Livestock product supervision system based on big data

Abstract

The application provides a livestock product supervision system based on big data, which comprises an electronic ear tag, a video monitoring camera module, a data acquisition base station, an intelligent evaluation processing module and a data processing display module; the electronic ear tag is used for collecting the position, body temperature, exercise amount and health state of animals in real time; the video monitoring camera module is used for visually supervising animals; the data acquisition base station is used for detecting and analyzing the data of each animal in real time; the intelligent evaluation processing module is used for establishing a risk evaluation model, importing and processing the data of each animal, and discovering abnormal conditions of animals in time; the data processing display module is used for processing the collected data and generating a report; and the visual display screen is used for displaying the intuitive data and report, so as to facilitate real-time grasping of the conditions of the mortgaged animals and post-loan management decision-making. The application can realize individual accurate identification and management, collect the data such as the position, body temperature, exercise amount and health state of cattle in real time, discover abnormal conditions in time, and establish a risk evaluation model to discover abnormal conditions in time.

Description

Technical Field

[0001] This invention relates to the field of supervision and management technology, and in particular to a livestock product supervision system based on big data. Background Technology

[0002] As banks provide credit to beef cattle farmers, the livestock farms are an important element in the assessment of credit assets. Banks need to confirm the livestock assets and continuously monitor the pledged biological assets after the credit transaction takes place. Currently, the confirmation and supervision of biological assets is carried out by third-party regulatory agencies sending staff to the site for supervision. The staff on site take stock of the number of cattle every day and report to the bank regularly. If any abnormal situation occurs at the supervised site, the bank will be notified by telephone.

[0003] Defects and shortcomings of existing technology: (1) High labor costs Continuous human resource investment: It requires hiring a large number of people to be stationed on-site for a long period of time, resulting in high labor costs, especially in large-scale farms.

[0004] Staff turnover issues: On-site staff may have high turnover due to harsh working conditions, poor treatment, and other issues, leading to unstable supervision.

[0005] (2) Low regulatory efficiency

[0006] Limited coverage: On-site personnel cannot achieve 24 / 7, all-round supervision, especially in large-scale farms or decentralized farming models, which can easily lead to blind spots in supervision.

[0007] Slow response speed: On-site personnel cannot monitor the cattle's condition in real time, and problems are often discovered too late, making it difficult to deal with emergencies in a timely manner.

[0008] (3) Inaccurate data collection

[0009] Highly subjective: Manually recording data such as cattle's body temperature, activity level, and health status is easily affected by subjective judgment, leading to inaccurate data.

[0010] Data discontinuity: Manually collected data is usually intermittent, making it impossible to achieve 24-hour continuous monitoring and difficult to fully reflect the true condition of cattle.

[0011] (4) Weak risk prevention and control capabilities

[0012] Collateral supervision risk: In the case of biological asset mortgage loans, manual supervision is difficult to effectively prevent the loss, transfer or death of collateral cattle, which poses a high financial risk.

[0013] Abnormal situations are difficult to detect in a timely manner: manual supervision cannot monitor abnormal behaviors of cattle (such as disease, estrus, escape, etc.) in real time, which may lead to an increase in risks.

[0014] (5) High management difficulty

[0015] Information transmission lag: Manual supervision requires reporting at multiple levels, resulting in low information transmission efficiency and making it difficult to achieve rapid decision-making and response.

[0016] Lack of data accumulation and analysis: Manual supervision makes it difficult to accumulate systematic data, and it is impossible to optimize breeding management or provide reliable post-loan supervision basis for financial institutions through data analysis.

[0017] (6) Poor traceability

[0018] Incomplete records: Manual records are prone to omissions or errors, making it difficult to create complete cattle files, which affects the standardization and traceability of breeding management.

[0019] Difficult to meet regulatory requirements: In areas such as food safety and disease prevention and control, manual supervision is insufficient to meet increasingly stringent regulatory requirements.

[0020] (7) Environmental impact of aquaculture farms

[0021] Harsh working environment: The environment in farms is usually quite harsh, and long-term on-site work may lead to staff fatigue and affect the quality of supervision.

[0022] Biosafety risks: Frequent contact between people and cattle may increase the risk of disease transmission.

[0023] (8) Lack of technological empowerment

[0024] Unable to achieve intelligent management: Manual supervision cannot be combined with technologies such as the Internet of Things, big data, and artificial intelligence, making it difficult to achieve intelligent and refined breeding management.

[0025] Unable to support large-scale development: As the scale of breeding expands, the manual supervision model is unable to meet the needs of efficient and precise management.

[0026] In summary, relying solely on on-site personnel to monitor beef cattle has drawbacks such as high costs, low efficiency, inaccurate data, and weak risk control capabilities, making it difficult to meet the demands of modern livestock farming and financial institutions for precise and intelligent supervision. By introducing technologies such as electronic ear tags, the Internet of Things (IoT), and big data, real-time, precise, and efficient monitoring of beef cattle can be achieved, effectively compensating for the shortcomings of manual supervision, reducing farming and financial risks, and improving management efficiency. Summary of the Invention

[0027] The present invention aims to provide a big data-based livestock product supervision system to overcome or at least partially solve the above-mentioned problems.

[0028] To achieve the above objectives, the technical solution of the present invention is specifically implemented as follows: This invention provides a livestock product monitoring system based on big data, comprising: Electronic ear tags are worn on the ears of animals and collect data on the animal's location, body temperature, activity level, and health status in real time. A video surveillance camera module is installed in the area where the animals are active, and the animals are visually monitored through video surveillance. An electronic fence, installed at the edge of an animal activity area, is used to prevent animals from exceeding the designated area during their activities; The data acquisition base station is connected to the electronic ear tag, video surveillance camera module and electronic fence respectively via wires, and performs real-time detection and analysis of data for each animal through the data acquisition base station; The intelligent assessment and processing module is installed inside the data acquisition base station and connected to the data acquisition base station via a wire. A risk assessment model is established inside the intelligent assessment and processing module. By importing and processing the data of each animal, abnormal conditions of the animals can be detected in a timely manner. A data processing and display module is installed inside a visualization display screen and is connected to the intelligent evaluation and processing module and the visualization display screen respectively via wires. The data processing and display module is used to process the collected data and generate reports. A visualization display screen is used to display intuitive data and reports, facilitating real-time monitoring of the status of mortgaged animals and enabling post-loan management decisions.

[0029] As a further aspect of the present invention, the electronic ear tag is connected to a temperature detection sensor, a GPRS positioning module, a motion sensing sensor, and a heart rate monitoring sensor, respectively, for real-time detection of the animal's location, body temperature, activity level, and health status.

[0030] As a further embodiment of the present invention, the electronic fence includes bollards, a front-end detection fence, and a fence host. The front-end detection fence is connected to the bollards, and multiple bollards are provided, which are placed sequentially according to the edge position of the animal activity area. The fence host is connected to the front-end detection fence through wires.

[0031] This invention provides a livestock product monitoring system based on big data, with the following advantages: It enables precise identification and management of individual cattle; it collects data on cattle location, body temperature, activity level, and health status in real time to promptly detect abnormalities; it allows for real-time monitoring of cattle location information, facilitating search and management; it effectively prevents cattle from getting lost, reducing breeding risks; it provides a scientific basis for breeding decisions through the analysis of historical data; and it establishes a risk assessment model to promptly detect abnormalities and reduce loan risks. Attached Figure Description

[0032] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a block diagram illustrating the working principle of the present invention.

[0034] In the diagram: 1. Electronic ear tag; 2. Video surveillance camera module; 3. Electronic fence; 4. Data acquisition base station; 5. Intelligent evaluation and processing module; 6. Data processing and display module; 7. Visual display screen. Detailed Implementation

[0035] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0036] See Figure 1 The present invention provides a big data-based livestock product monitoring system, comprising: Electronic ear tag 1 is worn on the animal's ear and its location, body temperature, activity level and health status are collected in real time through the electronic ear tag 1. Video surveillance camera module 2 is installed in the area where animals are active and provides visual monitoring of the animals through video surveillance. Electronic fence 3 is installed at the edge of the animal activity area to prevent animals from exceeding the designated area during their activities. Data acquisition base station 4 is connected to electronic ear tag 1, video monitoring camera module 2 and electronic fence 3 via wires, and the data of each animal is detected and analyzed in real time through data acquisition base station 4; The intelligent assessment and processing module 5 is installed inside the data acquisition base station 4 and connected to the data acquisition base station 4 via wires. A risk assessment model is established inside the intelligent assessment and processing module 5. By importing and processing the data of each animal, abnormal conditions of the animals can be detected in a timely manner. The data processing and display module 6 is installed inside the visualization display screen 7 and is connected to the intelligent evaluation and processing module 5 and the visualization display screen 7 respectively via wires. The data processing and display module 6 is used to process the collected data and generate reports. Visual display screen 7 is used to display intuitive data and reports, facilitating real-time monitoring of the mortgaged animals and enabling post-loan management decisions.

[0037] The electronic ear tag 1 is equipped with a temperature sensor, a GPRS positioning module, a motion sensor, and a heart rate monitoring sensor, which are used to detect the animal's location, body temperature, activity level, and health status in real time.

[0038] The electronic fence 3 includes bollards, a front-end detection fence, and a fence host. The front-end detection fence is connected to the bollards. Multiple bollards are set up and placed sequentially according to the edge of the animal activity area. The fence host is connected to the front-end detection fence via wires.

[0039] During the use of this invention: Each cow is fitted with a unique electronic ear tag 1, and a video monitoring camera module 2 can collect data on the animal's location, body temperature, activity level, and health status in real time, enabling timely detection of abnormalities and precise individual identification and management. It also allows for real-time monitoring of the cows' locations, facilitating search and management. The electronic fence 3 effectively prevents cows from getting lost, reducing farming risks. The data collection base station 4 can perform real-time detection and analysis of each animal's data. A risk assessment model is established within the intelligent assessment and processing module 5, importing and processing data from each animal to promptly detect any abnormalities. The data processing and display module 6 then processes the collected data and generates reports. Finally, the intuitive data and reports are displayed on a visualization screen 7, and the analysis of historical data provides a scientific basis for farming decisions.

[0040] By establishing a risk assessment model, abnormal situations can be detected in a timely manner, thereby reducing loan risks.

[0041] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A livestock product monitoring system based on big data, characterized in that, include: Electronic ear tag (1), the electronic ear tag (1) is worn on the animal's ear, and the animal's location, body temperature, activity level and health status are collected in real time through the electronic ear tag (1); The video surveillance camera module (2) is set in the area where the animals are active and the animals are visually monitored through video surveillance. An electronic fence (3) is installed at the edge of the animal activity area to prevent animals from exceeding the designated area during their activities; The data acquisition base station (4) is connected to the electronic ear tag (1), the video monitoring camera module (2) and the electronic fence (3) respectively through wires, and the data of each animal is detected and analyzed in real time through the data acquisition base station (4); The intelligent assessment and processing module (5) is set inside the data acquisition base station (4) and connected to the data acquisition base station (4) by a wire. A risk assessment model is established inside the intelligent assessment and processing module (5). By importing and processing the data of each animal, abnormal situations of the animals can be detected in a timely manner. The data processing and display module (6) is set inside the visualization display screen (7) and is connected to the intelligent evaluation processing module (5) and the visualization display screen (7) respectively by wires. The data processing and display module (6) is used to process the collected data and generate reports. The visualization display screen (7) is used to display intuitive data and reports, so as to facilitate real-time monitoring of the mortgaged animals and make post-loan management decisions.

2. The livestock product supervision system based on big data according to claim 1, characterized in that, The electronic ear tag (1) is equipped with a temperature detection sensor, a GPRS positioning module, a motion sensing sensor, and a heart rate monitoring sensor, which are used to detect the animal's location, body temperature, activity level, and health status in real time.

3. The livestock product supervision system based on big data according to claim 1, characterized in that, The electronic fence (3) includes bollards, a front-end detection fence, and a fence host. The front-end detection fence is connected to the bollards. Multiple bollards are set up and placed sequentially according to the edge position of the animal activity area. The fence host is connected to the front-end detection fence through wires.

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