Laying Hens, Wise and Intelligent Breeders
The layer chicken breeding robot has very powerful functions. It can perform chicken house environment monitoring, infrared body temperature monitoring, image activity monitoring, chicken house abnormal warning, chicken house sound monitoring, remote confirmation of abnormalities, abnormal location tracking, emergency response assistance, and automatic data analysis 8 functions.
Environmental Monitoring of Chicken House
In the system, laying hen breeding is based on chicken house, chick hatching is based on incubator, egg storage is based on egg storage, and egg transportation is based on transport vehicle. Environmental parameters such as temperature, humidity, light and harmful gas concentration are monitored in real time. The sensor network module transmits remote monitoring data to the application data management module, analyzes on-site environmental parameters and image data, and scientifically adjusts environmental parameters such as temperature, humidity, light, water, gas, and oxygen, for livestock breeding provide an optimal environment to achieve the purpose of increasing production and income. At the same time, through the early warning data to cooperate with the implementation of the monitoring system, remote control and adjustment of equipment operation status.
Infrared Body Temperature Monitoring
As the scale of breeding increases, large-scale breeding farms have higher requirements for disease control. At the beginning of a disease, a layer will have a high body temperature. In order to prevent disease and find abnormal problems immediately, this project selects an infrared temperature measurement system to monitor the body temperature of the layer. In order to reduce the construction cost, the infrared temperature measurement system is grafted on the automatic inspection system to realize the itinerant body temperature measurement of the laying hens and find the sick chickens immediately.
Robot infrared general measurement is to set multiple detection points in advance, and the operator can set the infrared general measurement task at any time, instead of manually collecting the overall temperature of the entire station equipment, and effectively avoiding the omission of regional equipment. At the same time, the equipment with important or urgent defects is regularly monitored. Monitor once, make a decision once, and then transfer the data to the general data platform for big data accumulation and analysis, track data development and change, and form a report. If an obvious mutation is found, the operator will receive prompt information for manual verification.
Imagized Activity Monitoring
The activity of chickens in the chicken house is obtained by installing an appropriate number of image acquisition equipment in the chicken house and analyzing it. When the chicken’s activity is too high, the lighting system in the chicken house is automatically adjusted to adjust the white light to red light. Image activity monitoring needs to transmit the collected image data to the application data management module for graphical analysis, and use image analysis and image processing technologies to comprehensively determine the activity of chickens.
Chicken House Warning System For Abnormal Status
In the breeding process, it is necessary to frequently hire expert consultants to the breeding farm for diagnosis and consultation. Because the farm is far away from the city, traveling takes a lot of time and manpower, and it is easy to delay the transmission of disease information. Thus,a remote diagnosis system architecture which is designed for poultry diseases based on sound and image information is proposed. The system and composition are described as follows:
The early warning of abnormality in the chicken house is actually an experts remote diagnosis system. To connect the breeding site with the experts remote diagnosis system, it is necessary to be equipped with video cameras, sound collector, microphones and other equipment.
The diagnosis system uses the Internet and multimedia information transmission technology to configure relevant equipment at the terminal of experts and farms to carry out real-time information communication between experts and farmers.
The system includes three main modules: a. Disease diagnosis knowledge base module, which can help complete the intelligent diagnosis of livestock (poultry) diseases through knowledge inference and database. b. The remote diagnosis module uses modern information technology such as 3G to realize the online diagnosis decision-making system and remote consultation. c. Epidemic early warning module, through the epidemic early warning knowledge base, according to the current local epidemic situation and climate and other factors, to make auxiliary early warning of the layer epidemic situation.
Coop Sound Monitoring
Installing sound sensors on fixed and mobile devices to monitor the yell and breathing sounds of chickens, an alarm will be triggled if cough or wheeze are caught. It is necessary to analyze the collected sounds, and construct an asthma or cough sound model library in advance, and monitor the abnormality of the chicken by matching the real-time collected sounds with the sound waveforms in the sound model library.
The acquisition and transmission of sound signals require audio acquisition modules, audio encoding modules, audio decoding modules and network communication modules. At the same time, the background needs to perform feature extraction, parameter comparison and real-time recognition of sound parameters. After model training Give the result of sound analysis. When it comes to the collection of breathing and coughing sounds, the sound signal is weak. The robot needs to configure a telescopic stand for the microphone as close as possible to the collecting body.
Remote Alarm Confirmation
In the robot inspection mode, the breeder can call the robot to quickly reach the designated equipment at the first time after receiving the alarms and instantly review and confirm the alarm content in order to quickly formulate response strategies. When the robot detects abnormal information in a flock of chickens in the chicken coop, it must locate the abnormal information (identify according to the manual calibration feature number or accurately locate according to the AGV trolley) upload the detected abnormal information and accurate abnormal positioning information to the server together, so that notify the administrator immediately.
Abnormality Tracking in Fixed-Location
The robot can automatically track and monitor the abnormality of the chicken house. Operators remotely select corresponding equipment through the client, set up defect tracking tasks, and select appropriate cycles to track and repeat inspections; or allowing control robots to monitor all day at fixed locations to perform real-time collection of information on defective equipment and reduce the workload of breeders.
The robot can also save equipment information, track information changes, upload data reports, and instantly alert if equipment defects develop.
Operators can grasp the status of laying hens breeding at the main operation station according to the defect reports automatically generated and uploaded by the robot. And according to the alarm information of the robot, check the status of the equipment in real time and report the dispatch processing.
Assist in emergency handling
After the operating station receives the information about the abnormal accident in the chicken house, it can click on the designated device through the navigation map of the robot client to establish a special patrol task, and send instructions. The robot will go to the accident site as soon as possible. Availables modes including, remotely adjust the position of the vehicle body, rotate the direction of the pan-tilt, quickly locate the faulty area, and record and read on-site information in real time, use the robot image transmission and information exchange technologies to quickly transmit on-site information to the operating station, and the breeder can quickly understand the site from a long distance situation, grasp the dynamics of the scene, and determine the processing method immediately.
Using robots as a mobile real-time monitoring platform, breeders can assist on-site personnel to make professional judgments and provide technical support without having to arrive at the scene. It is conducive to the establishment of a joint analysis team of remote network breeders and experts, strengthen the real-time analysis of chicken house abnormalities, and improve the efficiency and scientificity of on-site professional conclusions during accident handling.
Information automatic analysis
During the inspection process, the robot will automatically transmit the inspection information to the back-end computer of the system through the wireless encryption network, and analyze and process the back-end software to obtain the intuitive inspection results. When the robot inspection background is connected to the system, it can automatically upload the inspection information according to the system's standard format and transmission protocol, and the breeder can directly review and summarize the equipment information in the system. Combining temperature and humidity information, visible image information, infrared temperature measurement information, and sound information, artificial intelligence methods can be used for neural network calculations, and multiple feature values can be fused to obtain an early warning level. The robot broadcasts the level intelligently through speakers. In addition, according to the combination of neural network, gray value calculation, regression analysis, etc., combined with the collected multiple information, the epidemic and abnormal information prediction can be carried out. Predict the possibility of epidemic disease in advance, and carry out voice broadcast; combined with voice recognition technology, complete human-machine functional dialogue, mainly through third-party software. Realize a robot that can interact with people (intelligent voice recognition can be considered later to improve the interaction between robots and people).
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