detection scheme, controls the radiation detector to perform the detection operation, and obtains the detection result data set corresponding to each partition. In this way, radiation detection can be assisted by smart wearable devices, which is conducive to improving the intelligence and comprehensiveness of smart wearable devices.

[0136] It can be understood that the functions of each program module of the radiation risk information processing device of this embodiment can be specifically implemented according to the method in the above method embodiment, and its specific implementation process can refer to the relevant description of the above method embodiment, which will not be repeated here.

[0137] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, the computer program enables a computer to execute part or all of the steps of any method recorded in the above method embodiments, and the above computer includes a smart wearable device.

[0138] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes a smart wearable device.

[0139] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0140] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0141] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0142] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0143] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0144] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially 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, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0145] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0146] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for processing radiation risk information, characterized in that: Applied to a smart wearable device, the smart wearable device is communicatively connected with a radiation detector; the method comprises: Acquire a surrounding environment image, and establish a 3D area model of the area to be detected based on the surrounding environment image; Divide the area to be detected into multiple partitions, and perform the following operations for each partition: Randomly calibrating at least one first detection point; Calculating a radius distance between each of the first detection points and the target object, wherein a plurality of sub-areas are formed between the at least one first detection point and the target object; Determining a target detection point corresponding to the partition according to the radius distance and the multiple sub-areas; Determining a radiation risk detection scheme corresponding to each of the partitions according to the target detection points corresponding to each of the partitions; According to the radiation risk detection scheme, controlling the radiation detector to perform a detection operation to obtain a detection result data set corresponding to each partition; Wherein, determining the target detection point corresponding to the partition according to the radius distance and the multiple sub-areas includes: if the radius distance indicates that the multiple sub-areas corresponding to the partition are all located in the same radius range, judging the change range of the surface height of the partition according to the 3D area model; if the change range of the surface height of the partition is greater than or equal to a preset threshold, setting the position greater than or equal to the preset threshold as a second detection point, and setting the second detection point and the at least one first detection point as the target detection point; if the change range of the surface height of the partition is less than the preset threshold, setting the at least one first detection point as the target detection point in the partition; or, If the radius distance indicates that some of the multiple sub-areas corresponding to the partition are located in the same radius range, and another part of the sub-areas are located in other radius ranges, then a third detection point is randomly set in each of the other radius ranges to obtain at least one third detection point; the variation range of the ground surface height within the same other radius range is determined according to the 3D area model; if the variation range of the ground surface height within the same other radius range is greater than or equal to the preset threshold, then a fourth detection point is set for a position greater than or equal to the preset threshold, and the at least one first detection point, the at least one third detection point and the fourth detection point are set as the target detection point, or the at least one first detection point, the second detection point, the at least one third detection point and the fourth detection point are set as the target detection point; or, If the change in the ground height within the same other radius is less than the preset threshold, the at least one first detection point and the at least one third detection point are set as the target detection point, or the at least one first detection point, the second detection point and the at least one third detection point are set as the target detection point.

2. The method according to claim 1, characterized in that According to the radiation risk detection scheme, controlling the radiation detector to perform a detection operation to obtain a detection result data set corresponding to each partition includes: Generate a prompt instruction according to the target detection point corresponding to each partition, wherein the prompt instruction is used to prompt the user to move to the target detection point in the corresponding partition; When it is detected that the user has arrived at the target detection point, a detection instruction is sent to the radiation detector to control the radiation detector to perform the detection operation, and the detection data of the radiation detector is acquired to obtain the detection result data set corresponding to each partition.

3. The method according to claim 2, characterized in that The step of dividing the area to be detected into a plurality of partitions comprises: The area to be inspected is divided into a first subarea at a first altitude range and used for farming, a second subarea bordering the first subarea at a second altitude range and used for traffic, and a third subarea at a third altitude and used for landscape.

4. The method according to claim 3, characterized in that: The method further comprises: According to the detection result data sets corresponding to the first partition, the second partition and the third partition respectively, and the water flow impact terrain distribution characteristics constrained by the first height range, the second height range and the third height range respectively, the surface radiation contamination remediation strategies corresponding to the first partition, the second partition and the third partition respectively are determined.

5. A radiation risk information processing device, characterized in that: Applied to a smart wearable device, the smart wearable device is communicatively connected with a radiation detector; the device comprises: An acquisition unit, used for acquiring a surrounding environment image and establishing a 3D area model of the area to be detected according to the surrounding environment image; An execution unit, used for dividing the area to be detected into a plurality of partitions, and performing the following operations for each of the partitions: randomly calibrating at least one first detection point; calculating the radius distance between each of the first detection points and the target object, wherein a plurality of sub-regions are formed between the at least one first detection point and the target object; determining the target detection point corresponding to the partition according to the radius distance and the plurality of sub-regions; determining the radiation risk detection scheme corresponding to each of the partitions according to the target detection point corresponding to each of the partitions; A control unit, configured to control the radiation detector to perform a detection operation according to the radiation risk detection scheme, and obtain a detection result data set corresponding to each of the partitions; Wherein, determining the target detection point corresponding to the partition according to the radius distance and the multiple sub-areas includes: if the radius distance indicates that the multiple sub-areas corresponding to the partition are all located in the same radius range, judging the change range of the surface height of the partition according to the 3D area model; if the change range of the surface height of the partition is greater than or equal to a preset threshold, setting the position greater than or equal to the preset threshold as a second detection point, and setting the second detection point and the at least one first detection point as the target detection point; if the change range of the surface height of the partition is less than the preset threshold, setting the at least one first detection point as the target detection point in the partition; or, If the radius distance indicates that some of the multiple sub-areas corresponding to the partition are located in the same radius range, and another part of the sub-areas are located in other radius ranges, then a third detection point is randomly set in each of the other radius ranges to obtain at least one third detection point; the variation range of the ground surface height within the same other radius range is determined according to the 3D area model; if the variation range of the ground surface height within the same other radius range is greater than or equal to the preset threshold, then a fourth detection point is set for a position greater than or equal to the preset threshold, and the at least one first detection point, the at least one third detection point and the fourth detection point are set as the target detection point, or the at least one first detection point, the second detection point, the at least one third detection point and the fourth detection point are set as the target detection point; or, If the change in the ground height within the same other radius is less than the preset threshold, the at least one first detection point and the at least one third detection point are set as the target detection point, or the at least one first detection point, the second detection point and the at least one third detection point are set as the target detection point.

6. A smart wearable device, characterized in that: The method comprises a processor and a memory, wherein the memory is used to store one or more programs and is configured to be executed by the processor, wherein the program comprises instructions for executing the steps in the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: A computer program for electronic data exchange is stored, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 4.

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