CN111122902A - Intelligent monitoring method for abnormal situation of cattle rumination based on wireless network - Google Patents

Intelligent monitoring method for abnormal situation of cattle rumination based on wireless network Download PDF

Info

Publication number
CN111122902A
CN111122902A CN202010049183.1A CN202010049183A CN111122902A CN 111122902 A CN111122902 A CN 111122902A CN 202010049183 A CN202010049183 A CN 202010049183A CN 111122902 A CN111122902 A CN 111122902A
Authority
CN
China
Prior art keywords
data
rumination
sensor
vibration
controller
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202010049183.1A
Other languages
Chinese (zh)
Inventor
刘丹
郭晓梅
丁丽艳
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Individual
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to CN202010049183.1A priority Critical patent/CN111122902A/en
Publication of CN111122902A publication Critical patent/CN111122902A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P15/00—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
    • G01P15/02—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration by making use of inertia forces using solid seismic masses
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
    • G01H11/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties
    • G01H11/06—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties by electric means

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

基于无线网络的牛反刍异常情况智能监控方法，涉及畜牧领域，本发明是为了解决目前对于牛的反刍异常情况存在的实时性差、智能化差、费时费力，以及监控误差大，数据取样有效性还较低的问题。本发明利用无线网络和牛体上穿戴的多种传感器实现对牛数据反刍异常情况智能监控，监控效果好，实时性强。

Figure 202010049183

A wireless network-based intelligent monitoring method for abnormal conditions of cattle rumination relates to the field of animal husbandry. The present invention aims to solve the current problems of poor real-time performance, poor intelligence, time-consuming and labor-intensive, large monitoring errors, and high data sampling effectiveness for abnormal conditions of cattle rumination. lower problem. The invention utilizes the wireless network and various sensors worn on the cow body to realize intelligent monitoring of the abnormal situation of cow data rumination, with good monitoring effect and strong real-time performance.

Figure 202010049183

Description

Intelligent monitoring method for abnormal situation of cattle rumination based on wireless network
Technical Field
The present invention relates to the field of livestock husbandry.
Background
Cattle are a standard ruminant. A ruminant. Ruminants are animals that ruminate, and are often herbivores because plant fibers are relatively indigestible. Ruminants generally eat food in a hurry, and particularly coarse feed is swallowed into rumens without being chewed sufficiently, and after the rumens are soaked and softened for a period of time, the food returns to the oral cavity again through retching, and is chewed again, mixed with saliva again and swallowed into the rumens again.
Rumination is the most typical and most main characteristic of ruminants, when rumination is abnormal (such as stopping rumination), although the body of the corresponding ruminant cannot be directly diagnosed to be diseased, the growth of cattle (particularly beef cattle) is mostly affected, and therefore, in the breeding process of cattle, the abnormal rumination condition of the cattle needs to be effectively monitored in time.
At present, the ruminant abnormal condition of the cattle is not divided into the following two modes:
firstly, trans-form monitored by the visual inspection of cultivation personnel;
secondly, shooting feeding and rumination images by adopting a camera, and judging whether the cattle completes rumination or not in an image processing mode;
however, both of these methods have disadvantages, and the first method has disadvantages of poor real-time performance, poor intelligence, and time and labor consumption;
the disadvantages of the second approach are: the monitoring error is large, and the data sampling effectiveness is low.
Disclosure of Invention
The invention aims to solve the problems of poor instantaneity, poor intellectualization, time and labor waste, large monitoring error and low data sampling effectiveness of the conventional cattle rumination abnormal condition, and provides a wireless network-based intelligent monitoring method for the cattle rumination abnormal condition
The intelligent monitoring method for the abnormal situation of the cattle rumination based on the wireless network is realized based on N pieces of wearable intelligent monitoring equipment for the abnormal situation of the cattle rumination, each piece of wearable intelligent monitoring equipment for the abnormal situation of the cattle rumination comprises two elastic nooses named as a noose (1) and a noose (2), two ends of the noose (1) and two ends of the noose (2) are fixed to form an integrated piece, and the integrated piece is used for being sleeved on a cheek of the cattle to be monitored, wherein: the first noose (1) is positioned at the palatal bone of the cow head; the second lasso (2) is positioned at the lower jaw bone of the cow head; each piece of wearable intelligent monitoring equipment for abnormal rumination conditions further comprises a first three-axis inclination angle sensor (18), a first three-axis acceleration sensor (12), a first vibration sensor (13), a first controller (14) and a first wireless signal communication receiving and transmitting terminal (15), wherein the first three-axis inclination angle sensor (18), the first three-axis acceleration sensor (12) and the first vibration sensor (13) are all fixed on the first noose (1);
the first three-axis tilt angle sensor (18) is used for detecting real-time three-axis tilt angle data of the upper jaw bone of the cow; the triaxial inclination angle data output end of the first triaxial inclination angle sensor (18) is connected with the triaxial inclination angle data input end of the first controller (14);
the first three-axis acceleration sensor (12) is used for detecting real-time three-axis acceleration data of a jaw bone on a cow head; the triaxial acceleration data output end of the first triaxial acceleration sensor (12) is connected with the triaxial acceleration data input end of the first controller (14);
the first vibration sensor (13) is used for detecting real-time vibration data of the first lasso (1); the vibration data output end of the first vibration sensor (13) is connected with the vibration data input end of the first controller (14);
the first controller (14) is accessed to the Internet through a first wireless signal communication receiving and transmitting terminal (15);
each piece of wearable intelligent monitoring equipment for abnormal rumination conditions further comprises a second three-axis inclination angle sensor (28), a second three-axis acceleration sensor (22), a second vibration sensor (23), a second controller (24) and a second wireless signal communication receiving and transmitting terminal (25), wherein the second three-axis inclination angle sensor (28), the second three-axis acceleration sensor (22) and the second vibration sensor (23) are all fixed on the second lasso (2);
the second three-axis inclination angle sensor (28) is used for detecting real-time three-axis inclination angle data of the lower jaw bone of the cow; the triaxial inclination angle data output end of the second triaxial inclination angle sensor (28) is connected with the triaxial inclination angle data input end of the second controller (24);
the second triaxial acceleration sensor (22) is used for detecting real-time triaxial acceleration data at the lower jaw bone of the cow; the triaxial acceleration data output end of the second triaxial acceleration sensor (22) is connected with the triaxial acceleration data input end of the second controller (24);
the second vibration sensor (23) is used for detecting real-time vibration data of the second lasso (2); the vibration data output end of the second vibration sensor (23) is connected with the vibration data input end of the second controller (24);
the second controller (24) is accessed to the Internet through a second wireless signal communication transceiving terminal (25);
each controller forms a wireless local area network;
is characterized in that: the intelligent cattle rumination abnormal condition monitoring method based on the wireless network comprises the following steps:
step one, a monitoring server is adopted to access the wireless local area network; after the access, the monitoring server can perform data interaction with the first controller (14) and the first controller (14) in a wireless network;
step two, collecting a group of three-axis inclination angle data of the upper jaw bone of the cattle in normal rumination, three-axis acceleration data of the upper jaw bone in normal rumination, vibration data of the first noose (1) in normal rumination, three-axis inclination angle data of the upper jaw bone in normal rumination, three-axis acceleration data of the lower jaw bone in normal rumination and vibration data of the first noose (1) in normal rumination, and uploading the three-axis inclination angle data and the three-axis acceleration data to a monitoring server through each controller and a wireless local area network;
step three, collecting triaxial inclination angle data of a lower jaw bone of a group of cattle in normal rumination, triaxial acceleration data of the lower jaw bone in normal rumination, vibration data of a noose (1) in normal rumination, triaxial inclination angle data of an upper jaw bone in normal rumination, triaxial acceleration data of the lower jaw bone in normal rumination and vibration data of a noose (2) in normal rumination, and uploading the three data to a monitoring server through each controller and a wireless local area network;
step four, the monitoring server classifies and summarizes the uploaded data, averages the data after the data are summarized respectively, and uses the data as standard parameters of the upper jaw bone and the upper jaw bone when the cattle ruminate normally and standard vibration quantity of the first lasso (2) and the second lasso (2) when the cattle ruminate normally;
step four, collecting the three-axis inclination angle data of the upper jaw bone when the current cow rumates, the three-axis acceleration data of the upper jaw bone when the cow rumates, the vibration data of the first noose (1) when the cow rumates, the three-axis inclination angle data of the lower jaw bone when the cow rumates, the three-axis acceleration data of the lower jaw bone when the cow rumates, and the vibration data of the second noose (2) when the cow rumates in real time, and uploading the data to a monitoring server through each controller and a wireless local area network;
step five, the monitoring server classifies and summarizes the uploaded data, the data are compared with the standard parameters after being summarized, if the error of the data is larger than a preset threshold value, if the judgment result is yes, the data are judged to be abnormal for rumination, the step six is executed, if the judgment result is no, the data are judged to be normal for rumination, and one-time rumination monitoring is finished;
and step six, the monitoring server prompts the feeding personnel to check the site through the Internet, and the process is finished.
The invention has the following beneficial effects and remarkable progress: the invention realizes intelligent monitoring of the abnormal rumination condition of the cattle data by utilizing the wireless network and various sensors worn on the cattle body, and has good monitoring effect and strong real-time property.
Drawings
FIG. 1 is a schematic diagram of the system of the present invention.
Fig. 2 is a schematic diagram of the system of the present invention.
Detailed Description
The specific embodiment mode I is a cattle rumination abnormal condition intelligent monitoring method based on a wireless network, and the method is realized based on N wearable type intelligent monitoring devices for rumination abnormal conditions, each wearable type intelligent monitoring device for rumination abnormal conditions comprises two elastic nooses named as a first noose (1) and a second noose (2), two ends of the first noose (1) and two ends of the second noose (2) are fixed to form an integrated piece, and the integrated piece is used for being sleeved on a cheek of a cattle to be monitored, wherein: the first noose (1) is positioned at the palatal bone of the cow head; the second lasso (2) is positioned at the lower jaw bone of the cow head; each piece of wearable intelligent monitoring equipment for abnormal rumination conditions further comprises a first three-axis inclination angle sensor (18), a first three-axis acceleration sensor (12), a first vibration sensor (13), a first controller (14) and a first wireless signal communication receiving and transmitting terminal (15), wherein the first three-axis inclination angle sensor (18), the first three-axis acceleration sensor (12) and the first vibration sensor (13) are all fixed on the first noose (1);
the first three-axis tilt angle sensor (18) is used for detecting real-time three-axis tilt angle data of the upper jaw bone of the cow; the triaxial inclination angle data output end of the first triaxial inclination angle sensor (18) is connected with the triaxial inclination angle data input end of the first controller (14);
the first three-axis acceleration sensor (12) is used for detecting real-time three-axis acceleration data of a jaw bone on a cow head; the triaxial acceleration data output end of the first triaxial acceleration sensor (12) is connected with the triaxial acceleration data input end of the first controller (14);
the first vibration sensor (13) is used for detecting real-time vibration data of the first lasso (1); the vibration data output end of the first vibration sensor (13) is connected with the vibration data input end of the first controller (14);
the first controller (14) is accessed to the Internet through a first wireless signal communication receiving and transmitting terminal (15);
each piece of wearable intelligent monitoring equipment for abnormal rumination conditions further comprises a second three-axis inclination angle sensor (28), a second three-axis acceleration sensor (22), a second vibration sensor (23), a second controller (24) and a second wireless signal communication receiving and transmitting terminal (25), wherein the second three-axis inclination angle sensor (28), the second three-axis acceleration sensor (22) and the second vibration sensor (23) are all fixed on the second lasso (2);
the second three-axis inclination angle sensor (28) is used for detecting real-time three-axis inclination angle data of the lower jaw bone of the cow; the triaxial inclination angle data output end of the second triaxial inclination angle sensor (28) is connected with the triaxial inclination angle data input end of the second controller (24);
the second triaxial acceleration sensor (22) is used for detecting real-time triaxial acceleration data at the lower jaw bone of the cow; the triaxial acceleration data output end of the second triaxial acceleration sensor (22) is connected with the triaxial acceleration data input end of the second controller (24);
the second vibration sensor (23) is used for detecting real-time vibration data of the second lasso (2); the vibration data output end of the second vibration sensor (23) is connected with the vibration data input end of the second controller (24);
the second controller (24) is accessed to the Internet through a second wireless signal communication transceiving terminal (25);
each controller forms a wireless local area network;
is characterized in that: the intelligent cattle rumination abnormal condition monitoring method based on the wireless network comprises the following steps:
step one, a monitoring server is adopted to access the wireless local area network; after the access, the monitoring server can perform data interaction with the first controller (14) and the first controller (14) in a wireless network;
step two, collecting a group of three-axis inclination angle data of the upper jaw bone of the cattle in normal rumination, three-axis acceleration data of the upper jaw bone in normal rumination, vibration data of the first noose (1) in normal rumination, three-axis inclination angle data of the upper jaw bone in normal rumination, three-axis acceleration data of the lower jaw bone in normal rumination and vibration data of the first noose (1) in normal rumination, and uploading the three-axis inclination angle data and the three-axis acceleration data to a monitoring server through each controller and a wireless local area network;
step three, collecting triaxial inclination angle data of a lower jaw bone of a group of cattle in normal rumination, triaxial acceleration data of the lower jaw bone in normal rumination, vibration data of a noose (1) in normal rumination, triaxial inclination angle data of an upper jaw bone in normal rumination, triaxial acceleration data of the lower jaw bone in normal rumination and vibration data of a noose (2) in normal rumination, and uploading the three data to a monitoring server through each controller and a wireless local area network;
step four, the monitoring server classifies and summarizes the uploaded data, averages the data after the data are summarized respectively, and uses the data as standard parameters of the upper jaw bone and the upper jaw bone when the cattle ruminate normally and standard vibration quantity of the first lasso (2) and the second lasso (2) when the cattle ruminate normally;
step four, collecting the three-axis inclination angle data of the upper jaw bone when the current cow rumates, the three-axis acceleration data of the upper jaw bone when the cow rumates, the vibration data of the first noose (1) when the cow rumates, the three-axis inclination angle data of the lower jaw bone when the cow rumates, the three-axis acceleration data of the lower jaw bone when the cow rumates, and the vibration data of the second noose (2) when the cow rumates in real time, and uploading the data to a monitoring server through each controller and a wireless local area network;
step five, the monitoring server classifies and summarizes the uploaded data, the data are compared with the standard parameters after being summarized, if the error of the data is larger than a preset threshold value, if the judgment result is yes, the data are judged to be abnormal for rumination, the step six is executed, if the judgment result is no, the data are judged to be normal for rumination, and one-time rumination monitoring is finished;
and step six, the monitoring server prompts the feeding personnel to check the site through the Internet, and the process is finished.
The basic principle of the invention is as follows: and comparing various sensor data acquired in real time with standard data to judge whether the abnormality occurs. Are well understood and implemented by those skilled in the art.
The invention has the following beneficial effects and remarkable progress: the invention realizes intelligent monitoring of the abnormal rumination condition of the cattle data by utilizing the wireless network and various sensors worn on the cattle body, and has good monitoring effect and strong real-time property.

Claims (1)

1.一种基于无线网络的牛反刍异常情况智能监控方法，它是基于N个穿戴式反刍异常情况智能监控设备实现的，所述每个穿戴式反刍异常情况智能监控设备均包括两根弹性套索，命名为一号套索（1）和二号套索（2），所述一号套索（1）的两端分别和二号套索（2）的两端固定形成一体件，该一体件用于套在待监控牛的面颊处，其中：一号套索（1）位于牛头的上颚骨处；二号套索（2）位于牛头的下颚骨处；所述每个穿戴式反刍异常情况智能监控设备还包括一号三轴倾角传感器（18）、一号三轴加速度传感器（12）、一号震动传感器（13）、一号控制器（14）和一号无线信号通信收发终端（15），所述一号三轴倾角传感器（18）、一号三轴加速度传感器（12）、一号震动传感器（13）均固定在一号套索（1）上；1. A wireless network-based intelligent monitoring method for abnormal conditions of cattle rumination, which is realized based on N wearable intelligent monitoring equipment for abnormal conditions of rumination, and each of the wearable intelligent monitoring equipment for abnormal conditions of rumination includes two elastic sleeves. No. 1 lasso (1) and No. 2 lasso (2), the two ends of the No. 1 lasso (1) are respectively fixed with the two ends of the No. 2 lasso (2) to form an integral piece, the The one-piece piece is intended to be placed on the cheek of the cow to be monitored, wherein: No. 1 noose (1) is located at the upper jawbone of the cow's head; No. 2 noose (2) is located at the lower jawbone of the cow's head; each wearable rumination The intelligent monitoring equipment for abnormal conditions also includes a No. 1 three-axis inclination sensor (18), a No. 1 three-axis acceleration sensor (12), a No. 1 vibration sensor (13), a No. 1 controller (14) and a No. 1 wireless signal communication transceiver terminal (15), the No. 1 three-axis inclination sensor (18), the No. 1 three-axis acceleration sensor (12), and the No. 1 vibration sensor (13) are all fixed on the No. 1 lasso (1); 所述一号三轴倾角传感器（18）用于检测牛的上颚骨的实时三轴倾角数据；所述一号三轴倾角传感器（11）的三轴倾角数据输出端与一号控制器（14）的三轴倾角数据数据输入端连接；The No. 1 three-axis inclination sensor (18) is used to detect real-time three-axis inclination data of the upper jawbone of the cow; the output end of the No. 1 three-axis inclination angle sensor (11) is connected to the No. 1 controller (14). ) is connected to the data input terminal of the three-axis inclination data; 一号三轴加速度传感器（12）用于检测牛头上颚骨的实时三轴加速度数据；所述一号三轴加速度传感器（12）的三轴加速度数据输出端与一号控制器（14）的三轴加速度数据输入端连接；The No. 1 three-axis acceleration sensor (12) is used to detect real-time three-axis acceleration data of the upper jawbone of the bovine head; the three-axis acceleration data output end of the No. 1 three-axis acceleration sensor (12) is connected to the three-axis acceleration data of the No. 1 controller (14). Shaft acceleration data input connection; 一号震动传感器（13）用于检测一号套索（1）的实时震动数据；所述一号震动传感器（13）的震动数据数据输出端与一号控制器（14）的震动数据数据输入端连接；The No. 1 vibration sensor (13) is used to detect the real-time vibration data of the No. 1 lasso (1); the vibration data data output terminal of the No. 1 vibration sensor (13) and the vibration data data input of the No. 1 controller (14) end connection; 一号控制器（14）通过一号无线信号通信收发终端（15）接入互联网；The No. 1 controller (14) accesses the Internet through the No. 1 wireless signal communication transceiver terminal (15); 所述每个穿戴式反刍异常情况智能监控设备还包括二号三轴倾角传感器（28）、二号三轴加速度传感器（22）、二号震动传感器（23）、二号控制器（24）和二号无线信号通信收发终端（25），所述二号三轴倾角传感器（28）、二号三轴加速度传感器（22）、二号震动传感器（23）均固定在二号套索（2）上；Each of the wearable intelligent monitoring devices for abnormal rumination conditions further includes a No. 2 three-axis inclination sensor (28), a No. 2 three-axis acceleration sensor (22), a No. 2 vibration sensor (23), a No. 2 controller (24) and The No. 2 wireless signal communication transceiver terminal (25), the No. 2 three-axis inclination sensor (28), the No. 2 three-axis acceleration sensor (22), and the No. 2 vibration sensor (23) are all fixed on the No. 2 lasso (2) superior; 所述二号三轴倾角传感器（21）用于检测牛的下颚骨处的实时三轴倾角数据；所述二号三轴倾角传感器（28）的三轴倾角数据输出端与二号控制器（24）的三轴倾角数据数据输入端连接；The No. 2 three-axis inclination sensor (21) is used to detect real-time three-axis inclination data at the mandible of the cow; the tri-axial inclination data output end of the No. 2 three-axis inclination sensor (28) is connected to the No. 2 controller ( 24) The three-axis inclination data data input terminal connection; 二号三轴加速度传感器（22）用于检测牛的下颚骨处的实时三轴加速度数据；所述二号三轴加速度传感器（22）的三轴加速度数据输出端与二号控制器（24）的三轴加速度数据输入端连接；The No. 2 three-axis acceleration sensor (22) is used to detect real-time three-axis acceleration data at the mandible of the cow; the three-axis acceleration data output end of the No. 2 three-axis acceleration sensor (22) is connected to the No. 2 controller (24) The three-axis acceleration data input terminal is connected; 二号震动传感器（23）用于检测二号套索（2）的实时震动数据；所述二号震动传感器（23）的震动数据数据输出端与二号控制器（24）的震动数据数据输入端连接；The No. 2 vibration sensor (23) is used to detect the real-time vibration data of the No. 2 lasso (2); the vibration data data output terminal of the No. 2 vibration sensor (23) and the vibration data data input of the No. 2 controller (24) end connection; 所述二号控制器（24）通过二号无线信号通信收发终端（25）接入互联网；The No. 2 controller (24) is connected to the Internet through the No. 2 wireless signal communication transceiver terminal (25); 各控制器组成无线局域网；Each controller forms a wireless local area network; 特征是：基于无线网络的牛反刍异常情况智能监控方法，它包括以下步骤：The feature is: a wireless network-based intelligent monitoring method for abnormal condition of cattle rumination, which includes the following steps: 步骤一、采用一台监控服务器接入所述无线局域网；接入后，所述监控服务器能够与一号控制器（14）和一号控制器（14）在无线网络中进行数据交互；Step 1, using a monitoring server to access the wireless local area network; after access, the monitoring server can perform data interaction with the No. 1 controller (14) and the No. 1 controller (14) in the wireless network; 步骤二、采集一组牛在正常反刍时的上颚骨的三轴倾角数据、正常反刍时的上颚骨的三轴加速度数据、正常反刍时一号套索（1）的震动数据、正常反刍时上颚骨的三轴倾角数据、正常反刍时的下颚骨的三轴加速度数据、正常反刍时一号套索（1）的震动数据，并通过各控制器与无线局域网上传给监控服务器；Step 2: Collect a set of triaxial inclination data of the upper jaw during normal rumination, triaxial acceleration data of the upper jaw during normal rumination, vibration data of No. 1 lasso (1) during normal rumination, and upper jaw during normal rumination. The triaxial inclination data of the bone, the triaxial acceleration data of the mandible during normal rumination, and the vibration data of the No. 1 lasso (1) during normal rumination are uploaded to the monitoring server through each controller and wireless LAN; 步骤三、采集一组牛在正常反刍时的下颚骨的三轴倾角数据、正常反刍时的下颚骨的三轴加速度数据、正常反刍时一号套索（1）的震动数据、正常反刍时上颚骨的三轴倾角数据、正常反刍时的下颚骨的三轴加速度数据、正常反刍时二号套索（2）的震动数据，并通过各控制器与无线局域网上传给监控服务器；Step 3: Collect a set of triaxial inclination data of the mandible during normal rumination, triaxial acceleration data of the mandible during normal rumination, vibration data of No. 1 lasso (1) during normal rumination, and upper jaw during normal rumination. The triaxial inclination data of the bone, the triaxial acceleration data of the mandible during normal rumination, and the vibration data of the No. 2 lasso (2) during normal rumination are uploaded to the monitoring server through each controller and wireless LAN; 步骤四、监控服务器对各上传的数据进行分类汇总，汇总后分别取平均，作为牛正常反刍时的上颚骨和上颚骨的标准参量，以及牛正常反刍时一号套索（2）和二号套索（2）的标准震动量；Step 4. The monitoring server classifies and summarizes the uploaded data, and takes the average after summarizing, which is used as the standard parameters of the upper jaw and the upper jaw during normal rumination, and the No. 1 lasso (2) and No. 2 when the cow is ruminating normally. Standard vibration of the lasso (2); 步骤四、实时采集当前牛的反刍时上颚骨的三轴倾角数据、反刍时的上颚骨的三轴加速度数据、反刍时一号套索（1）的震动数据、反刍时下颚骨的三轴倾角数据、反刍时的下颚骨的三轴加速度数据、反刍时二号套索（2）的震动数据，并通过各控制器与无线局域网上传给监控服务器；Step 4. Collect the triaxial inclination data of the upper jawbone during rumination, the triaxial acceleration data of the upper jawbone during rumination, the vibration data of No. 1 lasso (1) during rumination, and the triaxial inclination of the mandible during rumination. The data, the triaxial acceleration data of the mandible during rumination, the vibration data of the No. 2 lasso (2) during rumination, are uploaded to the monitoring server through each controller and wireless LAN; 步骤五、监控服务器对各上传的数据进行分类汇总，汇总后分别与各标准参量进行对比，如果其误差大于预设的阈值 如果判断结果为是，则判定为反刍异常，执行步骤六，如果判断结果为否，则判定为反刍正常，结束一次反刍监控；Step 5. The monitoring server classifies and summarizes the uploaded data, and then compares them with each standard parameter. If the error is greater than the preset threshold, if the judgment result is yes, it is judged that the rumination is abnormal. Step 6 is executed. If the result is no, it is judged that the rumination is normal, and one rumination monitoring is ended; 步骤六、监控服务器通过互联网提示饲养人员进行现场查看，并结束。Step 6: The monitoring server prompts the breeder to conduct on-site inspection through the Internet, and ends.
CN202010049183.1A 2020-01-16 2020-01-16 Intelligent monitoring method for abnormal situation of cattle rumination based on wireless network Pending CN111122902A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010049183.1A CN111122902A (en) 2020-01-16 2020-01-16 Intelligent monitoring method for abnormal situation of cattle rumination based on wireless network

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010049183.1A CN111122902A (en) 2020-01-16 2020-01-16 Intelligent monitoring method for abnormal situation of cattle rumination based on wireless network

Publications (1)

Publication Number Publication Date
CN111122902A true CN111122902A (en) 2020-05-08

Family

ID=70491005

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010049183.1A Pending CN111122902A (en) 2020-01-16 2020-01-16 Intelligent monitoring method for abnormal situation of cattle rumination based on wireless network

Country Status (1)

Country Link
CN (1) CN111122902A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112243891A (en) * 2020-09-30 2021-01-22 黑龙江省农业科学院畜牧兽医分院 Intelligent goose breeding system and method based on wireless network

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101123874A (en) * 2005-01-19 2008-02-13 Scr工程有限公司 Method and apparatus for detecting estrus
CN101472469A (en) * 2006-04-18 2009-07-01 Iti苏格兰有限公司 Method and system for monitoring the condition of livestock
WO2011069512A1 (en) * 2009-12-11 2011-06-16 Syddansk Universitet Method and system for estimating herbage uptake of an animal
CN105091938A (en) * 2015-07-09 2015-11-25 北京农业信息技术研究中心 Poultry health monitoring method and system
CN205813178U (en) * 2016-04-29 2016-12-21 内蒙古牧野昕光信息技术有限公司 A kind of ruminant ruminate information collecting device and system
CN207665013U (en) * 2018-01-15 2018-07-27 内蒙古大学 Milk cow information collecting device
CN110169374A (en) * 2019-06-19 2019-08-27 北京农业信息技术研究中心 A kind of wearable monitoring device and monitoring system of cow feeding behavior and feed intake
CN110664413A (en) * 2019-10-15 2020-01-10 银川奥特信息技术股份公司 Animal rumination monitoring device and method

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101123874A (en) * 2005-01-19 2008-02-13 Scr工程有限公司 Method and apparatus for detecting estrus
CN101472469A (en) * 2006-04-18 2009-07-01 Iti苏格兰有限公司 Method and system for monitoring the condition of livestock
WO2011069512A1 (en) * 2009-12-11 2011-06-16 Syddansk Universitet Method and system for estimating herbage uptake of an animal
CN105091938A (en) * 2015-07-09 2015-11-25 北京农业信息技术研究中心 Poultry health monitoring method and system
CN205813178U (en) * 2016-04-29 2016-12-21 内蒙古牧野昕光信息技术有限公司 A kind of ruminant ruminate information collecting device and system
CN207665013U (en) * 2018-01-15 2018-07-27 内蒙古大学 Milk cow information collecting device
CN110169374A (en) * 2019-06-19 2019-08-27 北京农业信息技术研究中心 A kind of wearable monitoring device and monitoring system of cow feeding behavior and feed intake
CN110664413A (en) * 2019-10-15 2020-01-10 银川奥特信息技术股份公司 Animal rumination monitoring device and method

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112243891A (en) * 2020-09-30 2021-01-22 黑龙江省农业科学院畜牧兽医分院 Intelligent goose breeding system and method based on wireless network

Similar Documents

Publication Publication Date Title
Schirmann et al. Validation of a system for monitoring rumination in dairy cows
AU2011218640B2 (en) Detection apparatus
JP2017060407A (en) System and method for health care of ruminant
JP2004504051A (en) Methods and systems for monitoring ruminant physiological conditions and / or suitability of animal feed for ruminants
KR20180052438A (en) Method of managing disease, and apparatuses operating the same
CN107426984A (en) Information processing system
CN110741962A (en) Oestrus and health monitoring method based on cow behavior recognition algorithm
KR101976519B1 (en) Apparatus for monitoring ruminant stomach of cattle and method thereof
Grodkowski et al. Comparison of different applications of automatic herd control systems on dairy farms–a review
CN205144565U (en) A monitoring system that ruminates in real time, moves for ruminant
CN205694933U (en) A kind of device gathering milk cow activity and system
CN111122902A (en) Intelligent monitoring method for abnormal situation of cattle rumination based on wireless network
CN108605860A (en) Livestock chews detection device and Intelligent pasture manages system
KR102418883B1 (en) Monitoring methods of ruminant stomach of cattle
CN107410082A (en) Recognition methods is ruminated based on ruminant noseband pressure change
CN108077106B (en) A kind of cattle estrus warning method
JP7410200B2 (en) Specific device, specific method, and program
CN110779575A (en) An animal husbandry monitoring system based on a big data platform
Baig et al. Ewe Health Monitoring Using IoT simulator
KR101799752B1 (en) Cow ear attached measuring devices of the inner ear temperature and ruminating activity
CN112235338A (en) Animal husbandry breeding monitoring system with artificial intelligence
CN116958611B (en) Cluster analysis method for piglet mortality events
US20250212846A1 (en) Free-range livestock management server apparatus, system, method, and program
CN116548341A (en) A kind of production breeding system for laying hens in a farm
CN215012589U (en) Cattle rumination data acquisition device in cattle breeding process

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20200508