Livestock and poultry farm informatization monitoring method and system

Abstract

The invention relates to a livestock and poultry farm informatization monitoring method and system. The system comprises a wireless transmission radar liquid level meter which is used for acquiring and transmitting excrement pool capacity data to a main monitoring platform; the wireless camera is used for collecting and transmitting a real-time video stream to the main monitoring platform; the GPS positioning equipment is used for collecting vehicle state information of the excrement transportation vehicle in real time and transmitting the vehicle state information to the main monitoring platform; and the main monitoring platform is used for analyzing the excrement pool capacity data, the real-time video stream and the vehicle state information, generating a corresponding anomaly recognition result, generating an early warning instruction and sending the early warning instruction to the early warning engine equipment and / or the management terminal. According to the system, the wireless transmission radar liquid level meter, the wireless camera and the GPS positioning equipment are integrated, so that comprehensive monitoring and analysis of the livestock and poultry farm manure pool capacity, real-time video streams and vehicle state information can be realized, an early warning instruction is generated in time and sent to a related terminal, and the environment management and operation efficiency of the farm is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of livestock and poultry breeding environment monitoring, and particularly relates to a livestock and poultry breeding farm informatization monitoring method and system. BACKGROUND

[0002] With the development of large-scale and intensive livestock and poultry breeding, the problems of manure treatment and breeding environment supervision in the breeding process are increasingly prominent, which seriously affects the ecological environment and the production and life of surrounding residents. However, the traditional livestock and poultry breeding farm supervision method has many shortcomings. On the one hand, the capacity of the manure pool of the breeding farm cannot be accurately grasped in real time, which easily leads to manure overflow and environmental pollution. Some breeding farms even have the phenomenon of random stacking and direct discharge of manure into rivers, which seriously damages the water body and the surrounding ecology. On the other hand, it is difficult to effectively supervise whether the breeding farm has irregularly set a sewage outlet, and the behavior of secretly discharging manure is repeated despite repeated prohibitions. There is a lack of technical means to timely discover and stop it. In addition, there is a lack of supervision of manure transport vehicles, and the driving route, position and emission behavior of the vehicles are difficult to control, which may cause secondary pollution during transportation. SUMMARY

[0003] Therefore, it is necessary to provide a livestock and poultry breeding farm informatization monitoring method and system aiming at the above technical problems, so as to enhance the accuracy and comprehensiveness of the supervision of livestock and poultry breeding farms and realize intelligent supervision of manure treatment in livestock and poultry breeding farms.

[0004] In a first aspect, the application provides a livestock and poultry breeding farm informatization monitoring system, comprising:

[0005] a total monitoring platform, a wireless transmission radar liquid level meter, a wireless camera, a GPS positioning device, a warning engine device and a management terminal;

[0006] The wireless transmission radar liquid level meter is deployed in the manure pool area of the breeding farm, used for acquiring manure pool capacity data and transmitting the manure pool capacity data to the total monitoring platform;

[0007] The wireless camera is deployed in the manure pool area of the breeding farm, used for collecting real-time video streams and transmitting the real-time video streams to the total monitoring platform;

[0008] The GPS positioning device is installed on the manure transport vehicle, used for collecting vehicle state information in real time and transmitting the vehicle state information to the total monitoring platform, wherein the vehicle state information includes position, driving speed and driving route;

[0009] The total monitoring platform is used for analyzing the manure pool capacity data, the real-time video streams and the vehicle state information respectively, generating corresponding abnormality recognition results, generating a warning instruction according to the abnormality recognition results, and sending the warning instruction to the warning engine device and / or the management terminal;

[0010] The early warning engine device is configured to execute the early warning instruction.

[0011] In one of the embodiments, the system further comprises an energy consumption supervision device configured to acquire, in real time, operation data of the manure treatment device, and transmit the operation data to the total monitoring platform, the operation data including current, voltage, power and device start-stop state;

[0012] The total monitoring platform is further configured to analyze the operation data, determine whether the manure treatment device is operating normally, obtain a device operation analysis result, and generate a device early warning instruction based on the device operation analysis result, and send the device early warning instruction to the early warning engine device and / or the management terminal;

[0013] The total monitoring platform obtains the device operation analysis result by analyzing the operation data through the following steps:

[0014] The current and the voltage are compared with corresponding safety thresholds respectively to obtain comparison results;

[0015] The manure treatment amount currently treated by the manure treatment device is acquired, and a reference power curve of the manure treatment device under the same manure treatment amount is acquired based on a historical database;

[0016] A dynamic deviation rate of the power and the reference power curve is calculated, and an efficiency analysis result is generated based on the dynamic deviation rate and a preset determination condition;

[0017] The device operation analysis result is obtained by combining the comparison results and the efficiency analysis result, and the device operation analysis result includes an abnormal type.

[0018] In one of the embodiments, the total monitoring platform is further configured to acquire breeding scale data, perform data verification and deviation analysis processing on the breeding scale data to obtain an abnormal data analysis result, and generate a data abnormality instruction based on the abnormal data analysis result, and send the data abnormality instruction to the management terminal, the breeding scale data including livestock and poultry species, inventory quantity and delivery quantity;

[0019] The total monitoring platform obtains the abnormal data analysis result by performing data verification and deviation analysis processing on the breeding scale data through the following steps:

[0020] The logical relationship between the inventory quantity and the delivery quantity is verified to determine whether it meets a preset logical rule, and the livestock and poultry species is matched with a preset breeding type database to obtain a data verification result;

[0021] A preset daily average manure generation parameter corresponding to the livestock and poultry species is acquired, and a theoretical manure amount is calculated based on the preset daily average manure generation parameter and the inventory quantity;

[0022] The actual manure transfer amount of the manure transport vehicle is acquired, and a manure deviation rate is calculated according to the actual manure transfer amount and the theoretical manure amount;

[0023] A deviation analysis result is generated based on the manure deviation rate;

[0024] The abnormal data analysis result is obtained in combination with the data verification result and the deviation analysis result.

[0025] In one of the embodiments, the system further comprises an odor monitoring device, which is configured to acquire odor data in real time and transmit the odor data to the total monitoring platform;

[0026] The total monitoring platform is further configured to analyze the odor data according to a preset odor emission threshold, determine whether the odor data exceeds the odor emission threshold, obtain an emission result, and generate an emission early warning instruction according to the emission result, and transmit the emission early warning instruction to the early warning engine device and / or the management terminal, wherein the odor data comprises odor concentration and odor components.

[0027] In one of the embodiments, the total monitoring platform is further configured to acquire manure treatment account information, analyze the manure treatment account information based on the manure pool capacity data and the operation data of the manure treatment device, obtain an account auditing result, and generate an account early warning instruction according to the account auditing result, and transmit the account early warning instruction to the management terminal, wherein the manure treatment account information comprises manure receiving quantity, receiving time, treatment method, treatment time and treatment product destination.

[0028] In one of the embodiments, the account auditing result is obtained by the following steps:

[0029] The manure receiving quantity in the manure treatment account information is associated with the change amount of the manure pool capacity data corresponding to the receiving time to obtain a verification result;

[0030] The treatment time in the manure treatment account information is compared with the operation period in the operation data of the manure treatment device to determine whether the treatment time is within the operation period, and an comparison result is obtained;

[0031] The account auditing result is obtained in combination with the verification result and the comparison result.

[0032] In one of the embodiments, the total monitoring platform comprises an image processing unit, which is configured to analyze the real-time video stream and generate a corresponding image abnormality recognition result by the following steps:

[0033] Video frame images are extracted from the real-time video stream at a preset sampling frequency;

[0034] The video frame images are subjected to noise reduction and contrast enhancement processing to obtain pre-processed image data;

[0035] According to the pre-processed image data, a U-Net semantic segmentation model is used to extract the fecal pool boundary region, and a fecal pool region segmentation map is obtained;

[0036] Based on the fecal pool region segmentation map, a target detection model based on a YOLOv7 network is used for detection to identify whether there is a sewage outlet in the fecal pool region segmentation map, and a preliminary identification result is obtained;

[0037] The preliminary identification result is matched with a preset compliant sewage outlet feature library to obtain a classification result, and the classification result includes the position and type of the sewage outlet, and the type is any one of non-existence of a sewage outlet, a compliant sewage outlet and a non-compliant sewage outlet;

[0038] When the type in the classification result is a non-compliant sewage outlet, the timestamp of the current abnormal video frame image corresponding to the classification result is obtained, and based on the timestamp, an abnormal video stream containing the timestamp of the current abnormal video frame image is automatically intercepted from the real-time video stream according to a preset rule;

[0039] In combination with the abnormal video stream and the classification result, an image anomaly recognition result is obtained.

[0040] In a second aspect, the present application also provides a livestock and poultry farm informatization monitoring method, comprising:

[0041] The fecal pool capacity data is obtained by a wireless transmission radar liquid level meter, and the fecal pool capacity data is transmitted to the total monitoring platform, and the wireless transmission radar liquid level meter is deployed in the fecal pool area of the farm;

[0042] The real-time video stream is collected based on a wireless camera, and the real-time video stream is transmitted to the total monitoring platform, and the wireless camera is deployed in the fecal pool area of the farm;

[0043] The vehicle state information is collected in real time according to a GPS positioning device, and the vehicle state information is transmitted to the total monitoring platform, and the vehicle state information includes position, driving speed and driving route, and the GPS positioning device is installed on the fecal sludge transport vehicle;

[0044] The fecal pool capacity data, the real-time video stream and the vehicle state information are analyzed by the total monitoring platform respectively, the corresponding abnormal recognition result is generated, the warning instruction is generated according to the abnormal recognition result, the warning instruction is sent to the warning engine device and / or the management terminal, and the warning engine device is used to execute the warning instruction.

[0045] In one of the embodiments, the method further comprises:

[0046] The odor data is obtained in real time by an odor monitoring device, and the odor data includes odor concentration and odor composition;

[0047] The odor data is analyzed according to a preset odor emission threshold, whether the odor data exceeds the odor emission threshold is judged, and an emission result is obtained;

[0048] An emission early warning instruction is generated based on the emission result, and the emission early warning instruction is sent to the early warning engine device and / or the management terminal.

[0049] In one of the embodiments, the method further comprises:

[0050] The operation data of the fecal sludge treatment device is acquired in real time by the energy consumption supervision device, and the operation data is transmitted to the total monitoring platform, the operation data including current, voltage, power and device start-stop state;

[0051] The operation data is analyzed by the total monitoring platform to determine whether the fecal sludge treatment device is operating normally, an operation analysis result of the device is obtained, and a device early warning instruction is generated according to the operation analysis result of the device;

[0052] The device early warning instruction is sent to the early warning engine device and / or the management terminal;

[0053] The total monitoring platform analyzes the operation data to obtain the operation analysis result of the device by the following steps:

[0054] The current and the voltage are compared with the corresponding safety threshold respectively to obtain a comparison result;

[0055] The current and the voltage are compared with the corresponding safety threshold respectively to obtain a comparison result;

[0056] The current and the voltage are compared with the corresponding safety threshold respectively to obtain a comparison result;

[0057] The current and the voltage are compared with the corresponding safety threshold respectively to obtain a comparison result;

[0058] The livestock and poultry farm informatization monitoring method and system realize the whole-process informationization supervision of the livestock and poultry farm manure treatment from generation, transportation to abnormal early warning. The wireless transmission radar liquid level meter provides a data basis for manure storage state monitoring by acquiring manure pool capacity data and transmitting the data to the total monitoring platform. The wireless camera can identify the sewage discharge port setting or abnormal discharge behavior by collecting real-time video streams and transmitting the video streams to the total monitoring platform. The GPS positioning device can track the vehicle running track throughout the process by collecting the position, speed, route and other state information of the manure transport vehicle, effectively preventing random dumping, deviating from the route and other irregular behaviors in the transportation process, and improving the controllability of the transportation link. The total monitoring platform generates abnormal identification results and triggers early warning instructions by comprehensively analyzing the above-mentioned various data, which not only realizes early warning of manure pool overflow, illegal sewage discharge, vehicle abnormal driving and other problems, but also ensures that the supervisor can master the dynamics of the breeding farm and the transportation link, and provides strong support for scientific decision-making and efficient law enforcement. BRIEF DESCRIPTION OF DRAWINGS

[0059] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the drawings needed to be used in the embodiments or the related art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0060] Figure 1 A livestock and poultry farm informatization monitoring system structure schematic diagram is provided for an exemplary embodiment of the present application.

[0061] Figure 2 A method flowchart for analyzing the operation data of the manure treatment equipment is provided for an exemplary embodiment of the present application.

[0062] Figure 3 A livestock and poultry farm informatization monitoring method flowchart is provided for an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0064] In one embodiment, as Figure 1As shown, a livestock and poultry farm information monitoring system 100 is provided. In this embodiment, the system includes a total monitoring platform 101, a wireless transmission radar liquid level meter 102, a wireless camera 103, a GPS positioning device 104, a warning engine device 105, and a management terminal 106.

[0065] The wireless transmission radar liquid level meter 102 is deployed in the manure pool area of the farm, used to obtain manure pool capacity data, and transmit the manure pool capacity data to the total monitoring platform 101.

[0066] Specifically, the wireless transmission radar liquid level meter 102 can use 80GHz-FMCW microwave radar technology and be deployed in the central area of the top of the manure pool to ensure that the measurement path is not blocked. The core component of the wireless transmission radar liquid level meter 102 is a radar sensor, which can calculate the liquid level height based on the time difference of radar wave reflection. The device can also have a built-in wireless transmission module, which can send the collected liquid level data to the total monitoring platform 101 in a preset time interval through long-distance wireless communication technology such as 4G / 5G network after packaging and encryption. In the data transmission process, error correction coding and retransmission mechanism can also be used to effectively avoid data loss or damage and ensure the integrity and accuracy of the data. After the total monitoring platform 101 analyzes the liquid level data, it can automatically convert the capacity value based on the geometric parameters of the manure pool.

[0067] The wireless camera 103 is deployed in the manure pool area of the farm, used to collect real-time video streams, and transmit the real-time video streams to the total monitoring platform 101.

[0068] The wireless camera 103 can be a network camera with high resolution and low-light imaging capability. It is deployed at key positions around the manure pool to ensure that it can capture real-time images of the manure pool and its surrounding environment in all directions. The wireless camera 103 can be equipped with a lens with adjustable focal length, so that the focal length and aperture size can be adjusted according to the actual monitoring distance and range requirements to obtain clear image frames. In order to meet the monitoring requirements at night and in low light conditions, the wireless camera 103 can be equipped with an infrared fill light or use a starlight-level sensor to output color and clear video images even in very low light conditions. In addition, the wireless camera 103 can use video compression and encoding technology to not only ensure video quality but also significantly reduce data transmission bandwidth and storage space. Then through the built-in wireless Wi-Fi module or 4G communication module, the wireless camera 103 can transmit the real-time video stream to the total monitoring platform 101 according to the preset network protocol. In the total monitoring platform 101, video analysis algorithms can be used to intelligently process the video stream. For example, based on deep learning target detection and recognition technology, it can automatically identify abnormal behaviors around the manure pool, such as personnel entering in violation, animals approaching, etc., and trigger an early warning mechanism in a timely manner, providing strong support for the safety management of the farm.

[0069] The GPS positioning device 104 is installed on the manure transport vehicle to collect vehicle status information in real time and transmit it to the total monitoring platform 101. The vehicle status information includes location, speed and route.

[0070] The GPS positioning device 104 can be integrated into the vehicle terminal and support GPS system positioning. The GPS positioning device 104 can collect vehicle status parameters such as speed, steering and brake signals through the CAN bus, and after fusion with positioning data, upload them to the total monitoring platform 101 through the communication network. The GPS positioning device 104 can also obtain the current driving route through positioning information at different times and upload it to the total monitoring platform 101 through the communication network. The platform can use geographic information system technology to visually display the vehicle's location and trajectory information on an electronic map, so that supervisors can view the vehicle's operating status in real time and achieve precise monitoring of the entire manure transport process. In addition, the GPS positioning device 104 also has an electronic fence function. When the vehicle deviates from the preset driving route or enters an unauthorized area, it can immediately send an alarm message to the total monitoring platform 101, which will notify the relevant management personnel through SMS, voice or APP push, etc. so that timely measures can be taken to intervene.

[0071] The total monitoring platform 101 is used for analyzing the fecal sludge pool capacity data, real-time video stream and vehicle state information respectively, generating corresponding abnormal identification results, and generating early warning instructions according to the abnormal identification results, and sending the early warning instructions to the early warning engine device 105 and / or the management terminal 106. The early warning engine device 105 is used for executing the early warning instructions.

[0072] The total monitoring platform 101 as the core hub of the system can be built on a server cluster in B / S architecture, and carry a PostgreSQL 9.6 and above version database for structured storage of various monitoring data such as fecal sludge pool capacity data, video stream data and vehicle state information. In addition, the total monitoring platform 101 can also integrate a WebGIS engine for spatial data visualization processing. In addition, the total monitoring platform 101 can also have a data backup and recovery mechanism, which can ensure that the data can be quickly recovered in the event of hardware failure, network attack or natural disaster and other unexpected situations, and ensure the continuous and stable operation of the system.

[0073] Illustratively, the platform can have an intelligent analysis module built-in, which uses a deep learning framework to analyze and process multiple source data in parallel. For example, for fecal sludge pool capacity data, a sliding window algorithm can be used to calculate the 24-hour trend slope, and when the slope abnormally increases, such as more than twice the historical average, it can be combined with the rainfall data in the same period to check whether there is rainwater mixing, generate an abnormal identification result, and generate an early warning instruction according to the abnormal identification result. For vehicle trajectory, a DBSCAN clustering algorithm can be used to identify frequent stopping points, and a surrounding sensitive area (such as rivers, farmland) database can be used to determine whether there is a risk of illegal discharge, to generate corresponding abnormal identification results. And all abnormal identification results can be scored by weighting to generate early warning instructions of corresponding levels. For example, a first-level early warning can trigger a sound and light alarm through the early warning engine device 105, and push a disposal work order to the management terminal 106, and a second-level early warning can only send a short message notification to the management terminal 106.

[0074] Illustratively, the early warning engine device 105 can be composed of an audio processor, an alarm controller and a linkage module. After receiving the early warning instruction, the early warning engine device 105 can play a preset warning voice such as "manure pool capacity exceeds the standard, please clean and transport in time" through the audio processor, and control the on-site LED screen to display the early warning code through the linkage module. The management terminal 106 can be an electronic device such as a computer, a tablet computer or a smart phone installed with a customized monitoring client software. The client software can be developed based on the C / S architecture and interact with the total monitoring platform 101 through a specific network communication protocol. The management personnel can view the manure pool capacity data, call the video monitoring screen, track the vehicle state and other information in real time through the management terminal 106, and can flexibly configure the early warning parameters according to the actual needs, such as setting the manure pool liquid level early warning threshold, the vehicle speed limit and the geographic fence range. In addition, the management terminal 106 can also support the query and analysis of historical data, so that the management personnel can filter according to the time, place, event type and other multi-dimensional conditions, and generate detailed statistical reports and analysis charts. In addition, the management terminal 106 can also have a remote control function. When necessary, the management personnel can send instructions to the early warning engine device 105 through the management terminal 106 to remotely start or stop the early warning notification.

[0075] In the above system, the wireless transmission radar liquid level meter 102 can master the change of the storage capacity of the manure pool in real time by acquiring the manure pool capacity data and transmitting it to the total monitoring platform 101. The wireless camera 103 is deployed in the manure pool area, which provides an intuitive on-site picture for the staff by collecting real-time video stream and transmitting it to the total monitoring platform 101, and realizes the dynamic monitoring of behaviors such as illegal discharge and illegal pollution. The GPS positioning device 104 is installed on the manure transportation vehicle, which can track the vehicle running track throughout the journey by collecting the vehicle position, driving speed and driving route and transmitting them to the total monitoring platform 101, and effectively judges whether the vehicle deviates from the prescribed route and whether there is illegal dumping behavior, providing clear data support for standardizing the transportation link. The total monitoring platform 101 can not only realize the accurate judgment of problems such as manure pool overflow, illegal pollution, abnormal vehicle driving and the like by analyzing the manure pool capacity data, real-time video stream and vehicle state information, but also can timely trigger a multi-level early warning mechanism, generate an early warning instruction and send it to the early warning engine device 105 and / or the management terminal 106, so as to ensure that the supervisor can master the abnormal situation of the breeding farm and the transportation link in real time, and effectively improve the supervision efficiency and response speed of the whole process of manure treatment in livestock and poultry breeding farms.

[0076] In one embodiment, the system further comprises an energy consumption supervision device for acquiring running data of the manure treatment device in real time and transmitting the running data to the total monitoring platform 101, wherein the running data includes current, voltage, power and device start-stop state;

[0077] The total monitoring platform 101 is also used for analyzing the operation data, judging whether the fecal pollution treatment equipment is normally operated, obtaining an equipment operation analysis result, and generating an equipment early warning instruction according to the equipment operation analysis result, and sending the equipment early warning instruction to the early warning engine equipment 105 and / or the management terminal 106;

[0078] As shown in FIG. 1, the total monitoring platform 101 is used for collecting operation data of the fecal pollution treatment equipment, and sending the operation data to the early warning engine equipment 105 and / or the management terminal 106. Figure 2 The total monitoring platform 101 obtains the equipment operation analysis result by analyzing the operation data through the following steps:

[0079] S201: Comparing the current and voltage with the corresponding safety threshold respectively to obtain a comparison result;

[0080] S202: Obtaining the current fecal pollution treatment amount of the fecal pollution treatment equipment, and obtaining a reference power curve of the fecal pollution treatment equipment under the same fecal pollution treatment amount based on a historical database;

[0081] S203: Calculating a dynamic deviation rate of the power and the reference power curve, and generating an efficiency analysis result according to the dynamic deviation rate and a preset judgment condition;

[0082] S204: Obtaining the equipment operation analysis result by combining the comparison result and the efficiency analysis result, and the equipment operation analysis result includes an abnormal type.

[0083] Specifically, the energy consumption supervision equipment can adopt an Internet of Things gateway architecture design, the hardware of which includes a current transformer, a voltage sensor and a power metering module, can be connected with the electrical control system of the fecal pollution treatment equipment such as a solid-liquid separator and a fermentation tank through an RS485 interface, can collect the current, voltage and active power in real time, and can obtain the start-stop state of the equipment through a dry contact point signal, wherein the high level is running and the low level is shutdown. Moreover, the equipment can be internally provided with a communication network module and a self-adaptive Ethernet port to encapsulate the original operation data into a JSON format frame for encrypted transmission to the total monitoring platform 101.

[0084] The total monitoring platform 101 can perform in-depth analysis on the received operating data to determine whether the fecal waste treatment device is in a normal operating state. First, the platform can accurately compare the real-time collected current and voltage data with the safety threshold set by the system. This safety threshold is determined according to the design specifications of the fecal waste treatment device, industry standards, and actual operation experience. For example, if the current exceeds 110% of the rated value or is lower than 90%, it may indicate that the device is overloaded or there is a mechanical failure, respectively. Similarly, if the voltage exceeds the allowed fluctuation range, it may indicate that there is a power supply anomaly or internal device problem. Through this comparison process, the platform can quickly identify potential safety hazards and device failures. And the total monitoring platform 101 can obtain the current amount of fecal waste being treated by the fecal waste treatment device in real time, and combine it with the information in its historical database to extract the baseline power curve of the device under the same amount of fecal waste treatment.

[0085] Specifically, the current amount of fecal waste treatment can be calculated by the difference between the front and back of the wireless transmission radar liquid level meter 102. And the historical database includes a large amount of operating data of the fecal waste treatment device under different working conditions. Through machine learning algorithms, the platform can establish a normal power consumption model of the device under various treatment amounts, i.e. the baseline power curve. This curve reflects the power variation trend of the device in the ideal state, and is an important basis for evaluating the current operating efficiency of the fecal waste treatment device. Illustratively, based on the normal operating data in the historical database for the past 3 months, a locally weighted regression algorithm can be used to fit the power values in the same treatment amount interval to generate a baseline power curve that changes with the treatment amount, with a dynamic deviation allowance range of ±15% as the confidence interval. Subsequently, the dynamic deviation rate of power from the baseline power curve can be calculated. The preset judgment conditions can be divided into three levels, for example, when the deviation rate exceeds 15%, it can be determined as low efficiency operation, when it exceeds 25%, it can be determined as moderate failure, and when it exceeds ±40% or deviates continuously for 30 minutes, it can be determined as severe efficiency anomaly.

[0086] Finally, the total monitoring platform 101 can integrate the current-voltage comparison result and the efficiency analysis result to obtain a device operation analysis result. Illustratively, a multi-dimensional weighted fusion mechanism can be used. If the comparison result is an electrical parameter overrun and the efficiency analysis result is a severe efficiency anomaly, it can be determined that there is an electrical fault. If there is only an electrical parameter overrun, it is determined that there is a power supply anomaly. If there is only an efficiency anomaly, the cumulative running time of the device can be calculated by accumulating the start-stop state. If the running time exceeds the preset maintenance period, it is determined that the device is aging and the efficiency is declining. Otherwise, it is determined that there is a process parameter anomaly. Finally, the device operation analysis result is obtained, which lists in detail whether the device has an anomaly and the specific type of the anomaly, such as overload operation, power supply anomaly, low-efficiency operation, or mechanical failure. According to the result, the platform can generate corresponding device warning instructions, and timely notify the on-site maintenance personnel and management personnel through the warning engine device 105 and the management terminal 106, so as to take targeted measures, such as adjusting the device operation parameters, performing maintenance, or emergency shutdown inspection, thereby ensuring the stable operation of the fecal treatment device and improving the management efficiency and environmental safety of the farm.

[0087] In one embodiment, the total monitoring platform 101 is also configured to obtain livestock scale data, perform data verification and deviation analysis on the livestock scale data to obtain an abnormal data analysis result, and generate a data anomaly instruction based on the abnormal data analysis result and send the data anomaly instruction to the management terminal 106. The livestock scale data includes livestock species, inventory quantity, and delivery quantity.

[0088] The total monitoring platform 101 performs data verification and deviation analysis on the livestock scale data to obtain an abnormal data analysis result by the following steps:

[0089] Verify whether the logical relationship between the inventory quantity and the delivery quantity meets a preset logical rule, and match the livestock species with a preset livestock type database to obtain a data verification result.

[0090] Obtain a preset daily average fecal production parameter corresponding to the livestock species, and calculate a theoretical fecal quantity based on the preset daily average fecal production parameter and the inventory quantity.

[0091] Obtain an actual fecal transfer quantity of the fecal transport vehicle, and calculate a fecal deviation rate based on the actual fecal transfer quantity and the theoretical fecal quantity.

[0092] Generate a deviation analysis result based on the fecal deviation rate.

[0093] Combine the data verification result and the deviation analysis result to obtain an abnormal data analysis result.

[0094] Specifically, the total monitoring platform 101 can be connected to the breeding scale reporting system of the farm through a dedicated data interface to obtain real-time breeding scale data. This data includes key information such as livestock and poultry species, inventory quantity, and marketable quantity. During data transmission, data encryption technology can be used to ensure data security and integrity. After receiving the data, the total monitoring platform 101 can first clean it to remove duplicate, incorrect, or incomplete records to ensure the accuracy of subsequent analysis. Then, according to the pre-set logical rules, it can check whether the relationship between the inventory quantity and the marketable quantity is reasonable. For example, the marketable quantity should not exceed a certain percentage of the inventory quantity, which can be set according to the growth cycle of different livestock and poultry and breeding practices. If the logical relationship violates the pre-set logical rules, the abnormal situation can be recorded. The reported livestock and poultry species can also be matched with the pre-set breeding type database. This pre-set database contains all the livestock and poultry types allowed to be bred in the region or farm and their characteristic information. This matching process can be completed through string exact matching or fuzzy matching algorithms to ensure that the reported livestock and poultry species has a corresponding record in the database. If the reported livestock and poultry species is not in the database, it can be marked as abnormal data.

[0095] Subsequently, the total monitoring platform 101 can extract the corresponding daily manure production parameters from the database according to the reported livestock and poultry species and inventory quantity, such as 5.2 kg of daily manure production per pig, 21.3 kg per cow, and 0.15 kg per egg chicken, and make coefficient corrections according to the climate conditions of the region where the farm is located (such as a 10% increase in pig manure production in winter) and the breeding mode. The theoretical manure quantity can be calculated from the daily manure production parameters and the inventory quantity. In addition, the total monitoring platform 101 can obtain the actual manure transfer quantity data of the manure transport vehicle by associating with the manure transport vehicle management system. This data includes the loading and unloading capacity of each transport task. By comparing the actual manure transfer quantity with the theoretical manure quantity, the manure deviation rate can be calculated. This manure deviation rate can reflect the degree of difference between the actual manure treatment and the theoretical expectation, which helps to identify potential problems in the manure treatment process, such as inaccurate estimation of manure production, low transportation efficiency, or illegal dumping. Finally, the abnormal data analysis results can be generated by combining the data verification results and the deviation analysis results. This abnormal data analysis result lists the types and degrees of data abnormalities in detail, such as logical relationship errors, livestock and poultry species mismatches, and insufficient manure transfer quantities. According to the abnormal data analysis results, the total monitoring platform 101 can generate data anomaly instructions to notify the management personnel in a timely manner through the management terminal 106. The management personnel can take appropriate measures according to the detailed information in the instructions, such as verifying the breeding scale data and adjusting the manure treatment plan, to ensure that the operation of the farm meets the environmental protection requirements and management standards. In addition, the platform can record the abnormal data analysis results and treatment measures for subsequent audit and continuous improvement.

[0096] In one embodiment, the system further comprises an odor monitoring device for acquiring odor data in real time and transmitting the odor data to the total monitoring platform 101.

[0097] The total monitoring platform 101 is also used to analyze the odor data according to the preset odor emission threshold, determine whether the odor data exceeds the odor emission threshold, obtain an emission result, and generate an emission warning instruction according to the emission result, and send the emission warning instruction to the warning engine device 105 and / or the management terminal 106, wherein the odor data includes odor concentration and odor components.

[0098] Specifically, the odor monitoring device can be installed at key positions around the farm, such as downwind and near residential areas, to ensure that the odor emitted by the farm can be accurately captured. The device is equipped with a high-sensitivity gas sensor that can detect odor concentration and components in real time. The gas sensor can detect specific pollutants in the air based on chemical adsorption or electrochemical reaction principles. For example, some sensors react with odor molecules to cause a change in the potential between the sensor electrodes, thereby enabling quantitative detection of odor concentration. The device also integrates a weather sensor to monitor environmental parameters such as wind direction, wind speed, temperature, and humidity, which have an important influence on the diffusion and dilution of odor. The odor monitoring device can also transmit the collected odor data to the total monitoring platform 101 in real time through a wireless communication module to ensure the timeliness and accuracy of the data.

[0099] The odor emission threshold is set according to national or local environmental protection standards and industry specifications, usually based on odor concentration and concentration limits of specific harmful gas components such as hydrogen sulfide and ammonia. The platform can first preprocess the collected odor concentration and component data, such as removing noise, to improve data reliability. Then compare the processed data with the preset threshold. For example, if the monitored hydrogen sulfide concentration exceeds the set threshold, it can be determined that the data exceeds the emission standard, triggering the warning mechanism. The total monitoring platform 101 can generate corresponding emission warning instructions based on factors such as the degree and duration of the exceedance. The instructions can include detailed abnormal information, such as the specific location, time, odor concentration, and components of the exceedance, and are pushed to the farm managers and relevant environmental protection departments in a timely manner through the warning engine device 105 and / or the management terminal 106. After receiving the warning information, the management personnel can take immediate action, such as adjusting the feed formula of the farm, optimizing the manure treatment process, increasing the operating time of the ventilation equipment, etc., to reduce odor emissions and reduce the impact on the surrounding environment. In addition, the platform can record each warning event and its handling process for subsequent data analysis and management decisions.

[0100] In an embodiment, the total monitoring platform 101 is further configured to acquire manure treatment account information, analyze the manure treatment account information based on the manure pool capacity data and the operation data of the manure treatment equipment, obtain an account audit result, and generate an account early warning instruction according to the account audit result, and send the account early warning instruction to the management terminal 106. The manure treatment account information includes the amount of received manure, the receiving time, the treatment method, the treatment time, and the destination of the treatment product.

[0101] The account audit result is obtained through the following steps:

[0102] The amount of received manure in the manure treatment account information is associated with the change in the manure pool capacity data corresponding to the receiving time for consistency verification, and a verification result is obtained.

[0103] The treatment time in the manure treatment account information is compared with the operation period in the operation data of the manure treatment equipment for consistency, and it is determined whether the treatment time is within the operation period to obtain a comparison result.

[0104] The account audit result is obtained in combination with the verification result and the comparison result.

[0105] Specifically, the total monitoring platform 101 can receive the manure treatment account information through a special interface. The information includes key data such as the amount of received manure, the receiving time, the treatment method, the treatment time, and the destination of the treatment product. The account information is uploaded by the manure treatment plant in real time, usually in a structured electronic data format such as XML or JSON, to facilitate the analysis and processing of the platform. First, the platform can perform consistency verification on the change in the manure pool capacity data corresponding to the amount of received manure and the receiving time. The manure pool capacity data is monitored in real time by the wireless transmission radar liquid level meter 102 deployed in the manure pool area and transmitted to the platform. The platform can calculate the capacity change of the manure pool in a specific time period according to the data of the liquid level meter. For example, if the capacity of the manure pool increases by 10 cubic meters in a certain period, and the corresponding account record shows that 8 cubic meters of manure is received in that period, the platform needs to evaluate the difference between the two to determine whether it is within a reasonable error range. The reasonable error range can be obtained by statistical analysis of historical data, for example, set to ±15%. If it exceeds this range, the verification result is marked as abnormal to prompt possible data recording errors or manure pool capacity measurement errors.

[0106] And the platform can compare the treatment time information in the fecal pollution treatment account with the operation period in the operation data of the fecal pollution treatment equipment, to determine whether the treatment time is within the actual operation period of the equipment. The operation data of the fecal pollution treatment equipment is collected by the energy consumption supervision equipment and transmitted to the platform, which can include detailed information such as start and stop time, operation state, etc. For example, if the account records show that a batch of fecal pollution is treated by anaerobic fermentation from 9:00 to 11:00, and the data of the energy consumption supervision equipment shows that the related treatment equipment is in a shutdown state during this period, the comparison result is marked as inconsistent, indicating that there may be false account records or equipment operation violations.

[0107] Finally, the platform can generate an account audit result by combining the verification result and the consistency comparison result. The audit result can list the types and degrees of abnormal situations and related data support, such as "the fecal pollution receiving quantity does not match the fecal pollution pool capacity change, the difference rate is 20%, exceeding the allowed range" or "the treatment time is inconsistent with the equipment operation period, the equipment did not run on the day". According to the audit result, the platform can generate an account warning instruction, detailing the abnormal situation and the corresponding account record, and send the instruction to the management terminal 106 to remind the relevant personnel to check and handle. The management personnel can trace back the fecal pollution treatment process to verify the accuracy of the account records, and if necessary, adjust or correct the fecal pollution treatment operation, to ensure that the fecal pollution treatment process meets the environmental protection requirements and management specifications.

[0108] In one embodiment, the total monitoring platform 101 includes an image processing unit for analyzing the real-time video stream and generating a corresponding image anomaly recognition result by the following steps:

[0109] Extract video frame images from the real-time video stream at a preset sampling frequency;

[0110] Perform noise reduction and contrast enhancement processing on the video frame images to obtain pre-processed image data;

[0111] According to the pre-processed image data, a U-Net semantic segmentation model is used to extract the fecal pollution pool boundary region to obtain a fecal pollution pool region segmentation map;

[0112] Based on the fecal pollution pool region segmentation map, a target detection model based on the YOLOv7 network is used for detection to identify whether there is a pollution outlet in the fecal pollution pool region segmentation map to obtain a preliminary recognition result;

[0113] Match the preliminary recognition result with a preset compliant pollution outlet feature library to obtain a classification result, which includes the position and type of the pollution outlet, and the type is any one of non-existent pollution outlet, compliant pollution outlet and illegal pollution outlet;

[0114] When the type in the classification result is a violation of the sewage outlet, the timestamp of the current abnormal video frame image corresponding to the classification result is obtained, and based on the timestamp, the abnormal video stream containing the timestamp of the current abnormal video frame image is automatically intercepted from the real-time video stream according to a preset rule;

[0115] The image anomaly recognition result is obtained in combination with the abnormal video stream and the classification result.

[0116] Specifically, a dynamic sampling mechanism can be used for frame extraction of the real-time video stream, that is, the preset sampling frequency is adaptively adjusted according to the motion characteristics of the monitoring scene. For example, for a scene mainly with a static background of a fecal pool, the sampling frequency is set to 1 frame / second to balance the data processing efficiency and the anomaly capture sensitivity. If it is detected by an inter-frame difference algorithm that there is a dynamic target (such as personnel activity or liquid flow) in the region, it is automatically increased to 5 frames / second to ensure that no motion details are missed. Moreover, the extracted video frame can include a timestamp accurate to milliseconds and device ID information, which is transmitted to the image processing server of the total monitoring platform 101 through a private network, and the transmission process can be encrypted by using an RSA asymmetric encryption algorithm to ensure data integrity. Moreover, the platform can optimize common image noise (such as fogging caused by fecal volatile matter and halos generated by night light compensation) in the breeding environment through a double optimization mechanism. For example, the noise reduction processing can use a non-local mean denoising algorithm to search for similar pixel blocks in the image for weighted averaging, effectively suppressing Gaussian noise and impulse noise. Contrast enhancement can use limited contrast adaptive histogram equalization to divide the image into 8x8 sub-blocks, and the contrast gain of each sub-block is limited to within 2.0 to avoid noise amplification caused by excessive enhancement, and to preserve the details of the key areas such as the pool edge and the sewage outlet. Moreover, the pre-processed image data can be standardized to normalize the pixel value to the range of 0-1, providing a unified input format for subsequent semantic segmentation.

[0117] Subsequently, based on the pre-processed image data, the extraction of the fecal pool boundary area can be implemented based on a U-Net semantic segmentation model. The model can adopt an encoder-decoder symmetric architecture. The encoder part down-samples the image through 4 layers of convolution operations, gradually extracting deep features such as pool outline, material texture, etc. The decoder part fuses shallow detail features through up-sampling and jump connection, finally outputs a segmentation mask consistent with the input image size, where the mask value of 1 represents the fecal pool and 0 represents the background, obtaining the fecal pool area segmentation map. Taking the fecal pool area segmentation map as input, the image processing unit can further adopt a target detection model based on the YOLOv7 network for detection. The model analyzes the segmentation map to identify whether there is a pollution outlet, and outputs the detection result. The result includes the position coordinates and confidence of the pollution outlet. Therefore, the validity of the detection result can be judged according to the confidence threshold to obtain the preliminary identification result. The pre-set compliant pollution outlet feature library is stored in the business application database of the total monitoring platform 101, which contains the recorded pollution outlet parameters of each farm, such as location information, physical features, approval document number, etc. The matching process can use multi-dimensional comparison. First, calculate the Euclidean distance between the detected pollution outlet and the recorded location. If the deviation is ≤30 cm and the physical features match, it can be determined as a compliant pollution outlet. If the location deviation is > 30 cm or the physical features do not match the record, it can be determined as a non-compliant pollution outlet. If no target frame is detected and there is no change for 20 consecutive frames, it is determined that there is no pollution outlet.

[0118] When the classification result is a non-compliant pollution outlet, the timestamp of the corresponding current abnormal video frame image can be recorded. Using the timestamp, a video segment containing the abnormal event is automatically intercepted from the real-time video stream according to the pre-set rules. For example, 10 seconds of video before and after the abnormal timestamp can be intercepted to form an abnormal video stream. The video stream combined with the classification result can generate an image anomaly identification result, providing direct visual evidence for subsequent investigation and processing. The image anomaly identification result can be presented to the administrator through the management terminal 106, including the abnormal video stream and detailed pollution outlet classification information, to quickly take measures such as on-site verification, rectification or administrative punishment, and timely stop illegal pollution behavior to protect the surrounding environment from pollution.

[0119] Based on the same inventive concept, as shown in Figure 3 The embodiments of the present application also provide a livestock and poultry farm informatization monitoring method. The implementation scheme of the problem solving provided by the method is similar to the implementation scheme described in the above system, so the specific limitations in one or more livestock and poultry farm informatization monitoring method embodiments provided below can refer to the limitations of the livestock and poultry farm informatization monitoring system in the above text, which will not be repeated here. The method comprises:

[0120] S301: Obtain the manure pool capacity data through the wireless transmission radar liquid level meter, and transmit the manure pool capacity data to the total monitoring platform, the wireless transmission radar liquid level meter is deployed in the manure pool area of the farm;

[0121] S302: Collect real-time video stream based on wireless camera, and transmit the real-time video stream to the total monitoring platform, the wireless camera is deployed in the manure pool area of the farm;

[0122] S303: Collect vehicle state information in real time according to the GPS positioning device, and transmit the vehicle state information to the total monitoring platform, the vehicle state information includes position, driving speed and driving route, the GPS positioning device is installed in the manure transport vehicle;

[0123] S304: Analyze the manure pool capacity data, real-time video stream and vehicle state information respectively through the total monitoring platform, generate corresponding abnormal identification results, generate early warning instructions according to the abnormal identification results, and send the early warning instructions to the early warning engine device and / or the management terminal, the early warning engine device is used to execute the early warning instructions.

[0124] The above-described embodiments only express several implementation manners of the application, the description is more specific and detailed, but it should not be understood as a limitation on the patent scope of the application. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the application, a number of modifications and improvements can be made, which are all within the protection scope of the application.

Claims

1. A livestock and poultry farm information monitoring system, characterized in that, The system comprises: a total monitoring platform, a wireless transmission radar liquid level meter, a wireless camera, a GPS positioning device, a warning engine device and a management terminal; The wireless transmission radar liquid level meter is deployed in the manure pool area of the farm, used to obtain manure pool capacity data and transmit the manure pool capacity data to the total monitoring platform; The wireless camera is deployed in the manure pool area of the farm, used to collect real-time video streams and transmit the real-time video streams to the total monitoring platform; The GPS positioning device is installed on a manure transport vehicle, used to collect vehicle state information in real time and transmit the vehicle state information to the total monitoring platform, the vehicle state information including position, driving speed and driving route; The total monitoring platform is used to analyze the manure pool capacity data, the real-time video streams and the vehicle state information respectively, generate corresponding abnormality recognition results, generate a warning instruction according to the abnormality recognition results, and send the warning instruction to the warning engine device and / or the management terminal; The warning engine device is used to execute the warning instruction.

2. The system of claim 1, wherein, The system further comprises an energy consumption supervision device, which is used to obtain operation data of manure treatment equipment in real time and transmit the operation data to the total monitoring platform, the operation data including current, voltage, power and equipment start-stop state; The total monitoring platform is further used to analyze the operation data, determine whether the manure treatment equipment is running normally, obtain equipment operation analysis results, generate an equipment warning instruction according to the equipment operation analysis results, and send the equipment warning instruction to the warning engine device and / or the management terminal; The total monitoring platform analyzes the operation data to obtain the equipment operation analysis results by the following steps: compare the current and the voltage with corresponding safety thresholds respectively to obtain comparison results; obtain the manure treatment capacity currently handled by the manure treatment equipment, and based on a historical database, obtain a reference power curve of the manure treatment equipment under the same manure treatment capacity; calculate a dynamic deviation rate of the power and the reference power curve, and generate an efficiency analysis result according to the dynamic deviation rate and a preset determination condition; combine the comparison results and the efficiency analysis result to obtain the equipment operation analysis results, the equipment operation analysis results including abnormality types.

3. The system of claim 1, wherein, The total monitoring platform is further used to obtain breeding scale data, perform data verification and deviation analysis processing on the breeding scale data to obtain abnormal data analysis results, generate a data abnormality instruction according to the abnormal data analysis results, and send the data abnormality instruction to the management terminal, the breeding scale data including livestock and poultry species, inventory quantity and marketable quantity; The total monitoring platform performs data verification and deviation analysis processing on the breeding scale data to obtain abnormal data analysis results by the following steps: The logical relationship between the number of livestock and the number of livestock is checked whether it meets the preset logical rule, and the livestock and poultry species is matched with the preset breeding type database to obtain a data verification result; Obtain the preset daily average manure production parameter corresponding to the livestock and poultry species, and calculate the theoretical manure amount according to the preset daily average manure production parameter and the number of livestock and poultry; Obtain the actual manure transfer amount of the manure transport vehicle, and calculate the manure deviation rate according to the actual manure transfer amount and the theoretical manure amount; Based on the manure deviation rate, a deviation analysis result is generated. The system also includes an odor monitoring device for real-time acquisition of odor data and transmission of the odor data to the total monitoring platform; 4. The system of claim 1, wherein, The total monitoring platform is also used to analyze the odor data according to a preset odor emission threshold, determine whether the odor data exceeds the odor emission threshold, obtain an emission result, and generate an emission warning instruction according to the emission result, and send the emission warning instruction to the warning engine device and / or the management terminal, wherein the odor data includes odor concentration and odor composition. The total monitoring platform is also used to obtain manure treatment account information, and analyze the manure treatment account information based on the manure pool capacity data and the operation data of the manure treatment equipment, obtain an account audit result, and generate an account warning instruction according to the account audit result, and send the account warning instruction to the management terminal, wherein the manure treatment account information includes the number of manure received, the receiving time, the processing method, the processing time and the processing product destination.

5. The system of claim 2, wherein, The account audit result is obtained by the following steps:

6. The system of claim 5, wherein, Correlate the amount of change of the manure pool capacity data corresponding to the receiving time with the number of manure received in the manure treatment account information, and obtain a verification result; Compare the processing time in the manure treatment account information with the operation period in the operation data of the manure treatment equipment, determine whether the processing time is within the operation period, and obtain a comparison result; Combine the verification result and the comparison result to obtain the account audit result. The total monitoring platform includes an image processing unit for analyzing the real-time video stream and generating a corresponding image anomaly recognition result by the following steps:

7. The system of claim 1, wherein, Extract video frame images from the real-time video stream at a preset sampling frequency; Perform noise reduction and contrast enhancement processing on the video frame images to obtain preprocessed image data; According to the preprocessed image data, a U-Net semantic segmentation model is used to extract the manure pool boundary area to obtain a manure pool area segmentation map; Based on the manure pool area segmentation map, a target detection model based on YOLOv7 network is used for detection to identify whether there is a pollution outlet in the manure pool area segmentation map to obtain a preliminary identification result; ​ The preliminary identification result is matched with a preset compliant outlet feature library to obtain a classification result, the classification result including a position and a type of the outlet, the type being any one of no outlet, compliant outlet, and non-compliant outlet; When the type in the classification result is the non-compliant outlet, a timestamp of a current abnormal video frame image corresponding to the classification result is obtained, and based on the timestamp, an abnormal video stream containing the timestamp of the current abnormal video frame image is automatically intercepted from the real-time video stream according to a preset rule; The image abnormality identification result is obtained in combination with the abnormal video stream and the classification result.

8. A livestock and poultry farm informationization monitoring method, characterized in that, The method comprises: acquiring manure pool capacity data through a wireless transmission radar liquid level meter, and transmitting the manure pool capacity data to the total monitoring platform, the wireless transmission radar liquid level meter being deployed in a manure pool area of a farm; based on the wireless camera, collecting real-time video streams and transmitting the real-time video streams to the total monitoring platform, the wireless camera being deployed in the manure pool area of the farm; according to the GPS positioning device, collecting vehicle state information in real time and transmitting the vehicle state information to the total monitoring platform, the vehicle state information including position, speed and route, the GPS positioning device being installed on a manure transport vehicle; through the total monitoring platform, analyzing the manure pool capacity data, the real-time video streams and the vehicle state information respectively, generating corresponding abnormality identification results, and generating a warning instruction according to the abnormality identification results, and sending the warning instruction to the warning engine device and / or the management terminal, the warning engine device being used to execute the warning instruction.

9. The method of claim 8, wherein, The method further comprises: real-time acquisition of odor data through an odor monitoring device, the odor data including odor concentration and odor composition; analysis of the odor data according to a preset odor emission threshold to determine whether the odor data exceeds the odor emission threshold to obtain an emission result; based on the emission result, generating an emission warning instruction and sending the emission warning instruction to the warning engine device and / or the management terminal.

10. The method of claim 8, wherein, The method further comprises: real-time acquisition of operation data of a manure treatment device through an energy consumption supervision device, and transmitting the operation data to the total monitoring platform, the operation data including current, voltage, power and device start-stop state; analysis of the operation data through the total monitoring platform to determine whether the manure treatment device is operating normally to obtain a device operation analysis result, and generation of a device warning instruction according to the device operation analysis result; sending the device warning instruction to the warning engine device and / or the management terminal; wherein the total monitoring platform analyzes the operation data to obtain the device operation analysis result by the following steps: comparing the current and the voltage with corresponding safety thresholds respectively to obtain comparison results; acquiring a current manure treatment amount of the manure treatment device, and based on a historical database, acquiring a reference power curve of the manure treatment device under the same manure treatment amount; calculating a dynamic deviation rate of the power from the reference power curve, and generating an efficiency analysis result according to the dynamic deviation rate and a preset judgment condition; combining the comparison result and the efficiency analysis result to obtain a device operation analysis result, the device operation analysis result including an abnormal type.

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