Dummy resource management method and system, electronic equipment, storage medium and program product

Abstract

The invention provides a dumb resource management method and system, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring an image of a passive optical network port resource through a micro camera; preprocessing the image through the edge cloud to obtain a preprocessing result; performing information extraction on the preprocessing result through the central cloud to obtain first resource information of the passive optical network port resource; and verifying the first resource information and the second resource information, and performing resource information management according to a verification result. According to the dumb resource management method provided by the invention, a passive optical network port resource image is collected through a micro camera, the edge cloud is utilized to preprocess the passive optical network port resource image to quickly obtain a preliminary result, and then the center cloud performs depth information extraction based on the preprocessing result to obtain first resource information; and the second resource information read by the resource system is verified, and accurate resource information management is realized according to a verification result, so that full-process automatic dumb resource management is realized.

Description

Technical Field

[0001] This invention relates to the field of resource management technology, and in particular to a dumb resource management method, system, electronic device, storage medium, and program product. Background Technology

[0002] In the telecommunications industry, "dumb resources" typically refer to physical resources that lack intelligent or active communication capabilities. A common example is passive optical network (PON) port resources, which are port resources that cannot be automatically collected and updated through the network during resource management. Common PON port resources include optical splitter ports and optical distribution box ports. These devices are passive and cannot transmit status information back. However, operators need to regularly manage these passive devices during network operation and maintenance to ensure that system resource allocation remains consistent with the actual situation.

[0003] In existing technologies, image recognition technology is used to automatically identify textual and physical information in images of relevant port resources, and then this information is entered into the relevant resource database. Although image recognition technology can complete data extraction and automatic entry, the process of collecting port resource images still requires manual labor. Because there are many passive devices, and some of them are located in hidden places and are difficult to find, this method of collection will bring high labor costs to operators, and often results in missed or incorrect collections, leading to inaccurate or incomplete data. Summary of the Invention

[0004] This invention provides a dumb resource management method, system, electronic device, storage medium, and program product to solve the problems of poor accuracy and high labor costs in existing dumb resource management methods.

[0005] In a first aspect, the present invention provides a method for managing dumb resources, comprising: Images of passive optical network port resources are captured using a miniature camera; The image is preprocessed using edge clouds to obtain the preprocessed result; The first resource information of the passive optical network port resources is obtained by extracting information from the preprocessing results through the central cloud. The central cloud verifies the first resource information and the second resource information, and manages the resource information based on the verification result; the second resource information is the resource information of the passive optical network port resources read through the resource system.

[0006] In one embodiment, the step of verifying the first resource information and the second resource information through the central cloud, and managing the resource information based on the verification result, includes: The central cloud performs a consistency check between the first resource information and the second resource information. If the first resource information and the second resource information are consistent, then the second resource information in the resource system will not be revised. If the first resource information and the second resource information are inconsistent, the second resource information in the resource system shall be revised.

[0007] In one embodiment, after managing resource information based on the verification result, the method further includes: Obtain the latest secondary resource information for various types of passive optical network port resources; Based on the latest second resource information of various passive optical network port resources, a global view of passive optical network port resources is generated. The passive optical network port resources are displayed in real time on a large front-end screen.

[0008] In one embodiment, the preprocessing of the image using edge clouds to obtain a preprocessing result includes: The validity of the image is detected using edge clouds; If the image is detected as valid, the image sharpness is adjusted using the edge cloud to obtain the adjusted image; The adjusted image is subjected to repeatability detection using the edge cloud. If duplicates are detected in the adjusted image, the duplicate images are discarded, and the preprocessed result is obtained. If it is detected that the adjusted image does not contain duplicates, then the adjusted image is determined as the preprocessing result.

[0009] In one embodiment, a passive device enclosure contains a type of passive optical network port resource and a miniature camera; the miniature camera and the passive optical network port resource are mounted on the same axis. When acquiring images of passive optical network port resources using a miniature camera, the following are included: Images are captured within a preset acquisition area of ​​passive optical network port resources on the same axis using a miniature camera; the images include at least passive device enclosure label information, port occupancy information, and fiber optic label information.

[0010] In one embodiment, the dumb resource management method further includes: After the miniature camera is installed and connected to the network, the device information of the miniature camera is registered in the configuration management database; Monitor the operational status of registered miniature cameras and implement corresponding alarm mechanisms when miniature cameras malfunction.

[0011] Secondly, the present invention also provides a dumb resource management system, including an access layer, an edge cloud, and a central cloud; The access layer is used to acquire images of passive optical network port resources captured by the miniature camera; The edge cloud is used to preprocess the image to obtain a preprocessing result; The central cloud is used to extract information from the preprocessing results to obtain the first resource information of the passive optical network port resources; the central cloud verifies the first resource information and the second resource information, and manages the resource information according to the verification result; the second resource information is the resource information of the passive optical network port resources read through the resource system.

[0012] Thirdly, the present invention provides an electronic device, the electronic device including a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the dumb resource management methods described above.

[0013] Fourthly, the present invention also provides a non-transitory computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of any of the above-described dumb resource management methods.

[0014] Fifthly, the present invention also provides a computer program product comprising a computer program that can be stored on a non-transitory computer-readable storage medium, wherein the computer program, when executed by the processor, implements the steps of any of the above-described dumb resource management methods.

[0015] The dumb resource management method, system, electronic device, storage medium, and program product provided by this invention acquire images of passive optical network (PON) port resources using a miniature camera, preprocess them using an edge cloud to quickly obtain preliminary results, and then perform deep information extraction based on the preprocessing results in the central cloud to obtain first resource information. This first resource information is then verified against second resource information read by the resource system. Based on the verification results, accurate resource information management is achieved, ensuring the accuracy of PON port resource information. The entire process achieves efficient collaboration from image acquisition to information extraction, verification, and management, realizing fully automated dumb resource management, greatly reducing labor costs, optimizing resource management processes, and improving network operation and maintenance efficiency and quality. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is one of the flowcharts of the dumb resource management method provided by the present invention.

[0018] Figure 2 This is the second flowchart of the dumb resource management method provided by the present invention.

[0019] Figure 3 This is a schematic diagram of the multi-level system architecture provided by the present invention.

[0020] Figure 4 This is a schematic diagram of the architecture of the dumb resource management system provided by the present invention.

[0021] Figure 5 This is a schematic diagram of the image acquisition hardware device provided by the present invention.

[0022] Figure 6 This is a schematic diagram of the installation position of the miniature camera in the passive device housing provided by the present invention.

[0023] Figure 7 This is a schematic diagram of the structure of the dumb resource management system provided by the present invention.

[0024] Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0026] The terms "first," "second," etc., used in this invention are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention can be implemented in orders other than those illustrated or described herein.

[0027] The following is combined Figures 1-8 This invention describes the dumb resource management method, system, electronic device, storage medium, and program product provided by the present invention.

[0028] It should be noted that the dumb resource management method provided in this embodiment of the invention is implemented based on a dumb resource management system. This embodiment of the invention uses a dumb resource management system as the execution subject to describe the dumb resource management method.

[0029] Combination Figure 1 and Figure 2 , Figure 1 This is one of the flowcharts illustrating the dumb resource management method provided by the present invention. Figure 2 This is the second flowchart of the dumb resource management method provided by the present invention.

[0030] like Figure 1 As shown, the method includes the following: Step 101: Acquire images of passive optical network port resources using a miniature camera; Step 102: Preprocess the image using edge clouds to obtain the preprocessing result; Step 103: Extract information from the preprocessing results through the central cloud to obtain the first resource information of the passive optical network port resources; Step 104: Verify the first resource information and the second resource information through the central cloud, and manage the resource information according to the verification result.

[0031] This invention introduces a multi-level system architecture of camera-edge cloud-central cloud, such as... Figure 3 As shown, Figure 3 This is a schematic diagram of the multi-level system architecture provided by the present invention.

[0032] This multi-level system architecture consists of miniature cameras, an edge cloud, and a central cloud, each undertaking different tasks and functions. The miniature cameras are the starting point of the multi-level system architecture, responsible for acquiring images of passive optical network (PON) port resources. The edge cloud, as the middle layer of the multi-level system architecture, possesses certain computing and storage capabilities. Physically closer to the camera devices, it can receive and process data from the miniature cameras more quickly. Its main task is to preprocess the images acquired by the miniature cameras and transmit the processed data to the central cloud for further analysis and management. The central cloud is the core of the entire multi-level system architecture. It receives data from the edge cloud and possesses large-scale computing and storage capabilities. Its main tasks include two aspects: first, auditing, revising, analyzing, and displaying a global view of port resource information; and second, managing the miniature cameras.

[0033] Applying this multi-level system architecture, this invention presents a dumb resource management system based on a miniature camera, such as... Figure 4 As shown, Figure 4This is a schematic diagram of the architecture of the dumb resource management system provided by the present invention. The multi-level system architecture consists of five layers: base, access layer, edge storage database, edge cloud (providing edge capabilities), and central cloud (providing central capabilities). The base uses miniature cameras to collect images of passive optical network (PON) port resources; the access layer provides access services, heartbeat services, and data channels; the edge storage database stores the collected port resource images using distributed file storage and uses a configuration management database (CMDB) to store camera device information; edge capabilities provide image AI processing services, data synchronization services, device management services, hardware OTA services, and northbound connection services; and central capabilities provide port resource data auditing and revision, data analysis and global view services, OTA upgrade services, and operation and maintenance management services.

[0034] Specifically, before managing dummy resources, a miniature camera needs to be installed in the passive equipment enclosure containing the passive optical network (PON) port resources. This means that each miniature camera is responsible for acquiring image data of the PON port resources located in the same passive equipment enclosure. Therefore, during the management of dummy resources, the system can acquire images of the PON port resources through the miniature cameras, further transmit the acquired images to the access layer via the communication transmission module, and store them in the edge storage database using a distributed file storage method. In reality, each miniature camera is responsible for acquiring images of its corresponding PON port resource, and the system then performs resource management based on the image information. For clarity, this process is described using the example of a single miniature camera acquiring image data and then managing resources based on that image information.

[0035] Furthermore, the access layer transmits the images of the acquired passive optical network port resources to the edge cloud. The edge cloud is characterized by its miniaturization and distribution, and can perform real-time preprocessing on the acquired images, including validity detection, sharpness adjustment and repeatability detection, to obtain the corresponding preprocessing results. When the preprocessing results meet the preset conditions, the edge cloud will transmit the final preprocessing results to the central cloud.

[0036] Furthermore, the central cloud, characterized by its large scale and centralized nature, can centrally process the preprocessing results transmitted from each edge cloud. It can uniformly extract key resource information from the received preprocessing results to obtain the first resource information of the passive optical network (PON) port resources. Simultaneously, it will read the second resource information of the same PON port resource from the resource system. Furthermore, it can perform consistency verification between the first and second resource information of the PON port resource to determine if the current port resource information has changed. Since the port resource information in the resource system needs to be accessed, real-time management of the port resource information in the resource system is necessary to achieve accurate resource access and improve resource utilization. Therefore, if the verification results of the first and second resource information of the PON port resource are inconsistent, the second resource information in the resource system needs to be revised to complete resource information management.

[0037] Finally, the central cloud also provides a global view service, which can construct a global view of passive optical network port resources based on the latest resource information of various types of passive optical network port resources. This view is also known as a dumb resource global view and can be displayed in real time on the front-end large screen.

[0038] The dumb resource management method provided by this invention acquires images of passive optical network (PON) port resources using a miniature camera, preprocesses them using an edge cloud to quickly obtain preliminary results, and then extracts deep information based on the preprocessed results from the central cloud to obtain first resource information. This first resource information is then verified against second resource information read by the resource system. Based on the verification results, precise resource information management is achieved, ensuring the accuracy of PON port resource information. The method achieves efficient collaboration from image acquisition to information extraction, verification, and management, realizing fully automated dumb resource management, greatly reducing labor costs, optimizing resource management processes, and improving network operation and maintenance efficiency and quality.

[0039] In some embodiments, based on step 101, when acquiring images of passive optical network port resources using a miniature camera, the specific steps include: Images are captured within a preset acquisition area of ​​passive optical network port resources on the same axis using a miniature camera; the images include at least passive device enclosure label information, port occupancy information, and fiber optic label information.

[0040] It should be noted that the multi-level system architecture base consists of IoT card miniature cameras installed inside the passive device enclosure.

[0041] The miniature camera uses FreeRTOS, a real-time operating system designed specifically for embedded devices. This operating system is lightweight, real-time, and supports multiple tasks, allowing concurrent execution of tasks such as camera control, data processing, and network communication while consuming minimal system resources. Furthermore, timed acquisition of port resources is achieved through a real-time clock (Real_TimeClock, RTC) in the camera hardware and cron task scheduling.

[0042] Miniature cameras utilize the lightweight publish / subscribe messaging protocol MQTT, which features low bandwidth consumption, reliability, bidirectional communication, and long-term connections, making it ideal for IoT scenarios. Through this protocol, miniature cameras can publish collected image data to specified topics, subscribe to configuration update topics, receive remote control commands, and send device status information such as battery level and storage space.

[0043] Miniature cameras provide a stable internet connection via 4G / 5G modules. The wide coverage of 4G / 5G modules allows camera devices to be deployed almost anywhere, and their high bandwidth and low latency characteristics support fast transmission of high-quality images.

[0044] Miniature cameras use the libjpeg image compression library to compress image size, which can significantly reduce image file size. The compression rate can be dynamically adjusted according to network conditions in the camera system to reduce the amount of data transmitted.

[0045] After determining the configuration of the IoT card miniature camera, a clip is added to the existing passive device enclosure to fix the miniature camera. The clip is usually installed on the inside of the front door of the enclosure and is on the same axis as the center of the area to be collected.

[0046] In one embodiment, taking a 1:8 plug-in PLC optical splitter with a fiber distribution box, widely used in passive optical network devices, as an example, the hardware device for image acquisition is described, such as... Figure 5 As shown, Figure 5 This is a schematic diagram of the image acquisition hardware device provided by the present invention.

[0047] The conventional fiber distribution box has a flat rectangular front door. In this embodiment of the invention, a buckle is added to the inside of the front door to secure the miniature camera. For newly manufactured fiber distribution boxes, an integrated device with the buckle can be manufactured; for fiber distribution boxes already in production, buckles made of the same PP plastic material as the fiber distribution box can be manufactured separately and bonded using KD-822PP special adhesive for small-area PP plastic.

[0048] like Figure 6 As shown, Figure 6This is a schematic diagram of the installation position of the miniature camera in the passive equipment enclosure provided by this invention. The splitter itself measures 13cm × 10cm × 2.5cm, and the configured fiber distribution box measures 40cm × 30cm × 20cm. The area to be captured by the miniature camera is the ABCD rectangular area shown in the diagram, which measures 10cm × 10cm. This area contains splitter enclosure label information, port occupancy information, and fiber optic label information. The miniature camera and the center of the ABCD rectangular area are on the same axis, with a distance of approximately 10cm between them. The miniature camera itself is approximately 3cm thick. A wide-angle macro camera is required to capture a complete and clear image of the rectangular area. The camera uses a wide-angle / macro dual-lens setup with a dynamic resolution of 5 megapixels and a static resolution of 1920*1080. The wide-angle angle must be greater than or equal to 160°, the minimum focusing distance must be less than or equal to 8mm, and the focusing method is single-focus. The image sensor is a highly integrated, low-power CMOS sensor. The miniature camera is powered by a built-in rechargeable battery with a capacity of 3000mAh. It uses a low-power timed wake-up mode, in which the miniature camera is only woken up once a day at the set collection time for 10 seconds. After the collection is completed, it enters standby mode. According to current technology, the camera can be used for about 365 days using this mode.

[0049] Specifically, such as Figure 2 As shown, after the IoT card miniature camera is installed, it can collect images within a preset acquisition area of ​​the passive optical network port resources on the same axis at set times. Figure 6 The ABCD rectangular area shown in the example is divided according to actual needs, ensuring it is on the same axis as the installation location of the miniature camera. The captured images must include at least the passive device enclosure label information, port occupancy information, and fiber optic label information. The time can be set using a monthly audit method, with the camera waking from standby mode at 00:00 on the first day of each month to begin image acquisition.

[0050] This invention integrates a miniature camera with passive optical network (PON) port resources on the same axis, enabling precise image acquisition of port resources within the passive device enclosure. The miniature camera efficiently captures key information within a preset acquisition area, providing intuitive and real-time data support for the management, monitoring, and maintenance of port resources. This achieves automated acquisition of port resource information, reducing the cost and error of manual shooting.

[0051] In some embodiments, based on step 102, when preprocessing the image using edge clouds to obtain a preprocessing result, the specific steps include: The validity of the image is detected using edge clouds; If the image is detected as valid, the image sharpness is adjusted using the edge cloud to obtain the adjusted image; The adjusted image is subjected to repeatability detection using the edge cloud. If duplicates are detected in the adjusted image, the duplicate images are discarded, and the preprocessed result is obtained. If it is detected that the adjusted image does not contain duplicates, then the adjusted image is determined as the preprocessing result.

[0052] The following content is for Figure 2 The process of validity testing, sharpness adjustment, and repeatability testing is described.

[0053] Specifically, edge cloud performs validity checks on images to avoid issues such as misalignment, overexposure, and blurriness in photos taken by the camera, ensuring that all images are valid. Specifically, the EfficientNet neural network model and the YOLO v5 real-time object detection algorithm can be used for image validity checks.

[0054] Before performing validity testing, the model is deployed to the edge cloud. The specific method is as follows: 1) First, collect a large number of sample images of passive optical network (PON) port resources, including various valid and invalid sample images, and use them as labels. Port type, brand, location, and image clarity should be considered to distinguish whether a sample image is valid; 2) Label each sample image to indicate whether it contains a valid network port and the specific location of the port, using this as a label; 3) Divide the dataset into training, validation, and test sets; 4) For the classification task of whether sample images are valid, the EfficientNet model can be selected and trained using the training set in step 1). For object detection of whether ports are valid, the YOLO v5 model can be selected and trained using the training set in step 2); 5) Train and fine-tune the model; 6) Deploy the model on edge devices.

[0055] Images of passive optical network (PON) port resources are input into the EfficientNet and YOLO v5 models. The EfficientNet model determines the validity of the image by identifying the absence of misalignment, overexposure, or blurring. The YOLO v5 model determines the validity of the ports within the image by identifying the absence of physical damage and proper connection. Only when the image clarity meets the requirements and the ports are functioning correctly can the image be considered valid; otherwise, it is considered invalid.

[0056] If an invalid image is detected, the image of the passive optical network port resource is re-acquired through the miniature camera, and the validity is checked again. If the re-acquired image is still invalid, an alarm is issued for the miniature camera, and the problem is manually checked to determine whether it is a problem with the miniature camera or the port, and relevant measures are taken for repair.

[0057] If the image is detected as valid, the edge cloud performs sharpness adjustment to make the acquired image clearer so that the central cloud can extract information from it. Specifically, a generative adversarial network (ESRGAN) can be used to generate high-resolution images.

[0058] Before sharpness adjustment, the model is deployed to an edge cloud. The specific method is as follows: 1) Histogram equalization of the image is performed using OpenCV. First, the gray-level histogram of the image needs to be calculated, then the cumulative distribution function (CDF) is calculated, and finally the CDF is linearized to remap the pixel values ​​to achieve image enhancement; 2) Prepare the dataset for the ESRGAN algorithm, including the low-resolution image after image enhancement and its corresponding high-resolution image; 3) Train the ESRGAN model using the training set in 2), extract features through residual dense blocks (RDB), use a relativistic discriminator to improve the generation quality, and use a perceptual loss function to improve the visual quality; 4) Deploy the model on an edge device and use the trained model for inference.

[0059] The image of the passive optical network port resources is input into the ESRGAN model, and the ESRGAN model generates a high-resolution image.

[0060] Furthermore, the edge cloud performs duplicate detection on the adjusted images to prevent the miniature cameras from repeatedly capturing images. Specifically, it can trace the image back to the miniature camera ID and the timestamp of the image capture. Since the miniature camera is awakened at a set capture time and only needs to capture one image within a preset capture area, reducing the computational load on the central cloud for extracting image information, it can determine whether multiple images were captured based on the miniature camera ID and the timestamp of the image capture. If multiple images are detected, the extra images are discarded, and only one is retained.

[0061] The image that is retained after passing through processes such as validity detection, sharpness adjustment, and repeatability detection is used as the preprocessing result after image preprocessing.

[0062] This invention utilizes edge cloud to preprocess acquired images. First, usable images are selected through validity detection. Then, sharpness adjustment is performed to optimize image quality. Redundant images are removed through repeatability detection, ultimately resulting in high-quality preprocessed results. This significantly improves the efficiency and accuracy of image processing, reduces the burden of data transmission and storage, and provides a reliable data foundation for subsequent port resource management and analysis.

[0063] In some embodiments, based on step 103, when verifying the first resource information and the second resource information through the central cloud and managing resource information according to the verification result, the specific steps include: The central cloud performs a consistency check between the first resource information and the second resource information. If the first resource information and the second resource information are consistent, then the second resource information in the resource system will not be revised. If the first resource information and the second resource information are inconsistent, the second resource information in the resource system shall be revised.

[0064] The following content is for Figure 2 The process of extracting resource information and revising resource audits is described.

[0065] Specifically, after image processing, Optical Character Recognition (OCR) technology can be used to extract key information from the image. OCR technology is a technique that extracts text content from an image into editable digital text. The extracted first resource information includes at least passive equipment enclosure label data, port occupancy data, and fiber optic label data. Further, the first resource information and its specific data content are stored in a hash table as key-value pairs. Similarly, the second resource information and its specific data content in the resource system are also stored in a hash table as key-value pairs, with both keys and values ​​maintaining consistency. Based on the two hash tables, a consistency check is performed on the first and second resource information. This involves comparing whether the values ​​corresponding to the same key in the two hash tables are consistent. Any inconsistency indicates that the first and second resource information are inconsistent.

[0066] If the first resource information and the second resource information are consistent, the central cloud will not revise the second resource information in the resource system.

[0067] If the first resource information and the second resource information are inconsistent, the central cloud will revise the second resource information in the resource system to ensure that the resource information in the resource system can be updated regularly.

[0068] This invention utilizes a central cloud to perform consistency verification between the first resource information and the second resource information. When the information is consistent, the system data remains unchanged; when the information is inconsistent, the second resource information in the resource system is automatically revised. This achieves efficient management and dynamic updating of resource information, ensuring the accuracy and real-time nature of resource information, significantly improving the reliability and automation level of resource management, greatly reducing labor costs, optimizing resource management processes, and improving network operation and maintenance efficiency and quality.

[0069] In some embodiments, after managing resource information based on the verification results, the method further includes: Obtain the latest secondary resource information for various types of passive optical network port resources; Based on the latest second resource information of various passive optical network port resources, a global view of passive optical network port resources is generated. The passive optical network port resources are displayed in real time on a large front-end screen.

[0070] The following content is for Figure 2 This describes the process of displaying a global view on the front-end large screen.

[0071] Specifically, through the above method, the resource information of each type of passive optical network port resource can be managed. The central cloud obtains the latest second resource information of each type of passive optical network port resource and generates a global view of passive optical network port resources based on the latest second resource information of each type of passive optical network port resource.

[0072] Furthermore, a global view of the passive optical network port resources is displayed in real time through a large front-end screen.

[0073] This invention integrates the latest second resource information of multiple types of passive optical network (PON) port resources to generate a global view, which is then displayed in real time on a large front-end screen. This enables comprehensive monitoring and visual management of PON port resources, providing not only a global insight into resource status but also enabling maintenance personnel to quickly locate problems and optimize resource configuration, thereby significantly improving the efficiency and decision-making capabilities of network maintenance.

[0074] In some embodiments, the dumb resource management method further includes: After the miniature camera is installed and connected to the network, the device information of the miniature camera is registered in the configuration management database; Monitor the operational status of registered miniature cameras and implement corresponding alarm mechanisms when miniature cameras malfunction.

[0075] Specifically, the system also has functions such as discovering and registering new cameras, monitoring camera operation, camera alarms, and displaying a global view of the cameras, enabling unified management of IoT card miniature cameras. The new camera discovery and registration feature can detect newly installed miniature cameras and register them in the CMDB (Configuration Center Database). Before installing a miniature camera, a unique identifier for the camera device must be determined, such as the device's MAC address and serial number. These identifiers are used to associate the device with a record in the CMDB. After a new camera device is installed and connected to the network, network scanning tools and automatic discovery technology are used to scan the network, detecting newly connected camera devices by detecting their MAC addresses, IP addresses, or other network characteristics, and adding them to the CMDB. Once a new camera device is discovered, its information can be automatically added to the CMDB through registration.

[0076] The camera operation monitoring function can monitor the operational status of registered miniature cameras. To monitor camera operation, the access layer provides a heartbeat service. Specifically, each camera captures and uploads an image from a passive optical network port resource daily, and the system checks whether the image has been received. Successful reception indicates the miniature camera is working normally; failure to receive the uploaded image indicates the miniature camera is down or malfunctioning. Through this simple yet effective "heartbeat" mechanism, we can promptly monitor the operational status of miniature cameras and take appropriate measures to resolve problems, ensuring continuous operation and maintaining normal working conditions.

[0077] The camera alarm function can take corresponding alarm mechanisms when the registered miniature camera fails to work properly. When the camera device fails to work properly, the device alarm needs to be triggered to remind the maintenance personnel to carry out maintenance. Miniature camera alarms are divided into the following situations: (1) Low battery alarm: If the camera's battery is depleted, it will not be able to continue to collect images and transmit data. A threshold can be preset for the camera's battery. When the battery is lower than the threshold, the camera will trigger a low battery alarm so that the miniature camera can be charged or the battery replaced in time; (2) Image misalignment alarm: When the collected image is not in the ABCD area, it is judged that the camera may have fallen off or the box is not in a closed state, resulting in misalignment of the collection area. At this time, an image misalignment alarm is triggered so that the position of the miniature camera can be checked and adjusted in time; (3) Image quality alarm: When the collected image is overexposed, too dark, or too blurry, it is judged that there is a problem with the camera's focal length, brightness, and other parameters or the camera quality is problematic, resulting in the collected image being unrecognizable. At this time, an image quality alarm is triggered so that the miniature camera parameters can be adjusted or the miniature camera can be replaced in time. The alarm mechanism can promptly identify cameras that are not working properly and alert maintenance personnel to perform repairs through central capabilities.

[0078] The camera global view display function enables the display of a complete view of the cameras on a large screen. The central capability provides a global view of miniature camera information and a large-screen display on the front end, showcasing the status information of the miniature cameras, including the total number of cameras, the number of cameras in each city, their operational status, alarm information, etc. Through the large-screen display, a centralized global view of the miniature cameras can be displayed, enabling comprehensive monitoring and management of the system's operational status.

[0079] This invention enables full lifecycle management of miniature cameras through functions such as discovering and registering new cameras, monitoring camera operation, camera alarms, and displaying a global view of the cameras. This significantly improves the management efficiency and reliability of miniature cameras and provides a stable guarantee for the continuous monitoring and data acquisition of passive optical network port resources.

[0080] The dumb resource management system provided by the present invention is described below. The dumb resource management system described below can be referred to in correspondence with the dumb resource management method described above.

[0081] Reference Figure 7 , Figure 7 This is a schematic diagram of the structure of the dumb resource management system provided by the present invention.

[0082] The dumb resource management system includes: Access layer 710 is used to acquire images of passive optical network port resources captured by miniature cameras.

[0083] Edge cloud 720 is used to preprocess the image to obtain a preprocessing result.

[0084] The central cloud 730 is used to extract information from the preprocessing results to obtain the first resource information of the passive optical network port resources; the central cloud verifies the first resource information and the second resource information, and manages the resource information according to the verification result; the second resource information is the resource information of the passive optical network port resources read through the resource system.

[0085] The dumb resource management system provided by this invention acquires images of passive optical network (PON) port resources using miniature cameras, preprocesses them using edge cloud to quickly obtain preliminary results, and then performs deep information extraction based on the preprocessing results in the central cloud to obtain first resource information. This first resource information is then verified against second resource information read by the resource system. Based on the verification results, accurate resource information management is achieved, ensuring the accuracy of PON port resource information. The system achieves efficient collaboration from image acquisition to information extraction, verification, and management, realizing fully automated dumb resource management, greatly reducing labor costs, optimizing resource management processes, and improving network operation and maintenance efficiency and quality.

[0086] Furthermore, the access layer 710 is also used for: Images are captured within a preset acquisition area of ​​passive optical network port resources on the same axis using a miniature camera; the images include at least passive device enclosure label information, port occupancy information, and fiber optic label information.

[0087] Furthermore, the edge cloud 720 is also used for: The validity of the image is detected using edge clouds; If the image is detected as valid, the image sharpness is adjusted using the edge cloud to obtain the adjusted image; The adjusted image is subjected to repeatability detection using the edge cloud. If duplicates are detected in the adjusted image, the duplicate images are discarded, and the preprocessed result is obtained. If it is detected that the adjusted image does not contain duplicates, then the adjusted image is determined as the preprocessing result.

[0088] Furthermore, the central cloud 730 is also used for: The central cloud performs a consistency check between the first resource information and the second resource information. If the first resource information and the second resource information are consistent, then the second resource information in the resource system will not be revised. If the first resource information and the second resource information are inconsistent, the second resource information in the resource system shall be revised.

[0089] Furthermore, the dumb resource management system is also used for: Obtain the latest secondary resource information for various types of passive optical network port resources; Based on the latest second resource information of various passive optical network port resources, a global view of passive optical network port resources is generated. The passive optical network port resources are displayed in real time on a large front-end screen.

[0090] Furthermore, the dumb resource management system is also used for: After the miniature camera is installed and connected to the network, the device information of the miniature camera is registered in the configuration management database; Monitor the operational status of registered miniature cameras and implement corresponding alarm mechanisms when miniature cameras malfunction.

[0091] It should be noted that the dumb resource management system provided by the present invention can execute the dumb resource management method described in any of the above embodiments during specific operation, which will not be elaborated in this embodiment.

[0092] Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 8 As shown, the electronic device may include: a processor 810, a communications interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communications interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 can call logical instructions in the memory 830 to execute a dumb resource management method, which includes: acquiring images of passive optical network (PON) port resources using a miniature camera; preprocessing the images using an edge cloud to obtain a preprocessing result; extracting information from the preprocessing result using a central cloud to obtain first resource information of the PON port resources; verifying the first resource information with second resource information using the central cloud, and managing resource information based on the verification result; the second resource information is the resource information of the PON port resources read through a resource system.

[0093] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0094] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is able to execute the dumb resource management method provided in the above embodiments, the method comprising: acquiring an image of a passive optical network port resource through a miniature camera; preprocessing the image through an edge cloud to obtain a preprocessing result; extracting information from the preprocessing result through a central cloud to obtain first resource information of the passive optical network port resource; verifying the first resource information and second resource information through the central cloud, and managing resource information according to the verification result; the second resource information being the resource information of the passive optical network port resource read through a resource system.

[0095] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the dumb resource management method provided in the above embodiments. The method includes: acquiring images of passive optical network port resources through a miniature camera; preprocessing the images through an edge cloud to obtain a preprocessing result; extracting information from the preprocessing result through a central cloud to obtain first resource information of the passive optical network port resources; verifying the first resource information and second resource information through the central cloud, and managing resource information according to the verification result; wherein the second resource information is resource information of the passive optical network port resources read through a resource system.

[0096] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0097] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for managing dumb resources, characterized in that, include: Images of passive optical network port resources are captured using a miniature camera; The image is preprocessed using edge clouds to obtain the preprocessed result; The first resource information of the passive optical network port resources is obtained by extracting information from the preprocessing results through the central cloud. The central cloud verifies the first resource information and the second resource information, and manages the resource information based on the verification result; the second resource information is the resource information of the passive optical network port resources read through the resource system.

2. The dumb resource management method according to claim 1, characterized in that, The step of verifying the first resource information and the second resource information through the central cloud, and managing the resource information based on the verification result, includes: The central cloud performs a consistency check between the first resource information and the second resource information. If the first resource information and the second resource information are consistent, then the second resource information in the resource system will not be revised. If the first resource information and the second resource information are inconsistent, the second resource information in the resource system shall be revised.

3. The dumb resource management method according to claim 2, characterized in that, After managing resource information based on the verification results, the following is also included: Obtain the latest secondary resource information for various types of passive optical network port resources; Based on the latest second resource information of various passive optical network port resources, a global view of passive optical network port resources is generated. The passive optical network port resources are displayed in real time on a large front-end screen.

4. The dumb resource management method according to claim 1, characterized in that, The preprocessing of the image using edge clouds to obtain the preprocessing result includes: The validity of the image is detected using edge clouds; If the image is detected as valid, the image sharpness is adjusted using the edge cloud to obtain the adjusted image; Repeatability detection is performed on the adjusted image using the edge cloud; If duplicates are detected in the adjusted image, the duplicate images are discarded, and the preprocessed result is obtained. If it is detected that the adjusted image does not contain duplicates, then the adjusted image is determined as the preprocessing result.

5. The dumb resource management method according to claim 1, characterized in that, A passive device enclosure contains a type of passive optical network port resource and a miniature camera; the miniature camera and the passive optical network port resource are mounted on the same axis. When acquiring images of passive optical network port resources using a miniature camera, the following are included: Images are captured within a preset acquisition area of ​​passive optical network port resources on the same axis using a miniature camera; the images include at least passive device enclosure label information, port occupancy information, and fiber optic label information.

6. The dumb resource management method according to claim 1, characterized in that, The dumb resource management method also includes: After the miniature camera is installed and connected to the network, the device information of the miniature camera is registered in the configuration management database; Monitor the operational status of registered miniature cameras and implement corresponding alarm mechanisms when miniature cameras malfunction.

7. A dumb resource management system, characterized in that, This includes the access layer, edge cloud, and central cloud; The access layer is used to acquire images of passive optical network port resources captured by the miniature camera; The edge cloud is used to preprocess the image to obtain a preprocessing result; The central cloud is used to extract information from the preprocessing results to obtain the first resource information of the passive optical network port resources; The central cloud verifies the first resource information and the second resource information, and manages the resource information based on the verification result; the second resource information is the resource information of the passive optical network port resources read through the resource system.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the dumb resource management method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium, wherein a computer program is stored on the non-transitory computer-readable storage medium, characterized in that, When the computer program is executed by a processor, it implements the steps of the dumb resource management method as described in any one of claims 1 to 6.

10. A computer program product, the computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the dumb resource management method as described in any one of claims 1 to 6.

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