JP2023144790A - Grain drying/preparing machine facility - Google Patents

Abstract

To provide a method of using data and making an evaluation in a grain drying/preparing machine facility in which cargo grain can be automatically sorted and data on machines including a drying tank to an unpolished rice tank can be automatically associated.SOLUTION: A method includes automatically creating a container for housing grain and a vehicle number from a charging time image and an identification number of the grain from a clock time of the charging, extracting data on each machine in time series, automatically recording the data for the identification number of grain, and comparing the recorded data with pre-recorded work step data. Accordingly, the value of the grain can be calculated at an early stage. In addition, the obtained data is stored in a server, external data is added thereto, and the data is shared so that a drying/preparing system having high accuracy can be formed.SELECTED DRAWING: Figure 1

Description

The present invention relates to data utilization and evaluation methods for grain drying and preparation facilities.

Even if data is automatically acquired from the dryer, huller, color sorter, taste meter (registered trademark), and discharge into the brown rice tank at a grain drying and preparation facility, there is no relationship with the received grain. Since the information is entered manually, it may not be possible to manage the data adequately. The background to this problem is that it is not possible to automatically identify the received grain, that the data formats of drying and processing machines differ between various manufacturers, and that data is not compatible with old and new machines even from the same manufacturer. This is cited as a factor.

JP2019-87274

In the above-mentioned conventional technology, there is a description to check whether the name of the producer, ID code, consignment number, and weight of sample paddy match when receiving the consignment, but there is no description of how to input the data. Not yet. In the present invention, these identifications are automatically determined based on the registered data of the container number for identifying the received grain and the transport vehicle number, and the video data at the time of receiving the cargo, and the time of receiving the cargo is simultaneously registered. Automatically identifies the recipient.

In addition, although the data of each drying preparation machine often has no commonality, by reading the data logs emitted from each controller and registering them in chronological order, it is possible to read these data logs when an abnormality occurs. By being able to do so, it is possible to assist in responding. In addition, for data that can be converted as common data, the objective is to evaluate it against a standard value by comparing it with pre-registered work process data.

The invention of claim 1 is solved by the following technical means.

An imaging means installed in the receiving part of the dryer reads the container number provided on the container containing the received grain, and creates a receiving number by combining the container number and the time when the container is received. , Drying operation data by the dryer and preparation operation data of the preparation machine after drying in the dryer are additionally registered in chronological order to form a management data group, and the management data group is used to determine the data for each container. Manage grain data.

The invention of claim 2 is solved by the following technical means.

Regarding drying operation data and preparation operation data, standard work process data 36A is stored in a database in advance, and the management data group and work process data 36A are compared and verified to calculate the value of the received grain.

The invention of claim 3 is solved by the following technical means.

It is characterized by converting drying operation data and preparation operation data into common information processing data, and registering the data in chronological order in the consignment number to generate a management data group.

The invention of claim 4 is solved by the following technical means.

The data log output from the dryer controller as drying operation data and the data log output from the preparation machine controller as preparation operation data are read using data log reading software, and drying operation is performed in the same data log format. The data and preparation operation data are additionally registered in the consignment number to generate a management data group.

The invention of claim 5 is solved by the following technical means.

An authentication system for registration of management data groups is placed on both the cloud server 121, which is an external server on the Internet, and the general terminal 36 of the drying and preparation facility, and the authentication system for user terminals 103, 104, 105 and regular data of the drying and preparation facility is installed. Transmissions 108 and 109 are performed by the central terminal 36, and when registering the newly acquired shared data for each time series in the receiving number on an external server, the authentication system 122 of the external server is activated and the data is authenticated. A request data transmission 107 is sent from the central terminal 36 to the user terminal, and at the same time, an external server is accessed at 150 and 144, and the shared data request is transmitted to other terminals as well, and information is shared at 145 and 146.

According to the invention of claim 1, it is possible to automatically identify the received grain, and the data of each machine from drying to the brown rice tank can be automatically correlated.

In the invention of claim 2, by comparing with standard work data, the quality of the received grain can be clearly determined, and the value of the grain can be estimated at an early stage.

According to the inventions of claims 3 and 4, it becomes possible to store and analyze data across manufacturers and between new and old models. Even for items whose data formats are not standardized, data logs are output in chronological order from that machine, and by extracting and storing these data logs, if a problem occurs later, this stored data can be used for each machine. It is also possible to clarify the cause of the malfunction by requesting an analysis from a machine manufacturer, etc.

According to the invention of claim 5, the data is revised by adding the latest data, and it becomes possible to maintain the basic data for the next year in a more appropriate state.

Schematic diagram of a drying preparation facility in an embodiment of the present invention Data communication diagram between user's mobile device, cloud server, and WAGRI Authentication flow and data communication diagram for cloud server and control terminal Receipt number creation diagram Distribution diagram of green rice on the sorting board of the huller Data layout diagram for registering data compatible with open API in the receiving number Data layout diagram for registering data that is not compatible with open API in the receiving number Examples of usage of work process data 36A Schematic diagram of receiving cargo in a drying and preparation facility according to an embodiment of the present invention

The present invention will be described below based on embodiments shown in the drawings.

The drying and preparation facility shown in Figure 1 is equipped with a grain circulation dryer 1 (hereinafter referred to as the dryer) and a huller 2, and performs grain receiving, drying, hulling, sorting, rice milling, etc. The dryer 1 is equipped with a tank 1A for storing grains in the upper part, a drying chamber 1B in the lower part, a combustion part 1C on one side of the drying chamber, a blower fan 1D on the opposite side through the drying chamber, and the grains are stored in the drying chamber. In order to circulate the water within the tank, transport devices are provided above and below, and these are connected by an elevator 1E. The elevator is equipped with an automatic moisture meter on the 1st floor, which regularly measures the moisture content of circulating grains.

The huller 2 dehulls the chaff from dried rice using the difference in rotation of rotating rubber rolls or impact using centrifugal force, and separates brown rice and chaff by the movement and wind selection of a sorting plate 2A equipped with many special holes. Select.

Below is a brief explanation of the equipment to be installed at the drying and preparation facility.

Paddy tank 3 temporarily stores dried paddy and enables continuous hulling work
A sorting machine 4 that passes the brown rice through a sorting net to sort out grains, immature grains, etc. according to grain size.

A color sorter 5 separates the colors of the sorted brown rice and removes foreign substances.

A grain taste meter (registered trademark) 6 that evaluates the taste of brown rice using optical spectroscopy.

Brown rice tank 7 temporarily stores selected brown rice.

A rice polishing machine 8 that separates the surface bran from brown rice to produce white rice.

A conveying device 9, a bagging machine 10, and a weighing device 11 connect each machine.

Offline controller 21 that communicates data from the dryer controller
Offline controller 22 that communicates data with the controller of the huller
Offline controller 23 that communicates data from the color sorter and taste meter (registered trademark)
Offline controller 24 that communicates data from the rice milling machine controller
Intermediate terminals that receive data from each offline controller include an intermediate terminal 31 for a dryer, an intermediate terminal 32 for a huller, an intermediate terminal 33 for a rice mill, and an intermediate terminal for data from mobile machines such as tractors. There is a terminal 34.

It also includes a general terminal 36 that manages and stores the data of these intermediate terminals and transmits and receives data to and from an external data management device 35, and a communication device 38 that wirelessly communicates with a user's mobile terminal 37. This refers to the mutual data management and system configuration of each piece of equipment in a drying facility that has some or all of these pieces of equipment.

Furthermore, as shown in FIG. 4, when grains are transported to a drying and preparation facility, the number is automatically determined from the images of the container 41 that stores the grains 40, the container number 42 that identifies the receiver, and the vehicle number 44 of the delivery vehicle 43. A receipt number 47 is created by combining the data 45 from the device with the time 46 of receipt. To this receiving number 47, the data of the drying operation of the dryer, the preparation operation data of the preparation machine after drying with the dryer, in the present invention, a huller, a sorter, a color sorter, a taste meter (registered trademark), This applies to rice milling machines, and the drying method is characterized in that the acquired data is additionally registered in chronological order to form a management data group, and the grain data for each container is managed using the management data group. It is a preparation system.

The automatic creation of numbers for identifying received grains according to the present invention will be explained.

If you have registered an image of the container 41 loaded on the loading vehicle 43 or an image of the flexible conveyor loaded on the loading vehicle 43, and if an object similar to this image is confirmed, the receiving number search system in the control terminal 36 will Operate. The user is guided to the selected dryer 1 using the audio device in the facility. A camera 1G provided in the dryer elevator 1E reads the container number 42 and the transport vehicle number 45. The system also creates a receiving number 47 by combining the time 46 of receiving the cargo, and registers subsequent drying preparation data in the automatically generated receiving number 47 in chronological order.

In the example of number creation, if the container number is 111, the vehicle number is 1212, and the receiving time is 13:00 on September 1, 2021 (202109011300), 1111212202109011300 is automatically created.

The container number 42 is individually attached to the container 41 and the flexible receiving container, and can also be identified using an image number recognition system or a QR code (registered trademark). In addition, the vehicle number 45 of the conveyance vehicle 43 has a user name registered in advance, and when recognizing the number, the user name is verified, and if there is no mistake in receiving the consignment or there is a change to the registered data, the user name can be changed. We have a system in place to accept data. Manual input is required when changing such data, and in cases where automatic recognition is not possible, search for your name from the control terminal 36 and read out the pre-registered work process data 36A to check it. It is also possible to manually create the receiving number 47. Further, the container number 42 may be a user number, and a device may be used in which the card number is read by a card reader.

The utilization of the registered work process data 36 of the present invention will be explained.

In the general terminal 36 of the drying and preparation facility, the receiving number 47 and user information are stored in the work process data 36A, and past work data is registered in this work process data 36A. By comparing the results with the previous year, it is possible to analyze the difference and to analyze the current year's grain condition at an early stage.

FIG. 8 explains an example of the use of the work process data 36A. The basic work flow of the past work process of consignment number 47, dryer number selection and settings, whether to mix or separate rice during hulling, whether to mill rice, etc. are registered. If you select it automatically, the work will be done using this route. However, if the quality of the grain is not good, the price may be better if it is shipped early using commercial rice, etc. In this case, the quality of the grain was rather poor, and the explanation was given by changing the work process from shipping individual brown rice. are doing. For example, if the initial moisture content at the time of loading last year was 20%, but this year it is 25% and the receiving time is the same, then the high moisture content will be added to the fuel cost for drying and the green rice will be added to the drying cost. It is possible to immediately infer that there is a possibility that there is a large number of cases, and to set the quality judgment to the lower side. Based on this early determination, the shipping format is changed to before the hulling operation. By registering the work style in the work process data 36A in this way, it is possible to perform the work in the best possible flow from receiving the goods to packing the brown rice into bags and polishing the rice. In particular, if the process is to match basic data such as drying speed, finished moisture content, containers that can be mixed, grain size and degree of husking, and discrimination using a taste meter (registered trademark), it is possible to perform the work unattended. Become.

Utilization of imaging data according to the present invention will be explained.

Once the cargo has been confirmed, safety sensors etc. will be checked and the system will automatically begin staking operation. A camera 1G photographs the state of grain being loaded into a loading hopper of a dryer. It has the function of continuously photographing the condition of grain during loading and estimating the amount of green rice by distinguishing the images. The amount of green rice in past video data is registered in the work process data 36A, and by comparing with this video, it is possible to compare with past grain data. It is also possible to estimate the grain unit price.

The camera 1G can also confirm that the vehicle has left, and can also be set to automatically enter ventilation mode after a predetermined period of time has elapsed. Note that in a dryer that has automatically entered ventilation operation, when a vehicle is detected again by camera IG, ventilation operation is stopped and the ventilation operation is changed to tension operation.

Weight measurement will be performed for each container. Each dryer is equipped with a weight measuring device 1H, which makes it possible to calculate the additional weight each time loading is completed, and registers the weight of each load in chronological order. The camera IG calculates the estimated filling amount based on the container size and filling condition, and compares it with the weight measured by the dryer weighing scale, thereby making it possible to prevent troubles when receiving cargo.

If the camera 1G has a function to confirm the user's face, it is also possible to have a function to collate data using face recognition. The user's face is registered in advance, and if the user can be verified, it is possible to manually stop the dryer or start drying. In automatic operation, everything except the filling amount is set using registered data. The filling amount setting which determines the drying temperature is set by automatic measurement using the weight measuring device 1H, but if it is unclear, start with the medium amount setting and perform correction control based on the drying speed.

The camera 1G of the dryer elevator 1E periodically takes images during drying and automatically registers them to the receiving number 47, thereby preventing equipment trouble and theft during unmanned operation. Camera 2B takes pictures of the spread of brown rice on the sorting plate of the huller, and in addition to controlling the tilt of the sorting plate, it is also used as data to judge the content of green rice and estimate the quality of the grain. The system automatically registers video data and the estimated content of green rice from the video to consignment number 47.

The drying data transfer and management system of the present invention will be explained.

An offline controller 21 is set for each dryer, and a plurality of dryers are assigned respective offline controller numbers. UUID (Universally Unique Identifier) numbers are used to take into account data management across regions and manufacturers that may differ.

For example, a unique number is created by combining the manufacturer's number, model number, serial number, and offline controller number. This model number setting is based on the same concept and is assigned to machines other than dryers, such as hullers, sorters, brown rice tanks, color sorters, and taste meters (registered trademark). This is a unique number for data utilization (programming interface), so it will not be duplicated in model data, etc.

The data of the off-line controller 21 of the dryer is collected in the intermediate terminal 31 via Bluetooth. The intermediate terminal is a system that automatically distributes dryer data to the mobile terminal 37 periodically, when an abnormality occurs, and when drying starts and ends. The content of distribution etc. has a function that can be selected depending on the terminal, and it is also possible to distribute video data from cameras installed in the facility and on each machine. The intermediate terminal 31 is connected to the central terminal 36 by wire or wirelessly such as Wi-Hi, and can also check data from other intermediate terminals 32, 33, and 34. By adopting the same communication form as the intermediate terminal 31 in the intermediate terminals 32, 33, and 34, it is possible to perform comparative analysis with the work process data 36A registered in advance using the central terminal 36.

In addition, safety management during drying is based on safety sensors on each machine. In the case of an abnormality in an individual machine, data is distributed from the intermediate terminals 32, 33, and 34 to the mobile terminal 37, but in the case of an abnormality in the power supply or an abnormality related to the entire facility, data is distributed to the mobile terminal 37 via the central terminal 36. There is also. One example is a facility that has a device that measures the air pressure difference within the facility, and if the pressure inside the facility is reduced beyond a predetermined value, it is determined that there is a lack of air throughout the facility, and the dryer is sequentially dried using a dryer with low moisture content. Stop. It has functions such as stopping the dryer in sequence and canceling the dryer's stoppage when the standard value is exceeded, and it automatically takes measures to deal with clogged ventilation holes, etc. By immediately distributing information to users, it is possible to respond in the event of an abnormality.

When the dryer reaches the set moisture level, the dryer automatically stops. It has a function of determining the discharge destination based on pre-registered work process data 36A, checking with a sensor that no grains are in the discharge destination, and automatically discharging the grain after completion of drying.

The content of analyzing the management data group of the consignment number 47 and the work process data 36A of the present invention will be explained.

In the drying and preparation system, in the drying, hulling, sorting, and rice milling processes, data is created using the pre-registered work process data 36A and the container number 42, vehicle number 45, and receiving time 46 of the container brought in by the user or the flexible conveyor. It has a function to collate the received consignment number 47 with the work process data 36A and automatically select the work process for the current consignment.

In the automatic control of dryer loading, in order to mix multiple containers in one dryer, it is necessary to manage the order in which containers are automatically combined with other containers. If the pre-registered work process data 36A specifies that the same dryer will be used to receive the same container number 42 and vehicle number 45, the audio device in the facility will be set to receive the same container number 42 and vehicle number 45 in the same dryer. Guidance takes place. In addition, for items that can be mixed and dried using the empty tank of one of the dryers, by registering the received weight and moisture content in the receiving number 47, it is possible to automatically control the mixed drying. do.

When the drying is nearing completion and the completion times of multiple dryers are estimated, the order of loading into the huller 2 and the hulling tank 3 is also determined in the order registered in the work process data 36A. Do it with In the work process data 36A, it is determined which cargo to be worked on with priority, and in the actual work flow, even if it is estimated that the drying will be completed later, the work process data 36A is emphasized and the cargo is removed from the dryer according to that process. This is to discharge paddy. However, it is also possible to give priority to the actual work, and if the setting is to change the drying finish order, automatic control is performed so that the drying is finished in the order in which it is discharged. In many cases, there are a plurality of dryers 1 and fewer hullers 2 than the number of dryers 1, and by automating this order, unmanned operation and labor saving can be achieved.

Furthermore, it is also possible to automatically create a group set of rice grains that do not cause any problems even if they are mixed after drying, and to determine the ranking of the rice grains to be sent to the huller 2 in the order in which the rice grains are finished. If the group set is automatically created, and a large group is formed, hulling work can be done at night, and automatic control can be used to change the process from paddy tank 3 to hulling machine 2 and sorting machine 4 to brown rice tank 7. Also possible. In addition, when grouping small batches, the priority of the registered work process data 36A is determined based on work efficiency, such as automatically deciding whether to postpone discharging to the brown rice tank and selecting bag filling process during the day. It is also possible to implement control that incorporates an artificial intelligence function that automatically makes selections.

The work process for the entire facility is distributed by e-mail from the general terminal 36 to the mobile terminal 37, and it also has the function of starting operations after obtaining user approval. In particular, if the pre-registered work process data 36A has a low priority, it is possible to prevent problems with automatic driving by preventing automatic work from occurring without user approval. be. This function allows the user to return to the facility at the same time as the brown rice bagging process, and the estimated time of completion of each drying process and discharge, as well as the working status of the huller, can be transmitted and user approval can be obtained externally. This can save labor.

In this way, by automatically performing the data analysis of the management data group and the work process 36A, it is possible to optimize the work and save labor.

Data transmission system for the huller to a mobile terminal The technology of the system for transmitting drying data in the dryer to a mobile terminal is widely known, but the huller 2 also has a sorter 3 connected after the huller. In this case, it is an offline controller installed in the huller 2 that takes in the data from the sorting machine 3 and has a function of transmitting it to the intermediate terminal 32 using Bluetooth. Information on the huller/sorter is sent from the intermediate terminal 32 to the mobile terminal 37 via email periodically, at the start or end of work, or in an emergency. Further, the intermediate terminal 32 is in mutual communication with the general terminal 36, and data on hulling and sorting are transferred to the general terminal 36 and registered. Typical data include the following:
・Send the initial voltage measurement value, the start and end time of hulling, efficiency at each specified time, cumulative throughput, sorting plate angle, wind selection air volume settings, and error information Data of these hulling machines The data is registered in the receiving number 47.

As for data utilization, by checking the efficiency at predetermined intervals, adjustments to the supply amount of the huller can be made remotely. The error information is such that it is possible to select whether or not to send data for each error content, and in the case of a highly urgent error, the information is immediately sent to the mobile terminal 37. The sorting machine 4 and the rice tank 3 are information-linked with the huller 2, and can be configured either wired or wirelessly, and are taken in as data for the huller. The sorting machine 4 is positioned as a measuring instrument for the hulling machine 2, and the efficiency of the sorting machine is registered as the performance of the hulling machine. The amount of immature rice is also measured by weight, and the weight ratio with the grain size is used as hulling data.

Grain quality evaluation using the amount of green rice in the huller of the present invention will be explained.

As shown in FIG. 5, there is also a method of installing a camera 2B to check the state of the sorting plate 2A of the huller and sensing the range of green rice on the sorting plate 2A. Estimating the green rice content from the range of green rice. Since the above-mentioned amount of immature rice has a correlation with the content of green rice, in a configuration where the weight of immature rice is not measured, it is possible to calculate the estimated amount of immature rice from this video data. By comparing this amount of green rice with past data in the work process data 36A, the grain unit price is estimated from the relationship between the past amount of green rice and the unit price of grain. This makes it possible to estimate grain quality at the stage of hulling, making it possible to perform evaluations as shown in FIG.

In addition, in large facilities, multiple hullers may be installed, and in many cases, the hulling operation determines the flow of the drying and preparation system. There is also an automatic control method that changes the order. In one example, there are multiple recipients of rice, and normally separate hullers are used to handle the drying in the order in which they are completed, but if shipping for a specific user is urgent, multiple hullers are used to handle the drying. It is also possible to change the process of distributing and hulling the grain received by the user.

If a system is provided that checks the presence or absence of paddy in the paddy tank 3 using a sensor and sends the information from the off-line controller 22 of the huller to the intermediate terminal 32 of the huller, the paddy can be automatically discharged after drying, and the paddy can be removed automatically after drying. Since the receiving number 47 on the tank is clear, there is no problem with mixing, and if there is a process change, it can be easily changed automatically from the general terminal 36.

This section explains how to score the efficiency of rice hulling.

The efficiency of rice hulling is converted into data as an indicator of quality. This is a mechanism to determine how high the current efficiency is relative to the basic efficiency of each machine. For example, if the basic efficiency of the machine is 40 bales/hour, if the actual efficiency of hulling is 44 bales/hour, the performance will increase by 10%. As an indicator, we have set standards such as -15% or less is poor, -15 to 10% is slightly poor, -9 to +4 is standard, +5 to 7% is somewhat good, and 8% or more is good. It is judged to be good. At the same time, the fact that the paddy is easy to rub means that the moisture difference is small, there is little slippage on the surface of the grain, and there is less immature rice, which means that the quality is good.

These evaluations also require correction. When it comes to hulling machines, there are differences in the ease and difficulty of rolling depending on the variety. In terms of data analysis, there is also a method of setting standards based on variety and evaluating the efficiency by multiplying the actual performance by a correction factor based on the variety. A correction rate is set, such as 98% for types that are easy to print, and 102% for types that are difficult to print.

Another method is to set regional standards and evaluate efficiency by multiplying actual performance by a correction factor. This is due to differences in water temperature and soil, and should be corrected as an indicator other than the variety.

Another method is to set a standard based on the cutting time and evaluate efficiency by multiplying the actual performance by a correction factor. Early rice has a large moisture difference, and efficiency often does not improve, so the correction factor should be higher for rice that is harvested early.

There is a method of evaluating grain by setting a grain temperature standard for paddy and multiplying the actual performance by a correction factor based on this grain temperature. If the grain temperature is high, the surface will be soft and the possibility of skin chafing will increase. Therefore, there may be cases where work is performed at a reduced efficiency, and corrections are made based on the lower efficiency.

For grain evaluation, if the above-mentioned hulling efficiency score is added to the brown rice Tastemeter (registered trademark) evaluation score, the evaluation will be more informative.

We will explain how to score green rice.

In the dryer 1, the moisture content is continuously measured using a moisture meter 1F during loading to detect variations in moisture content. There is a standard moisture deviation, and rice with an upper deviation above a predetermined value is treated as green rice. This is an evaluation method that evaluates the green rice content by weighting both the green rice evaluation by the moisture meter 1F and the green rice evaluation by the image of the container. There are ``those with fruit but high moisture content'' and ``those without fruit and high moisture''. If the amount of green rice in the container image is large and the amount of green rice is low in the moisture value of the dryer, it is judged that there are many immature grains, and the evaluation score is lowered. On the other hand, if the amount of green rice in the container image is large and the amount of green rice in the moisture value of the dryer is high, it is assumed that there is a large amount of green rice with fruit, and the evaluation score should not be significantly lowered.

The following describes how to convert data into common information processing data according to the present invention.

Conversion into data for common information processing refers to data supported by an open API (Application Programming Interface).

When it comes to facility-related equipment, there are machines from different companies, and even if they are from the same manufacturer, the data formats and data arrays emitted from the controllers are different depending on the model and production period, and it is difficult to convert data using the same reading software. It is difficult. Under these circumstances, we will explain how to process open API data that is supported as common data and data that is not supported.

The data published as common data is a CSV data file with clear data items and arrangement, as shown in FIG. Therefore, at the intermediate terminal 31 or the central terminal 36, specific data is cut out from the CSV file using dedicated software, and the data is automatically formed by item or arrangement using the dedicated software. Also, depending on the machine, there is dedicated reading software for that machine, and there are some that output CSV data using this, so it is also possible to cut out predetermined data from this data and format it using dedicated software.

These data are unilaterally output from each machine, and are not processed in a two-way manner. This is what is called "flowing data". Therefore, a system is required as dedicated software on the receiving side that captures data each time it is transmitted, formats the data, stamps the time, and registers it.

As this stamp, the time is automatically stamped in the data of the receiving number 47, and the user has a function to add and register text data. Generally, a CVS data file is formed using special software after data acquisition is completed, but the work process at the facility requires a long cycle time, and it is necessary to analyze data from multiple machines side by side. This requires the user to write into the acquired data in real time. As a stamp function, there is also a method such as providing two types of files, a read file and a registered file, and existing technology will be used to process the electronic data. Furthermore, it is easy to register several types of text data as stamps in advance and to select and stamp them. Examples include stamps such as "Good", "Grain problem", "Mechanical problem", "Data confirmation required", "Work is running late", etc. If there is no stamp response from the user within a predetermined time, the time of the acquired data is only automatically stamped. In addition to CSV data, there is also video data from cameras installed in dryers and hullers, and the stamp function also has a function to simultaneously register video data related to the acquisition time in association. There is. By registering open API information in the receipt number 47 for any data, the system allows data processing across manufacturers and data management at the central terminal 36.

Processing of data that has not been converted into common information processing data according to the present invention will be described.

There are two main types of APIs that have not been converted into so-called open APIs. There are items, such as item A in FIG. 7, which have been output as CSV files, but whose data items and data order are unknown, and items, such as item B, which can only be retrieved using a data log. Both are difficult to mold using specialized software. However, this data can be deciphered by each machine manufacturer. Therefore, as a safety measure, even though the contents of the data are unknown, the data corresponding to the time is obtained, the time is automatically stamped, and the data is registered. In this way, if a problem occurs later, it will be possible to investigate the problem by having the manufacturer decode the relevant CSV data or data log. By registering any data or information that is not converted into an open API in the consignment number 47 in its data format, there is an advantage in that the data can be managed on the central terminal 36 and searched easily when the data needs to be verified. .

This function can be used not only for data management in drying and preparation facilities, but also as a data processing method for mobile devices such as tractors, rice transplanters, combines, and management machines. This is handled by extracting data from the intermediate terminal 34 of the mobile device. However, if the models are different, it is even more difficult to unify the data. In such a case, it will be effective later that data that has not been made into an open API can also be imported according to the content of the present invention, and that it can be searched in association with the receipt number 47. The system allows you to search for machine data from the grain that becomes the final product, so if the grain is of poor quality, you can search for all related machine data and perform operations such as tilling, puddling, raising seedlings, planting, fertilizing, disinfection, reaping, etc. Analysis can be made from mechanical data such as drying and hulling. Many farming groups often manage other machinery and data at their drying facilities, so it is possible to handle this as part of the data management of the drying facilities.

Agricultural management at drying and preparation facilities will be explained.

In various types of agricultural machinery that have a controller and have the above-mentioned function of recording the operation of the machinery as a data log, a system for reading out the data log using the agricultural management software 36B and registering it in chronological order will be described. With this function, various agricultural machinery can be managed using the drying and preparation facility. Agricultural machinery comes from different manufacturers and old and new models, making common management of data difficult. However, by keeping data logs for each machine, it can be a good foothold to solve problems when they occur. It is possible to manage it at the facility. This makes it possible to investigate problems for the next year by determining the quality of the grain that will become the final product.

A fixed drying facility is in an environment where it is easy to check the distance to the field. Each mobile device is equipped with GPS, etc., making it easy to confirm location information. However, individual mobile devices cannot analyze or manage much data, including those of other mobile devices. Therefore, by distributing the necessary data from the centrally located drying and preparation facility, it is possible to promote rationalization of work. In the farming management software 36B, data is accumulated in a system that allows each user to manage product information. "Rice planting time and field location", "Last year's disinfection time and field location", "reaping time and field location", "dry period and field location", etc. will be aligned with this year's month and date, and the implementation period will be adjusted. By confirming that there are no delays, etc., and transmitting these to the mobile terminal 37, it is possible to respond to the omission of work by workers and to grain producers.

By using information from the agricultural data collaboration platform "WAGRI" and artificial intelligence, it is possible to calculate how to rebuild plans, including drying preparation, in the event that earlier processes such as rice planting are delayed, and subsequent processes are delayed. It also becomes possible to assume risks, etc. For example, if data analysis shows that the weather and other conditions are the same as in previous years, if the rice planting time is delayed and the reaping time needs to be the same as in previous years, if past users By accumulating evaluation information for each crop, AI can estimate the yield.
・The paddy will be brought in with high moisture content, and how much will the cost of kerosene for drying increase?
- Estimate the increase in the amount of green rice, what will be the hulling yield, and how much will be the annual loss?
・What is the taste value?
It is also possible to calculate information such as the following and provide an estimated evaluation.

The amount to be paid to the user can be calculated based on the standard amount calculated, and farm management can be managed by calculating the estimated amount to be paid to the user at an early stage based on annual data. .

The development of field data evaluation will be explained.

The registered consignment number 47 is linked to the work process data 36 and is also managed as field data. In the field data, the production amount of agricultural products and related production material data such as "seedlings", "fertilization amount", "disinfection cost", "labor cost", "transportation cost", "fuel cost" are linked. . From these, it is possible to calculate the production cost per person, and calculate the profit made by each person and the profit made by each field.

Separately, it also calculates the profit earned by each user. It is possible to calculate profits for producers, facility managers, and fields. By comparing these calculated data with manufacturer's management data, etc., we will be able to confirm differences with the national level and build a data management system that will allow data managers to submit appropriate indicators.

When managing profit data for each field, it is also possible to calculate and report whether it is due to defective grain, poor conditions such as weather, poor management by humans, or poor efficiency of agricultural machinery. Eliminate uncontrollable items such as bad weather and grain defects, select items that can be improved by people or machines, and display the data as improvement plans.

Multiple arrangements for dry preparation will be explained with reference to FIG.

The dryers described above have a video camera and a function to measure weight, and if all dryers were equipped with this, it would be an expensive piece of equipment. For this reason, we will explain a case where the dryer is installed as an inexpensive equipment in a system where each function is arranged.

The dryer is equipped with a camera 1G and a weighing scale 1H as a primary dryer, and is mainly used for receiving goods. The secondary dryer is a so-called semi-drying dryer that dries to an intermediate moisture content. The tertiary dryer is a dryer for main drying that completely dries the material. Although the second and third dryers are not equipped with a camera 1G and a weight scale 1H, they are equipped with an offline controller 21 and data communication is possible. In this installed facility, it is possible to measure the weight of the receiving cargo, but it is not possible to measure the finished weight data at the end of drying. The finished weight data at the end of drying is a calculated value from the moisture change amount measured on the moisture meter 1F of the dryer and the initial weight.

Each dryer can be operated by the control terminal 36, but errors between them can be prevented by directly sending the error to the linked dryer. In the case of an abnormality due to the transportation of grain between each dryer, both dryers are automatically stopped in an emergency, and as an immediate response to the abnormality, the user can send the abnormality data to the central terminal 36 and intermediate terminals 31, 32, and 33. It is also transmitted to the mobile terminal 37 that the user has.

The automatic recovery function for conveyance errors allows the user to operate from a mobile terminal and retry in the event of a shutter opening/closing abnormality, such as when the ejection shutter does not open. Furthermore, if a motor overload or paddy clogging is confirmed, rather than a shutter opening/closing abnormality such as the discharge shutter not opening, the discharge shutter will be automatically closed. A notification is sent to the user's mobile device to determine whether the switch from ejection to stakeout mode is permitted, and if permission is granted, the system automatically shifts to stakeout mode. When changing discharge or tensioning operations by remote control, the dryer will sound an abnormal buzzer to alert workers on site.

If there is a problem with the conveyance system of a dryer, and if it becomes clogged in the discharge mode and can be recovered in the loading mode, it is assumed that the conveyance system lacks capacity or the electric system has deteriorated. In this case, it is necessary to change the conveyance capacity. We will respond by making it possible to change the error evacuation capacity automatically or remotely.

Regarding the number and capacity of dryers, the number of dryers for tertiary receiving shall be the same as or greater than for secondary receiving. The capacity of the tertiary receiving dryer shall be the same as or smaller than the capacity of the secondary receiving dryer. The primary dryer enables high-speed circulation and high-speed discharge, and removes muddy dust, surface moisture, and gruel during one circulation. It is also possible to use an initial sample to determine taste by linking with a taste meter (registered trademark). Items whose taste can be analyzed in the primary dryer are automatically transported to the secondary dryer and sorted. Distribution to the secondary dryer is performed according to "distribution based on moisture" and "protein content measured by Tastemeter (registered trademark)".

In the secondary drying, for the purpose of semi-drying, drying is performed until the tertiary dryer is empty and can be loaded, or until the moisture content is below a predetermined value. If the tertiary dryer is not empty, the secondary dryer is used until the tertiary dryer is empty. There is also a method in which finishing drying is performed in a secondary dryer and a tertiary dryer is used as a cooling tank. In this case, by effectively utilizing the fact that it is a dryer, the tertiary dryer is controlled to circulate the grain without ventilation. In a cooling system using a tertiary dryer, the temperature of the grain can be measured, this temperature is displayed, and circulation operation is stopped when a predetermined temperature is reached.

We will explain how to import data from the agricultural data collaboration platform "WAGRI."

In the data management of the drying and preparation system described above, by importing external data and additionally registering in-facility data, it becomes possible to construct agricultural management data with an even larger amount of information. FIG. 2 shows this.

As external data, there is the above-mentioned agricultural data collaboration infrastructure "WAGRI" 61. The WAGRI61 platform has databases of weather information, farmland information, map information, growth predictions, soil information, etc., and past data can also be searched. These data are provided in the form of application programming interfaces (APIs). Data can be mutually imported using a reading conversion application that is compatible with these data formats and data arrangements. It is also possible for the ICT vendors 62, 63, and 64 to handle this data conversion and mutual utilization of data.

In one example, the drying and preparation facility 71 is a facility that performs operations from a dryer to rice polishing. The drying and preparation facility 72 is a facility that performs operations from dryers to hulling, but is also a comprehensive farming facility that also performs rice cultivation operations such as land leveling, planting, and harvesting. FIG. 2 shows how information is being taken in from tractors 72A and 72B.

Both facilities transmit shared data to WAGRI 61 through cloud server 121. Although the cloud server is defined in FIGS. 2 and 3, it is an external data management unit, and may be a rental server of a communication company or a server of an agricultural machinery manufacturer.

This sharable external data can be retrieved by registered users through the programs of the ICT vendors 62, 63, and 64. This allows 71 facilities to obtain general information on everything from tilling to harvesting. Rice milling data and rice sales data are also available for 72 facilities. The user terminals 66, 67, 68, and 69 can obtain all data for each facility from the central terminal of each facility, but can utilize common data from the information of the ICT vendor.

In the weather information and farmland information initiative, information such as outside temperature, humidity, weather, etc. is obtained from WAGRI 61 and the data is registered in the receiving number 47. Since this data is highly reliable, by registering it as data obtained from WAGRI 61 in the receiving data, products with high commercial value can be obtained. These can also be used as backing data at the time of sale. Weather information can also vary in small areas, so users can change it as well. In this case, a system for approval and confirmation by the relevant members is required. Even if the weather at the time of harvesting is sunny according to the weather data, there are times when it rains near the field, so these differences are checked with multiple members and the data is recorded.

There is also material information as data on local facilities. Seedlings, fertilizers, disinfectants, transportation costs, and work fuel costs are items that must be entered by the manager, but by registering these data as shared data within the facility and having a system for approval based on data confirmation from outside, it is possible to Able to operate safely. When dealing with an even larger area, WAGRI's database can be used to manage and approve material costs.

Since the material information is the total cost of each material, the total cost is automatically distributed based on the size of the field. Alternatively, it can be automatically distributed based on grain yields, and these are also implemented within the approval system. In terms of labor costs, tractors, rice transplanters, and combines are equipped with GPS, allowing them to clearly see their location and working hours. Material costs and labor costs for each field are distributed based on the work time data and calculated as the cost of production materials for each field. By using the data, it is possible to detect fields that take a long time to work per unit area and calculate the work efficiency of workers.

The authentication system of the present invention will be explained with reference to FIG.

A simple authentication system 101 is set in the central terminal 36 that manages facility data. By logging in 103 from the user's mobile terminal 102, it is confirmed whether the terminal is capable of communicating with the communication company. This login information becomes authentication verification 104 and is verified against the authentication system 101. Unless this verification is possible, operations such as reading and rewriting data from the mobile terminal 102 cannot be performed. If the authentication can be confirmed, the authentication of the mobile terminal 102 is completed in authentication verification 105 and the reception of the data request 106 is permitted. The control terminal 36 searches for request data and performs request data transmission 107. By transmitting and receiving this data, the mobile terminal 102 can read and write data from the central terminal 36 from the outside.

The data to be periodically transmitted in advance by the drying preparation system is transmitted from the general data in the periodic abnormality data transmission 108. Periodic data is also transmitted from the intermediate terminal 31, and this data is general periodic data that also includes data from the huller, rice milling machine, etc. This data is sent by email to the mobile terminal 102 by the communication company 111 in a periodic abnormality data transmission 109.

Next, reading and writing of the shared data described above will be explained. Shared data is registered in the cloud server 121. The cloud server 121 may be a server owned by an agricultural machinery manufacturer and used to register shared data of users' agricultural machinery information, or a rental server rented out to users by a communication company. This server is equipped with an authentication system. One example of a system is the OAuth system. The OAuth system 122 is an authentication system using a simple password system, and a token is used to issue the password.

Token is issued 124 for authentication confirmation. The communication company is equipped with an authentication confirmation 123, performs token authentication 125 and token storage, and performs cloud access authentication work 128 to the user's mobile terminal 102. The user inputs information on the user interface 127 screen to confirm authentication. If the communication company is able to confirm the information input, it gives the stored token 126, authenticates the issued token to the OAuth system 122 in a token confirmation 129, and issues a data issue instruction 131. Only when this authentication is obtained, it is possible to read and write data on the cloud server and update important data on the general terminal 38.

After the authentication is confirmed, the cloud server is accessed by shared data requests 143 and 144. If these operations involve simply searching for data, the data is transmitted to the mobile terminal 102 in the flow of request transmission 145 and 146. However, as mentioned above, although changes in weather data in the district, seedlings, fertilizers, disinfectants, transportation costs, and work fuel costs are input by the administrator, these data cannot be shared as shared data within the facility. In the case of registration and approval based on data confirmation from the outside, the request transmission takes the flow of 149 and corresponds to reading and writing of data on the central terminal 36. The changed data is checked against the cloud server again in shared data requests 150 and 144, and the information is transmitted to the mobile terminal in the flow of request data transmission 145 and 146. This series of cloud accesses will also be sent to other mobile devices, information will be shared among members, and shared data will be registered and changed in advance. After that, each other device enters the authentication system, checks the changes on the cloud server, and approves the changes, allowing them to register and change the shared data.

1 Dryer 1G camera (dryer receiving area)
2 Husking machine 2A Sorting board 2B Camera (hulling machine sorting board)
31 Intermediate terminal 29 Moisture meter 31 Outside air temperature sensor 36 Control terminal 36A Work process data 42 Container number 47 Receiving number 61 WAGRI
121 Cloud server 122 Authentication system OAuth token issuance

Claims (5)

A container number provided on a container containing the received grain is read by an imaging means installed in a receiving part for the dryer, and a receiving number is created by combining the container number and the time when the container is received,
Drying operation data by the dryer and preparation operation data of the preparation machine after drying in the dryer are additionally registered in the consignment number in chronological order as a management data group,
A drying and preparation system, characterized in that grain data for each container is managed using the management data group. Regarding the drying operation data and the preparation operation data, standard work process data (36A) is stored in a database in advance,
2. The drying and preparation system according to claim 1, wherein the management data group and work process data (36A) are compared and verified to calculate the value of the received grain. 3. The drying operation data and the preparation operation data are converted into common information processing data and registered in the consignment number in chronological order to generate a management data group. dry preparation system. The data log output from the controller of the dryer as the drying operation data and the data log output from the controller of the preparation machine as the preparation operation data are read using data log reading software,
The drying/preparing system according to claim 1 or 2, wherein the drying operation data and the preparation operation data in the data log format are additionally registered in the consignment number to generate a management data group. . The authentication system for registering the management data group is placed on both the cloud server (121), which is an external server on the Internet, and the control terminal (36) of the drying and preparation facility.
Authentication of user terminals (103), (104), (105) and regular data transmission of drying and preparation facilities (108), (109) are performed on the central terminal (36).
When registering the newly acquired time-series shared data for the consignment number on an external server, the external server's authentication system (122) is activated, and if it is authenticated, the request data is sent from the central terminal (36). (107) to the user terminal,
Claims 1, 2, and 3, characterized in that (150) and (144) simultaneously access an external server and transmit a shared data request to other terminals (145) and (146) to share information. 4. The dry preparation system according to 4.