Mobile office method and system applied to secret visit of rivers and lakes

Abstract

The invention provides a mobile office method and system applied to river and lake secret visit, and relates to the field of water resource management and environmental protection, and the method comprises the steps: after a new problem clue is received, carrying out the severity grade classification and influence range grade classification of the problem clue through an intelligent algorithm, and obtaining a classification result; according to the position information corresponding to the problem clues and the classification result, determining a priority order of the problem clues in a patrol queue; in the process that the worker carries out evidence collection according to the priority ranking, obtaining field evidence data corresponding to each problem clue through mobile equipment carried by the worker; and generating an investigation report according to the investigation template corresponding to the problem clue and the field evidence data. By implementing the method, intelligent allocation and mobile office of problem clues are realized, so that resource allocation is optimized, and response time delay of report generation is reduced.

Description

Technical Field

[0001] The present application relates to the field of water resource management and environmental protection, and in particular to a mobile office method and system for unannounced inspections of rivers and lakes. Background Art

[0003] In related technologies, by integrating more advanced information technologies, such as geographic information systems (GIS) and mobile office tools, supervisors can plan inspection routes for uploaded problem clues on the built-in map of the GIS system, and then field staff can use mobile office tools to input data and complete report filling according to the route planning results, which improves work flexibility and response speed to a certain extent.

[0004] However, the order in which problem clues are processed in related technologies is easily affected by human subjective judgment, resulting in insufficient intelligent allocation of problem clues, waste of resources and delayed response time. Summary of the invention

[0005] The present application provides a mobile office method and system for secret inspections of rivers and lakes, which is used to address the problem of insufficient intelligent allocation of problem clues in river and lake supervision, resulting in waste of resources and delayed response time.

[0006] In a first aspect, a mobile office method for unannounced inspection of rivers and lakes is applied to a mobile office system, and the method comprises: After receiving new problem clues, the problem clues are classified by severity level and impact scope level through intelligent algorithms to obtain classification results; Determining the priority ranking of the problem clues in the inspection queue according to the location information corresponding to the problem clues and the classification result, the inspection queue including a plurality of problem clues to be inspected; In the process of the staff collecting evidence according to the priority order, the on-site evidence data corresponding to each problem clue is obtained through the mobile device carried by the staff; Generate a research report based on the research template corresponding to the problem clues and the on-site evidence data.

[0007] Through the above embodiments, the mobile office system classifies the severity and impact scope of problem clues through intelligent algorithms, and determines the priority of problem clues in combination with location information, thereby avoiding the waste of resources and response delays caused by subjective judgment. At the same time, staff use mobile devices to collect evidence data on site and automatically generate research reports, which improves the flexibility and efficiency of undercover investigations of rivers and lakes. This method realizes the intelligent allocation of problem clues and mobile office, thereby optimizing resource allocation and reducing the response delay of report generation.

[0008] In some embodiments, the step of determining the priority ranking of the problem clues in the inspection queue according to the location information corresponding to the problem clues and the classification results specifically includes: Determine the inspection area corresponding to the problem clue according to the location information corresponding to the problem clue; Preliminarily sorting all problem clues in the inspection area according to the severity level classification, and the same severity level classification corresponds to the same sorting number; The problem clues with the same sorting numbers in the preliminary sorting are sorted again according to the impact range level classification to obtain the priority sorting in the inspection queues of different inspection areas.

[0009] Through the above embodiment, the mobile office system preliminarily sorts the problem clues in the same area according to the severity level, and then re-sorts the clues with the same number in the preliminary sorting according to the impact range level, and finally obtains the priority ranking in the area. This method can more accurately and scientifically reflect the urgency of different problem clues, ensuring that the most serious and most widely affected problems can be dealt with first, thereby minimizing the harm and improving the pertinence and timeliness of river and lake supervision work.

[0010] In some embodiments, after the step of re-sorting the problem clues with the same sorting number in the preliminary sorting according to the impact range level classification to obtain the priority sorting in the inspection queues of different inspection areas, the method further includes: Dividing the priority ranking into a plurality of category sequences in order, each of the category sequences including at least one question clue; In the same category sequence, a patrol sequence is generated according to the location information of the staff and the location information of each problem clue, so that the patrol path of the staff is the shortest; All the inspection sequences are integrated to obtain the adjusted priority ranking.

[0011] Through the above embodiments, the mobile office system divides the priority order into several category sequences; then plans the shortest inspection path in each sequence according to the location of the staff and the location of the problem clues; finally, integrates the inspection paths of all sequences to obtain the overall optimized path. This method can minimize the walking distance and time cost of the staff and improve the inspection efficiency. At the same time, while taking into account the priority of the problem clues, the spatial optimization of the path is considered, making the secret inspection of rivers and lakes more economical and efficient.

[0012] In some embodiments, the step of obtaining on-site evidence data corresponding to each problem clue through the mobile device carried by the staff specifically includes: Acquire audio data and text data corresponding to each question clue through a mobile device, wherein the audio data includes video data and voice data; Recognize the voice data through voice input conversion technology to generate annotation information of the video data; The audio data, the text data and the annotation information are integrated to generate on-site evidence data.

[0013] Through the above embodiments, the mobile office system collects on-site evidence data through mobile devices, automatically recognizes and transcribes voice data, generates text annotations for videos, and finally integrates audio, text, annotations and other information to form complete on-site evidence data. This method allows data collection, input, storage and other tasks to be highly synchronized, and retains the information chain throughout the process. At the same time, intelligent processing such as voice transcription greatly reduces the workload of staff and improves data sorting efficiency.

[0014] In some embodiments, after the step of obtaining on-site evidence data corresponding to each problem clue through a mobile device carried by the staff during the process of collecting evidence according to the priority order, the method further includes: When the device detects that the network is unstable or has no service, the on-site evidence data is stored in a local database; When reconnection to the Internet is detected, the on-site evidence data stored in the local database is synchronized to the cloud server.

[0015] Through the above-mentioned embodiments, during the process of evidence collection, if the mobile device detects that the network signal is poor or there is no network service, it will automatically save the evidence data to the local database first, and then synchronize the local data to the cloud server after the network is restored. This can solve the network bottleneck problem in undercover visits to rivers and lakes in the wild, ensure the continuity and integrity of data collection work, and avoid the risk of data loss caused by network interruptions.

[0016] In some embodiments, after the step of generating a research report based on the research template corresponding to the problem clue and the on-site evidence data, the step further includes: Obtain all the research reports within a preset time period; Conduct statistics on the survey reports to determine the number of problem clues corresponding to different patrol areas in different seasons; Determine the seasonality and regionality of the problem clues based on the number of the problem clues; The current first key monitoring area is determined based on the seasonal and regional laws.

[0017] Through the above embodiments, the mobile office system summarizes and compiles research reports within a certain time range, analyzes the distribution characteristics of problem clues in different regions in different seasons, discovers the temporal and spatial laws of problem clues, and determines the areas that need to be monitored at present. This method allows river and lake supervision work to shift from passive investigation to active prevention, and curbs the occurrence of problems at the source through early intervention and precise policy implementation.

[0018] In some embodiments, after the step of determining the current first key monitoring area according to the seasonal law and the regional law, the method further includes: Determine the second key monitoring area based on weather forecasts and social activity schedules; Generating a current key monitoring area list according to the first key monitoring area and the second key monitoring area; Current human and material resources are deployed based on the list of key monitoring areas.

[0019] Through the above embodiments, the mobile office system integrates external information such as weather forecasts and social activity schedules to form a more comprehensive and dynamic key monitoring area determination mechanism. This comprehensive use of internal and external data allows supervision work to predict and proactively prevent factors that may cause problems in advance.

[0020] In a second aspect, the present application provides a mobile office system, the mobile office system comprising: one or more processors and a memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, and the computer program codes include computer instructions. The one or more processors call the computer instructions so that the mobile office system can implement a mobile office method for unannounced visits to rivers and lakes provided in the above-mentioned embodiment, which will not be repeated here.

[0021] In a third aspect, the present application provides a computer-readable storage medium, including instructions. When the instructions are executed on a mobile office system, the mobile office system can implement a mobile office method for undercover visits to rivers and lakes provided in the above-mentioned embodiment, which will not be repeated here.

[0022] In a fourth aspect, the present application provides a computer program product. When the computer program product runs on a mobile office system, the mobile office system can implement a mobile office method for undercover visits to rivers and lakes provided in the above-mentioned embodiment, which will not be repeated here.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Intelligent algorithms are used to classify problem clues by severity and scope of impact, and priority is determined in combination with location information, thus realizing intelligent allocation of problem clues. This method overcomes the drawbacks of subjective judgment by humans, can minimize the response delay of major problems, improve the pertinence and timeliness of supervision work, and optimize the efficiency of the use of scarce supervision resources. At the same time, the system further optimizes the inspection path, minimizes the time and space costs of personnel, and makes the unannounced inspection of rivers and lakes more economical and efficient.

[0024] 2. Make full use of mobile devices for on-site evidence collection, and form a complete information chain through the collection of multi-source data such as audio, video, and text, intelligent voice transcription, and information-based data integration. This solution greatly facilitates front-line work, making evidence collection, data entry, storage and other links highly integrated, which not only reduces work intensity but also improves data integrity. At the same time, the fault-tolerant mechanism of local storage and cloud synchronization effectively copes with the problem of unstable network in the field, ensuring data security and work continuity.

[0025] 3. Summarize and analyze historical data to explore the temporal and spatial distribution patterns of problem clues; integrate external information such as weather and social activities to form a more comprehensive and dynamic monitoring model. Big data analysis enables supervision to shift from passive to active, and prevent problems from occurring at the source through early prediction and precise deployment. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a mobile office method applied to secret visits to rivers and lakes in an embodiment of the present application; Figure 2 It is another flowchart diagram of a mobile office method applied to secret visits to rivers and lakes in an embodiment of the present application; Figure 3 It is a schematic diagram of a physical device structure of a mobile office system in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0028] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0029] For ease of understanding, the following is a description of the process of the method provided by this implementation. Figure 1 , which is a flow chart of a mobile office method applied to secret visits to rivers and lakes in an embodiment of the present application.

[0030] S101. After receiving new problem clues, the problem clues are classified by severity level and impact scope level using an intelligent algorithm to obtain classification results.

[0031] When the mobile office system receives new clues about river and lake problems, it first classifies and evaluates the severity and scope of impact of the clues. This can be done automatically by applying intelligent algorithms. For example, the system can use natural language processing technology to analyze keywords in clue descriptions, such as "pollution," "leakage," and "depletion," and combine preset rules to determine the severity level of the problem. At the same time, the geographic information system can also be used to calculate parameters such as the area where the problem occurred and the surrounding population density to obtain a quantitative assessment of the scope of impact.

[0032] S102. Determine the priority ranking of the problem clues in the inspection queue based on the location information and classification results corresponding to the problem clues.

[0033] After completing the classification and evaluation of problem clues, the mobile office system determines the handling priority of each problem and forms an orderly inspection queue.

[0034] Specifically, the mobile office system divides problem clues into different inspection areas based on location information. Usually, there is a dedicated inspection team in charge of each area. The regional division can refer to administrative divisions or river basin distribution. In each area, the system prioritizes the severity level and the impact range level. The severity level is usually the primary reference factor, and high-level problems are handled first. In the case of the same severity level, problems with a larger impact range are ranked higher.

[0035] S103. When the staff collects evidence according to priority, the on-site evidence data corresponding to each problem clue is obtained through the mobile device carried by the staff.

[0036] When the inspection team arrives at the scene of the problem according to the priority queue, they will start collecting evidence to provide first-hand information for subsequent analysis and disposal. Specifically, on-site evidence data can be collected through mobile devices carried by staff, which can be done by taking photos, recording videos, manual recording, etc., which are not limited here. Among them, mobile devices can be terminals such as smart phones and tablets that have data collection and network transmission functions. Staff can use the pre-installed evidence collection APP on the device, which integrates functions such as shooting, recording, positioning, and text input. When collecting evidence on site, the APP will automatically record key information such as latitude and longitude, timestamp, etc. to ensure the integrity and accuracy of the evidence.

[0037] S104. Generate a research report based on the research template corresponding to the problem clues and the on-site evidence data.

[0038] After completing the evidence collection at the scene of the problem, the mobile office system calls up the preset research template to sort out and process the collected raw data to form a structured research report for reference in subsequent case trials and administrative decision-making. Among them, the research template is a standardized form designed in advance according to different types of problems. It stipulates the basic framework and information elements of the report. For example, the research template of a pollution incident may include chapters such as "cause of the incident", "type of pollutant", "scope of pollution", "ecological damage", and "rectification measures". The on-site evidence data is the "filler" of the template, which provides the material for generating the report. The system identifies, extracts, and classifies the collected unstructured data such as pictures and videos, and converts them into structured information that can be used for report generation.

[0039] In the above embodiment, the mobile office system classifies the severity and impact scope of problem clues through intelligent algorithms, and determines the priority of problem clues in combination with location information, thereby avoiding the waste of resources and response delays caused by subjective judgment. At the same time, staff use mobile devices to collect evidence data on site and automatically generate research reports, which improves the flexibility and efficiency of undercover investigations of rivers and lakes. This method realizes the intelligent allocation of problem clues and mobile office, thereby optimizing resource allocation and reducing the response delay of report generation.

[0040] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of a mobile office method applied to secret visits to rivers and lakes in an embodiment of the present application.

[0041] S201. Determine the inspection area corresponding to the problem clue based on the location information corresponding to the problem clue.

[0042] The mobile office system analyzes the location information of problem clues and divides them into corresponding inspection areas. Specifically, the mobile office system integrates the Geographic Information System (GIS) component, which can geocode the received problem clues and extract their latitude and longitude information. At the same time, the system has built-in vector boundary data for each inspection area. Through spatial query and topological analysis, it can be determined in which inspection area the problem point falls, thereby achieving automatic classification.

[0043] S202. Preliminary sorting of all problem clues in the inspection area according to severity levels.

[0044] After completing the regional classification of problem clues, the mobile office system conducts severity assessment and preliminary sorting of problem clues in each region. Specifically, the system uses rule engine technology to parameterize the judgment rules and thresholds. Based on the rule engine, the system can evaluate the problem clue data one by one, derive the severity level, and sort them from high to low according to the severity level, and store the sorting results in the system background.

[0045] S203. Sort the problem clues with the same sorting number in the preliminary sorting again according to the impact range level classification to obtain the priority sorting in the patrol queue of different patrol areas.

[0046] Based on the severity ranking of problem clues, the mobile office system evaluates the impact of each problem as a reference factor for determining the final disposal priority.

[0047] Specifically, the mobile office system uses a spatial database to store various geographic elements, and uses GIS methods such as spatial analysis and raster computing to achieve quantitative assessment of the impact range. Based on the severity sorting, the system uses the impact range level as the second sorting key value to further sort the problem clues with the same severity. Through two rounds of sorting, each patrol area eventually forms a unified, prioritized queue of problems to be dealt with.

[0048] In the above embodiment, the mobile office system preliminarily sorts the problem clues in the same area according to the severity level, and then re-sorts the clues with the same number in the preliminary sorting according to the impact range level, and finally obtains the priority ranking in the area. This method can more accurately and scientifically reflect the urgency of different problem clues, ensuring that the most serious and most widely affected problems can be dealt with first, thereby minimizing the harm and improving the pertinence and timeliness of river and lake supervision work.

[0049] S204: Divide the priority ranking into multiple category sequences in order.

[0050] After forming the regional priority queue, the mobile office system divides the queue into several category sequences. Each sequence aggregates a group of issues with similar priorities and similar handling requirements, which can be uniformly scheduled as independent task units. Optionally, multiple sequence division parameters such as severity, impact range, and location proximity can be set. Based on the cluster analysis algorithm, the system comprehensively considers various parameter elements and automatically divides the priority queue into several problem clusters. Each problem cluster corresponds to a category sequence, and the order of the sequence is positively correlated with the comprehensive score of the cluster center.

[0051] For example, in a specific embodiment, the queue of river and lake problems in a certain area is finally divided into 5 categories: Category I is water quality problems involving drinking water sources, Category II is ecological damage problems involving protected areas, Category III is large-scale river and lake surface pollution problems, Category IV is medium-scale industrial wastewater illegal discharge problems, and Category V is scattered and minor riverbank garbage problems. After the sequence division, Category I problems are prioritized for rapid inspection by special inspection teams, Category II problems are coordinated with the management office of the protected area for joint law enforcement, Category III problems are handed over to cities and counties to jointly carry out agricultural pollution control projects, Category IV problems are included in the key supervision objects of daily inspections, and Category V problems are included in the daily maintenance scope of river and lake cleaning volunteers.

[0052] S205. In the same category sequence, a patrol sequence is generated based on the location information of the staff and the location information of each problem clue, so that the patrol path of the staff is the shortest.

[0053] Based on the formation of a problem category sequence, the mobile office system further optimizes the path of the arrangement order of problem clues within each sequence, aiming to minimize the time and space costs of inspectors and improve supervision efficiency.

[0054] Specifically, the system obtains the current location of the staff member as the starting point of the patrol path. Then, the geographic coordinates of the problem clues in the category sequence are used as city nodes, and the road network data is used to construct a complete graph, with the road distance between nodes as the edge weight. Next, a number of ants (software agents) are initialized and randomly placed in the starting city. Ants gradually select the next city to visit according to certain state transition rules until all nodes are traversed. After one iteration is completed, the total path length of each ant is compared, the pheromone concentration of the optimal path is increased, and all ants are relocated to the starting point. This iteration is repeated many times until it converges to a relatively stable shortest path. This path is the optimal patrol order for the problem clues in the category sequence.

[0055] S206. Integrate all inspection sequences to obtain adjusted priority ranking.

[0056] After completing the path optimization within each category sequence, the mobile office system will integrate the results of each sequence again to form the final regional problem resolution plan.

[0057] First, the system evaluates the timeliness requirements for handling problems in each sequence, estimates the deadline for task completion, and sets the corresponding penalty coefficient. Then, the shortest paths of all sequences are sorted in ascending order according to the total distance. Next, a similar idea to heuristic search is adopted, with each path as the basic extension line, to explore whether it can be partially merged with other paths, and further compress the total inspection distance while meeting the timeliness constraints. Among them, if the merger causes a delay in the deadline, the total distance is measured and corrected according to the penalty coefficient. After a step-by-step iterative search, an overall path plan that achieves a good balance between task timeliness and inspection mileage can be obtained.

[0058] Taking the five category sequences in the above step S204 as an example, the tasks of categories I and II involve sensitive targets and have a tight deadline for disposal, so they are executed independently as a single line. The timeliness requirements for tasks of categories III, IV, and V are relatively loose, and they can be integrated. Assuming that the distribution area of ​​the water surface problem of category III rivers and lakes is adjacent to the distribution area of ​​the problem of illegal industrial discharge of category IV, the single-line disposal requires 80 kilometers and 100 kilometers respectively. If the combined inspection can reduce the mileage by 20% and does not violate the disposal deadline of category IV problems, the two paths can be merged. However, the distribution of category V minor garbage problems is quite different from that of the first two categories of problems, and the detour mileage caused by the merger exceeds 20%, so it will not be integrated. Finally, the system generates three parallel optimal overall inspection routes, which are assigned to different inspection teams respectively. This dynamic planning-based task integration further reduces the total inspection mileage and balances the resource allocation for emergency disposal and daily maintenance.

[0059] In the above embodiment, the mobile office system divides the priority order into several category sequences; then plans the shortest inspection path in each sequence according to the location of the staff and the location of the problem clues; finally, the inspection paths of all sequences are integrated to obtain the overall optimized path. This method can minimize the walking distance and time cost of the staff and improve the inspection efficiency. At the same time, while taking into account the priority of the problem clues, the spatial optimization of the path is considered, making the secret inspection of rivers and lakes more economical and efficient.

[0060] S207. Acquire audio data and text data corresponding to each question clue through a mobile device.

[0061] During the undercover investigation of rivers and lakes, after the staff arrives at the scene of the problem with their mobile devices, they use the multimedia collection function of the devices to obtain audio and text evidence related to the clues of the problem. The mobile office system can deploy a special evidence collection application on the mobile device, integrating functions such as recording, taking photos, and recording videos. The staff can use this program to collect all-round evidence on illegal pollution discharge, illegal fishing and other problematic behaviors.

[0062] S208. Recognize the voice data through voice input conversion technology, generate annotation information for the video data, and integrate it with the audio data and text data to obtain on-site evidence data.

[0063] After acquiring unstructured evidence such as audio and video, the mobile office system processes it intelligently and extracts key information so that it can be converted into structured data that can be used for report generation.

[0064] Furthermore, the mobile office system introduces speech-to-text (STT) technology. This technology uses a machine learning algorithm that combines acoustic models and language models to automatically convert audio streams into text. Specifically, the system preprocesses the audio, filters out background noise, and separates the human voice. Then, the acoustic features of the human voice (such as spectrum, resonance peaks) are extracted and sent to the acoustic model for pronunciation unit (phoneme) recognition. Next, the language model infers the most likely text expression based on the phoneme sequence and contextual semantics. The entire process can be completed in real time on the cloud server, and the recognition results are synchronously returned to the mobile end of the mobile office system in the form of subtitles.

[0065] In the above embodiment, the mobile office system collects on-site evidence data through mobile devices, automatically recognizes and transcribes voice data, generates text annotations for videos, and finally integrates audio, text, annotations and other information to form complete on-site evidence data. This method allows data collection, input, storage and other tasks to be highly synchronized, and retains the information chain throughout the process. At the same time, intelligent processing such as voice transcription greatly reduces the workload of staff and improves data sorting efficiency.

[0066] S209. Generate a research report based on the research template corresponding to the problem clues and the on-site evidence data.

[0067] This step is the same as step S104 and will not be repeated here.

[0068] S210. Count the number of problem clues corresponding to different patrol areas in different seasons in all investigation reports within a preset time period, determine the seasonal and regional patterns of the problem clues, and the current first priority monitoring area.

[0069] After obtaining the river and lake problem investigation report within a certain time range, the mobile office system uses data mining technology to conduct in-depth analysis of the report data to discover the spatiotemporal distribution pattern of the problem events. Specifically, the system summarizes the number of problems in different seasons and regions to generate a multidimensional data set that reflects the spatiotemporal distribution characteristics of the problems. Then, the system uses algorithms such as time series analysis and spatial clustering to model the data set and extract the periodic and regional laws contained therein.

[0070] In the above embodiment, the mobile office system collects and compiles the research reports within a certain time range, analyzes the distribution characteristics of problem clues in different regions in different seasons, discovers the temporal and spatial laws of problem clues, and determines the areas that need to be monitored at present. This method allows the supervision of rivers and lakes to shift from passive investigation to active prevention, and curbs the occurrence of problems at the source through early intervention and precise policy implementation.

[0071] S211. Determine the second key monitoring area based on weather forecasts and social activity schedules.

[0072] In addition to relying on historical data to summarize areas with high incidence of problems, the mobile office system also dynamically adjusts the focus of supervision by obtaining data on external factors that affect river and lake problems. Specifically, the system obtains weather forecast information and major social event arrangements for a period of time in the future through a data interface, and determines the second key monitoring area based on preset association rules. For example, the forecast shows that there will be heavy rainfall in a certain place in the next week, and the accumulated rainfall may reach more than twice that of the same period in previous years. Then, the system sets this area as the second key monitoring area.

[0073] S212: Generate a current list of key monitoring areas based on the first key monitoring area and the second key monitoring area, and perform location deployment of current human and material resources.

[0074] After the mobile office system determines the first and second key monitoring areas respectively, it integrates the information of the two to form a complete distribution map of the key monitoring areas.

[0075] Furthermore, the system combines the problem type, risk level, and regulatory time requirements of each key area to match the appropriate regulatory force for each area. For example, for areas where problems are prone to occur and the risk level is high, priority is given to deploying regulatory teams with strong law enforcement capabilities and equipped with advanced equipment such as drones; for areas where problems occur frequently and the regulatory time requirements are high, additional patrol personnel are dispatched to increase the frequency of patrols; for areas where problems occur occasionally and the risk level is average, daily patrols are the main focus, supplemented by necessary special inspections.

[0076] In the above embodiment, the mobile office system integrates external information such as weather forecasts and social activity schedules to form a more comprehensive and dynamic key monitoring area determination mechanism. This comprehensive use of internal and external data allows supervision work to predict and proactively prevent factors that may cause problems in advance.

[0077] S213. When the device detects that the network is unstable or has no service, the on-site evidence data is stored in a local database.

[0078] In offline mode, on-site evidence data (photos, videos, texts, etc.) are directly stored in the local database of the device. The mobile office system uses the large-capacity storage of mobile terminal devices to provide a hardware foundation for offline data storage.

[0079] S214: When reconnection to the Internet is detected, the on-site evidence data stored in the local database is synchronized to the cloud server.

[0080] The mobile office system monitors the network recovery status in real time. Once it detects that the device is reconnected to the Internet, the system triggers the data synchronization mechanism and uploads the offline data in the local database to the cloud.

[0081] In the above embodiment, during the evidence collection process, if the mobile device detects that the network signal is poor or there is no network service, it will automatically save the evidence data to the local database first, and then synchronize the local data to the cloud server after the network is restored. This can solve the network bottleneck problem in field undercover visits to rivers and lakes, ensure the continuity and integrity of data collection, and avoid the risk of data loss caused by network interruptions.

[0082] The mobile office system of the embodiment of the present invention is applied to electronic equipment. Figure 3 A schematic diagram of the architecture of an electronic device suitable for implementing an embodiment of the present invention is shown.

[0083] It should be noted that Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0084] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructions (computer programs), or by controlling related hardware through instructions (computer programs), and the instructions can be stored in a computer-readable storage medium and loaded and executed by a processor. The electronic device of this embodiment includes a storage medium and a processor, wherein a plurality of instructions are stored in the storage medium, and the instructions can be loaded by the processor to execute any step of the method provided in the embodiment of the present invention.

[0085] Specifically, the storage medium and the processor are electrically connected directly or indirectly to realize data transmission or interaction. For example, these elements can be electrically connected to each other through one or more signal lines. The storage medium stores computer execution instructions for implementing the data access control method, including at least one software function module that can be stored in the storage medium in the form of software or firmware. The processor executes various functional applications and data processing by running the software program and module stored in the storage medium. The storage medium can be, but is not limited to, random access storage medium (Random Access Memory, referred to as: RAM), read-only storage medium (Read Only Memory, referred to as: ROM), programmable read-only storage medium (Programmable Read-Only Memory, referred to as: PROM), erasable read-only storage medium (Erasable Programmable Read-Only Memory, referred to as: EPROM), electrically erasable read-only storage medium (Electric Erasable Programmable Read-Only Memory, referred to as: EEPROM), etc. Among them, the storage medium is used to store programs, and the processor executes the program after receiving the execution instruction.

[0086] Furthermore, the software programs and modules in the above-mentioned storage medium may also include an operating system, which may include various software components and / or drivers for managing system tasks (such as memory management, storage device control, power management, etc.), and may communicate with various hardware or software components to provide an operating environment for other software components. The processor may be an integrated circuit chip having signal processing capabilities. The above-mentioned processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc., which may implement or execute the various methods, steps, and logic flow diagrams disclosed in this embodiment. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0087] Since the instructions stored in the storage medium can execute the steps in any method provided in the embodiments of the present invention, the beneficial effects of any method provided in the embodiments of the present invention can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0088] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A mobile office method for unannounced inspection of rivers and lakes, applied to a mobile office system, characterized in that: The method comprises: After receiving new problem clues, the problem clues are classified by severity level and impact scope level through intelligent algorithms to obtain classification results; Determining the priority ranking of the problem clues in the inspection queue according to the location information corresponding to the problem clues and the classification result, the inspection queue including a plurality of problem clues to be inspected; In the process of the staff collecting evidence according to the priority order, the on-site evidence data corresponding to each problem clue is obtained through the mobile device carried by the staff; Generate a research report based on the research template corresponding to the problem clues and the on-site evidence data.

2. The method according to claim 1, characterized in that The step of determining the priority ranking of the problem clues in the inspection queue according to the location information corresponding to the problem clues and the classification results specifically includes: Determine the inspection area corresponding to the problem clue according to the location information corresponding to the problem clue; Preliminarily sorting all problem clues in the inspection area according to the severity level classification, and the same severity level classification corresponds to the same sorting number; The problem clues with the same sorting numbers in the preliminary sorting are sorted again according to the impact range level classification to obtain the priority sorting in the inspection queues of different inspection areas.

3. The method according to claim 2, characterized in that After the step of re-sorting the problem clues with the same sorting number in the preliminary sorting according to the impact range level classification to obtain the priority sorting in the inspection queues of different inspection areas, the method further includes: Dividing the priority ranking into a plurality of category sequences in order, each of the category sequences including at least one question clue; In the same category sequence, a patrol sequence is generated according to the location information of the staff and the location information of each problem clue, so that the patrol path of the staff is the shortest; All the inspection sequences are integrated to obtain the adjusted priority ranking.

4. The method according to claim 1, characterized in that The step of obtaining on-site evidence data corresponding to each problem clue through the mobile device carried by the staff specifically includes: Acquire audio data and text data corresponding to each question clue through a mobile device, wherein the audio data includes video data and voice data; Recognize the voice data through voice input conversion technology to generate annotation information of the video data; The audio data, the text data and the annotation information are integrated to generate on-site evidence data.

5. The method according to claim 1, characterized in that After the step of obtaining on-site evidence data corresponding to each problem clue through a mobile device carried by the staff during the process of collecting evidence according to the priority order, the method further includes: When the device detects that the network is unstable or has no service, the on-site evidence data is stored in a local database; When reconnection to the Internet is detected, the on-site evidence data stored in the local database is synchronized to the cloud server.

6. The method according to claim 1, characterized in that After the step of generating a research report based on the research template corresponding to the problem clue and the on-site evidence data, the method further includes: Obtain all the research reports within a preset time period; Conduct statistics on the survey reports to determine the number of problem clues corresponding to different patrol areas in different seasons; Determine the seasonality and regionality of the problem clues based on the number of the problem clues; The current first key monitoring area is determined based on the seasonal and regional laws.

7. The method according to claim 6, characterized in that After the step of determining the current first key monitoring area according to the seasonal law and the regional law, the method further includes: Determine the second key monitoring area based on weather forecasts and social activity schedules; Generating a current key monitoring area list according to the first key monitoring area and the second key monitoring area; Current human and material resources are deployed based on the list of key monitoring areas.

8. A mobile office system, characterized in that: The mobile office system includes: one or more processors and memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, wherein the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the mobile office system to execute the method according to any one of claims 1 to 7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on the mobile office system, the mobile office system is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a mobile office system, the mobile office system is enabled to execute the method according to any one of claims 1 to 7.

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