JP2021111069A - Livestock farmer management support method and livestock farmer management support system - Google Patents

Abstract

To provide a method and a system to support management of a livestock farmer by constantly monitoring a breeding state of livestock and feeding back the breeding state to the livestock farmer in a timely manner.SOLUTION: A livestock farmer management support method includes a weight estimation step S1 and a state determination step S2. In the weight estimation step S1, a computer estimates an average body weight of a plurality of pieces of livestock born in a predetermined period. In the state determination step S2, the computer determines the quality of a breeding state of the livestock based on the average body weight and a predetermined threshold value.SELECTED DRAWING: Figure 1

Description

The present invention relates to a method and a system for supporting the management of a livestock farmer.

In recent years, for example, the management of livestock farmers has become extremely difficult due to the increase in imports of cheap foreign meat and soaring feed costs.

In particular, the impact of feed costs on management is extremely large. Therefore, it is necessary to improve breeding efficiency so that many livestock can be shipped with as little feed as possible.

In order to improve breeding efficiency, it is desirable that the breeding condition is constantly monitored, and problems such as poor feed quality are discovered early and fed back to livestock farmers.

However, this breeding condition is generally fed back to livestock farmers every time the livestock are shipped, that is, every few months.

Therefore, it is a main object of the present invention to provide a method and a system for supporting the management of a livestock farmer by constantly monitoring the breeding state of livestock and feeding back the breeding state to the livestock farmer in a timely manner.

The present invention is a method of supporting the management of a livestock farmer, based on a weight estimation stage for estimating the average weight of a plurality of livestock born in a predetermined period, the average weight, and a predetermined threshold. Provided is a livestock farmer management support method including a state determination stage for determining the quality of the livestock breeding condition.
The body weight estimation step may include an acquisition step of capturing an image of the livestock to obtain an image and an analysis step of analyzing the image to estimate the weight of the livestock.
The state determination step is a step of dividing the feed consumption by the weight gain of the average weight of the livestock to obtain the feed conversion ratio, and the breeding of the livestock based on the feed conversion ratio and a predetermined threshold. It may include a step of determining the quality of the condition.
After the state determination step, a defect cause estimation step for estimating the defect cause of the breeding state based on the average body weight may be further included.
After the state determination step, a state display step for displaying the breeding state of the livestock may be further included.
The state display stage can display the change over time in the average body weight.
After the weight estimation step, a shipping prediction step for predicting the shipping time of the livestock based on the average weight may be further included.
The livestock can be fattening pigs.
Further, this technology is a system that supports the management of livestock farmers, and is a weight estimation unit that estimates the average weight of a plurality of livestock born in a predetermined period, and the breeding state of the livestock based on the average weight. It provides a livestock farmer management support system equipped with a state judgment unit for judging the quality of the livestock.

According to the present invention, it is possible to provide a method and a system for supporting the management of a livestock farmer by constantly monitoring the breeding state of livestock and feeding back the breeding state to the livestock farmer in a timely manner.

It is a flowchart of an example of the livestock farmer management support method which concerns on this invention. It is a flowchart of an example of the weight estimation stage which concerns on this invention. It is a flowchart of an example of the state determination stage which concerns on this invention. It is a flowchart of an example of the state determination stage which concerns on this invention. It is a flowchart of an example of the livestock farmer management support method which concerns on this invention. It is a flowchart of an example of the defect cause estimation stage which concerns on this invention. This is an example of a database used by the defect cause estimation stage according to the present invention. It is a flowchart of an example of the livestock farmer management support method which concerns on this invention. This is an example of a table displayed in the state display stage according to the present invention. This is an example of a graph displayed at the state display stage according to the present invention. It is a flowchart of an example of the livestock farmer management support method which concerns on this invention. It is a flowchart of an example of the shipment prediction stage which concerns on this invention. It is a hardware block diagram which shows one Embodiment of the computer used by the livestock farmer support method which concerns on this invention. It is a conceptual diagram which shows one Embodiment of the livestock farmer management support system which concerns on this invention.

Hereinafter, suitable embodiments for carrying out the present invention will be described with reference to the attached drawings. The embodiments described below show typical embodiments of the present invention, and the scope of the present invention is not limited to these embodiments.

In the following description of the embodiment, expressions with "abbreviations" such as substantially parallel and substantially orthogonal may be used. For example, substantially parallel means not only completely parallel, but also substantially parallel, that is, including a difference of, for example, about several percent. The same applies to other expressions with "abbreviations". Further, each figure is a schematic view and is not necessarily exactly illustrated.

Further, in each figure, substantially the same components are designated by the same reference numerals, and duplicate description may be omitted or simplified.

The present invention will be described in the following order.
1. 1. The first embodiment according to the present invention (livestock farmer management support method)
(1) Outline of the present invention (2) Weight estimation (3) Status determination (4) Defect cause estimation (5) Status display (6) Shipment forecast (7) Hardware 2. Second Embodiment according to the present invention (livestock farmer management support system)

<1. First Embodiment (Livestock Farmer Management Support Method)>
<(1) Outline of the present invention>
Conventionally, it has been difficult to grasp the breeding state of livestock, so that there is a problem that the cost of sales is high. In particular, the impact of feed costs on management was extremely large. Breeding costs generally account for 60 to 70% of the cost of sales. It is conceivable that this reduction in feed costs will lead to a reduction in cost of sales.

It is common practice to obtain feed consumption efficiency by dividing feed consumption by the number of livestock shipped. However, this consumption efficiency is obtained at the time of shipment of livestock. Therefore, this consumption efficiency is obtained every few months. In order for livestock farmers to make timely management decisions, it is desirable that this consumption efficiency be obtained in a timely manner.

The livestock farmer management support method according to the present invention is a method of supporting the management of a livestock farmer by using a computer. The livestock farmer management support method according to the present invention will be described with reference to FIG. FIG. 1 is a flowchart of an example of a livestock farmer management support method according to the present invention. As shown in FIG. 1, the livestock farmer management support method according to the present invention includes a body weight estimation stage (S1) and a state determination stage (S2).

In the weight estimation stage (S1), a computer estimates the average weight of a plurality of livestock born in a predetermined period. In the state determination step (S2), the computer determines the quality of the breeding state of the livestock based on the average body weight and a predetermined threshold value.

As a result, the breeding state of livestock is fed back to the livestock farmer in a timely manner, which can improve the management of the livestock farmer.

<(2) Weight estimation>
In the weight estimation stage (S1), a computer estimates the average weight of a plurality of livestock born in a predetermined period. The predetermined period can be set arbitrarily, but may be set, for example, one week.

The method for estimating the weight of livestock is not particularly limited. An example of a method for estimating the weight of livestock will be described with reference to FIG. FIG. 2 is a flowchart of an example of the weight estimation stage (S1) according to the present invention. As shown in FIG. 2, the weight estimation stage (S1) according to the present invention may include, for example, an acquisition stage (S11) and an analysis stage (S12).

In the acquisition stage (S11), the imaging device images the livestock to obtain an image. This imaging device can be, for example, a camera. Furthermore, this imaging device is preferably, for example, a 3D (3-Dimention) camera.

A 3D camera, like the human eye, has multiple lenses. The 3D camera converts the light incident from each of the plurality of lenses into image data. By synthesizing images captured from a plurality of angles, a 3D camera can obtain a 3D image.

In the analysis stage (S12), the computer analyzes the image to estimate the weight of the livestock. For example, when this image is a 3D image, the 3D image may contain information about the volume of livestock captured. The computer can estimate the weight of livestock by multiplying this volume by the density (weight per unit volume).

Furthermore, livestock have different weights for each part. Therefore, the density may vary from site to site.

The image pickup device may be arranged, for example, near the ceiling of the hut where livestock are raised, facing the floor. The imaging device can image an area of a predetermined size on the floor surface. This area can be, for example, a rectangle with a side length of 2 meters. There can be multiple areas on the floor. It is preferable that the intervals between regions are even so that the estimation results are not biased.

The imaging device randomly images a plurality of livestock existing in this area. Imaging can be performed several to hundreds of times a day. The computer estimates the average weight of multiple livestock.

Each of the livestock born within a given period of time, eg, a week, tends to grow in the same way. Therefore, it is not necessary to identify each of the plurality of livestock in order to obtain a tendency of livestock growth. In order to obtain the growth tendency of livestock, it is sufficient to be able to obtain the average weight of a plurality of livestock. Furthermore, the same livestock may be duplicated in the plurality of livestock.

The method by which the computer estimates the average body weight in the weight estimation stage (S1) is not limited to this method. For example, the weight of livestock may be measured using a weight scale such as a load cell. Alternatively, the imaging device may be movable.

<(3) Status judgment>
In the state determination stage (S2), the computer determines the quality of the breeding state of the livestock based on the average body weight and a predetermined threshold value.

This determination will be described with reference to FIG. FIG. 3 is a flowchart of an example of the state determination stage (S2) according to the present invention. As shown in FIG. 3, in the state determination stage (S2) according to the present invention, first, a computer calculates the standard weight of livestock (S21).

When a plurality of livestock born in a predetermined period is defined as one lot, the average body weight of the plurality of lots is defined as the standard body weight. At the stage of calculating the standard weight (S21), the computer calculates the standard weight. Specifically, for example, the computer can calculate this standard weight by dividing the sum of the average weights of each of the plurality of lots by the number of lots.

The standard weight generally varies depending on the type of livestock. Furthermore, for example, when the livestock is a fattening pig, the standard weight generally differs depending on the breed of the fattening pig. This variety may include, for example, Landrace, Large White, Medium Yorkshire, Duroc, Berkshire and the like. Therefore, the computer may have a standard weight for each breed.

Subsequently, using this standard body weight as a threshold value, the computer can compare this threshold value with the estimated average body weight to determine the quality of the breeding state of the livestock. More specifically, for example, when the estimated average body weight is equal to or higher than the threshold value (S22: Yes), the computer determines that the breeding state of the livestock is normal (S23). On the other hand, when the estimated average body weight is less than the threshold value (S22: No), the computer determines that the breeding state of the livestock is abnormal (S24).

Alternatively, the computer may determine the quality of the breeding condition of the livestock by comparing the breeding conditions at a plurality of time points. For example, by comparing the average body weight on a predetermined date with the average body weight on the previous day, the computer may determine the quality of the livestock breeding condition. For example, when the difference between the average body weight on a predetermined date and the average body weight on the previous day is less than a predetermined value, the computer can determine that the breeding state of the livestock is abnormal.

In this case, in addition to the average body weight, the quality of the livestock breeding state may be determined based on, for example, the weight gain of the livestock, the feed consumption amount, the feed conversion ratio, the water supply amount, and the like.

As a result, the breeding status of livestock can be fed back to the livestock farmer in a timely manner. Therefore, the management of livestock farmers can be improved.

By the way, there is an index called feed conversion ratio for managing breeding costs. Feed conversion ratio refers to the amount of feed required to increase livestock by 1 kg. Specifically, the feed conversion ratio can be obtained by dividing the feed consumption by the weight gain of livestock. It can be said that the lower the feed conversion ratio, the more efficiently the feed is consumed, which is a preferable state.

In the state determination stage (S2), the computer may determine the quality of the livestock breeding state based on the feed conversion ratio and a predetermined threshold value.
This determination will be described with reference to FIG. FIG. 4 is a flowchart of an example of the state determination stage (S2) according to the present invention. As shown in FIG. 4, in the state determination stage (S2) according to the present invention, the computer first calculates the feed conversion ratio of livestock (S25). The method for calculating the feed conversion ratio is as described above.

Subsequently, the computer calculates the standard feed conversion ratio (S26). The standard feed conversion ratio is the average feed conversion ratio of a plurality of lots. Specifically explaining the calculation method, for example, the computer can calculate this standard feed conversion ratio by dividing the total feed conversion ratio of each of a plurality of lots by the number of lots.

The standard feed conversion ratio, as well as the standard weight, generally varies depending on the type of livestock. Furthermore, for example, when the livestock is a fattening pig, the standard feed conversion ratio generally differs depending on the breed of the fattening pig.

Subsequently, using this standard feed conversion ratio as a threshold value, the computer can compare this threshold value with the calculated feed conversion ratio to determine the quality of the livestock breeding condition. More specifically, for example, when the difference between the calculated feed conversion ratio and the standard feed conversion ratio is less than a predetermined value (S27: Yes), the computer determines that the livestock breeding condition is normal. (S28). On the other hand, when the difference between the calculated feed conversion ratio and the standard feed conversion ratio is equal to or greater than a predetermined value (S27: No), the computer determines that the breeding state of the livestock is abnormal (S29). This predetermined value can be set arbitrarily. This predetermined value can be, for example, 0.5.

The method of comparing the feed conversion ratio and the standard feed conversion ratio is not limited to this method. For example, the computer may compare the high feed conversion ratio with the high standard feed conversion ratio to determine the quality of the livestock breeding condition.

There is a close relationship between feed consumption and livestock weight, as is the indicator of feed conversion ratio. Nevertheless, traditionally, feed consumption and livestock weight have been evaluated individually. Therefore, it was difficult to grasp the breeding condition of livestock.

In the livestock farm management support method according to the present invention, a computer can integrate the amount of feed consumed and the weight of the livestock to determine the quality of the livestock breeding condition. Therefore, the livestock farmer can easily grasp the breeding state of the livestock. Furthermore, since this judgment is made in a timely manner, management can be improved at an early stage.

The computer may hold information about the feed industry. Information about the feed industry may include, for example, feed price information.

This allows the computer to determine when the feed arrives, which is most profitable for the livestock farmer. Specifically, when the feed price is lower than a predetermined value, the computer can determine that the feed is available.

<(4) Estimating the cause of failure>
The livestock farmer management support method according to the present invention may further include a defect cause estimation step of estimating the defect cause of the breeding condition based on the average body weight after the condition determination stage (S2).

This estimation will be described with reference to FIG. FIG. 5 is a flowchart of an example of the livestock farmer management support method according to the present invention. As shown in FIG. 5, in the livestock farmer management support method according to the present invention, after the state determination stage (S2), the defect cause estimation stage (S3) for estimating the defect cause of the breeding condition based on the average body weight is performed. Including further.

The defect cause estimation stage (S3) will be further described with reference to FIG. FIG. 6 is a flowchart of an example of the defect cause estimation stage (S3) according to the present invention. As shown in FIG. 6, in the defect cause estimation stage (S3), the computer first compares the standard body weight with the estimated average body weight (S31). The standard weight calculation method is as described above.

When the standard body weight and the average body weight are significantly different (S31: Yes), the computer estimates the first cause of failure (S32). Examples of the first cause of failure include failure of the feeder, failure of the water dispenser, poor ventilation, and improper control temperature.

On the other hand, when the average body weight and the standard body weight are substantially the same (S31: No), the computer compares the standard feed conversion ratio with the calculated feed conversion ratio (S33). When the standard feed conversion ratio and the feed conversion ratio are significantly different (S33: Yes), the computer estimates the second cause of failure (S34). An example of the cause of this second defect is that the control temperature is inappropriate.

Further, the computer can estimate the cause of the defect by associating the breeding state with the cause of the defect. This will be described with reference to FIG. 7. FIG. 7 is an example of a database used by the defect cause estimation stage according to the present invention.

As shown in FIG. 7, as an example of the breeding state, a decrease in feed consumption (or insufficient than the standard), an increase in feed consumption (or exceeding the standard), a large difference between the average body weight and the standard body weight, and the increase in body weight. There are a decrease, a large fluctuation in feed conversion ratio, a decrease in water supply (or a shortage from the standard), an increase in water supply (or an increase from the standard), and the like.

Examples of causes of failure are diseases of livestock, improper control temperature, poor ventilation (including wind speed), defective equipment such as feeders or water dispensers, deterioration of feed, lack of nutritional value of feed, feeding water supply. (For example, spilled food) and the like.

In this database, the breeding status and the cause of the defect are associated with each other. For example, when the breeding condition is "decrease in feed consumption", the corresponding causes of failure are "disease of livestock", "inappropriate control temperature", "poor ventilation", "deficiency of equipment such as feeder or water dispenser". Is.

The computer can have this database. By referring to this database, the computer can estimate the cause of the defect based on the breeding condition.

As described above, in the livestock farmer management support method according to the present invention, the computer estimates the cause of the defect. Therefore, the livestock farmer can easily remove the cause of the defect. As a result, the management of livestock farmers can be improved.

In addition, it is desirable that the cause of the defect be removed at an early stage. In the livestock farmer management support method according to the present invention, the computer can feed back the cause of the defect to the livestock farmer in a timely manner. Therefore, the livestock farmer can eliminate the cause of the defect at an early stage. As a result, the management of livestock farmers can be improved.

<(5) Status display>
The livestock farmer management support method according to the present invention may further include a state display stage for displaying information on the breeding state of the livestock after the state determination stage (S2).

This display will be described with reference to FIG. FIG. 8 is a flowchart of an example of the livestock farmer management support method according to the present invention. As shown in FIG. 8, the livestock farmer management support method according to the present invention further includes a state display stage (S4) for displaying information on the breeding state of the livestock after the state determination stage (S2).

This state display stage (S4) will be further described with reference to FIG. FIG. 9 is an example of a table displayed in the state display stage (S4) according to the present invention. As shown in FIG. 9, in this example, the lot identification number, the average body weight, the average weight gain, the average feed consumption, the feed conversion ratio, the average water supply, and the number of animals raised are displayed.

The date is displayed in the upper left of FIG. By specifying this date, the livestock farmer can grasp the breeding state of livestock at any time.

The lot identification number is a number for identifying a lot. The average body weight is the average body weight per lot on the specified date. The average weight gain is the difference between the average body weight on the specified date and the average body weight on the previous day in each lot. The average feed consumption is the amount of feed consumed per livestock (or one animal) on the specified date. Feed conversion ratio is the feed conversion ratio on the specified date for each lot. The average water supply is the amount of water supplied per livestock (or one animal) on the specified date in each lot. The number of livestock raised is the number of livestock per lot.

By displaying the breeding status of a plurality of lots in a list in this way, the livestock farmer can easily grasp the breeding status of the plurality of lots.

Further, when the computer determines that the breeding state of the livestock is abnormal in the state determination stage (S2), the item may be highlighted in the state display stage (S4). In the example shown in FIG. 9, for example, a warning mark is displayed in the feed conversion ratio item of lot identification number 01. This indicates that the feed conversion ratio of lot identification number 01 is an abnormal value. When this item is selected by the livestock farmer, the computer may display, for example, the cause of the defect. This defect cause can be estimated in the defect cause estimation stage (S3) described above.

Although not shown, the status display stage (S4) may display historical information regarding the breeding status of livestock. For example, when a predetermined period is specified by the livestock farmer, the computer may display historical information regarding the breeding state of the livestock during that period. For example, a computer may display changes in the average body weight of livestock over time during that period.

By displaying the history information in this way, the livestock farmer can easily grasp the tendency of the breeding state of the livestock.

Further, in the state display stage (S4), the change with time of the average body weight may be displayed in a graph.

This display will be described with reference to FIG. FIG. 10 is an example of a graph displayed in the state display stage (S4) according to the present invention. In FIG. 10, the horizontal axis is the month and day, and the vertical axis is the average body weight. As shown in FIG. 10, changes in average body weight over time are displayed. More specifically, the average body weight increases with the passage of time. Then, when the time for shipping livestock is reached, the average weight is decreasing because livestock are shipped. The livestock shipment time is around June 3 in this example.

Further, if the livestock farmer selects any time point in this graph, detailed information at this time point may be displayed. In this example, the date selected by the livestock farmer, Total Readings, Weight, Growth, Uniformity, and Standard Deviation. ) Is displayed.

As a result, livestock farmers can easily grasp the tendency of livestock to grow. For example, when the average weight gain rate is low, it can be inferred that the livestock farmer is not in good condition. Furthermore, since this display is performed in a timely manner, management can be improved at an early stage.

<(6) Shipment forecast>
The livestock farmer management support method according to the present invention may further include a shipping prediction step of predicting the shipping time of the livestock based on the average weight after the weight estimation step (S1).

This prediction will be described with reference to FIG. FIG. 11 is a flowchart of an example of the livestock farmer management support method according to the present invention. As shown in FIG. 11, the livestock farmer management support method according to the present invention further includes a shipping prediction stage (S5) for predicting the shipping time of the livestock based on the average weight after the weight estimation stage (S1). Includes.

This shipping forecast stage (S5) will be further described with reference to FIG. FIG. 12 is a flowchart of an example of the shipping prediction stage (S5) according to the present invention. As shown in FIG. 12, in the shipping prediction stage (S5), first, a computer creates a regression curve related to the average body weight by using, for example, the least squares method (S51). As shown in FIG. 10, for example, the horizontal axis of this regression curve may be the date and the vertical axis may be the average body weight.

Next, the computer estimates the date at the time of shipment by comparing this regression curve with the average body weight at the time of shipment (S52). For example, when the average body weight at the time of shipment is set to 120 kg, the computer estimates the date when the average body weight becomes about 120 kg.

Conventionally, the timing of shipping livestock has been determined by the livestock farmer by visually observing the livestock. It is very difficult to visually judge the shipping timing. Further, if the weight of the livestock at the time of shipment is too heavy or lighter than the ideal weight, there is a problem that the value of the livestock is lowered.

In the livestock farm management support method according to the present invention, the timing at which the computer ships the livestock can be accurately determined. Therefore, it is possible to prevent a decrease in the value of livestock and contribute to the improvement of the management of livestock farmers.

The computer may also hold information about the livestock market. The information about the livestock market may include, for example, market price information.

This allows the computer to determine the shipping timing at which the livestock farmer is most profitable. Specifically, when the market price is higher than a predetermined value, the computer can determine that it can be shipped.

<(7) Hardware>
The livestock farmer support method according to the present invention can be realized by using a program and hardware. The hardware configuration of the computer used by the livestock farmer support method according to the present invention will be described with reference to FIG. FIG. 13 is a hardware configuration diagram showing an embodiment of a computer used by the livestock farmer support method according to the present invention. As shown in FIG. 13, the computer 1 may include a CPU 101, a ROM 102, a RAM 103, a storage unit 104, a display unit 105, a communication I / F (interface) 106, and an acquisition unit 107 as components. Each component is connected by a bus, for example, as a data transmission line.

The CPU 101 is realized by, for example, a microcomputer and controls each component of the computer 1. The CPU 101 can, for example, read a program that realizes a function such as a state determination stage (S2) and realize the function.

The ROM 102 stores control data such as programs and calculation parameters used by the CPU 101.

The RAM 103 temporarily stores, for example, a program executed by the CPU 101.

The storage unit 104 stores various data. The storage unit 104 functions as, for example, a database that holds information on the breeding state of livestock, information shown in FIG. 7, and the like. The storage unit 104 can be realized by using, for example, a storage device or the like.

The display unit 105 displays information to the livestock farmer. The display unit 105 is realized by, for example, an LCD (Liquid Crystal Display) or an OLED (Organic Light-Emitting Diode). The display unit 105 can realize, for example, a state display stage (S4) under the control of the CPU 101.

The communication I / F 106 has a function of communicating via an information communication network by using communication technology such as Wi-Fi, Bluetooth (registered trademark), LTE (Long Term Evolution) and the like.

The acquisition unit 107 acquires information. The acquisition unit 107 acquires, for example, an image acquired by the image pickup apparatus. The CPU 101 can estimate the weight of livestock based on the acquired image.

Although not shown, the computer 1 may include a position information acquisition unit. The position information acquisition unit has a function of detecting the current position of the computer 1 based on an acquisition signal from the outside. Specifically, the position information acquisition unit is realized by, for example, a GPS (Global Positioning System) positioning unit, receives radio waves from GPS satellites, and detects and detects the position where the position information acquisition unit exists. The position information is output to the CPU 101. Alternatively, the position information acquisition unit may detect the position by transmission / reception with, for example, Wi-Fi (registered trademark), a mobile phone / PHS / smartphone, or short-range communication, in addition to GPS.

Since the computer 1 is provided with the position information acquisition unit, the livestock farmer can grasp the position information of the hut in which the livestock is bred, for example. Therefore, the livestock farmer can grasp the breeding state of a plurality of huts, for example.

The computer 1 is, for example, a smartphone terminal, a tablet terminal, a mobile phone terminal, a PDA (Personal Digital Assistant), a PC (Personal Computer), a server, or a wearable terminal (HMD: Head Mounted Display, glasses-type HMD, clock-type terminal, band-type). It can be a terminal, etc.).

The program for realizing the livestock farmer support method according to the present invention may be stored in another computer device or computer system of the computer 1. In this case, the computer 1 can use the cloud service that provides the function of this program. Examples of this cloud service include SaaS (Software as a Service), IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and the like.

In addition, the program can be stored and supplied to a computer using various types of non-transitory computer readable medium. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-temporary computer-readable media include magnetic recording media (eg flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (eg magneto-optical disks), Compact Disc Read Only Memory (CD-ROM), CD- Includes R, CD-R / W, semiconductor memory (eg, mask ROM, Programmable ROM (PROM), Erasable PROM (EPROM), flash ROM, Random Access Memory (RAM)). The program may also be supplied to the computer by various types of transient computer readable medium. Examples of temporary computer-readable media include electrical, optical, and electromagnetic waves. The temporary computer-readable medium can supply the above program to the computer via a wired communication path such as an electric wire and an optical fiber, or a wireless communication path.

In addition to this, as long as the gist of the present technology is not deviated, the configuration described in the above embodiment can be selected or changed to another configuration as appropriate.

<2. Second Embodiment according to the present invention (livestock farmer management support system)>
The livestock farmer management support system according to the present invention is a system that supports the management of a livestock farmer by using a computer.

The livestock farmer management support system according to the present invention will be described with reference to FIG. FIG. 14 is a conceptual diagram showing an embodiment of the livestock farmer management support system according to the present invention. As shown in FIG. 14, in the livestock farmer management support system 50 according to the present invention, the client terminal 20 which is a computer and the server 40 are connected via the information communication network 30.

The livestock farmer management support system 50 according to the present invention may further include an image pickup device 11. Since the image pickup apparatus 11 has been described in the first embodiment, the description thereof will be omitted again.

The image pickup device 11 and the client terminal 20 are connected. The image pickup device 11 takes an image of livestock and obtains an image. This image is transferred to the client terminal 20. The communication I / F (not shown) included in the client terminal 20 transmits this image to the server 40 via the information communication network 30. The communication I / F (not shown) included in the server 40 receives this image.

The server 40 includes at least a weight estimation unit 41 and a state determination unit 42.

The weight estimation unit 41 estimates the average weight of a plurality of livestock born in a predetermined period. More specifically, the weight estimation unit 41 analyzes the received image to estimate the weight of the livestock. Since this analysis method has been described in the first embodiment, the description will be omitted again.

The state determination unit 42 determines the quality of the breeding state of the livestock based on the average body weight. Since this determination method has been described in the first embodiment, the description will be omitted again.

The determination result by the state determination unit 42 is transmitted from the server 40 to the client terminal 20 via the information communication network 30. The display unit (not shown) included in the client terminal 20 displays this determination result.

The livestock farmer management support system according to the present invention may further include an automatic feeding device 12, an automatic water supply device 13, and an air conditioning control device 14. These are connected to, for example, the client terminal 20.

The automatic feeding device 12 can automatically control the feed supply amount based on, for example, the determination result of the state determination unit 42. For example, when the standard body weight and the average body weight are significantly different, the state determination unit 42 sets an appropriate feed supply amount. Information about this supply amount is transmitted to the automatic feeding device 12. Based on this information, the automatic feeder 12 can supply an appropriate amount of feed.

The automatic water supply device 13 can automatically control the amount of water supply based on the determination result of the state determination unit 42. For example, when the standard body weight and the average body weight are significantly different, the state determination unit 42 sets an appropriate amount of water supply. Information regarding the amount of water supplied is transmitted to the automatic water supply device 13. Based on this information, the automatic water supply device 13 can supply an appropriate amount of feed.

The air conditioning control device 14 can automatically control the control temperature based on the determination result of the state determination unit 42. For example, when the standard feed conversion ratio and the feed conversion ratio are significantly different, the air conditioning controller 14 can adjust the control temperature.

The number of servers 40 may be one or a plurality. Similarly, the number of client terminals 20 may be one or a plurality. Further, all the servers 40 may not be connected to the information communication network 30, and all client terminals 20 may not be connected to the information communication network 30.

The client terminal 20 can be provided with some or all of the functions of the server 40. For example, the client terminal 20 may include a weight estimation unit 41.

The function of the weight estimation unit 41 or the state determination unit 42 may be stored in another computer device or computer system in the livestock farm management support system. In this case, the client terminal 20 and the server 40 can use the cloud service that provides this function. Examples of this cloud service include SaaS (Software as a Service), SaaS (Infrastructure as a Service), PaaS (Platform as a Service), and the like.

The information communication network 30 is, for example, a wired network such as a LAN (Local Area Network) or WAN (Wide Area Network), a wireless LAN (WLAN: Wireless Local Area Network), or a wireless WAN (WWAN: Wireless Wide Area) via a base station. It can be realized by a wireless network such as Network) or the Internet using a communication protocol such as TCP / IP (Transmission Control Protocol / Internet Protocol).

The weight estimation unit 41 or the state determination unit 42 can be realized by using a program and hardware. The hardware configuration of the client terminal 20 and the server 40 may be the hardware configuration of the computer 1 shown in FIG. Therefore, a detailed description of the hardware configuration of the client terminal 20 and the server 40 will be omitted.

In addition to this, as long as the gist of the present invention is not deviated, the configuration described in the above embodiment can be selected or changed to another configuration as appropriate. The livestock farmer management support system can utilize the technique described in the first embodiment. The technique described in the first embodiment will not be described again.

It should be noted that the effects described in the present specification are merely examples and are not limited, and other effects may be obtained.

The present invention may also have the following configuration.
[1]
It ’s a way to support the management of livestock farmers.
A weight estimation stage that estimates the average weight of multiple livestock born in a given period, and
A state determination step for determining the quality of the breeding state of the livestock based on the average body weight and a predetermined threshold value is included.
Livestock farm management support method.
[2]
The weight estimation stage
At the acquisition stage where the livestock is imaged and an image is obtained,
Includes an analysis step of analyzing the image to estimate the weight of the livestock.
The livestock farmer support method described in [1].
[3]
The state determination stage is
The stage of obtaining the feed conversion ratio by dividing the feed consumption by the weight gain of the average weight of the livestock.
A step of determining the quality of the breeding state of the livestock based on the feed conversion ratio and a predetermined threshold value is included.
The livestock farmer support method according to [1] or [2].
[4]
After the state determination step, a defect cause estimation step for estimating the defect cause of the breeding state based on the average body weight is further included.
The livestock farmer support method according to any one of [1] to [3].
[5]
After the state determination step, a state display step for displaying the breeding state of the livestock is further included.
The livestock farmer support method according to any one of [1] to [4].
[6]
The state display stage displays a change in the average body weight over time.
The livestock farmer support method described in [5].
[7]
After the weight estimation stage, a shipping prediction stage for predicting the shipping time of the livestock based on the average weight is further included.
The livestock farmer support method according to any one of [1] to [6].
[8]
The livestock is a fattening pig,
The livestock farmer support method according to any one of [1] to [7].
[9]
A system that supports the management of livestock farmers
A weight estimater that estimates the average weight of multiple livestock born during a given period,
A state determination unit for determining the quality of the breeding state of the livestock based on the average body weight is provided.
Livestock farm management support system.

S1 Weight estimation stage S2 Status determination stage S3 Defect cause estimation stage S4 Status display stage S5 Shipment prediction stage 11 Imaging device 12 Automatic feeding device 13 Automatic water supply device 14 Air conditioning control device 20 Client terminal 30 Information and communication network 40 Server 41 Weight estimation unit 42 Status judgment unit 50 Livestock farm management support system 101 CPU
102 ROM
103 RAM
104 Storage unit 105 Display unit 106 Communication I / F
107 Acquisition section

Claims (9)

It ’s a way to support the management of livestock farmers.
A weight estimation stage that estimates the average weight of multiple livestock born in a given period, and
A livestock farmer management support method including a state determination step of determining the quality of the breeding state of the livestock based on the average weight and a predetermined threshold value. The weight estimation stage
At the acquisition stage where the livestock is imaged and an image is obtained,
Includes an analysis step of analyzing the image to estimate the weight of the livestock.
The livestock farmer management support method according to claim 1. The state determination stage is
The stage of obtaining the feed conversion ratio by dividing the feed consumption by the weight gain of the average weight of the livestock.
A step of determining the quality of the breeding state of the livestock based on the feed conversion ratio and a predetermined threshold value is included.
The livestock farmer management support method according to claim 1 or 2. After the state determination step, a defect cause estimation step for estimating the defect cause of the breeding state based on the average body weight is further included.
The livestock farmer management support method according to any one of claims 1 to 3. After the state determination step, a state display step for displaying the breeding state of the livestock is further included.
The livestock farmer management support method according to any one of claims 1 to 4. The state display stage displays a change in the average body weight over time.
The livestock farmer management support method according to claim 5. After the weight estimation stage, a shipping prediction stage for predicting the shipping time of the livestock based on the average weight is further included.
The livestock farmer management support method according to any one of claims 1 to 6. The livestock is a fattening pig,
The livestock farmer management support method according to any one of claims 1 to 7. A system that supports the management of livestock farmers
A weight estimater that estimates the average weight of multiple livestock born during a given period,
A livestock farmer management support system including a state determination unit for determining the quality of the breeding state of the livestock based on the average body weight.

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