Radiation-resistant camera coordination control method based on internet of things

Abstract

The application relates to the technical field of data communication, and discloses a radiation-resistant camera coordination control method based on the Internet of Things, which comprises the following steps: establishing a safe communication link between a radiation-resistant camera device and a coordination server to obtain device connection state data; determining a priority weight; assigning tasks to the radiation-resistant camera device according to the device connection state data and the priority weight to obtain a task coordination instruction; generating a control parameter set based on the task coordination instruction, sending the control parameter set to the radiation-resistant camera device to obtain a synchronization signal broadcast; generating synchronization control data according to the control parameter set and a local clock of the synchronization signal broadcast; synchronously controlling and collecting the radiation-resistant camera device according to the synchronization control data, and performing aggregation processing on the data of the synchronous control and collection to obtain a target coordination output result; and the application can improve the efficiency of radiation-resistant camera coordination control.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data communication, and in particular to a radiation-resistant camera coordination control method based on Internet of Things. BACKGROUND

[0002] The prior art has significant deficiencies in the communication link establishment and device priority determination links of the radiation-resistant camera coordination control based on Internet of Things. The safe communication link is not established through the double verification of the device unique identifier and the digital certificate, and only simple identity authentication or non-encrypted transmission is adopted, resulting in low device connection security and the risk of data leakage or illegal control of the device. At the same time, when determining the priority weight of the device, the real-time environmental radiation intensity and the device health state are not combined for quantitative calculation, and only fixed sorting or single index is used to determine the priority, which cannot accurately reflect the actual adaptive capacity of the device in different radiation environments, so that the device in a high radiation area or with poor health state may be assigned a task beyond its carrying capacity, reducing the reliability of the overall coordination control.

[0003] The prior art has significant deficiencies in the task allocation, synchronization control and data processing links. In the task allocation, the operable devices are not selected based on the device connection state, and the matching degree between the device and the task is not calculated through the adaptive degree scoring formula, only the task is randomly allocated, which easily leads to device overload or repeated regional coverage, and conflict detection and resource balance verification are not performed, further exacerbating the irrationality of task allocation. In the synchronization control stage, the device local clock deviation is not adjusted based on the reference timestamp, and the acquisition time point sequence without time overlap is not generated, only the acquisition is triggered by a unified signal, resulting in chaotic multi-device acquisition timing and out-of-sync data in space and time. In the data aggregation processing, low-quality image frames are not excluded or multi-source data is not spliced and fused according to the rules, only the images are simply summarized, and the output result generated lacks completeness and accuracy, which cannot meet the needs of high efficiency and accuracy of the radiation-resistant camera coordination control. SUMMARY

[0004] The present application provides a radiation-resistant camera coordination control method based on Internet of Things to solve the problems raised in the background art.

[0005] To achieve the above-mentioned purpose, the present application provides a radiation-resistant camera coordination control method based on Internet of Things, comprising:

[0006] S1, establishing a secure communication link between the radiation-resistant camera device and the coordination server through the Internet of Things platform, and obtaining the device connection state data of the radiation-resistant camera device;

[0007] S2, determining the priority weight of the radiation-resistant camera device according to the real-time environmental radiation intensity and the device health state of the radiation-resistant camera device;

[0008] S3. Based on the device connection status data and the priority weight, assign tasks to the radiation-resistant camera device to obtain task coordination instructions for the radiation-resistant camera device, including:

[0009] In the coordination server, based on the device connection status data, radiation-resistant camera devices that are currently in an operable state are filtered out to obtain a candidate device list of the radiation-resistant camera devices;

[0010] The task requirements of the data acquisition task to be executed are parsed to obtain the task feature descriptor of the data acquisition task to be executed.

[0011] The priority weights of the radiation-resistant camera devices in the candidate device list are matched with the task feature descriptors to calculate the matching degree, thereby determining the suitability score of the radiation-resistant camera device for the current task. The formula for calculating the suitability score is as follows:

[0012] ;

[0013] In the formula, For the first The compatibility rating of each radiation-resistant camera. This refers to the task requirement vector in the task feature descriptor. This refers to the device capability vector in the task feature descriptor. For modulo symbol, This is the vector dot product operator. The coefficient contributing to the matching degree. Contribution coefficient to priority level The priority weight;

[0014] Based on the suitability score, a specific acquisition sub-task is assigned to each candidate device in the candidate device list to obtain the initial task allocation scheme for the radiation-resistant camera device.

[0015] The initial task allocation scheme is subjected to conflict detection and resource balance verification to ensure that there is no equipment overload and no area coverage overlap, and the task coordination instructions of the radiation-resistant camera equipment are obtained.

[0016] S4. Generate a set of control parameters for the radiation-resistant camera device based on the task coordination instruction, and send the set of control parameters to the radiation-resistant camera device to obtain the synchronization signal broadcast of the radiation-resistant camera device;

[0017] S5. Generate synchronization control data for the radiation-resistant camera device based on the set of control parameters and the local clock broadcast by the synchronization signal;

[0018] S6. Based on the synchronous control data, the radiation-resistant camera device is synchronously controlled and collected, and the collected data is aggregated to obtain the target coordination output result of the radiation-resistant camera device.

[0019] In a preferred embodiment, establishing a secure communication link between the radiation-resistant camera device and the coordination server via an IoT platform to obtain device connection status data of the radiation-resistant camera device includes:

[0020] The radiation-resistant camera device sends a device registration request to the coordination server, wherein the device registration request includes: the unique identifier and digital certificate of the radiation-resistant camera device;

[0021] The coordination server receives the device registration request, verifies the legality of the digital certificate and the authenticity of the unique identifier, and generates session key establishment parameters for the radiation-resistant camera device.

[0022] Based on the session key establishment parameters, the radiation-resistant camera device and the coordination server exchange keys to obtain a secure communication link between the radiation-resistant camera device and the coordination server.

[0023] In a preferred embodiment, determining the priority weight of the radiation-resistant camera device based on the real-time environmental radiation intensity and device health status includes:

[0024] Calculate the initial weight of the radiation-resistant camera device based on its current radiation intensity value and current health status value.

[0025] The initial weights are normalized to obtain the standardized weights of the radiation-resistant camera device.

[0026] By removing outliers from the standardized weights, the priority weights of the radiation-resistant camera equipment are obtained.

[0027] In a preferred embodiment, the initial weights are calculated using the following formula:

[0028] ;

[0029] In the formula, The initial weights, The preset radiation intensity coefficient, The preset health status coefficient, The reference radiation intensity value, The current radiation intensity value, As a baseline health status value, This refers to the current health status value.

[0030] In a preferred embodiment, the step of generating a set of control parameters for the radiation-resistant camera device based on the task coordination instructions, and sending the set of control parameters to the radiation-resistant camera device to obtain a synchronization signal broadcast from the radiation-resistant camera device includes:

[0031] Extract the task execution time window and image acquisition quality requirements from the task coordination instructions to generate the basic control parameter framework for the radiation-resistant camera device;

[0032] Based on the aforementioned basic control parameter framework and the hardware characteristic database of the radiation-resistant camera device, personalized control parameters are generated for the radiation-resistant camera device, resulting in the initial control parameter set of the radiation-resistant camera device.

[0033] The initial set of control parameters is subjected to device compatibility verification to obtain the control parameter set of the radiation-resistant camera device;

[0034] The control parameter set is distributed to the corresponding radiation-resistant camera device through the secure communication link, and the parameter confirmation signal returned by the radiation-resistant camera device is received.

[0035] Based on the parameter confirmation signal, a synchronization signal for the radiation-resistant camera device is generated, and the synchronization signal is broadcast to the radiation-resistant camera device through the Internet of Things platform.

[0036] In a preferred embodiment, generating synchronization control data for the radiation-resistant camera device based on the set of control parameters and the local clock broadcast by the synchronization signal includes:

[0037] The local clock of the radiation-resistant camera device is adjusted for deviation based on the reference timestamp in the set of control parameters.

[0038] Read the device-specific configuration parameters from the control parameter set to obtain the individual acquisition plan for the radiation-resistant camera device;

[0039] Based on the local clock adjusted for deviation and the individual acquisition plan, the acquisition time point sequence of the radiation-resistant camera equipment is determined;

[0040] Synchronization control data for the radiation-resistant camera device is generated based on the non-overlapping sequence of acquisition time points.

[0041] In a preferred embodiment, the step of synchronously controlling and acquiring data from the radiation-resistant camera device based on the synchronous control data includes:

[0042] Based on the execution timing diagram in the synchronous control data, the image acquisition function of the radiation-resistant camera device is started under a unified time reference.

[0043] Add timestamps and device identifiers to the collected standardized image data to obtain the synchronous acquisition data packet of the radiation-resistant camera device;

[0044] The synchronously acquired data packets are transmitted to the coordination server via the secure communication link.

[0045] In a preferred embodiment, the aggregation processing of the synchronously acquired data to obtain the target coordination output result of the radiation-resistant camera device includes:

[0046] Based on the timestamp and device identifier in the synchronous acquisition data packet, the acquisition data is spatiotemporally aligned to obtain the multi-source image data of the radiation-resistant camera device.

[0047] Remove image frames from the multi-source image data that do not meet the quality requirements;

[0048] The qualified image data are stitched and fused according to preset rules to obtain a panoramic monitoring image of the multi-source image data;

[0049] Metadata identifiers are added to the panoramic monitoring image to obtain the target coordination output result of the radiation-resistant camera device.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] 1. This invention constructs a secure communication link between radiation-resistant camera devices and a coordination server through an IoT platform. Communication security is ensured through device unique identifiers, digital certificate verification, and session key exchange. Simultaneously, it accurately acquires device connection status data, laying a reliable connection foundation for subsequent coordination and control. Furthermore, by combining real-time environmental radiation intensity and device health status, initial weights are calculated using standardized formulas and then normalized and outlier-removing to obtain priority weights. This accurately reflects the device's adaptability in different environments, providing a scientific basis for task allocation and significantly improving the security of device coordination and control and the accuracy of priority determination.

[0052] 2. This invention filters operable devices based on their connection status, calculates the matching degree using a suitability scoring formula by combining task feature descriptors and priority weights, generates an initial task allocation scheme, and obtains task coordination instructions through conflict detection and resource balancing verification to ensure reasonable task allocation and no resource waste. Based on the task coordination instructions, a set of control parameters containing personalized parameters is generated, distributed to devices and a synchronization signal is broadcast after compatibility verification. Then, the local clock deviation is adjusted by a reference timestamp to generate a sequence of acquisition time points without time overlap, realizing synchronous acquisition by multiple devices. Finally, the acquired data is spatiotemporally aligned, low-quality frames are removed, and stitched together to generate a panoramic monitoring image with metadata identification, comprehensively improving the task allocation efficiency, synchronous acquisition accuracy, and data output quality of radiation-resistant camera coordinated control. Attached Figure Description

[0053] Figure 1 A flowchart illustrating a coordinated control method for radiation-resistant cameras based on the Internet of Things (IoT) according to an embodiment of the present invention;

[0054] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0055] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0056] This application provides an IoT-based coordinated control method for radiation-resistant cameras. The executing entity of this IoT-based coordinated control method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the IoT-based coordinated control method for radiation-resistant cameras can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cluster of cloud servers. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0057] Reference Figure 1 The diagram shown is a flowchart illustrating a coordinated control method for radiation-resistant cameras based on the Internet of Things (IoT) according to an embodiment of the present invention. In this embodiment, the coordinated control method for radiation-resistant cameras based on the IoT includes:

[0058] S1. Establish a secure communication link between the radiation-resistant camera device and the coordination server through the Internet of Things platform to obtain the device connection status data of the radiation-resistant camera device.

[0059] In this embodiment of the invention, the step of establishing a secure communication link between the radiation-resistant camera device and the coordination server through an IoT platform to obtain device connection status data of the radiation-resistant camera device includes:

[0060] The radiation-resistant camera device sends a device registration request to the coordination server, wherein the device registration request includes: the unique identifier and digital certificate of the radiation-resistant camera device;

[0061] The coordination server receives the device registration request, verifies the legality of the digital certificate and the authenticity of the unique identifier, and generates session key establishment parameters for the radiation-resistant camera device.

[0062] Based on the session key establishment parameters, the radiation-resistant camera device and the coordination server exchange keys to obtain a secure communication link between the radiation-resistant camera device and the coordination server.

[0063] Specifically, after the radiation-resistant camera device is started, it will automatically generate a device registration request containing its own unique identifier and digital certificate. The unique identifier is a globally unique string that is pre-generated when the device leaves the factory and is used to uniquely identify the device in the Internet of Things (IoT) platform. The digital certificate is an electronic document issued by an authoritative certificate authority, which contains the device's public key, device information, and the certificate authority's signature. Subsequently, the radiation-resistant camera device sends the device registration request to the coordination server through the communication protocol provided by the IoT platform.

[0064] Furthermore, after receiving the device registration request from the radiation-resistant camera device, the coordination server first extracts the digital certificate from the request. It verifies the legality of the digital certificate by verifying the signature of the certificate authority, that is, checking whether the digital certificate was issued by a trusted certificate authority and has not been tampered with. At the same time, the server compares the unique identifier in the request with a pre-stored list of device identifiers to verify the authenticity of the unique identifier and confirm that the device is an authorized access device. After the verification is successful, the coordination server generates session key establishment parameters for the radiation-resistant camera device according to the preset key generation rules. These parameters are used for the subsequent establishment of session keys between the two parties.

[0065] Furthermore, the radiation-resistant camera device and the coordination server exchange keys based on the generated session key establishment parameters. The specific process is as follows: the coordination server sends the session key establishment parameters to the radiation-resistant camera device, which processes the parameters using its own private key to generate its own session key portion and sends the processed result back to the coordination server. Upon receiving the result, the coordination server, in conjunction with its own reserved parameter portion, calculates the same session key with the radiation-resistant camera device. Subsequently, both parties use this session key to encrypt and decrypt the transmitted data during communication, thereby establishing a secure communication link between the radiation-resistant camera device and the coordination server. Data transmitted through this link can ensure confidentiality and integrity, preventing it from being stolen or tampered with by unauthorized parties.

[0066] In summary, radiation-resistant camera devices send registration requests containing a unique identifier and a digital certificate, providing dual identification for the device. The unique identifier ensures that the device can be accurately distinguished in the IoT platform, avoiding confusion with other devices, while the digital certificate provides authoritative proof of the device's authenticity, ensuring the legitimacy of the accessed device from the source and preventing unauthorized devices from accessing the system.

[0067] In summary, the coordination server verifies the legitimacy of digital certificates and the authenticity of unique identifiers. It can confirm that digital certificates have not been tampered with and that their source is trustworthy by verifying the certificate authority's signature, and confirm that the device is an authorized device by comparing it with a pre-stored identifier list. This effectively blocks registration requests from unauthorized devices, reduces the risk of malicious intrusion or data leakage into the system, and ensures the security of communication link establishment.

[0068] In summary, by establishing parameters based on the session key to exchange keys and form a secure communication link, all subsequent data transmitted between the radiation-resistant camera equipment and the coordination server is encrypted using the jointly generated session key, ensuring that the data is not stolen or tampered with during transmission. At the same time, this link can stably transmit device connection status data, providing a reliable connection status basis for subsequent device coordination and control, and improving the overall stability of coordination and control.

[0069] S2. Determine the priority weight of the radiation-resistant camera device based on the real-time environmental radiation intensity and device health status.

[0070] In this embodiment of the invention, determining the priority weight of the radiation-resistant camera device based on the real-time environmental radiation intensity and device health status includes:

[0071] Calculate the initial weight of the radiation-resistant camera device based on its current radiation intensity value and current health status value.

[0072] The initial weights are normalized to obtain the standardized weights of the radiation-resistant camera device.

[0073] By removing outliers from the standardized weights, the priority weights of the radiation-resistant camera equipment are obtained.

[0074] The formula for calculating the initial weights is as follows:

[0075] ;

[0076] In the formula, The initial weights, The preset radiation intensity coefficient, The preset health status coefficient, The reference radiation intensity value, The current radiation intensity value, As a baseline health status value, This refers to the current health status value.

[0077] Specifically, the current radiation intensity value and current health status value of the radiation-resistant camera equipment are acquired. The current radiation intensity value is collected in real time by the equipment's built-in radiation sensor and transmitted to the processing module. This value directly reflects the radiation intensity of the environment in which the equipment is located. The current health status value is obtained through the equipment's internal status monitoring unit. The monitoring unit monitors the operating parameters of key components such as lens performance, circuit stability, and data transmission module in real time, and converts the detection results into corresponding values ​​according to preset standards, which are the current health status values. The processing module combines the current radiation intensity value and the current health status value according to preset calculation rules. For example, a higher ambient radiation intensity corresponds to a higher calculation weight, and a better equipment health status also corresponds to a corresponding calculation weight. The value obtained through this combined calculation is the initial weight of the radiation-resistant camera equipment.

[0078] Furthermore, when normalizing the obtained initial weights, the initial weights of all radiation-resistant camera devices involved in the calculation are first counted, and the maximum and minimum initial weights are identified. The processing module subtracts the minimum initial weight from the initial weight of each radiation-resistant camera device, obtaining the difference between the initial weight and the minimum value. This difference is then divided by the difference between the maximum and minimum initial weights, resulting in a value within a fixed range. This value is used as the normalized result for that radiation-resistant camera device, which is the standardized weight of the radiation-resistant camera device. This process ensures that the weights of different devices have a unified comparison scale.

[0079] Furthermore, when removing outliers from the standardized weights, the criteria for identifying outliers are first determined. This criterion is calculated based on the standardized weights of all radiation-resistant camera devices. For example, the average of all standardized weights is calculated first, and then the deviation of each standardized weight from the average is calculated. A fixed deviation range is set as the normal range, and standardized weights exceeding this range are considered outliers. The processing module compares the standardized weight of each radiation-resistant camera device with the normal range one by one, removing standardized weights that exceed the normal range and retaining those within the normal range. These retained standardized weights are the priority weights of the radiation-resistant camera devices, which can be directly used for subsequent priority ranking of the devices.

[0080] Specifically, the preset radiation intensity coefficient is a fixed value pre-set based on historical data and actual application scenarios, used to reflect the importance of radiation intensity in the initial weight calculation; the preset health status coefficient is also a fixed value pre-determined based on historical experience and specific needs, used to reflect the degree of influence of health status on the initial weight. The baseline radiation intensity value is a standard radiation intensity value determined after multiple tests and verifications, serving as a reference benchmark for measuring the current radiation intensity; the current radiation intensity value is the actual radiation intensity data obtained through real-time detection of the target area by radiation detection equipment. The baseline health status value is a set standard health status reference value used to assess the quality of the current health status; the current health status value is the actual health status data obtained through real-time monitoring of the monitored object by health monitoring equipment.

[0081] Furthermore, the significance of the formula is to comprehensively consider the relationship between the current radiation intensity and the reference radiation intensity, the relationship between the current health status and the reference health status, and combine the preset radiation intensity coefficient and health status coefficient to calculate the initial weight, thereby quantifying the comprehensive evaluation result under the combined effect of radiation intensity and health status, and providing a basis for subsequent decision-making or analysis based on this weight.

[0082] Furthermore, the formula shows a trend where the smaller the current radiation intensity value, the larger the ratio to the reference radiation intensity value, leading to an increase in the initial weight under the influence of the radiation intensity coefficient. Similarly, the larger the current health status value, the larger the ratio to the reference health status value, also leading to an increase in the initial weight under the influence of the health status coefficient. Conversely, the larger the current radiation intensity value or the smaller the current health status value, the smaller the corresponding ratio, resulting in a decrease in the initial weight. Overall, the closer the current radiation intensity is to or below the reference radiation intensity, and the closer the current health status is to or better than the reference health status, the larger the initial weight value.

[0083] In summary, the initial weights are calculated by combining the current radiation intensity value and the current health status value, which quantitatively reflects the adaptability of radiation-resistant camera equipment in real-time environments. The current radiation intensity value reflects the radiation pressure of the environment in which the equipment is located, while the current health status value reflects the equipment's own operational reliability. The combined calculation of the two can avoid the one-sidedness of judging the equipment priority based on a single indicator, and provide comprehensive basic data support for the subsequent determination of priority weights.

[0084] In summary, normalizing the initial weights to obtain standardized weights can eliminate the incomparability caused by differences in the numerical range of the initial weights of different devices, unify the weights of all devices within a fixed comparison scale, make the priority evaluation standards of different devices consistent, avoid the impact of differences in numerical magnitude on the fairness and accuracy of priority determination, and lay a unified benchmark for subsequent outlier removal and priority ranking.

[0085] In summary, removing outliers from the standardized weights to obtain priority weights can eliminate weight deviations caused by special circumstances such as temporary equipment failures and sensor errors. This ensures that the final priority weights can truly reflect the actual adaptability of the equipment, avoid misleading task allocation with outlier weights, make equipment scheduling based on these weights more in line with actual needs, and improve the reliability of coordinated control of radiation-resistant camera equipment.

[0086] In summary, the formula, through preset radiation intensity coefficients and health status coefficients, can flexibly adjust the influence ratio of real-time environmental radiation intensity and equipment health status in the initial weight calculation. It can optimize the weight calculation logic according to actual application scenarios, avoid the limitations of single-dimensional evaluation, and make the initial weights more in line with actual needs.

[0087] In summary, by introducing the ratio of the baseline radiation intensity value to the current radiation intensity value, and the ratio of the baseline health status value to the current health status value, the difference between the current environment and equipment status and the baseline can be quantified. When the current radiation intensity is lower than the baseline value, the corresponding ratio increases and the initial weight is increased. When the current health status is better than the baseline value, the corresponding ratio also increases and the initial weight is increased. This can intuitively reflect the equipment's adaptability advantage in the current scenario and provide an objective and quantifiable basis for calculating the initial weight.

[0088] In summary, the formula integrates radiation intensity and health status-related parameters in a linear combination manner. The calculation logic is clear and traceable, which facilitates the coordination of the server to execute calculations quickly and allows for reverse verification of the weight calculation process through parameters. This avoids calculation errors or uninterpretable results caused by complex algorithms, ensuring the accuracy and reliability of the initial weight calculation and providing high-quality basic data for subsequent standardization and outlier removal.

[0089] S3. Based on the device connection status data and the priority weight, the task of the radiation-resistant camera device is assigned to obtain the task coordination instruction of the radiation-resistant camera device.

[0090] In this embodiment of the invention, the step of allocating tasks to the radiation-resistant camera device based on the device connection status data and the priority weight to obtain the task coordination instruction for the radiation-resistant camera device includes:

[0091] In the coordination server, based on the device connection status data, radiation-resistant camera devices that are currently in an operable state are filtered out to obtain a candidate device list of the radiation-resistant camera devices;

[0092] The task requirements of the data acquisition task to be executed are parsed to obtain the task feature descriptor of the data acquisition task to be executed.

[0093] The priority weights of the radiation-resistant camera devices in the candidate device list are matched with the task feature descriptors to calculate the matching degree and determine the suitability score of the radiation-resistant camera devices for the current task.

[0094] Based on the suitability score, a specific acquisition sub-task is assigned to each candidate device in the candidate device list to obtain the initial task allocation scheme for the radiation-resistant camera device.

[0095] The initial task allocation scheme is subjected to conflict detection and resource balancing verification to ensure that there is no equipment overload and no overlap in area coverage, thereby obtaining the task coordination instructions for the radiation-resistant camera equipment.

[0096] The formula for calculating the fit score is as follows:

[0097] ;

[0098] In the formula, For the first The compatibility rating of each radiation-resistant camera. This refers to the task requirement vector in the task feature descriptor. This refers to the device capability vector in the task feature descriptor. For modulo symbol, This is the vector dot product operator. The coefficient contributing to the matching degree. Contribution coefficient to priority level The priority weight is...

[0099] Specifically, in the coordination server, when filtering operable radiation-resistant camera devices based on device connection status data, the online, communication, and hardware status information of all devices is extracted to determine whether the operability conditions are met, and the devices that meet the conditions are organized into a candidate device list of radiation-resistant camera devices.

[0100] Furthermore, when parsing the task requirements of the data acquisition task to be performed, the requirements such as acquisition area, resolution, frequency, and radiation threshold are obtained, transformed into structured descriptive information, and integrated to form the task feature descriptor of the data acquisition task to be performed.

[0101] Furthermore, when calculating the suitability score between candidate devices and tasks, the priority weight of each device is extracted, and the weights of each dimension are compared with the corresponding requirements of the task feature descriptor. The matching scores of each dimension are assigned according to the comparison results and added together to obtain the suitability score of each radiation-resistant camera device for the current task.

[0102] Furthermore, when allocating acquisition sub-tasks based on the suitability score, candidate devices are sorted by score, the total task is split into sub-tasks, complex or critical sub-tasks are assigned to high-scoring devices, and simple or minor sub-tasks are assigned to low-scoring devices. The corresponding relationships are then organized to form the initial task allocation scheme for radiation-resistant camera devices.

[0103] Furthermore, when verifying the initial task allocation scheme, it checks for time overlaps or regional conflicts, calculates the equipment workload to determine if there is overload, and after adjusting for conflicts and overload issues, the final allocation relationship is transformed into a task coordination instruction for radiation-resistant camera equipment containing equipment identifiers and sub-task details.

[0104] Specifically, the task requirement vector originates from the task feature descriptor of the acquisition task to be performed. Task requirements such as acquisition area range, image resolution, acquisition frequency, and radiation intensity threshold are extracted from the task feature descriptor. These requirements are then converted into numerical vector elements and combined to form the task requirement vector.

[0105] Furthermore, the device capability vector also originates from the task feature descriptor. From the candidate radiation-resistant camera device parameters corresponding to the task feature descriptor, capability indicators such as the effective acquisition area, maximum image resolution, highest acquisition frequency, and radiation tolerance limit of the device are extracted. These indicators are then converted into numerical vector elements and combined to form the device capability vector.

[0106] Furthermore, the matching contribution coefficient is a fixed value pre-set based on historical task allocation experience and actual application scenarios, used to adjust the degree of influence of the matching result between task requirements and equipment capabilities on the suitability score; the priority contribution coefficient is also a fixed value pre-determined based on historical data and task importance requirements, used to adjust the proportion of priority weight in the suitability score.

[0107] Furthermore, the priority weight is a value obtained after the candidate device list is selected, based on the performance of the radiation-resistant camera device, the quality of past task completion, and other dimensions, and is directly used for the suitability score calculation.

[0108] Furthermore, the formula comprehensively considers the degree of matching between task requirements and equipment capabilities, as well as the priority weight of the equipment itself, to calculate the suitability score for each radiation-resistant camera device. By quantifying the matching effect between tasks and equipment through vector dot product and modulo operations, and then adjusting the influence of the matching results and priority weights using preset contribution coefficients, the final suitability score can serve as the core basis for task allocation, ensuring that the allocated tasks are highly compatible with equipment capabilities and meet priority requirements.

[0109] Furthermore, the formula shows that the higher the matching degree between the task requirement vector and the equipment capability vector (i.e., the closer their vector directions), the larger the result obtained through the dot product and modulo operation. Under the influence of the matching degree contribution coefficient, the fit score will increase accordingly. Similarly, the higher the equipment priority weight, the greater the fit score will be under the influence of the priority contribution coefficient. Conversely, if the task and equipment matching degree is low or the equipment priority weight is low, the fit score will decrease. Overall, the radiation-resistant camera equipment with a higher matching degree between task requirements and equipment capabilities, and a higher equipment priority weight, will have a larger fit score.

[0110] In summary, the system filters operable devices based on device connection status data to form a candidate device list. This process can exclude devices that are offline, have communication failures, or hardware malfunctions, ensuring that devices participating in task allocation have basic execution capabilities. This avoids assigning tasks to devices that are not functioning properly, which could lead to task delays, and provides a reliable device pool to support subsequent task allocation.

[0111] In summary, parsing task requirements to generate task feature descriptors can transform vague task requirements into structured parameters, clarify the specific requirements of the task on the device capabilities, provide a clear and quantifiable basis for comparison of the suitability between computing devices and tasks, and avoid allocation deviations caused by vague task requirements.

[0112] In summary, by calculating the fit score through priority weights and task feature descriptors, the device's adaptability in the real-time environment and the specific requirements of the task can be combined to quantitatively evaluate the degree of matching of the device with the current task. This makes task allocation no longer dependent on subjective judgment, but rather on selecting suitable devices based on objective scores, thereby improving the scientific nature and accuracy of task allocation.

[0113] In summary, assigning sub-tasks based on suitability scores to form an initial plan allows devices with high suitability to undertake critical and complex sub-tasks, while devices with low suitability can undertake secondary sub-tasks. This achieves precise matching between tasks and device capabilities, avoids resource waste or device overload, and improves overall task execution efficiency.

[0114] In summary, conflict detection and resource balancing verification of the initial plan can promptly identify and resolve issues such as overlapping equipment times, duplicate area coverage, or equipment overload, ensuring the feasibility of the final task coordination instructions, avoiding task execution interruptions due to plan defects, and guaranteeing the stable progress of collaborative data acquisition tasks using radiation-resistant camera equipment.

[0115] In summary, the formula calculates the matching degree between the task requirement vector and the equipment capability vector through vector dot product and modulo operation, which can accurately quantify the degree of fit between the two. Vector dot product reflects the consistency of vector direction, and modulo operation standardizes the vector length. The combination of the two can objectively assess whether the equipment capability meets the task requirements, avoid the bias in matching degree judgment caused by comparing only a single parameter, and provide a scientific matching basis for the suitability score.

[0116] In summary, the introduction of matching degree contribution coefficient and priority contribution coefficient allows for flexible adjustment of the influence ratio of task matching degree and device priority weight in the scoring, and can optimize the scoring logic according to the actual scenario, making the matching degree score more in line with the task scheduling needs, and improving the flexibility and practicality of the scoring.

[0117] In summary, the integration of task matching degree and device priority weight in calculating the adaptability score considers both the fit between device capabilities and task requirements, as well as the device's adaptability in the real-time environment. This avoids improper device selection due to a single-dimensional evaluation and ensures that the score results comprehensively reflect the device's adaptability value to the current task, providing a reliable basis for the subsequent accurate allocation of data collection sub-tasks.

[0118] In summary, the formula calculation logic is clear and the parameters have explicit meanings. The calculation process at each stage is traceable, which facilitates the coordination of the server to execute the calculation quickly. At the same time, the scoring process can be checked in reverse through the parameters, avoiding calculation errors or uninterpretable results caused by the complexity of the algorithm. This ensures the accuracy and reliability of the suitability score and lays the foundation for the rationality of task allocation.

[0119] S4. Generate a set of control parameters for the radiation-resistant camera device based on the task coordination instruction, and send the set of control parameters to the radiation-resistant camera device to obtain the synchronization signal broadcast of the radiation-resistant camera device;

[0120] In this embodiment of the invention, the step of generating a set of control parameters for the radiation-resistant camera device based on the task coordination instruction, and sending the set of control parameters to the radiation-resistant camera device to obtain a synchronization signal broadcast from the radiation-resistant camera device includes:

[0121] Extract the task execution time window and image acquisition quality requirements from the task coordination instructions to generate the basic control parameter framework for the radiation-resistant camera device;

[0122] Based on the aforementioned basic control parameter framework and the hardware characteristic database of the radiation-resistant camera device, personalized control parameters are generated for the radiation-resistant camera device, resulting in the initial control parameter set of the radiation-resistant camera device.

[0123] The initial set of control parameters is subjected to device compatibility verification to obtain the control parameter set of the radiation-resistant camera device;

[0124] The control parameter set is distributed to the corresponding radiation-resistant camera device through the secure communication link, and the parameter confirmation signal returned by the radiation-resistant camera device is received.

[0125] Based on the parameter confirmation signal, a synchronization signal for the radiation-resistant camera device is generated, and the synchronization signal is broadcast to the radiation-resistant camera device through the Internet of Things platform.

[0126] Specifically, when extracting the task execution time window and image acquisition quality requirements from the task coordination instructions to generate the basic control parameter framework for the radiation-resistant camera equipment, the task execution time window is first read from the task coordination instructions, including the task start time, end time, and time nodes of each acquisition stage. Then, the image acquisition quality requirements are extracted, covering specific indicators such as image resolution, color depth, and exposure time range. These time information and quality indicators are organized according to the conventional classification method of control parameters to form a basic structure containing two major modules: time control and image quality control. This structure is the basic control parameter framework for the radiation-resistant camera equipment.

[0127] Furthermore, based on the basic control parameter framework and the hardware characteristic database of the radiation-resistant camera equipment, personalized control parameters are generated for the radiation-resistant camera equipment. When obtaining the initial control parameter set of the radiation-resistant camera equipment, the hardware parameters of the corresponding radiation-resistant camera equipment are first retrieved from the hardware characteristic database, including the maximum resolution supported by the equipment, the adjustable exposure time range, and the compatible transmission rate. Then, the time and quality requirements in the basic control parameter framework are compared and adjusted with the hardware parameters. For example, if the resolution required by the basic framework exceeds the range supported by the equipment hardware, the resolution is adjusted to the maximum resolution supported by the equipment. If the exposure time of the basic framework is not within the adjustable range of the equipment, it is corrected to the exposure time compatible with the equipment. All the adjusted control parameters are integrated to form the initial control parameter set of the radiation-resistant camera equipment.

[0128] Furthermore, the initial set of control parameters is verified for device compatibility. When obtaining the control parameter set of the radiation-resistant camera device, each parameter in the initial set of control parameters is compared one by one with the hardware limitations of the device in the hardware characteristic database. It is checked whether the parameter is within the range supported by the device hardware. For example, it is checked whether the transmission rate parameter is within the maximum transmission rate of the device and whether the frame rate parameter is within the frame rate range that the device can achieve. If there is a parameter that exceeds the hardware limitation, the parameter is corrected again to the device compatibility range. After all parameters are verified and there are no compatibility issues, the final control parameters are determined. The set of these parameters is the control parameter set of the radiation-resistant camera device.

[0129] Furthermore, when distributing the control parameter set to the corresponding radiation-resistant camera device via a secure communication link and receiving the parameter confirmation signal returned by the radiation-resistant camera device, a secure communication link is first established between the coordination server and the corresponding radiation-resistant camera device. This link uses encrypted transmission to ensure that the parameter information is not leaked or tampered with. Then, the control parameter set is packaged in a format that the device can recognize and sent to the device via the secure communication link. After receiving the parameters, the device performs local verification of the parameters. If the parameters are confirmed to be parsable normally and meet its own hardware requirements, a parameter confirmation signal is generated after the verification is passed and sent back to the coordination server via the same secure communication link. The coordination server receives the signal and records it.

[0130] Furthermore, based on the parameter confirmation signal, a synchronization signal for the radiation-resistant camera devices is generated. When broadcasting the synchronization signal to the radiation-resistant camera devices through the IoT platform, the device identifier and parameter reception time in the parameter confirmation signal are first used to determine that all target radiation-resistant camera devices have successfully received and confirmed the control parameters. Then, the synchronization signal is generated. This signal contains a unified task start time, instruction codes for synchronous execution of each stage, and abnormal feedback trigger conditions. The synchronization signal is uploaded to the IoT platform, which then sends the signal to all radiation-resistant camera devices with confirmed parameters through the broadcast channel, ensuring that all devices receive the same synchronization instructions.

[0131] In summary, extracting the task execution time window and image acquisition quality requirements from the task coordination instructions to generate a basic control parameter framework can transform task requirements into a structured control parameter base, clarify the time boundaries and quality standards for device task execution, prevent subsequent control parameter generation from deviating from the core task requirements, and provide a unified and standardized framework support for personalized parameter configuration.

[0132] In summary, by combining the basic control parameter framework with the hardware characteristic database to generate personalized control parameters, the parameters can be adjusted according to the hardware limitations of different radiation-resistant camera devices. For example, resolutions exceeding the device hardware support can be corrected to device-compatible values, ensuring that the initial control parameter set matches the actual capabilities of the device and avoiding the device's inability to perform tasks properly due to parameter mismatch with hardware.

[0133] In summary, verifying the device compatibility of the initial set of control parameters allows for the checking of each parameter to ensure it is within the range supported by the device hardware, eliminating or correcting incompatible parameters. The resulting set of control parameters can be directly recognized and executed by the device, ensuring the validity of the parameters and the stability of the device operation.

[0134] In summary, the control parameter set is distributed and parameter confirmation signals are received through a secure communication link. The previously established encrypted communication link ensures that the parameters are not stolen or tampered with during transmission. At the same time, the confirmation signal returned by the device confirms that the parameters have been successfully received and verified, avoiding deviations in device execution due to parameter loss or errors, and laying a reliable foundation for subsequent synchronous control.

[0135] In summary, generating and broadcasting a synchronization signal based on the parameter confirmation signal ensures that all radiation-resistant camera devices with confirmed parameters receive a unified synchronization command, avoiding timing chaos caused by asynchronous commands from multiple devices, enabling collaborative acquisition by multiple devices, and improving the synchronization and efficiency of the overall acquisition task.

[0136] S5. Generate synchronization control data for the radiation-resistant camera device based on the set of control parameters and the local clock broadcast by the synchronization signal;

[0137] In this embodiment of the invention, generating synchronization control data for the radiation-resistant camera device based on the control parameter set and the local clock broadcast by the synchronization signal includes:

[0138] The local clock of the radiation-resistant camera device is adjusted for deviation based on the reference timestamp in the set of control parameters.

[0139] Read the device-specific configuration parameters from the control parameter set to obtain the individual acquisition plan for the radiation-resistant camera device;

[0140] Based on the local clock adjusted for deviation and the individual acquisition plan, the acquisition time point sequence of the radiation-resistant camera equipment is determined;

[0141] Synchronization control data for the radiation-resistant camera device is generated based on the non-overlapping sequence of acquisition time points.

[0142] Specifically, when adjusting the local clock of the radiation-resistant camera device based on the reference timestamp in the control parameter set, the preset reference timestamp is first extracted from the control parameter set. This timestamp is a standard time node uniformly followed by all devices. Then, the current time displayed by the local clock of the radiation-resistant camera device is read, and the difference between the local clock time and the reference timestamp is calculated. If the local clock time is earlier than the reference timestamp, the local clock is adjusted forward to match the reference timestamp. If the local clock time is later than the reference timestamp, the local clock is adjusted backward to match the reference timestamp, ensuring that the adjusted local clock has no deviation from the reference timestamp.

[0143] Furthermore, when reading the device-specific configuration parameters from the control parameter set to obtain the individual acquisition plan for the radiation-resistant camera device, the device-specific configuration parameters are selected from the control parameter set. These parameters include the acquisition frequency of the device, the duration of each acquisition, the resolution parameters of the acquired images, and the coordinate information of the specific acquisition area. These individual configuration parameters are organized in chronological order and acquisition logic to clarify the acquisition operations that the device needs to perform in different time periods and the corresponding parameter requirements. The resulting structured plan is the individual acquisition plan for the radiation-resistant camera device.

[0144] Furthermore, when determining the acquisition time point sequence of the radiation-resistant camera equipment based on the bias-adjusted local clock and the individual acquisition plan, the bias-adjusted local clock is used as the time reference. According to the acquisition frequency and task execution time window in the individual acquisition plan, the start time point of each acquisition operation is calculated sequentially. For example, if the acquisition frequency is once every ten minutes and the task execution time window lasts for two hours starting from the reference timestamp, then a time point is marked every ten minutes starting from the reference timestamp. At the same time, combined with the duration of each acquisition in the individual acquisition plan, it is ensured that the interval between each time point can accommodate the complete acquisition process. All the calculated acquisition start time points are arranged in chronological order to form the acquisition time point sequence of the radiation-resistant camera equipment.

[0145] Furthermore, when generating synchronization control data for the radiation-resistant camera device based on the non-overlapping acquisition time point sequence, the system first checks whether the acquisition duration corresponding to each time point in the acquisition time point sequence overlaps. If the acquisition operations of two adjacent time points overlap, the start time of the latter time point is adjusted so that it starts after the former acquisition has finished, ensuring that the operations corresponding to all acquisition time points do not overlap. Then, the non-overlapping acquisition time point sequence is associated with the corresponding device-specific configuration parameters to clarify the acquisition parameters and operation instructions to be executed at each time point. These associated information are integrated in a format that the device can recognize, and the resulting dataset is the synchronization control data for the radiation-resistant camera device.

[0146] In summary, adjusting the local clock deviation of the radiation-resistant camera equipment based on the reference timestamp in the control parameter set can unify the local clocks of all devices to the same time reference, eliminate time differences caused by clock drift between different devices, avoid data timing disorder due to time asynchrony during subsequent acquisition, lay a unified time foundation for multi-device collaborative acquisition, and ensure the time consistency of acquired data.

[0147] In summary, by reading the device-specific configuration parameters from the control parameter set to generate individual acquisition plans, it is possible to specify the acquisition frequency, duration of each acquisition, and coordinates of the acquisition area for each device based on its hardware characteristics and task allocation needs. This ensures that the acquisition plan is precisely matched with the device capabilities and task requirements, avoiding the waste of device resources or the failure to meet task execution standards caused by a generic plan.

[0148] In summary, by combining the local clock after deviation adjustment with the individual acquisition plan to determine the acquisition time sequence, a unified time base can be used as a basis to calculate the specific acquisition start time of each device according to the frequency and time window in the individual acquisition plan. This ensures that the time sequence not only conforms to the acquisition rhythm of the device itself, but also is consistent with the overall task time plan, providing a clear time node basis for avoiding time overlap in the future.

[0149] In summary, synchronous control data is generated based on the non-overlapping acquisition time point sequence. By adjusting the overlapping time points, it is ensured that each acquisition operation of the device is performed independently without time conflicts. At the same time, the time point sequence is associated and integrated with the device's unique configuration parameters to form synchronous control data containing clear acquisition time, parameters, and operation instructions. This enables the device to accurately execute acquisition tasks according to this data, avoids the chaos of acquisition sequence from multiple devices, and improves the orderliness and synchronization of the overall acquisition task.

[0150] S6. Based on the synchronous control data, the radiation-resistant camera device is synchronously controlled and collected, and the collected data is aggregated to obtain the target coordination output result of the radiation-resistant camera device.

[0151] In this embodiment of the invention, the step of synchronously controlling and acquiring data from the radiation-resistant camera device based on the synchronous control data includes:

[0152] Based on the execution timing diagram in the synchronous control data, the image acquisition function of the radiation-resistant camera device is started under a unified time reference.

[0153] Add timestamps and device identifiers to the collected standardized image data to obtain the synchronous acquisition data packet of the radiation-resistant camera device;

[0154] The synchronously acquired data packets are transmitted to the coordination server via the secure communication link.

[0155] The aggregation and processing of the synchronously controlled and acquired data to obtain the target coordination output result of the radiation-resistant camera equipment includes:

[0156] Based on the timestamp and device identifier in the synchronous acquisition data packet, the acquisition data is spatiotemporally aligned to obtain the multi-source image data of the radiation-resistant camera device.

[0157] Remove image frames from the multi-source image data that do not meet the quality requirements;

[0158] The qualified image data are stitched and fused according to preset rules to obtain a panoramic monitoring image of the multi-source image data;

[0159] Metadata identifiers are added to the panoramic monitoring image to obtain the target coordination output result of the radiation-resistant camera device.

[0160] Specifically, based on the execution timing diagram in the synchronization control data, when starting the image acquisition function of the radiation-resistant camera device under a unified time reference, the execution timing diagram is first extracted from the synchronization control data. This diagram clearly marks the start time, execution duration, and sequence of each acquisition stage of the device. Then, the local clock after the previous deviation adjustment is used as the unified time reference, and the time change is monitored in real time. When the time displayed by the local clock reaches the start time of the first acquisition stage in the execution timing diagram, a start command is sent to the image acquisition module of the radiation-resistant camera device, triggering the device to start performing image acquisition operations according to the acquisition parameters in the synchronization control data.

[0161] Furthermore, to obtain the synchronous acquisition data packet of the radiation-resistant camera device, a timestamp and device identifier are added to the acquired standardized image data. First, the standardized image data acquired by the device is obtained. This data has been standardized according to the control parameters in terms of resolution, color, etc. Then, the local clock time after the current device deviation adjustment is read as the timestamp, and the unique hardware number of the radiation-resistant camera device is extracted as the device identifier. The timestamp and device identifier are embedded into the file header of the standardized image data in a preset format to form a complete data unit containing image data, timestamp, and device identifier. This data unit is the synchronous acquisition data packet of the radiation-resistant camera device.

[0162] Furthermore, when transmitting the synchronous acquisition data packet to the coordination server via the secure communication link, it is first confirmed that the secure communication link between the radiation-resistant camera equipment and the coordination server is in a normal connection state. This link has been pre-configured with encryption to ensure data transmission security. Then, the synchronous acquisition data packet is encapsulated according to the transmission format supported by the link. After encapsulation, the data packet is sent to the coordination server via the secure communication link. At the same time, transmission status monitoring is started. If a transmission interruption is detected, the transmission is immediately re-initiated until the coordination server successfully receives the synchronous acquisition data packet.

[0163] Specifically, based on the timestamps and device identifiers in the synchronously acquired data packets, the acquired data is spatiotemporally aligned to obtain multi-source image data of the radiation-resistant camera equipment. First, the timestamp and corresponding device identifier of each data packet are extracted from all synchronously acquired data packets. Data packets acquired by different devices at the same time are classified according to the timestamps. Then, based on the device deployment location information corresponding to the device identifier, the spatial coverage of the images acquired by each device is determined. Image data from the same time but different spatial ranges are associated and integrated to ensure that the data matches each other in terms of time sequence and spatial location, forming a dataset containing acquisition information from multiple devices and multiple time periods. This dataset is the multi-source image data of the radiation-resistant camera equipment.

[0164] Furthermore, when removing image frames that do not meet the quality requirements from the multi-source image data, image quality judgment criteria are first set, including whether the image clarity meets the preset visual effect, whether there is obvious noise or distortion, and whether the color reproduction is normal. Then, each image frame in the multi-source image data is checked one by one, and image frames with insufficient clarity, severe noise, distortion, or abnormal color are marked as unqualified. All marked unqualified image frames are deleted from the multi-source image data, and only image frames that meet the quality requirements are retained.

[0165] Furthermore, when stitching and fusing qualified image data according to preset rules to obtain a panoramic monitoring image of multi-source image data, the preset stitching and fusion rules are first determined. That is, according to the spatial coordinates of the images collected by each device, the image frames collected by adjacent devices are aligned at the pixel level in the overlapping area to eliminate the visual differences in the overlapping parts. Then, according to the spatial distribution order of the device deployment, all the aligned image frames are stitched together in sequence to form a preliminary image covering the complete monitoring area. Finally, the color and brightness of the preliminary image are uniformly adjusted to ensure that the overall visual effect is consistent. The adjusted complete image is the panoramic monitoring image of multi-source image data.

[0166] Furthermore, when adding metadata identifiers to the panoramic monitoring images to obtain the target coordination output results of the radiation-resistant camera equipment, the information contained in the metadata identifiers is first determined, including the generation time of the panoramic monitoring images, the list of equipment identifiers involved in the acquisition, the coordinate range of the monitoring area covered by the image, the image resolution, etc. Then, these metadata information are embedded into the file attributes of the panoramic monitoring images according to a preset format, so that the metadata is associated with the image data and stored together, forming the final result containing the panoramic monitoring images and complete metadata identifiers. This result is the target coordination output result of the radiation-resistant camera equipment.

[0167] In summary, by starting the image acquisition function under a unified time reference based on the execution timing diagram in the synchronization control data, it can ensure that all radiation-resistant camera devices strictly perform acquisition operations according to the preset time nodes, avoid acquisition timing chaos caused by differences in device startup time, achieve time synchronization of multi-device collaborative acquisition, and ensure time consistency during subsequent data aggregation.

[0168] In summary, adding timestamps and device identifiers to the collected standardized image data allows for precise marking of the specific time of data collection, while device identifiers clearly identify the device from which the data originates. The combination of these two features gives each synchronously collected data packet a unique and traceable "spatiotemporal identifier," avoiding issues such as time confusion or unclear device attribution during subsequent data processing. This provides a crucial basis for data spatiotemporal alignment and multi-source integration.

[0169] In summary, transmitting synchronously collected data packets via a secure communication link, leveraging the previously established encrypted communication link, ensures that the collected data is not stolen, tampered with, or leaked during transmission. It also guarantees the stability of data packet transmission, preventing the loss or corruption of data that could lead to missing critical information in subsequent aggregation processing. This provides a secure and reliable transmission guarantee for the coordination server to accurately receive and process the collected data, maintaining the security and integrity of the overall data collection process.

[0170] In summary, spatiotemporal alignment based on timestamps and device identifiers in synchronously acquired data packets allows for the categorization of data collected by different devices during the same time period by timestamp. Combining the deployment location corresponding to the device identifier determines the spatial coverage of the image, enabling precise matching of scattered data collected by multiple devices in both time sequence and spatial location. This results in complete multi-source image data, avoiding distortion of subsequent processing results due to spatiotemporal misalignment of data, and providing an orderly and correlated data source for the generation of panoramic monitoring images.

[0171] In summary, by removing image frames that do not meet quality requirements from multi-source image data and filtering qualified data through preset standards, low-quality data caused by temporary equipment failures, environmental interference, etc., can be eliminated. This ensures that the images subsequently stitched and fused are all valid data, avoids low-quality frames from affecting the overall clarity and accuracy of the panoramic monitoring images, and improves the quality foundation of the final output results.

[0172] In summary, by stitching and fusing qualified image data according to preset rules, a panoramic monitoring image can be obtained. Based on the spatial coordinates of the images collected by each device, pixel-level alignment can be achieved in overlapping areas to eliminate visual differences. Then, the images are stitched together according to the deployment order of the devices to form an image covering the entire monitoring area. At the same time, color and brightness are uniformly adjusted to ensure visual consistency. This solves the problem of limited acquisition range of a single device and provides users with a comprehensive and coherent monitoring field of view, meeting the needs of large-scale radiation environment monitoring.

[0173] In summary, adding metadata identifiers to panoramic monitoring images allows image data to be stored in association with key background information. This facilitates subsequent tracing of key information such as data source and acquisition time, and also enables users to quickly understand the monitoring range and technical parameters of the images. It improves the usability and traceability of the target coordination output results, and provides clear information support for subsequent analysis, archiving and other operations.

[0174] In the several embodiments provided by this invention, it should be understood that the disclosed method can be implemented in other ways.

[0175] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0176] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, and technology that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0177] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for coordinating control of radiation-hardened cameras based on the Internet of Things, characterized by, The method comprises: S1, establishing a secure communication link between the radiation-resistant camera device and the coordination server through the Internet of Things platform, obtaining the device connection state data of the radiation-resistant camera device; S2, according to the real-time environmental radiation intensity and the device health state of the radiation-resistant camera device, determine the priority weight of the radiation-resistant camera device; S3, according to the device connection state data and the priority weight, task allocation is carried out on the radiation-resistant camera device, and the task coordination instruction of the radiation-resistant camera device is obtained, including: In the coordination server, based on the device connection state data, the radiation-resistant camera devices currently in the operable state are screened out, and the candidate device list of the radiation-resistant camera device is obtained; Resolve the task requirements of the to-be-executed collection task, and obtain the task feature descriptor of the to-be-executed collection task; The priority weight of the radiation-resistant camera device in the candidate device list is matched with the task feature descriptor to calculate the matching degree, and the adaptation score of the radiation-resistant camera device for the current task is determined, wherein the calculation formula of the adaptation score is as follows: ； wherein, is the fitness score of the nthradiation-hardened camera, is the task requirement vector in the task feature descriptor, is the device capability vector in the task feature descriptor, is the modulo symbol, is the vector dot product operator symbol, is the matching degree contribution coefficient, is the priority contribution coefficient, is the priority weight;​ Based on the adaptation score, each candidate device in the candidate device list is allocated a specific collection subtask, and an initial task allocation scheme of the radiation-resistant camera device is obtained; The initial task allocation scheme is subjected to conflict detection and resource balance verification to ensure that there is no device overload and no repetition in regional coverage, and the task coordination instruction of the radiation-resistant camera device is obtained; S4, based on the task coordination instruction, generate the control parameter set of the radiation-resistant camera device, and send the control parameter set to the radiation-resistant camera device, obtain the synchronization signal broadcast of the radiation-resistant camera device; S5, according to the control parameter set and the local clock of the synchronization signal broadcast, generate the synchronization control data of the radiation-resistant camera device; S6, according to the synchronization control data, the radiation-resistant camera device is subjected to synchronous regulation and control collection, and the data of the synchronous regulation and control collection is subjected to aggregation processing, and the target coordination output result of the radiation-resistant camera device is obtained. 2.The radiation-resistant camera coordination control method based on the Internet of Things according to claim 1, wherein The method comprises: The radiation-resistant camera device sends a device registration request to the coordination server, wherein the device registration request includes: the unique identifier and the digital certificate of the radiation-resistant camera device; The coordination server receives the device registration request, verifies the legality of the digital certificate and the authenticity of the unique identifier, and generates the session key establishment parameter of the radiation-resistant camera device; Based on the session key establishment parameter, the radiation-resistant camera device and the coordination server are subjected to key exchange, and the secure communication link between the radiation-resistant camera device and the coordination server is obtained. 3.The radiation-resistant camera coordination control method based on the Internet of Things according to claim 1, wherein, The method comprises: According to the current radiation intensity value and the current health status value of the radiation-resistant camera device, an initial weight of the radiation-resistant camera device is calculated; The initial weight is normalized to obtain a standardized weight of the radiation-resistant camera device; The standardized weight is removed from the abnormal value to obtain the priority weight of the radiation-resistant camera device. 4.The radiation-resistant camera coordination control method based on the Internet of Things according to claim 3, wherein, The calculation formula of the initial weight is as follows: ; In the formula, the initial weight, a preset radiation intensity coefficient, a preset health state coefficient, a reference radiation intensity value, the current radiation intensity value, a reference health state value, the current health state value. 5.The radiation-resistant camera coordination control method based on the Internet of Things according to claim 1, wherein, The control parameter set of the radiation-resistant camera device is generated based on the task coordination instruction, and the control parameter set is sent to the radiation-resistant camera device to obtain the synchronization signal broadcast of the radiation-resistant camera device, including: Extract the task execution time window and image acquisition quality requirement in the task coordination instruction to generate the basic control parameter framework of the radiation-resistant camera device; Based on the basic control parameter framework and the hardware characteristic database of the radiation-resistant camera device, individualized control parameters are generated for the radiation-resistant camera device to obtain the initial control parameter set of the radiation-resistant camera device; The initial control parameter set is verified for device compatibility to obtain the control parameter set of the radiation-resistant camera device; The control parameter set is distributed to the corresponding radiation-resistant camera device through the secure communication link, and a parameter confirmation signal returned by the radiation-resistant camera device is received; Based on the parameter confirmation signal, a synchronization signal of the radiation-resistant camera device is generated, and the synchronization signal is broadcast to the radiation-resistant camera device through the Internet of Things platform. 6.The radiation tolerant camera coordinated control method based on Internet of Things according to claim 1, wherein, The synchronization control data of the radiation-resistant camera device is generated based on the control parameter set and the local clock of the synchronization signal broadcast, including: The local clock of the radiation-resistant camera device is adjusted based on the reference timestamp in the control parameter set; The device-specific configuration parameters in the control parameter set are read to obtain the individual acquisition plan of the radiation-resistant camera device; Based on the deviation-adjusted local clock and the individual acquisition plan, the acquisition time point sequence of the radiation-resistant camera device is determined; According to the acquisition time point sequence without time overlap, the synchronization control data of the radiation-resistant camera device is generated. 7.The radiation tolerant camera coordinated control method based on Internet of Things of claim 1, wherein, The radiation-resistant camera device is synchronously regulated and controlled for acquisition according to the synchronization control data, including: According to the execution timing diagram in the synchronization control data, the image acquisition function of the radiation-resistant camera device is started under a unified time reference; Timestamps and device identifiers are added to the acquired standardized image data to obtain the synchronization acquisition data packet of the radiation-resistant camera device; The synchronization acquisition data packet is transmitted to the coordination server through the secure communication link. 8.The radiation tolerant camera coordinated control method based on Internet of Things of claim 7, wherein, The data of the synchronous regulation and control acquisition is aggregated to obtain the target coordination output result of the radiation-resistant camera device, including: According to the timestamps and device identifiers in the synchronization acquisition data packet, the acquisition data is spatio-temporally aligned to obtain the multi-source image data of the radiation-resistant camera device; The image frames in the multi-source image data that do not meet the quality requirements are removed; The qualified image data is spliced and fused according to the preset rules to obtain the panoramic monitoring image of the multi-source image data; Metadata identification is added to the panoramic monitoring image, and a target coordination output result of the radiation-hardened camera device is obtained.

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