Multi-stage gridding inspection responsibility dynamic tracking method and system based on forest leader system

Abstract

The invention relates to the field of forestry resource management, in particular to a multi-level gridding polling responsibility dynamic tracking method and system based on a forest growth system, and the method comprises the steps: dividing a forest region into grids according to the distribution of forestry resources and landforms, constructing a multi-level grid system, and formulating a polling task for each grid; an Internet of Things equipment intelligent terminal is arranged for the inspection personnel, the position and working state information of the inspection personnel is collected in real time, and the task of the inspection personnel is dynamically adjusted; in the inspection process, inspection personnel record found problems through the intelligent terminal, and perform responsibility dynamic tracking according to the record; and establishing a multi-level grid information sharing platform, uploading inspection data, problem processing conditions and personnel allocation information of each level of grid to the platform in real time, and carrying out information sharing and collaboration. According to the method, responsibility dynamic tracking is realized by constructing a multi-stage grid system, and the efficiency and effect of forestry resource protection are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of forestry resource management, in particular to a multi-level grid-based inspection responsibility dynamic tracking method and system based on the forest long system. BACKGROUND

[0002] With the advancement of ecological civilization construction, the forest long system, as an important system for protecting and developing forest and grassland resources, is widely implemented in various places. However, there are many problems in the implementation of the forest long system. For example, although the grids at different levels are divided, the allocation of inspection tasks in the grids lacks scientific planning, resulting in excessive frequent inspection in some areas and insufficient inspection in some areas; in the scheduling of inspection personnel, there is a lack of effective dynamic management mechanism, and the work arrangement of the inspection personnel cannot be adjusted in a timely manner according to the actual situation; for the tracking of inspection responsibility, it is mostly after-the-fact tracing, and it is difficult to grasp the responsibility implementation situation in real time during the inspection, resulting in untimely problem discovery and low problem solving efficiency. In addition, the information sharing between different levels of grids in the prior art is not timely and comprehensive, which affects the overall inspection effect and the efficiency of forestry resource protection. SUMMARY

[0003] The present application provides a multi-level grid-based inspection responsibility dynamic tracking method and system based on the forest long system to solve the problems of unscientific, untimely and difficult-to-track implementation of multi-level grid-based inspection responsibility in the implementation process of the existing forest long system, and improve the efficiency and effect of forestry resource protection.

[0004] The present application is realized by the following technical solutions: A multi-level grid-based inspection responsibility dynamic tracking method based on the forest long system is provided, which comprises the following steps: Step S10: According to the distribution of forestry resources and topography, etc., the forest area is divided into county-level, township-level, village-level and smaller basic grids, a multi-level grid system is constructed, individualized inspection tasks are formulated for each grid through big data analysis, and the number of inspection personnel and working time are reasonably allocated according to the grid area and inspection difficulty, etc.; Step S20: The inspection personnel are equipped with Internet of Things equipment intelligent terminals to collect the position and working state of the inspection personnel in real time, and the task arrangement of the inspection personnel is dynamically adjusted according to the forest area situation through artificial intelligence algorithm; Step S30: During the inspection, the inspection personnel record the problems found through the intelligent terminal, and the responsibility is dynamically tracked according to the record; Step S40: A multi-level grid information sharing platform is established, and the inspection data, problem handling situation and personnel allocation information of each level of grid are uploaded to the platform in real time for information sharing and collaboration.

[0005] Preferably, the step S10 of constructing a multi-level grid system includes the step of formulating personalized inspection tasks for each grid through big data analysis. Grid division: According to the forestry resource distribution and topography and other factors in step S10, the forest area is divided into different levels of grids by geographic information system (GIS) technology, including county-level grids, township-level grids, village-level grids and basic grids. The county-level grids cover the entire county forest area, the township-level grids are further refined on the basis of the county-level grids, the village-level grids are divided on the basis of administrative villages, and the basic grid is the smallest inspection unit in the divided grid. The area of each basic grid is controlled within a certain range according to the actual situation; Inspection task formulation: A grid risk analysis model based on big data analysis is established. Historical forest fire occurrence data and pest occurrence data are imported into the model, combined with current forestry resource distribution and topography information, and the risk level of each grid is output. According to the risk level of the grid, the inspection frequency is determined, and according to the grid area and inspection difficulty, the number of inspection personnel required for each grid is reasonably determined. According to the inspection task allocation information, a detailed inspection task list is generated for each inspection personnel, including inspection area, inspection route and inspection focus, etc., and is pushed to the corresponding inspection personnel through the intelligent terminal.

[0006] Preferably, the step S20 of dynamically adjusting the task arrangement of the inspection personnel includes: Inspection personnel information collection: Each inspection personnel is equipped with an intelligent terminal with positioning function and data transmission function. The intelligent terminal collects real-time position information, motion state (walking, staying, etc.) and working time data of the inspection personnel, and uploads them to the cloud; Dynamic task arrangement: When a fire occurs in the forest area, the cloud immediately starts the emergency response mechanism, analyzes the distribution of inspection personnel and the work progress of the surrounding grids of the fire occurrence area through artificial intelligence algorithm, and selects the nearest inspection personnel with relatively light work tasks for deployment; Inspection process tracking: During the inspection process, the intelligent terminal continuously monitors the work progress and state of the inspection personnel. When it is monitored that a certain inspection personnel cannot complete the inspection task on time due to special reasons, the inspection task of the area is automatically re-planned, and the remaining task is allocated to other inspection personnel or the inspection time arrangement is adjusted.

[0007] Preferably, the step S30 of dynamically tracking responsibility according to the record includes: Real-time feedback of inspection problems: During the inspection process, when the inspection personnel find problems related to the protection of forestry resources, they immediately take photos to record detailed information through the intelligent terminal, including problem location, discovery time and problem description, etc., and upload them to the cloud; Construction of unique identification of inspection problems: through the blockchain technology, a unique identification code is generated for each problem, and the whole process information of problem discovery, reporting and processing is recorded on the blockchain; Inspection problem early warning mechanism: set up an early warning mechanism for grid leaders at all levels and relevant management personnel, set different processing time limits for problems of different emergency degrees, and when the problem exceeds the set processing time limit and is not solved, automatically send warning information to the relevant person in charge, including SMS reminders and smart terminal pop-up window reminders, etc., and at the same time, highlight the problems that are not handled on time on the information sharing platform, so that the superior department can supervise and coordinate.

[0008] Preferably, the step S40 of sharing and cooperating information includes: Establishment of grid information sharing platform: a multi-level grid information sharing platform is established, which is based on cloud computing technology and has powerful data storage and processing capacity. The inspection data, problem handling situation and personnel deployment information of each level of grid are uploaded to the platform in real time; Interaction and collaborative work: different levels of grids can interact and work together through the platform. When the village-level grid discovers forest disaster problems, the village-level grid leader fills out the forest disaster report through the platform, describes the category, scope and severity of the forest disaster in detail, and sends a request for technical support and resource allocation to the town-level grid and the county-level grid. After receiving the request, the town-level grid and the county-level grid organize relevant experts to conduct remote consultation or on-site inspection, develop prevention and control programs according to the actual situation, and allocate pesticides and prevention and control equipment to the village-level grid through the platform. At the same time, the county-level grid can coordinate the prevention and control work of the whole county according to the forest disaster occurrence situation in each region on the platform, reasonably arrange the prevention and control team and resources, and avoid resource waste and repeated labor; Information query and statistics: set information query and statistical analysis functions on the information sharing platform. The grid leaders and relevant management personnel at all levels can query the forestry resource protection information of the region or other regions according to their permissions. The platform can also statistically analyze various data to generate reports and charts to provide data support for decision-making.

[0009] In addition, in order to achieve the above purpose, the present application also proposes a multi-level grid-based inspection responsibility dynamic tracking system based on the forest ranger system, which comprises: Grid construction and inspection task setting module: used for dividing the forest area into county-level, town-level, village-level and smaller basic grids according to forestry resource distribution and topography, etc., constructing a multi-level grid system, setting individualized inspection tasks for each grid through big data analysis, and reasonably allocating the number of inspection personnel and working time according to the grid area and inspection difficulty, etc.; The patrol personnel dynamic scheduling module is used for equipping the patrol personnel with an Internet of Things device intelligent terminal, collecting the position and working state of the patrol personnel in real time, dynamically adjusting the task arrangement of the patrol personnel according to the forest area situation through an artificial intelligence algorithm; The responsibility dynamic tracking module is used for recording the problems found by the patrol personnel through the intelligent terminal during the patrol process, and dynamically tracking the responsibility according to the record. The information sharing and cooperation module is used for establishing a multi-level grid information sharing platform, uploading the patrol data, problem processing situation and personnel deployment information of the grids at all levels to the platform in real time, and performing information sharing and cooperation.

[0010] In addition, in order to achieve the above purpose, the application also provides a multi-level grid patrol responsibility dynamic tracking device based on the forest long system, which comprises a memory, a processor and a multi-level grid patrol responsibility dynamic tracking algorithm based on the forest long system and the like program stored on the memory and capable of running on the processor.

[0011] In addition, in order to achieve the above purpose, the application also provides a computer program product, which comprises a multi-level grid patrol responsibility dynamic tracking algorithm based on the forest long system and the like program, which realizes the multi-level grid patrol responsibility dynamic tracking method based on the forest long system as described above when executed by the processor.

[0012] The advantages and effects of the application are as follows: The multi-level grid patrol responsibility dynamic tracking method and system based on the forest long system can ensure that the patrol work is more reasonable and efficient, avoid resource waste and patrol loopholes, and timely find and handle problems in the protection of forestry resources through scientific grid division and task allocation, dynamic scheduling of patrol personnel, and the use of blockchain technology to realize dynamic tracking of responsibility, so that the responsibility of each link is clear and explicit, effectively supervising the performance of duties of patrol personnel at all levels, improving the timeliness and effectiveness of problem solving, and promoting communication and cooperation between grids at different levels through the establishment of an information sharing and cooperation platform, breaking down information barriers, realizing overall linkage of forestry resource protection work, and improving the ability to respond to emergencies and major problems. BRIEF DESCRIPTION OF DRAWINGS

[0013] In order to make the technical solutions in the embodiments of the present application or the prior art clearer, the accompanying drawings needed in the embodiments or prior art description will be briefly introduced. Obviously, the accompanying drawings in the following description only represent some embodiments of the present application, and other drawings can be obtained by those of ordinary skill in the art without any creative effort.

[0014] Figure 1 A flow chart of the multi-level grid-based patrol responsibility dynamic tracking method based on the forest long system of the present application.

[0015] Figure 2 A structural schematic diagram of the multi-level grid-based patrol responsibility dynamic tracking system based on the forest long system of the present application.

[0016] Figure 3 A structural schematic block diagram of the multi-level grid-based patrol responsibility dynamic tracking electronic device based on the forest long system of the present application. DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments only represent some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without any creative effort fall within the scope of the present application.

[0018] As shown in Figure 1 In one embodiment of the present application, the multi-level grid-based patrol responsibility dynamic tracking method based on the forest long system includes the following steps: Step S10: According to forestry resource distribution and topography, etc., the forest area is divided into county-level, township-level, village-level and smaller basic grids to construct a multi-level grid system. Through big data analysis, combined with historical forest fire frequency, high-incidence areas of pests and diseases, distribution of rare species, etc., individualized patrol tasks are formulated for each grid. For example, for the grid with high incidence of forest fires, the patrol frequency is increased and the focus is on fire hazards; for the area with distribution of rare species, the survival environment of the species and whether there is human damage, etc. are emphasized, and the number of patrol personnel and working hours are reasonably allocated according to the grid area and patrol difficulty, etc.

[0019] Specifically, the step of constructing a multi-level grid system in step S10 and formulating individualized patrol tasks for each grid through big data analysis includes: Grid division: Through geographic information system (GIS) technology, the forest area is divided into different levels of grids based on the distribution of forestry resources and topography in step S10, including county-level grids, township-level grids, village-level grids, and basic grids. County-level grids cover the entire county forest area, township-level grids are further refined based on county-level grids, village-level grids are divided based on administrative villages, and basic grids are the smallest patrol units in the divided grids. The area of each basic grid is controlled within a certain range, such as 100 to 500 mu, according to actual conditions; Patrol task formulation: Establish a grid risk analysis model based on big data analysis, import historical forest fire occurrence data and pest and disease occurrence data into the model, combine current forestry resource distribution and topography information, and output the risk level of each grid. According to the risk level of the grid, determine the patrol frequency. For high-risk grids, such as areas with frequent historical fires or high pest and disease incidence, set a higher patrol frequency, such as 2-3 times per week. For low-risk grids, patrol 1-2 times per month. At the same time, according to the grid area and patrol difficulty, reasonably determine the number of patrol personnel required for each grid, such as arranging 3-5 patrol personnel for grids with large area and complex terrain, and arranging 1-2 patrol personnel for grids with small area and simple terrain. According to the patrol task allocation information, generate a detailed patrol task list for each patrol personnel, including patrol area, patrol route, and patrol focus, and push it to the corresponding patrol personnel through the intelligent terminal.

[0020] Step S20: Equip patrol personnel with Internet of Things (IoT) device intelligent terminals to collect real-time information such as patrol personnel's location and working status. Through artificial intelligence algorithms, dynamically adjust the task arrangement of patrol personnel according to forest area conditions such as fire, pest and disease outbreak, etc. For example, when a fire occurs in a certain area, the system automatically allocates patrol personnel from surrounding grids to the fire area for support and re-plans patrol tasks in other areas to ensure that overall patrol work is not greatly affected.

[0021] Specifically, the step of dynamically adjusting the task arrangement of patrol personnel in step S20 includes: Patrol personnel information collection: Equip each patrol personnel with an intelligent terminal with positioning function and data transmission function, such as a smart watch or a customized handheld device. The intelligent terminal collects real-time data such as patrol personnel's location information, motion state (walking, staying, etc.), and working time, and uploads them to the cloud; Dynamic task arrangement: when a forest fire occurs, such as through forest fire high-altitude lookout video monitoring platform or mass reporting, if a fire is found in a certain area, the cloud immediately starts the emergency response mechanism, analyzes the distribution of patrol personnel and the work progress of the surrounding grid of the fire area through artificial intelligence algorithms, such as genetic algorithm, particle swarm optimization algorithm, etc., selects the patrol personnel closest to the fire site and with relatively lighter work tasks, for example, when a fire occurs in A village grid, the cloud finds that two patrol personnel in the adjacent B village grid have completed most of the patrol tasks and are close to the fire site, automatically sends a support task instruction to the intelligent terminal of the two patrol personnel, and adjusts the tasks of other patrol personnel in the B village grid to ensure that the patrol work in the B village grid can still proceed normally; Patrol process tracking: during the patrol process, the intelligent terminal continuously monitors the work progress and state of the patrol personnel, and when it is found that a patrol personnel cannot complete the patrol task on time due to special reasons such as illness, equipment failure, etc., the patrol task of the area is automatically re-planned, the remaining tasks are allocated to other patrol personnel or the patrol time is adjusted, for example, when a patrol personnel suddenly falls ill during the patrol, the unfinished patrol task is re-allocated to the patrol personnel of the adjacent grid, and the relevant management personnel are notified to arrange medical assistance.

[0022] Step S30: During the patrol process, the patrol personnel record the problems found through the intelligent terminal, such as tree cutting, signs of pests and diseases, fire hazards, etc., and upload them to the cloud, and dynamically track the responsibility according to the records.

[0023] Specifically, the step of dynamically tracking responsibility according to records in step S30 includes: Real-time feedback of patrol problems: during the patrol process, when the patrol personnel find forestry resource protection related problems, such as finding that trees have been illegally cut, signs of pests and diseases appear in the forest, or there are fire hazards, etc., they immediately take photos through the intelligent terminal to record detailed information, including problem location, discovery time and problem description, etc., and upload them to the cloud; Constructing a unique identifier for patrol problems: through blockchain technology, a unique identifier is generated for each problem, and the whole process information of the problem, such as discovery, reporting and handling, is recorded on the blockchain, for example, when the patrol personnel of the village grid report a tree cutting problem, the information of the patrol personnel, the reporting time, the problem details, etc. are recorded, when the problem is transferred to the town grid for processing, the information of the town grid responsible person receiving the problem, the handling measures taken, etc. are recorded, to ensure that the responsibility of each link is clear and traceable; Patrol problem early warning mechanism: set up early warning mechanism for grid responsible persons at all levels and relevant management personnel, set different processing time limits for different emergency problems, for example, set the processing time limit for 3 working days for general problems, and set the processing time limit for 1 hour for urgent problems such as fire hazards, when the problem exceeds the set processing time limit and is not solved, the relevant responsible person is automatically sent warning information, including SMS reminder and intelligent terminal pop-up window reminder, etc., at the same time, the problem not handled on time is highlighted on the information sharing platform, so that the superior department can supervise and coordinate.

[0024] Step S40: Establish a multi-level grid information sharing platform, upload the patrol data, problem handling situation and personnel deployment information of each level grid to the platform in real time, share and cooperate information, different levels of grids can work together through the platform, for example, when the village-level grid discovers major pest problems, it can request technical support and resource allocation to the town-level and county-level grids through the platform, and the county-level grid can coordinate the resources of the whole district according to the platform information to carry out pest control work.

[0025] Specifically, the steps of information sharing and cooperation in step S40 include: Establish grid information sharing platform: establish a multi-level grid information sharing platform, which is based on cloud computing technology and has powerful data storage and processing capacity, the patrol data, problem handling situation and personnel deployment information of each level grid are uploaded to the platform in real time, for example, the village-level grid uploads the patrol records, discovered problems and preliminary handling situation to the platform every day, the town-level grid supplements and summarizes the overall situation within the town based on the village-level grid data and uploads it, and the county-level grid summarizes the county data to realize the gradual gathering and sharing of information; Interaction and cooperative work: different levels of grids can interact and work together through the platform, when the village-level grid discovers forest disaster problems, such as major pest problems, the village-level grid responsible person fills out the forest disaster report through the platform, describes the category, scope and severity of forest disaster information in detail, and sends technical support and resource allocation request to the town-level grid and county-level grid, after receiving the request, the town-level grid and county-level grid organize relevant experts to conduct remote consultation or on-site inspection, formulate prevention and control scheme according to the actual situation, and allocate pesticide and prevention and control equipment resources to the village-level grid through the platform, at the same time, the county-level grid can coordinate the prevention and control work of the whole county according to the forest disaster occurrence situation of each region on the platform, reasonably arrange the prevention and control team and resources, avoid resource waste and repeated labor; Information query and statistics: Set up information query and statistical analysis functions on the information sharing platform. The grid managers at all levels and relevant management personnel can query the forestry resource protection information of their own region or other regions, such as patrol records, problem handling progress, etc. according to their permissions. The platform can also statistically analyze various data and generate reports and charts to provide data support for decision-making. For example, by statistically analyzing the number of forest fires and the incidence of pests and diseases in different regions, the effectiveness of forestry resource protection in each region can be evaluated to provide a basis for subsequent adjustment of patrol strategies and resource allocation.

[0026] In addition, as Figure 2 shown, in one embodiment of the present application, a multi-level grid-based patrol responsibility dynamic tracking system based on the forester system is proposed, which comprises: Grid construction and patrol task setting module: used for dividing the forest area into county-level, township-level, village-level and smaller basic grids according to forestry resource distribution and topography, etc., constructing a multi-level grid system, and setting individualized patrol tasks for each grid through big data analysis, and reasonably allocating the number of patrol personnel and working time according to the grid area and patrol difficulty, etc. Patrol personnel dynamic scheduling module: used for equipping patrol personnel with Internet of Things equipment intelligent terminals to collect information such as the location and working state of patrol personnel in real time, and dynamically adjusting the task arrangement of patrol personnel according to the forest area conditions such as forest fires, mass outbreaks of pests and diseases, etc. through artificial intelligence algorithms; Responsibility dynamic tracking module: used for recording the problems found by patrol personnel in the patrol process through intelligent terminals, such as tree felling, signs of pests and diseases, fire hazards, etc., and conducting dynamic tracking of responsibility according to the records; Information sharing and collaboration module: used for establishing a multi-level grid information sharing platform to upload the patrol data, problem handling conditions and personnel allocation information of each level of grid to the platform in real time for information sharing and collaboration.

[0027] The multi-level grid-based patrol responsibility dynamic tracking system based on the forester system provided by the present application adopts the multi-level grid-based patrol responsibility dynamic tracking method based on the forester system in the above embodiment, which can solve the technical problems of unscientific, untimely and difficult-to-track responsibility implementation in the implementation process of the existing forester system. Compared with the prior art, the multi-level grid-based patrol responsibility dynamic tracking system based on the forester system provided by the present application has the same beneficial effects as the multi-level grid-based patrol responsibility dynamic tracking method based on the forester system provided by the above embodiment, and other technical features in the multi-level grid-based patrol responsibility dynamic tracking system based on the forester system are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0028] The application provides a multi-level grid-based inspection responsibility dynamic tracking device based on the system of forest supervisors. The multi-level grid-based inspection responsibility dynamic tracking device based on the system of forest supervisors comprises at least one processor and a memory connected with the at least one processor in communication. The memory stores instructions executable by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform the multi-level grid-based inspection responsibility dynamic tracking method based on the system of forest supervisors in the first embodiment.

[0029] As shown in Figure 3 In one embodiment of the application, a structural diagram of a multi-level grid-based inspection responsibility dynamic tracking device based on the system of forest supervisors is shown, which is suitable for implementing the embodiments of the application. The multi-level grid-based inspection responsibility dynamic tracking device based on the system of forest supervisors in the embodiments of the application can include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistant), PADs (Portable Application Description), PMPs (Portable Media Player), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. Figure 3 The multi-level grid-based inspection responsibility dynamic tracking device based on the system of forest supervisors shown is only an example and should not bring any limitation to the functions and use range of the embodiments of the application.

[0030] Figure 3The illustrated forest long system-based multi-level gridding inspection responsibility dynamic tracking device can include a processing system 1001 (e.g., a central processor, a graphics processor, etc.) that can perform various appropriate actions and processes according to programs stored in a read only memory (ROM) 1002 or programs loaded from a storage system 1003 into a random access memory (RAM) 1004. In the RAM 1004, various programs and data required for the forest long system-based multi-level gridding inspection responsibility dynamic tracking device to operate are also stored. The processing system 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input system 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output system 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; the storage system 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication system 1009. The communication system 1009 can allow the forest long system-based multi-level gridding inspection responsibility dynamic tracking device to communicate with other devices wirelessly or by wire to exchange data. Although the forest long system-based multi-level gridding inspection responsibility dynamic tracking device with various systems is illustrated in the figure, it should be understood that all of the illustrated systems are not required to be implemented or possessed. More or fewer systems can be alternatively implemented or possessed.

[0031] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program carrying computer program code for performing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication system, or installed from the storage system 1003, or installed from the ROM 1002. When the computer program is executed by the processing system 1001, the above-mentioned functions defined in the methods of the embodiments of the present disclosure are performed.

[0032] The multi-level grid-based inspection responsibility dynamic tracking device based on the system of forest rangers provided by the application adopts the multi-level grid-based inspection responsibility dynamic tracking method based on the system of forest rangers in the above embodiment, and can solve the technical problems that the responsibility implementation is not scientific, not timely and difficult to track in the implementation process of the system of forest rangers. Compared with the prior art, the multi-level grid-based inspection responsibility dynamic tracking device based on the system of forest rangers provided by the application has the same beneficial effects as the multi-level grid-based inspection responsibility dynamic tracking method based on the system of forest rangers provided by the above embodiment, and other technical features in the multi-level grid-based inspection responsibility dynamic tracking device based on the system of forest rangers are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0033] Parts of the application can be implemented in hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0034] The application also provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the multi-level grid-based inspection responsibility dynamic tracking method based on the system of forest rangers as described above.

[0035] The computer program product provided by the application can solve the technical problems that the responsibility implementation is not scientific, not timely and difficult to track in the implementation process of the system of forest rangers. Compared with the prior art, the computer program product provided by the application has the same beneficial effects as the multi-level grid-based inspection responsibility dynamic tracking method based on the system of forest rangers provided by the above embodiment, which will not be repeated here.

[0036] Obviously, those skilled in the art can make various modifications and variations to the application without departing from the spirit and scope of the application. Thus, if these modifications and variations of the application belong to the scope of the claims of the application and their equivalent technologies, the application also intends to include these modifications and variations.

Claims

1. A multi-level grid-based dynamic tracking method for inspection responsibilities based on the forest chief system, characterized in that, The method includes the following steps: Step S10: Divide the forest area into grids according to the distribution of forestry resources and topography, construct a multi-level grid system, formulate inspection tasks for each grid through big data analysis, and reasonably allocate the number of inspection personnel and working time according to the grid area and inspection difficulty factors. Step S20: Equip patrol personnel with IoT smart terminals to collect their location and work status information in real time, and dynamically adjust their task assignments based on the forest area conditions using artificial intelligence algorithms; Step S30: During the inspection process, the inspection personnel record the problems they find through the smart terminal and track the responsibility dynamically based on the records; Step S40: Establish a multi-level grid information sharing platform to upload inspection data, problem handling status, and personnel allocation information of each level of grid to the platform in real time for information sharing and collaboration.

2. The multi-level grid-based dynamic tracking method for inspection responsibilities based on the forest chief system according to claim 1, characterized in that, The steps in step S10, which involve constructing a multi-level grid system and using big data analysis to formulate inspection tasks for each grid, include: Grid division: Using geographic information system technology, the forest area is divided into different levels of grids based on the distribution of forestry resources and topography as described in step S10, including county-level grids, town-level grids, village-level grids and basic grids. The county-level grids cover the entire county forest area, the town-level grids are further refined based on the county-level grids, the village-level grids are divided based on administrative villages, and the basic grids are the smallest inspection units in the divided grids. The area of ​​each basic grid is controlled within a certain range according to the actual situation. Inspection task formulation: Establish a grid risk analysis model based on big data analysis, import historical forest fire occurrence data and pest occurrence data into the model, combine it with current forestry resource distribution and topographic information, output the risk level of each grid, determine the inspection frequency based on the grid risk level, and at the same time, reasonably determine the number of inspection personnel in each grid based on the grid area and inspection difficulty. Based on the inspection task allocation information, generate an inspection task list for each inspection personnel, including inspection area, inspection route and inspection focus, and push it to the corresponding inspection personnel through smart terminals.

3. The multi-level grid-based dynamic tracking method for inspection responsibilities based on the forest chief system according to claim 1, characterized in that, The steps in step S20 of dynamically adjusting the task assignments of inspection personnel include: Inspection personnel information collection: Each inspection personnel is equipped with a smart terminal with positioning and data transmission functions. The smart terminal collects the location information, movement status and working time of the inspection personnel in real time and uploads it to the cloud. Dynamic task allocation: When a forest fire occurs, the cloud immediately activates the emergency response mechanism, analyzes the distribution and work progress of patrol personnel in the grid surrounding the fire area through artificial intelligence algorithms, and selects the patrol personnel closest to the fire scene for deployment; Inspection process tracking: During the inspection process, the smart terminal continuously monitors the work progress and status of the inspection personnel. When it is detected that an inspection personnel cannot complete the inspection task on time, the inspection task for that area is automatically re-planned, and the remaining tasks are assigned to other inspection personnel or the inspection time is adjusted.

4. The multi-level grid-based dynamic tracking method for inspection responsibilities based on the forest chief system according to claim 1, characterized in that, The step of dynamically tracking responsibility based on records in step S30 includes: Real-time feedback on inspection issues: When inspection personnel discover forestry resource protection-related issues during their inspections, they immediately use smart terminals to take photos and record detailed information, including the location of the problem, the time of discovery, and a description of the problem, and then upload it to the cloud. Construct a unique identifier for inspection issues: Using blockchain technology, generate a unique identifier for each issue and record the entire process of issue discovery, reporting, and handling on the blockchain; Inspection Problem Early Warning Mechanism: An early warning mechanism is set up for grid leaders and relevant management personnel at all levels. Different processing time limits are set for problems of different urgency. When a problem is not resolved within the set processing time limit, an early warning message is automatically sent to the relevant responsible person, including SMS reminders and smart terminal pop-up reminders.

5. The multi-level grid-based dynamic tracking method for inspection responsibilities based on the forest chief system according to claim 1, characterized in that, The steps for information sharing and collaboration in step S40 include: Establish a grid information sharing platform: A grid information sharing platform will be established, which is based on cloud computing technology. Inspection data, problem handling status and personnel allocation information of grids at all levels will be uploaded to the platform in real time. Interactive and collaborative work: Different levels of grids exchange information and collaborate through the platform. When a village-level grid discovers a forest disaster, the person in charge of the village-level grid fills out a forest disaster report through the platform, describing the type, scope and severity of the forest disaster, and sends a request for technical support and resource allocation to the township-level grid and the county-level grid. After receiving the request, the township-level grid and the county-level grid organize relevant experts to conduct remote consultations or on-site inspections, formulate prevention and control plans based on the actual situation, and allocate pesticides and prevention and control equipment resources to the village-level grid through the platform. At the same time, the county-level grid coordinates the prevention and control work of the whole county based on the forest disaster situation in each region on the platform. Information Query and Statistics: The information sharing platform is equipped with information query and statistical analysis functions. Grid leaders and relevant management personnel at all levels can query forestry resource protection information in their own region or other regions according to their permissions. The platform performs statistical analysis on various types of data and generates reports and charts.

6. A multi-level grid-based dynamic tracking system for inspection responsibilities based on the forest chief system, characterized in that: The multi-level grid-based dynamic tracking system for inspection responsibilities based on the forest chief system includes: The grid construction and inspection task formulation module is used to divide the forest area into grids based on the distribution of forestry resources and topography, construct a multi-level grid system, formulate inspection tasks for each grid through big data analysis, and reasonably allocate the number of inspection personnel and working time according to factors such as grid area and inspection difficulty. Dynamic scheduling module for patrol personnel: This module equips patrol personnel with IoT smart terminals to collect their location and work status information in real time, and dynamically adjusts their task assignments based on the forest area conditions using artificial intelligence algorithms. The responsibility dynamic tracking module is used by inspection personnel to record problems they find during inspections through smart terminals, and to dynamically track responsibilities based on the records. Information sharing and collaboration module: Used to establish a multi-level grid information sharing platform, which uploads inspection data, problem handling status and personnel allocation information of each level of grid to the platform in real time for information sharing and collaboration.

7. A multi-level grid-based dynamic tracking device for inspection responsibilities based on the forest chief system, characterized in that: include: The system includes a memory, a processor, and a dynamic tracking program for multi-level grid-based inspection responsibilities based on the forest chief system, which is stored in the memory and can run on the processor. When the processor executes the dynamic tracking program for multi-level grid-based inspection responsibilities based on the forest chief system, it implements the dynamic tracking method for multi-level grid-based inspection responsibilities based on the forest chief system as described in any one of claims 1 to 5.

8. A computer program product, characterized in that, When the processor executes the multi-level grid-based inspection responsibility dynamic tracking program based on the forest chief system, it implements the multi-level grid-based inspection responsibility dynamic tracking method based on the forest chief system as described in any one of claims 1 to 5.

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