Artificial intelligence system for managing poultry house

Abstract

A system for an aviary, comprising: a control server; the network gateway is arranged in the poultry house and has wireless communication capability; the mobile sensing module is arranged in the poultry house, and the mobile sensing module can move in the poultry house to obtain a plurality of environmental parameters related to a plurality of specific positions in the poultry house; and the sampling machine is arranged in the poultry house and is used for sampling poultry manure samples on the ground of the poultry house. The mobile sensing module transmits the environmental parameters to the network gateway, and the network gateway transmits the environmental parameters to the control server so as to process the environmental parameters.

Description

[0001] Cross - reference to related applications

[0002] This application claims priority to U.S. Patent Application No. 62 / 944,949, filed on December 6, 2019. Technical Field

[0003] The present invention relates to an artificial intelligence system for managing poultry houses. Background Art

[0004] The egg industry (e.g., the egg - laying chicken industry) faces multiple challenges in many key technologies. For example, in existing chicken houses, aspects such as the monitoring of harmful environmental chemicals, bacteria, and / or viruses, the automatic sensing and monitoring of laying hens, the recycling and reuse of chicken excrement as manure, the health management of laying hens, and the prevention of zoonotic diseases are all areas that can be improved. With the progress of various technologies, such as artificial intelligence of things (abbreviated as AIoT, which is the combination of artificial intelligence and the Internet of Things), big data processing (which includes the storage, analysis, and digitization of large amounts of data), etc., applying newly developed technologies to the egg industry may be helpful. Summary of the Invention

[0005] Therefore, an object of the present invention is to provide an artificial intelligence system for a poultry house.

[0006] According to an embodiment of the present invention, an artificial intelligence system for a poultry house includes:

[0007] A control server;

[0008] A network gateway, which is set in the poultry house and has wireless communication capabilities;

[0009] A mobile sensing module, which is set in the poultry house, and wherein the mobile sensing module can move within the poultry house to obtain multiple environmental parameters related to multiple specific positions within the poultry house; and

[0010] A sampler, which is set in the poultry house and is used to take samples of poultry manure on the ground of the poultry house.

[0011] Wherein, the mobile sensing module communicates with the network gateway to transmit the environmental parameters to the network gateway, and the network gateway is configured to transmit the environmental parameters to the control server to process the environmental parameters.

[0012] According to an embodiment of the present invention, an artificial intelligence system for a poultry house includes:

[0013] Control server

[0014] A network gateway, disposed in the poultry house and having wireless communication capabilities;

[0015] A mobile sensing module, disposed in the poultry house, wherein the mobile sensing module is capable of moving within the poultry house to obtain a plurality of environmental parameters related to a plurality of specific positions within the poultry house; and

[0016] A sampler, disposed in the poultry house, for taking samples of poultry manure on the ground of the poultry house.

[0017] The mobile sensing module communicates with the network gateway to transmit the environmental parameters to the network gateway, and the network gateway is configured to transmit the environmental parameters to the control server for processing the environmental parameters.

[0018] The system further includes a mass spectrometer disposed in the poultry house.

[0019] When it is determined that the environmental parameters are abnormal, the control server controls the sampler to take the poultry manure sample at the position of the mobile sensing module.

[0020] After obtaining the poultry manure sample, the control server controls the sampler to provide the poultry manure sample to the mass spectrometer to determine whether the poultry manure sample contains specific fecal bacteria.

[0021] The control server is configured to divide the poultry house into a plurality of areas.

[0022] The mobile sensing module is configured to obtain the environmental parameters of each of the areas.

[0023] The control server is configured to obtain representative parameters for each of the areas, at least based on the environmental parameters obtained by the mobile sensing module in the area.

[0024] The control server is configured to assign each of the areas to one of a plurality of states, the states including at least a normal state and an abnormal state.

[0025] The control server is configured to sort the representative parameters of the areas, and among all the areas, assign a preset number of the areas with the highest representative parameters to the abnormal state and assign the remaining areas to the normal state.

[0026] According to an embodiment of the present invention, an artificial intelligence system for a plurality of poultry houses located in different geographical regions, and includes: for each of the poultry houses

[0027] Control server;

[0028] A network gateway, which is set in the poultry house and has wireless communication capabilities;

[0029] A mobile sensing module, which is set in the poultry house, wherein the mobile sensing module can move within the poultry house to obtain a plurality of environmental parameters related to a plurality of specific positions within the poultry house; and

[0030] A sampling machine, which is set in the poultry house and is used to collect samples of poultry manure on the ground of the poultry house.

[0031] The mobile sensing module communicates with the network gateway to transmit the environmental parameters to the network gateway, and the network gateway is configured to transmit the environmental parameters to the control server to process the environmental parameters.

[0032] The system also includes, in each of the poultry houses: a mass spectrometer, a plurality of feeding machines, and a mobile conveyor.

[0033] When it is determined that the environmental parameters are abnormal, the control server controls the sampling machine to collect the poultry manure sample at the position of the mobile sensing module.

[0034] After obtaining the poultry manure sample, the control server controls the sampling machine to provide the poultry manure sample to the mass spectrometer to determine whether a specific fecal bacterium is contained in the poultry manure sample.

[0035] When the control server determines that the specific fecal bacterium is contained in the poultry manure sample, the control server controls the mobile conveyor to provide medicine to one of the feeding machines corresponding to the position of the mobile sensing module.

[0036] The system includes a plurality of the mobile sensing modules, and each mobile sensing module is for a corresponding one of the poultry houses. For each poultry house, the mobile sensing module is used to obtain the environmental parameters of the poultry house.

[0037] The control server is configured to, for each poultry house, obtain a representative parameter at least based on the environmental parameters obtained by the mobile sensing module in the poultry house.

[0038] The control server is configured to sort the representative parameters of the poultry house, designate a preset number of the poultry houses with the highest representative parameters as the abnormal state, and designate the remaining poultry houses as the normal state.

[0039] The control server is further configured to determine whether a disease is spreading in the poultry house at least based on the spatial distribution of the poultry houses in the abnormal state. Description of the Drawings

[0040] Other features and advantages of the present invention will become apparent from the following detailed description of embodiments in conjunction with the accompanying drawings, wherein:

[0041] Figure 1 and Figure 2 shows a poultry house according to an embodiment disclosed by the present invention;

[0042] Figure 3 is a schematic diagram of a mobile sensing module;

[0043] Figures 4A to 4C shows a plurality of exemplary mechanisms for enabling the mobile sensing module to move;

[0044] Figure 5 is an example diagram showing statistical data based on data obtained during a day;

[0045] Figure 6 is an example diagram showing a network gateway 250 communicating with a control server 600, a monitor screen, and a mobile device via a communication network;

[0046] Figure 7 is an example diagram showing a sampling machine;

[0047] Figure 8 shows the results of a mass spectrometer detecting specific fecal bacteria;

[0048] Figure 9 shows an interface of a mobile device for transmitting signals to control one or more exhaust fans to turn on or off;

[0049] Figure 10 shows a display screen of the status of a plurality of virtual areas of the poultry house;

[0050] Figure 11 shows a plurality of sentinels equipped with microphones for obtaining sentinel voiceprint data and cameras for obtaining images of the sentinels' cloacas;

[0051] Figure 12 shows using the sentinels' voiceprint data to control one or more exhaust fans to turn on or off;

[0052] Figure 13 shows the voiceprint data of healthy sentinels (left) and unhealthy sentinels (right);

[0053] Figure 14 shows an interface for enabling personnel in the poultry house to input other data related to the sentinels through the interface; and

[0054] Figure 15Disclosed is an interface for monitoring multiple poultry houses located in different geographical regions. Detailed Description of the Invention

[0055] Before describing the present invention in more detail, it should be noted that, where appropriate, reference numerals or terminal portions of reference numerals are repeated in the drawings to indicate corresponding or similar elements, which optionally have similar features.

[0056] The present invention provides an intelligent system for managing poultry houses, for example, to increase the egg production. Specifically, the intelligent system implements various functions, such as intelligent laying hen production and management, monitoring of harmful substances and bacteria, monitoring of laying hen health indices, prevention of zoonotic diseases, and improvement of laying hen health. The realization of the above functions can be achieved through AIoT, big data management, and digitization. The resulting artificial intelligence system for laying hen production can be configured to operate alone or in combination with existing automated equipment.

[0057] The functions covered by the artificial intelligence system of the present invention include but are not limited to the following: 1) sampling, sensing, and monitoring harmful substances and zoonotic bacteria in the poultry house; 2) automatic sensing and monitoring for physiological research and study of the egg production of laying hens; 3) performing intelligent remote control and hierarchical application of the Internet of Things; 4) big data storage, analysis, and digitization.

[0058] Figure 1 and Figure 2 Illustrated is a poultry house 200 according to an embodiment of the present invention. In the embodiment, the poultry house 200 is a chicken house and is configured to accommodate, for example, laying hens (also referred to as egg poultry) for egg production. The poultry house 200 may be equipped with one or more windows 210, one or more air conditioning devices 220, one or more exhaust fans 230, one or more feeding machines 240, at least one network gateway 250, at least one mobile sensing module 260, a sampling machine 270, and a mass spectrometer 280.

[0059] It is worth noting that each of the above components placed in the poultry house 200 may be equipped with a microprocessor and a Bluetooth 5.0 ( 5.0, or written as BT-5.0) device so as to be able to communicate with the network gateway 250. In addition, the network gateway 250 is configured to communicate with a control server 600 through a communication network (please refer to Figure 6)。The control server 600 can be implemented using a remote server (e.g., a cloud server) installed outside the poultry house 200 and communicating with the network gateway 250 via the Internet, or using a microserver installed inside the poultry house 200 and communicating with the network gateway 250 via a near-field communication network.

[0060] Considering the communication range of the BT-5.0 protocol (about 400 meters), a large number of components equipped with Bluetooth 5.0 communication functions inside the poultry house 200 can communicate with each other. In this embodiment, about two thousand components are provided in the poultry house 200.

[0061] In this configuration, the operation of the components in the poultry house 200 can be controlled by the control server 600 that executes an operating system (OS) including multiple applications and algorithms, and can be monitored by a user operating an electronic device that executes an application program.

[0062] Specifically, each window can be controlled to open or close. The air conditioning device 220 can be controlled to maintain the temperature inside the poultry house 200 at about a predetermined temperature level.

[0063] As Figure 3 shown, the mobile sensing module 260 is configured to sense multiple environmental parameters at different positions in the poultry house 200 and can have various sensors (e.g., a thermometer, a hygrometer, a carbon dioxide sensor, etc.). The environmental parameters can include temperature, relative humidity (Rh), and the concentration of specific gas substances (e.g., ammonia, carbon dioxide, etc.). As is well known, the temperature in the poultry house 200 directly affects egg production. The concentration of ammonia can be regarded as a health index of the laying hens in the poultry house 200 because ammonia is excreted from the cloaca of the laying hens.

[0064] In this embodiment, the sensor is provided on a main body of the mobile sensing module 260, and the main body is provided on a wheel set including at least one wheel (as Figure 4A shown in an example). The wheel set can be controlled by a microprocessor executing an application program to drive the main body to move inside the poultry house 200. In other embodiments, the sensor can be provided in a spherical housing of the mobile sensing module 260 (as Figure 4B shown in an example), and the spherical housing can be driven to roll so that the sensor assembly moves inside the poultry house 200. In some embodiments, one or more slide rails extending inside the poultry house 200 can be installed in the poultry house 200 (as Figure 4CAs shown in one example), the mobile sensing module 260 can be disposed on the slide rail to move thereon.

[0065] In this way, the mobile sensing module 260 can obtain data of the environmental parameters at various positions in the poultry house 200 and transmit the data of the environmental parameters to the control server 600. In some embodiments, the mobile sensing module 260 is provided with on-device AI (artificial intelligence) so that the mobile sensing module 260 can process the data of the environmental parameters thus obtained.

[0066] Next, the control server 600 can process the data of the environmental parameters to obtain statistical data related to the environment of the poultry house 200, the health status of the laying hens, etc. For example, as Figure 5 shown, the statistical data of the data obtained in a day can be displayed in a chart for further analysis (e.g., identifying highs, lows, trends, etc.).

[0067] By using the mobile sensing module 260 to monitor the environmental parameters at different positions in the poultry house 200, many advantages can be achieved. For example, the poultry house 200 usually houses a large number of laying hens. Due to the different health status and conditions of the laying hens, the detected values of each environmental parameter may be different at different positions in the poultry house 200 (e.g., different body temperatures of the laying hens will affect the environmental temperature of the poultry house 200). Therefore, using a single fixed sensor installed at a fixed position in the poultry house 200 to monitor the environment of the poultry house 200 may not produce accurate results sufficient to represent the dynamic situation of the poultry house 200.

[0068] In addition, monitoring the environmental parameters in the poultry house 200 is beneficial because it is desired to keep the environment of the poultry house 200 stable, and deviation from the predetermined optimal state (e.g., a one-degree increase or decrease in temperature) may have an adverse effect on egg production. Therefore, by using the mobile sensing module 260 to monitor the environmental parameters at different positions in the poultry house 200, it is easier to detect the deviation of the environmental parameters at different positions in the poultry house 200 from the predetermined optimal state.

[0069] Since the mobile sensing module 260 communicates with the network gateway 250, data related to the environmental parameters detected by the mobile sensing module 260 can be transmitted to the network gateway 250 in real time. Subsequently, the network gateway 250 can transmit data related to the environmental parameters to the control server 600. In this way, the control server 600 can process the data to determine whether the poultry house 200 is in an optimized state. It should be noted that in some embodiments, the above data processing can be completed by the microprocessor of the network gateway 250 or by the mobile sensing module 260 (device-side AI).

[0070] When it is determined by means of the mobile sensing module 260 that an abnormality is detected at a certain position in the poultry house 200 (for example, as indicated by the values of the detected environmental parameters, such as a relatively high temperature, an ammonia concentration higher than a preset standard, etc.), the control server 600 can determine that the health status of the laying hens in the detection area near the corresponding position of the mobile sensing module 260 in the poultry house 200 at the time of detection may need to be checked. Subsequently, the control server 600 can automatically control the sampler 270 to move to the detection area.

[0071] As Figure 7 shown, the sampler 270 can have a continuous track and can be controlled to move to multiple specific positions in the poultry house 200. In one embodiment, the sampler 270 can be controlled to move to the above-mentioned detection area. When the sampler 270 moves to the detection area, a set of robotic arms (not shown in the figure) of the sampler 270 can be used to take a poultry manure sample on the ground of the detection area.

[0072] Subsequently, the sampler 270 can be controlled to move to the position where the mass spectrometer 280 is located to provide the poultry manure sample to the mass spectrometer 280 for further inspection. The mass spectrometer 280 is configured to be able to detect several types of fecal bacteria to determine whether the laying hens in the detection area are diseased. The detection results of specific fecal bacteria can be displayed in the manner Figure 8 shown.

[0073] In one embodiment, after determining that the laying hens in the detection area may be diseased, the control server 600 can control the mobile conveyor to apply a drug for treating the disease (such as probiotics) to one or more feeding machines 240 in the detection area. The conveyor can be integrated with the feeding machine 240 (thus not shown separately in the figure), or can be implemented in the same manner as the mobile sensing module 260. That is, the conveyor can include a track belt or a wheel set for moving within the poultry house 200 (as Figures 4A to 4C shown). Additionally, the control server 600 can generate an alarm (such as a push message, a text message, an audible sound, etc.) to notify the situation to the personnel. In some embodiments, the conveyor can be omitted, and an automatic supply mechanism can be provided above the feed tray for accommodating the laying hen feed. The supply mechanism accommodates the drug for treating the disease and can be controlled to supply the drug to the feed tray.

[0074] In short, the intelligent system is configured to implement artificial intelligence of things (AIoT) in the poultry house 200 and can perform various operations, such as detecting the environmental parameters at different positions in the poultry house 200, real-time processing the data of the detected environmental parameters, sampling the poultry manure in the detection area where abnormal environmental parameters are detected, and moving the poultry manure sample to the mass spectrometer 280 for detection to immediately determine whether the laying hens in the detection area are diseased. By implementing artificial intelligence of things (AIoT), all the above operations can be automatically completed by the control server 600 controlling the components.

[0075] Each feeding machine 240 can be connected to a feed storage where the feed is stored and is configured to transport the feed from the feed storage to one or more positions in the poultry house 200 through a plurality of transfer pipes and a plurality of openings, and the openings can be controlled to open (start releasing the feed) or close (stop releasing the feed).

[0076] In one embodiment, in response to different detected values of the environmental parameters, the operation of the components of the poultry house 200 may be different. For example, the exhaust fan 230 may be controlled to turn on or off individually or jointly based on the temperature detected within the area, the temperature detected outside the poultry house 200, and / or the general temperature of the geographical area where the poultry house 200 is located. Specifically, when the difference between the temperature detected in the area and the temperature detected outside the poultry house 200 is greater than a predetermined threshold, the exhaust fan 230 is turned on to adjust the temperature in the poultry house 200. One or more air conditioning devices 220 are controlled to operate based on one or more of the following parameters: the detected temperature in the poultry house 200, the detected humidity, the concentration of detected harmful gas substances, etc. Also, each exhaust fan 230 can also be controlled by a person through an electronic device (such as a mobile device, such as a mobile phone running an application), and the electronic device is configured to be able to display the environmental parameters. For example, the mobile device can be controlled to display the environmental parameters, and based on the environmental parameters, the person can operate the mobile device to send a signal to control the exhaust fan 230 to turn on or off (as Figure 9 shown).

[0077] It should be noted that all data obtained and processed by the control server 600 can be stored in a data memory for further analysis (such as big data) through one or more neural networks that make up an artificial intelligence network. As the number of poultry houses 200 adopting the intelligent system increases, the amount of data collected will also increase, which is beneficial to the future big data analysis, digitization, and optimization of the intelligent system.

[0078] In some embodiments, a plurality of fixed sensing modules may be provided at various positions in the poultry house 200. The number and position of the fixed sensing modules can be determined based on the effective range of the fixed sensing modules.

[0079] In some embodiments, within the internal space of the poultry house 200, a plurality of cages are provided to accommodate the laying hens.

[0080] In some embodiments, the internal space of the poultry house 200 can be divided into a plurality of virtual regions. That is to say, there are no physical boundaries. The virtual regions can be defined based on the coverage range of the fixed sensing module. In other embodiments, the internal space of the poultry house 200 can be divided into a plurality of virtual regions based on a three-dimensional coordinate system, and each virtual region is defined by a set of three-dimensional coordinates of the three-dimensional coordinate system. Each virtual region can be covered by the effective range of one of the fixed sensing modules, or covered by one or more of the mobile sensing modules 260. In other examples, the control server 600 can designate the area of one cage as a virtual region, or designate the areas of a predetermined number of cages (for example, two or three) as virtual regions. In each virtual region, a fixed sensing module can be installed to detect the environmental parameters in the virtual region.

[0081] Thus, each virtual region can be designated as one of a plurality of states to indicate whether the environment of the virtual region is normal, or to indicate whether the environment of the virtual region is abnormal and may require treatment (for example, providing medicine). The state of the virtual region is designated by the control server 600 based on one or more environmental parameters (such as temperature) detected within the virtual region.

[0082] In one embodiment, the poultry house 200 has two floors, and each floor is divided into twelve virtual regions. When the environmental parameters detected in each virtual region are transmitted to the control server 600, the control server 600 can determine whether each virtual region is in a normal state or an abnormal state. As Figure 10 shown, both the first floor and the second floor of the poultry house 200 are divided into twelve virtual regions. The virtual regions considered to be in the normal state can be represented by one color (for example, green), and the virtual regions considered to be in the abnormal state (referred to as abnormal regions) are represented by another color (for example, red). It should be noted that in some embodiments, additional states can be designated to indicate various environmental states of the virtual regions, and represented by other colors (for example, yellow). Thus, the health states of all virtual regions can be displayed on the screen in different colors, which is convenient for people to see at a glance.

[0083] In one embodiment, the effective temperature of each of the twenty-four virtual areas (e.g., the average value over a period of time) is collected, and the twenty-four effective temperatures are sorted to determine a preset number (e.g., four) of the highest effective temperatures. Then, the four virtual areas with the four highest effective temperatures are designated as the abnormal state, and the remaining virtual areas are designated as the normal state. In other embodiments, other environmental parameters (e.g., the concentration of ammonia) can be included in the calculation to obtain a representative parameter for each of the twenty-four virtual areas, and based on the representative parameters of each area, a judgment can be made to designate the preset number of virtual areas as the abnormal state. For example, each environmental parameter can be assigned a predetermined weight, and calculating the representative parameter can include calculating a weighted average from the environmental parameters as the representative parameter.

[0084] By using the configuration, the control server 600 can further determine whether the disease indicated by the abnormal state is spreading in the poultry house 200 according to the distribution of the virtual areas designated as the abnormal state.

[0085] Specifically, in one example as Figure 10 shown, the spatial distribution of the four virtual areas with the highest effective temperatures (i.e., B-3, C-1, G-2, and H-3) in the poultry house 200 can be regarded as being randomly distributed (i.e., without a specific pattern and no adjacent abnormal areas). This judgment can also be used to consider the environmental parameters of other virtual areas (e.g., the location of the virtual area with the fifth highest effective temperature), and / or the change rate of the environmental parameters.

[0086] On the other hand, when the four virtual areas with the highest effective temperatures are close to each other (e.g., all adjacent), it can be considered that the situation in these virtual areas requires special attention. In this case, the control server 600 can assign a first-level alarm to the poultry house 200 to indicate that the poultry house 200 may be in the initial stage of a disease outbreak.

[0087] At this stage, the control server 600 can execute a control protocol, which includes providing medicine to the laying hens located in the abnormal area and selectively providing medicine to the laying hens in other virtual areas (referred to as adjacent areas) adjacent to the abnormal area, and disinfecting the environment of the abnormal area and selectively the environment of the adjacent area. It should be noted that in the embodiment, the medicine can be provided via the feeding machine 240.

[0088] Moreover, in the subsequent monitoring of the poultry house 200, the preset number of designated abnormal areas can be increased (e.g., increased to six).

[0089] After that, monitoring is performed to determine whether, for example, after a predetermined period of time following the execution of the control protocol in the initial stage of the outbreak, the situation is in a controlled state (e.g., the spatial distribution of the abnormal area changes to a random distribution) or is deteriorating (e.g., the distribution of the abnormal area is aggregating and spreading, or the environmental parameters of the abnormal area indicate a more deteriorated environmental state).

[0090] When it is determined that the situation is deteriorating, the control server 600 can assign a second-level alarm to the poultry house 200 to indicate that the poultry house 200 may be in the mid-stage of a disease outbreak.

[0091] At this stage, the control server 600 can execute an enhanced control protocol, which includes providing medications to the laying hens located in the abnormal area and the adjacent areas, and enhancing the disinfection of the entire environment of the poultry house 200. Moreover, in subsequent monitoring of the laying hen breeding area, the preset number designated as the abnormal area can be further increased (e.g., increased to ten).

[0092] After that, monitoring is performed to determine whether, for example, after a predetermined period of time following the execution of the enhanced control protocol in the mid-stage of the outbreak, the situation is in a controlled state (e.g., the spatial distribution of the abnormal area changes to a random distribution) or is still deteriorating (e.g., the distribution of the abnormal area is similarly aggregating and spreading, or the environmental parameters of the abnormal area indicate a more deteriorated environmental state).

[0093] When it is determined that the situation continues to deteriorate, the control server 600 can assign a third-level alarm to the poultry house 200 to indicate that the poultry house 200 may be in the late stage of a disease outbreak.

[0094] At this stage, the control server 600 can execute an even stronger control protocol, which includes providing medications to the laying hens in all virtual areas, and disinfecting the entire environment of the poultry house 200. Moreover, according to the regulations of a specific country, the control server 600 can generate an alarm to notify the situation to personnel and designated government officials. And the government officials can authorize measures such as culling the livestock in the poultry house 200. In some embodiments, certain statutory agencies (e.g., the Department of Health) can obtain the data in the control server 600 so that the statutory agencies can take preventive measures (e.g., dispatching supplies or manpower to assist in disinfection) or execute culling.

[0095] In one embodiment, for each virtual area in the poultry house 200, multiple sentinels can be designated. The term "sentinel" can be regarded as a laying hen selected to be equipped with detection devices on its body to obtain one or more health parameters of the laying hen, and the laying hen can represent multiple laying hens in the same virtual area, or the virtual area itself.

[0096] As Figure 11 and Figure 12 shown, in this embodiment, each sentinel can be equipped with a microphone 1100 for obtaining the voiceprint data of the sentinel, a temperature sensor 1110 for obtaining the body temperature of the sentinel, and a camera 1120 for obtaining an image of the cloaca of the sentinel. It should be noted that, in some embodiments, the temperature sensor 1110 can be installed in the poultry house 200. In this way, the temperature sensor 1110 can be used to detect the temperature in the poultry house 200, and the body temperature of the sentinel can be estimated.

[0097] Processing the voiceprint data of the sentinel can help determine whether the sentinel is healthy. For example, as Figure 13 shown, the voiceprint data of a healthy sentinel can have a waveform as shown on the left side of Figure 13 , while the voiceprint data of an unhealthy sentinel (e.g., suffering from nasal discomfort) can have a waveform as shown on the right side of Figure 13 . Similarly, the body temperature of the sentinel can indicate the health status of the sentinel. By observing the image of the cloaca of the sentinel, the control server 600 can determine whether there are specific fecal bacteria (e.g., by identifying certain colors in the image), and when it is determined that there are specific fecal bacteria, the control server 600 can control the sampler 270 to take a poultry manure sample for the treatment as described above. Using the above data, health parameters (such as nasal comfort, cloaca health) can be calculated.

[0098] In addition, the data collected from the sentinels can be stored as template data. When more data is collected, the template data can be used for comparison (e.g., comparing voiceprint data to determine whether another laying hen has nasal discomfort), for example, to facilitate the detection of unhealthy laying hens.

[0099] It should be noted that the health parameters of the sentinels can be used together with the above-mentioned environmental parameters to determine the representative parameters of the virtual area and to determine the state of the virtual area (i.e., the normal state or the abnormal state). And the health parameters of the sentinels can be used to determine whether it is necessary to adjust the operation of the components in the poultry house 200. For example, as Figure 12 shown, when the voiceprint data of the sentinel indicates that the sentinel is unhealthy, one or more exhaust fans 230 can be started to remove pollutants in the air.

[0100] It should be noted that other types of data can also be input by the personnel in the poultry house 200 using the mobile device. For example, as Figure 14 shown, the personnel can manually operate the mobile device to input the weight of the sentry, the number of eggs laid in a day, a photo of the sentry, etc. These data can be processed and displayed in a graph for further analysis (e.g., identifying the health trends in the life of the sentry, performing health checks, etc.).

[0101] In one embodiment, the configuration for monitoring multiple virtual areas in a poultry house 200 can be applied to multiple poultry houses 200 located in different geographical regions (as Figure 15 shown). For each poultry house 200, the health parameters and / or the environmental parameters can be detected and uploaded to the control server 600 (which can be located in a central facility). In this way, the data related to the poultry house 200 can be displayed in an interface as Figure 10 shown, and each poultry house 200 can be regarded as a region. The poultry houses 200 that are relatively close (e.g., the distance between them is within 0.5 to 5 kilometers) can be regarded as adjacent to each other.

[0102] The control server 600 can be configured to designate a preset number of poultry houses 200 as being in the abnormal state. The way of designating the state is similar to the aforementioned way, that is, by sorting the values of the representative parameters of the poultry house 200 and designating the preset number of poultry houses 200 with the highest representative parameters as being in the abnormal state.

[0103] Using the configuration, the control server 600 can use the aforementioned method to determine whether a disease has spread between the poultry houses 200. That is, a three - level alarm mechanism can be adopted to determine whether nearby poultry houses 200 are simultaneously designated as being in the abnormal state and whether the abnormal state is spreading to other nearby poultry houses 200.

[0104] In one example, when one of the poultry houses 200 is considered to be in the third - level alarm, in addition to performing the aforementioned measures on the poultry house 200, nearby poultry houses 200 can be alerted so as to be prepared for the potential coming disease. In this case, appropriate measures can be taken to solve the potential disease problem.

[0105] It should be noted that for each poultry house 200, the personnel can view an interface as Figure 15 shown. In this way, not only can the personnel see the poultry house 200 where they are located, but also other poultry houses 200 in the nearby geographical area. Therefore, when one or more nearby poultry houses 200 have a third - level alarm, preventive measures can be taken.

[0106] In summary, the intelligent system described in the present invention includes the following various functions and potential effects:

[0107] 1. Obtain the values of the health parameters from a group of sentinels;

[0108] 2. Collect the environmental parameters for big data analysis;

[0109] 3. Collect fecal bacteria for big data analysis;

[0110] 4. The cloud server, the control server 600 in each poultry house 200, and the components in each poultry house 200 can be used to establish an AI cloud integration platform for monitoring the health of laying hens;

[0111] 5. By obtaining relevant data from one or more poultry houses 200 accommodating a large number of laying hens, further research in various fields (such as big data analysis, deep learning, and artificial intelligence applications) can be promoted;

[0112] 6. Using the above system, based on the time analysis of the health parameter values or the change in the rate of change of the health parameter values, the trend of disease transmission among the laying hens in one poultry house 200 or among multiple poultry houses 200 can be monitored;

[0113] 7. By dividing the poultry house 200 into multiple virtual areas and setting the fixed sensing module and / or the mobile sensing module 260, the control server 600 can judge the status of the sentinels in a specific area within the poultry house 200 (and thus judge the status of the corresponding laying hen group), and can use colors to display on the monitor to represent the status of the specific area in the poultry house 200;

[0114] 8. By setting multiple components capable of communicating through a BT-5.0 gateway, the detection, feeding, and drug supply of the environmental parameters and the health parameters can be performed for one or more specific areas within the poultry house 200. In this way, the effects of intelligent feeding and partition isolation can be achieved; and

[0115] 9. By designating multiple laying hens as sentinels and having the sentinels obtain the health parameters, the health parameters of the sentinels can be further analyzed to assist in evaluating the health of the laying hens. By implementing the above three-level protocol, large-scale culling due to disease transmission can be avoided. And a database containing the health parameters of the sentinels in one or more poultry houses 200 can be established for future analysis. The relevant health data can also be transmitted to nearby poultry houses 200 and one or more legal institutions to alert them of potential disease transmission.

[0116] In the foregoing description, for purposes of explanation, numerous specific details have been set forth in order to provide a thorough understanding of the embodiments. However, it will be apparent to one of ordinary skill in the art that one or more other embodiments may be practiced without some of these specific details. It should be understood that throughout this specification, references to "one embodiment", "an embodiment", embodiments with ordinal indication, etc., mean that a particular feature, structure, or characteristic may be included in the disclosed implementations. It should also be understood that in the description, for purposes of streamlining the disclosure and aiding in the understanding of the various inventive aspects, various features are sometimes grouped together in a single embodiment, figure, or description thereof, and in the implementations of the present disclosure, where appropriate, one or more features or specific details from one embodiment may be implemented together with one or more features or specific details from another embodiment.

[0117] Although the present disclosure has been described in connection with the embodiments, it should be understood that the present disclosure is not limited to the disclosed embodiments, but is intended to cover various arrangements included within the spirit and scope of the broadest interpretation, thereby covering all such modifications and equivalent arrangements.

Claims

1. An artificial intelligence system for a poultry house, comprising: A control server; A network gateway, disposed in the poultry house and having wireless communication capabilities; A mobile sensing module is arranged in the poultry house, wherein, The mobile sensing module can move within the poultry house to obtain a plurality of environmental parameters related to a plurality of specific locations within the poultry house; A sampling machine, disposed in the poultry house, for taking samples of poultry manure on the ground of the poultry house; Wherein, the mobile sensing module communicates with the network gateway to transmit the environmental parameters to the network gateway, and the network gateway is configured to transmit the environmental parameters to the control server to process the environmental parameters.

2. The system according to claim 1, further comprising a mass spectrometer disposed in the poultry house, Among them, When it is determined that the environmental parameters are abnormal, the control server controls the sampling machine to take the poultry manure sample at the position of the mobile sensing module; After obtaining the poultry manure sample, the control server controls the sampling machine to provide the poultry manure sample to the mass spectrometer to determine whether a specific fecal bacterium is contained in the poultry manure sample.

3. The system according to claim 2, further comprising a plurality of feeding machines and a mobile conveyor; Among them, When the control server determines that the poultry manure sample contains the specific fecal bacterium, the control server controls the mobile conveyor to provide medicine to one of the feeding machines corresponding to the position of the mobile sensing module.

4. The system according to claim 1, wherein: The control server is configured to divide the poultry house into a plurality of areas; The mobile sensing module is configured to obtain the environmental parameters of each of the areas; And The control server is configured to, for each of the areas, obtain a representative parameter at least based on the environmental parameters obtained by the mobile sensing module in the area.

5. The system according to claim 4, wherein: The control server is configured to assign each of the areas to one of a plurality of states, and the states at least include a normal state and an abnormal state.

6. The system according to claim 5, wherein: The control server is configured to sort the representative parameters of the areas, and among all the areas, assign a preset number of areas with the highest representative parameters to the abnormal state, and assign the remaining areas to the normal state.

7. The system according to claim 6, wherein: The control server is further configured to determine whether a disease is spreading in the poultry house at least based on the spatial distribution of the areas in the abnormal state.

8. The system according to claim 7, wherein: When it is determined that a disease is spreading in the poultry house, the control server is further configured to assign an alarm level related to the poultry house and generate a control signal based on the alarm level to execute a control protocol.

9. The system according to claim 7, wherein: When the areas in the abnormal state are randomly distributed in space in the poultry house, the control server determines that there is no disease spread.

10. The system according to claim 9, wherein: When it is determined that the areas in the abnormal state are distributed in a specific pattern in space, the control server is configured to assign an alarm level to the poultry house and generate a control signal based on the alarm level to execute a control protocol.

11. The system according to claim 10, wherein: The control protocol includes at least one of the following: providing medicine, disinfecting one or more of the areas of the poultry house, alerting personnel of a legal agency, and culling livestock in the poultry house.

12. The system according to claim 4, wherein: For each of the areas, a sentinel is selected to obtain at least one health parameter, which is obtained from the voiceprint data of the sentinel, the body temperature of the sentinel, and an image of the cloaca of the sentinel.

13. The system according to claim 12, wherein: The control server is configured to, for each of the areas, also obtain the representative parameter based on the health parameter of the sentinel in the area.

14. The system according to claim 12 further includes a plurality of exhaust fans arranged around the poultry house, and at least one of the exhaust fans is associated with each of the areas. Among them, For each of the areas, the control server is configured to at least control the start or stop of at least one of the exhaust fans associated with the area based on the representative parameter of the area.

15. The system according to claim 4, wherein: The poultry house includes a plurality of cages for accommodating a plurality of laying hens, and each of the areas is defined to cover at least one cage.

16. The system according to claim 15, wherein: A fixed sensing module is provided in each of the areas.

17. When the system according to claim 1 is applied to a plurality of poultry houses in different geographical regions, wherein: The system includes a plurality of the mobile sensing modules, and each of the mobile sensing modules is for a corresponding one of the poultry houses. For each of the poultry houses, the mobile sensing module is configured to obtain the environmental parameter of the poultry house. The control server is configured to, for each of the poultry houses, obtain a representative parameter at least based on the environmental parameter obtained by the mobile sensing module in the poultry house.

18. The system according to claim 17, wherein: The control server is configured to sort the representative parameters of the poultry houses, designate a preset number of the poultry houses with the highest representative parameters as the abnormal state, and designate the remaining poultry houses as the normal state.

19. The system according to claim 18, wherein: The control server is further configured to judge whether a disease is spreading in the poultry house at least based on the spatial distribution of the poultry houses in the abnormal state.

20. The system according to claim 19, wherein: When it is judged that a disease is spreading in the poultry house, the control server is further configured to designate an alarm level to the poultry house and generate a control signal based on the alarm level to execute the control protocol.

21. The system according to claim 18, wherein: When one of the poultry houses is designated as an alarm level indicating that the poultry house may be in the late stage of a disease outbreak, the control server is configured to also transmit an alarm to other poultry houses adjacent to the one poultry house.

22. The system according to claim 1, wherein: The wireless communication capability includes at least one of Bluetooth 5.0 (BT-5.0) capability, 4G capability, and Wi-Fi capability.

23. An artificial intelligence system for a poultry house, comprising: A control server; A network gateway provided in the poultry house and having wireless communication capability; The mobile sensing module is arranged in the poultry house, wherein, The mobile sensing module can move within the poultry house to obtain a plurality of environmental parameters related to a plurality of specific positions within the poultry house; And A sampler provided in the poultry house for taking samples of poultry manure on the ground of the poultry house. Wherein, the mobile sensing module communicates with the network gateway to transmit the environmental parameters to the network gateway, and the network gateway is configured to transmit the environmental parameters to the control server for processing the environmental parameters; Wherein, the system further includes a mass spectrometer disposed in the poultry house; Wherein, when it is determined that the environmental parameters are abnormal, the control server controls the sampler to collect the poultry manure sample at the position of the mobile sensing module; After obtaining the poultry manure sample, the control server controls the sampler to provide the poultry manure sample to the mass spectrometer to determine whether a specific fecal bacterium is contained in the poultry manure sample; Wherein, the control server is configured to divide the poultry house into multiple regions; The mobile sensing module is configured to obtain the environmental parameters of each of the regions; and The control server is configured to obtain representative parameters for each of the regions based at least on the environmental parameters obtained by the mobile sensing module in the region; The control server is configured to assign each of the regions to one of multiple states, and the states at least include a normal state and an abnormal state; Wherein, the control server is configured to sort the representative parameters of the regions, and among all the regions, assign a preset number of regions with the highest representative parameters to the abnormal state and assign the remaining regions to the normal state; 24. The system according to claim 23, wherein: For each of the regions, a sentry is selected to obtain at least one health parameter, and the health parameter is obtained from the voiceprint data of the sentry, the body temperature of the sentry, and the image of the cloaca of the sentry; Wherein, the control server is configured to further obtain the representative parameters for each of the regions based on the health parameters of the sentries in the region; 25. The system according to claim 23, wherein: The poultry house includes a plurality of cages for accommodating laying hens, and each of the regions is defined to cover at least one cage; Wherein, a fixed sensing module is provided in each of the regions; 26. An artificial intelligence system for a plurality of poultry houses located in different geographical regions, comprising: for each of the poultry houses a control server; a network gateway, disposed in the poultry house and having wireless communication capabilities; a mobile sensing module, disposed in the poultry house, wherein the mobile sensing module can move within the poultry house to obtain a plurality of environmental parameters related to a plurality of specific positions within the poultry house; and a sampler, disposed in the poultry house, for collecting poultry manure samples on the ground of the poultry house; Wherein, the mobile sensing module communicates with the network gateway to transmit the environmental parameters to the network gateway, and the network gateway is configured to transmit the environmental parameters to the control server for processing the environmental parameters; Wherein, the system further includes a mass spectrometer, a plurality of feeding machines and a mobile conveyor in each of the poultry houses; Wherein, when it is determined that the environmental parameters are abnormal, the control server controls the sampler to collect the poultry manure sample at the position of the mobile sensing module; After obtaining the poultry manure sample, the control server controls the sampling machine to provide the poultry manure sample to the mass spectrometer to determine whether the poultry manure sample contains specific fecal bacteria; Wherein, when the control server determines that the poultry manure sample contains the specific fecal bacteria, the control server controls the mobile conveyor to provide medicine to one of the feeding machines corresponding to the position of the mobile sensing module; The system includes a plurality of the mobile sensing modules, and each of the mobile sensing modules is used for a corresponding poultry house; For each of the poultry houses, the mobile sensing module is used to obtain the environmental parameters of the poultry house; The control server is configured to obtain a representative parameter for each of the poultry houses, at least based on the environmental parameters obtained by the mobile sensing module in the poultry house; Wherein, the control server is configured to sort the representative parameters of the poultry house, designate a preset number of the poultry houses with the highest representative parameters as the abnormal state, and designate the remaining poultry houses as the normal state; Wherein, the control server is further configured to determine whether a disease is spreading in the poultry house at least based on the spatial distribution of the poultry houses in the abnormal state.

27. The system according to claim 26, wherein: When it is determined that a disease is spreading in the poultry house, the control server is further configured to designate an alarm level to the poultry house and generate a control signal based on the alarm level to execute a control protocol; and Wherein, when one of the poultry houses is designated as an alarm level indicating that the poultry house may be in the late stage of a disease outbreak, the control server is configured to further send an alarm to other poultry houses adjacent to the one poultry house.

28. The system according to claim 26, wherein: For each of the poultry houses, a sentinel is selected to obtain at least one health parameter, and the health parameter is obtained from the voiceprint data of the sentinel, the body temperature of the sentinel, and an image of the cloaca of the sentinel; Wherein, the control server is configured to obtain the representative parameter for each of the poultry houses, further based on the health parameter of the sentinel in the poultry house.

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