CN113139778B - Intelligent decision system and method based on big data - Google Patents
Intelligent decision system and method based on big data Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000005554 pickling Methods 0.000 claims abstract description 170
- 241000238557 Decapoda Species 0.000 claims abstract description 35
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 25
- 150000003839 salts Chemical class 0.000 claims abstract description 20
- 208000000884 Airway Obstruction Diseases 0.000 claims description 133
- 206010008589 Choking Diseases 0.000 claims description 133
- 239000012267 brine Substances 0.000 claims description 92
- HPALAKNZSZLMCH-UHFFFAOYSA-M sodium;chloride;hydrate Chemical compound O.[Na+].[Cl-] HPALAKNZSZLMCH-UHFFFAOYSA-M 0.000 claims description 91
- 238000012544 monitoring process Methods 0.000 claims description 50
- 239000013505 freshwater Substances 0.000 claims description 41
- 238000001816 cooling Methods 0.000 claims description 22
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- 235000011389 fruit/vegetable juice Nutrition 0.000 description 1
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- 210000001113 umbilicus Anatomy 0.000 description 1
- 238000009423 ventilation Methods 0.000 description 1
- 235000021419 vinegar Nutrition 0.000 description 1
- 239000000052 vinegar Substances 0.000 description 1
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Abstract
The invention provides an intelligent decision-making system and method based on big data. The system and the method are based on the characteristic that the curing of the choked crabs is greatly influenced by temperature, salt water concentration and curing time, and establish a choked crab curing database with a large number of accurate corresponding temperatures, salt water concentrations and curing time; predicting to obtain optimal pickling starting time according to order information, weather forecast information and a crab choking pickling database; meanwhile, in the actual curing process, the actual curing temperature is monitored in real time to acquire a large amount of temperature data for system judgment, and the system automatic intervention and manual reminding modes are adopted to prevent the conditions that curing overtime cannot be performed on time or curing oversalty influences eating and the like, so that the curing qualification rate of the choked crabs is improved.
Description
Technical Field
The invention belongs to the field of accurate food processing, and particularly relates to an intelligent decision system and method based on big data.
Background
The crab choke is one of the best known help in Jiang Zhe and Shanghai, and the production process is mainly three steps.
The first step is to select a good quality female crab, preferably a live crab. Only the mature old crabs grown from red paste to corners are qualified to be used for making the choked crabs with good taste.
The second step is to formulate brine. The salt can be mixed according to the individual liking according to the water of 500 g and the edible salt of 175 g. If the pickling time is shortened, the salt content is increased, and the salt juice is prepared by the ratio of 500 g of water to 210 g of salt. The crab container is recommended to select a plurality of glass jars or ceramic vessels, and has better sealing performance.
The third step is curing. After the crabs are washed clean, the crabs are put into the prepared brine, the umbilicus of the crabs faces upwards, the water is required to overflow the body of the crabs, then some white spirit with high alcohol content is poured, and the weight is pressed or the cover is covered. The time for making the red paste choked crabs is generally 10 hours in winter and 8 hours in summer. The salted crabs are frozen by removing ice boxes, are convenient to form and attractive, and finally are cut into pieces and are put on a tray for being dipped in vinegar for eating.
Obviously, the conventional crab choke curing process mainly depends on personal experience to determine proper curing temperature, salt water concentration and curing time, and has great limitation on commercial mass curing.
Disclosure of Invention
To solve at least some of the above problems, the present invention provides an intelligent decision system based on big data, the system comprising: a crab choking curing database containing corresponding curing time under the conditions of corresponding temperature and corresponding salt water concentration; the crab-choking order processing module is used for receiving crab-choking order information, and comprises order quantity, order placing time and order taking time, and when the order quantity is smaller than the crab-choking inventory quantity of the day before the order taking time, the temperature information of the day before the order taking time is called, the temperature information of the day before the order taking time comprises the highest temperature and a predicted average temperature, the highest temperature and a first threshold are compared, and the crab-choking inventory quantity of the day before the order taking time is updated; the crab-choking pickling determination module is used for obtaining predicted pickling duration from the crab-choking pickling database according to the predicted average temperature and the preset brine concentration when the highest temperature is smaller than the first threshold value; determining the pickling starting time according to the predicted pickling time length and the picking time; the temperature monitoring module is used for monitoring the temperature; the crab choking curing monitoring module is connected with the temperature monitoring module and is used for calculating the average curing temperature according to the real-time monitoring temperature after curing begins; obtaining actual pickling time from the crab choke pickling database according to the average pickling temperature and the preset brine concentration; when the actual pickling time is longer than the predicted pickling time, a brine starting instruction is sent to a brine releasing device, and timeout information is sent to a terminal; a crab-choking curing container for curing the crab-choking; the brine container is used for containing strong brine; the brine releasing device is arranged between the crab-choking pickling container and the brine container; when the brine releasing device is started, the concentrated brine flows to the crab-choking pickling container.
Furthermore, the crab-choking order processing module is used for zeroing the crab-choking inventory quantity of the day before the order taking time and sending the replenishment information to the terminal when the order quantity is larger than the crab-choking inventory quantity of the day before the order taking time.
Further, the crab-choking curing determination module is configured to obtain the predicted curing time from the crab-choking curing database according to a preset temperature and the preset brine concentration when the maximum temperature is greater than the first threshold and the predicted average temperature is greater than the second threshold.
Further, the system also comprises a cooling device which is in communication connection with the crab-choking curing determining module; when the time is the pickling starting time, the crab choking pickling determining module sends a refrigerating instruction to the cooling device; the cooling device executes the refrigeration instruction, and the refrigeration instruction comprises the preset temperature.
Further, the crab-choking pickling monitoring module is configured to send a fresh water start instruction to a fresh water release device and send early warning information to a terminal when the actual pickling duration is less than the predicted pickling duration and the absolute value of the difference between the actual pickling duration and the predicted pickling duration is greater than a third threshold; the system further comprises a fresh water container for holding fresh water; the fresh water release device is arranged between the crab-choking pickling container and the fresh water container; when the fresh water releasing device is started, the fresh water flows to the crab-choking pickling container.
Correspondingly, the invention also discloses an intelligent decision method based on big data, which specifically comprises the following steps: s10: receiving order information of crabs, wherein the order information comprises order quantity, ordering time and order taking time, and when the order quantity is smaller than the stock quantity of crabs choked on the day before the order taking time, calling the temperature information on the day before the order taking time, wherein the temperature information on the day before the order taking time comprises a highest temperature and a predicted average temperature, comparing the highest temperature with a first threshold value and updating the stock quantity of crabs choked on the day before the order taking time; s20: when the highest temperature is smaller than the first threshold value, obtaining predicted pickling time from a crab-choking pickling database according to the predicted average temperature and the preset brine concentration; determining the pickling starting time according to the predicted pickling time length and the picking time; the crab choking curing database comprises corresponding curing time under the conditions of corresponding temperature and corresponding salt water concentration; s30: monitoring the temperature in real time after starting pickling, calculating the average pickling temperature, and obtaining the actual pickling time from the crab choking pickling database according to the average pickling temperature and the preset brine concentration; and when the actual pickling time is longer than the predicted pickling time, sending a brine starting instruction to a brine releasing device and sending timeout information to a terminal.
Further, in the step S10, when the order quantity is greater than the crab-choking stock quantity one day before the order taking time, the crab-choking stock quantity one day before the order taking time is zeroed and the replenishment information is sent to the terminal.
Further, in the step S20, when the maximum temperature is greater than the first threshold value and the predicted average temperature is greater than the second threshold value, the predicted pickling duration is obtained from the crab-choking pickling database according to a preset temperature and the preset brine concentration. Further, when the time is the pickling starting time, sending a refrigeration instruction to the cooling device; the cooling device executes the refrigeration instruction, and the refrigeration instruction comprises the preset temperature.
Further, when the actual pickling time period is smaller than the predicted pickling time period and the absolute value of the difference between the two is larger than a third threshold value, the method further includes step S40: and sending a fresh water starting instruction to the fresh water releasing device and sending early warning information to the terminal.
The beneficial effects are that: the invention provides an intelligent decision-making system and method based on big data, wherein the system and method are based on the characteristic that the curing of the choked crabs is greatly influenced by temperature, salt water concentration and curing time, and establish a choked crab curing database with a large number of accurate corresponding temperatures, salt water concentrations and curing time; predicting to obtain optimal pickling starting time according to order information, weather forecast information and a crab choking pickling database; meanwhile, in the actual curing process, the actual curing temperature is monitored in real time to acquire a large amount of temperature data for system judgment, and the system automatic intervention and manual reminding modes are adopted to prevent the conditions that curing overtime cannot be performed on time or curing oversalty influences eating and the like, so that the curing qualification rate of the choked crabs is improved.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent decision system based on big data according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, the embodiment of the invention comprises an intelligent decision system based on big data, which comprises a crab-choking pickling database, a crab-choking order processing module, a crab-choking pickling determining module, a temperature monitoring module, a crab-choking pickling container, a brine container and a brine releasing device.
Wherein, the crab choking curing database comprises corresponding curing time under the conditions of corresponding temperature and corresponding brine concentration. The main influencing factors of crab-choking curing are temperature, brine concentration and curing time, and by combining personal experience and test, the corresponding temperature, the corresponding brine concentration and the corresponding curing time are taken as a group of data, delicious crab-choking can be cured under the condition of each group of data, and a large number of groups of data are stored in a database to establish a crab-choking curing database. So that the pickling time of the delicious choked crabs can be obtained from the database according to the temperature and the brine concentration.
The pickling is carried out in a room, and the temperature is room temperature; obviously, when the environmental variation of the curing place is not large, the room temperature can be simply calculated from the air temperature according to the temperature difference between the indoor and outdoor of the general room. For example, weather forecast shows that the temperature difference between the ordinary indoor temperature and the outdoor temperature of the pickling place is 5 ℃ at 29 ℃/21 ℃ in the open day, and the room temperature of the place at 24 ℃/16 ℃ in the open day can be obtained. Similarly, the predicted average room temperature can be calculated approximately according to the temperature trend of weather forecast.
The crab-choking order processing module is used for receiving crab-choking order information, comprises order quantity, ordering time and order taking time, and when the order quantity is smaller than the crab-choking inventory quantity of one day before the order taking time, the temperature information of the previous day of the order taking time is called, the temperature information of the previous day comprises the highest temperature and the predicted average temperature, the highest temperature and a first threshold value are compared, and the crab-choking inventory quantity of the day before the order taking time is updated.
The order information can be manually input and stored in the order information data table, at least comprises the order quantity, namely the quantity of reserved crabs, and is used for judging whether the stock of the crabs is sufficient; at least comprises ordering time for ordering orders and completing the crab choking curing of the orders according to the sequence; the crab is soaked with salt to reduce the taste of the crab even if stored at low temperature, so that the pickling time is optimal about 1 day before the picking time, and the picking time is particularly important.
Therefore, the crab-choking order processing module compares the order quantity with the crab-choking stock quantity one day before the order taking time; when the stock of the choking crabs is sufficient, the temperature information of the previous day of the single time is called, and the temperature information can be obtained from a third party, such as local weather forecast data; the temperature information of the previous day includes a maximum temperature, which is the air temperature, and a predicted average temperature, which is the room temperature of the curing place simply calculated from the temperature trend of the weather forecast and the general indoor and outdoor temperature difference of the curing place.
And comparing the highest temperature with a first threshold value and updating the stock quantity of the choked crabs one day before the picking time. The first threshold value is a preset highest air temperature suitable for curing choked crabs, and is different due to different factors such as indoor and outdoor temperature differences or curing places; under the condition of not considering cooling measures and reducing cost, the pickling is performed indoors at natural air temperature as much as possible, and the first threshold value can be set to be 28 ℃ in the Jiangzhe region. When the comparison result shows that the highest temperature is smaller than the first threshold value, pickling can be performed at room temperature; otherwise, cooling measures are required. And updating the stock quantity of the crabs choked in the day before the order taking time, namely subtracting the stock quantity of the crabs choked in the day before the order taking time from the stock quantity of the crabs choked in the day before the order taking time to serve as the new stock quantity of the crabs choked in the day before the order taking time.
The crab-choking curing determination module is used for obtaining predicted curing time from a crab-choking curing database according to the predicted average temperature and the preset brine concentration when the highest temperature is smaller than the first threshold value; and determining the pickling starting time according to the predicted pickling time length and the picking time. When the highest temperature is smaller than the first threshold value, pickling can be carried out at room temperature, and the average temperature is predicted to be the average room temperature; the preset brine concentration is a brine concentration value preset by the system, for example, the brine concentration can be 500 g of water in the background art, namely 175 g of edible salt; according to the predicted average temperature and the preset brine concentration, a matched data set can be found from a crab choking pickling database, and the pickling time corresponding to the data set is the predicted pickling time. Pushing the picking time forward according to the predicted pickling time length, so as to obtain the pickling starting time; here, a certain amount of time may be reserved for curing preparation, specific curing operations, and freezing after curing is completed, resulting in a more reasonable time to begin curing.
The temperature monitoring module is used for monitoring the temperature. The temperature monitoring module can be an intelligent temperature sensor and can transmit the temperature to a data processing terminal such as a mobile phone terminal or a computer terminal. The temperature monitoring module can be used for monitoring the room temperature in real time or monitoring the room temperature once every fixed time, and transmitting the monitored temperature to the crab-choking curing monitoring module. The intelligent temperature sensor should be arranged near the pickling container and not easy to be placed at the ventilation opening and the like.
The crab choking curing monitoring module is connected with the temperature monitoring module and is used for calculating the average curing temperature according to the monitored temperature after curing begins; obtaining actual pickling time from a crab-choking pickling database according to the average pickling temperature and the preset brine concentration; when the actual pickling time is longer than the predicted pickling time, a brine starting instruction is sent to a brine releasing device, and timeout information is sent to the terminal. The crab-choking curing monitoring module is connected with the temperature monitoring module, can be in wired connection or wireless connection and is used for receiving the monitored temperature in a communication way. The crab choking curing monitoring module receives the monitored temperature obtained by monitoring, namely the actual room temperature, and calculates the average curing temperature according to the monitored temperatures measured at a plurality of different times; and obtaining the actual pickling time from a crab-choking pickling database according to the average pickling temperature and the preset brine concentration. The temperature monitoring module can be configured to monitor the temperature once every fixed time to reduce the data volume and improve the calculation efficiency, for example, monitor the temperature once every 10 minutes and send the monitored temperature to the crab-choking curing monitoring module for calculating the average curing temperature.
Comparing the actual pickling time with the predicted pickling time, and sending a brine starting instruction to a brine releasing device by the crab choke pickling monitoring module when the actual pickling time is longer than the predicted pickling time. The brine releasing device is in communication connection with the crab choking curing monitoring module, and can be in limited connection or wireless connection. The brine releasing device is started after receiving the brine starting instruction, and then strong brine flows into the crab-choking pickling container. The instruction may comprise a release period of time, the saline release device simply activating the release period of time and then closing. In one embodiment, the brine releasing device is an intelligent water valve, a water outlet of the intelligent water valve is arranged above the crab-choking pickling container, when the intelligent water valve is started after receiving a brine starting instruction with the releasing time of 5 minutes, the brine flows to the crab-choking pickling container, and after 5 minutes, the brine is automatically closed. According to the scheme, based on a large number of data sets in the crab choking curing database, the actual curing time is judged in time, so that the judgment decision has a overtime risk, and the method of autonomously improving the salt water concentration is adopted, so that the actual curing time is shortened.
Meanwhile, the crab choking pickling monitoring module sends overtime information to the terminal so as to remind overtime risks, and people can conveniently decide to take proper countermeasures. The terminal can be a display, a mobile phone, a computer screen, an alarm device and the like, and when people find out the reminding of the terminal, the people can make a decision in time to adopt proper measures, such as improving the concentration of the pickling brine and the like.
In a more preferable scheme, a concentration monitoring module is arranged in a crab-choking pickling container to monitor the actual brine concentration in consideration of the fact that people do not see overtime reminding or overtime information and a brine releasing device is controlled by a crab-choking pickling monitoring module for a plurality of times to improve the brine concentration; the crab-choking curing monitoring module receives the actual brine concentration, and obtains new actual curing time from a crab-choking curing database according to the average curing temperature and the actual brine concentration. The concentration monitoring module is in communication connection with the crab choking curing monitoring module, and the concentration monitoring module can be a brine concentration meter and a salinity sensor.
A crab-choking curing container for curing the crab-choking; the brine container is used for containing strong brine; the brine releasing device is arranged between the crab-choking pickling container and the brine container, and when the brine releasing device is started, the concentrated brine flows to the crab-choking pickling container. In one embodiment, the brine releasing device is an intelligent pipeline switch, and the intelligent pipeline switch can be provided with a choking crab pickling container side or a re-brine container side; the crab-choking pickling container is communicated with the brine container through a pipeline, and when the intelligent pipeline switch is turned on, strong brine in the brine container flows to the crab-choking pickling container.
In one embodiment, the crab-choking order processing module is configured to, when the order quantity is greater than the crab-choking inventory quantity one day before the order taking time, zero the crab-choking inventory quantity one day before the order taking time and send the replenishment information to the terminal. The scheme can accurately determine the stock quantity of the crabs choking every day, and can help users to make reasonable replenishment decisions. The terminal can be a display, a mobile phone, a computer screen, an alarm device and the like, and can give specific information so as to be convenient for making a replenishment decision, such as displaying the information of the order number, the choking crab stock number and the like.
In one embodiment, the crab-choking curing determination module is configured to obtain a predicted curing time from a crab-choking curing database according to a preset temperature and the preset brine concentration when the highest temperature is greater than a first threshold value and the predicted average temperature is greater than a second threshold value. According to the scheme, according to the highest temperature of the day before the taking time obtained from a third party platform and the predicted average temperature obtained through calculation, when the highest temperature is larger than a first threshold value and the predicted average temperature is larger than a second threshold value, the natural room temperature which is changed to the day is judged to be too high, and the crab is not suitable to be cured, wherein the second threshold value is recorded into the system in advance according to personal experience or experimental results; under the condition, according to preset temperature and preset brine concentration which are set in advance, the predicted pickling duration is obtained from a crab choking pickling database, and then the accurate pickling starting time is obtained through calculation. In one embodiment, the first threshold is 35 ℃ and the second threshold is 30 ℃, i.e. when the highest temperature of the day is greater than 35 ℃ and the predicted average temperature is 30 ℃, then the curing is not suitable for curing at natural room temperature, and curing is required at a preset temperature, such as 20 ℃, which is a temperature value preset by the system; obtaining predicted pickling time from a crab-choking pickling database according to the preset temperature and the preset brine concentration, and then calculating to obtain accurate starting pickling time.
In one embodiment of the above scheme, the system further comprises a cooling device, and the cooling device is in communication connection with the crab-choking curing determination module; when the time is the pickling starting time, the crab choking pickling determining module sends a refrigerating instruction to the cooling device; and the cooling device executes the refrigeration instruction, wherein the refrigeration instruction comprises a preset temperature. Specifically, because the natural room temperature in the day is too high to be suitable for curing, when curing time begins, the crab choking curing determining module sends a refrigeration instruction to the cooling device to control the cooling device to start refrigeration, and the refrigeration temperature is set to be a preset temperature. In one embodiment, the cooling device is an intelligent air conditioner, and the intelligent air conditioner is in communication connection with the crab choking pickling determining module and can receive and execute the refrigerating instruction sent by the crab choking pickling determining module. The scheme comprehensively makes decisions and intelligently controls the intelligent air conditioner to be started at fixed time and fixed temperature based on the choking crab curing data and the weather forecast data so as to ensure that the curing temperature is reasonable.
In one embodiment, the crab choking pickling monitoring module is used for sending a fresh water starting instruction to the fresh water releasing device and sending early warning information to the terminal when the actual pickling time is smaller than the predicted pickling time and the absolute value of the difference between the actual pickling time and the predicted pickling time is larger than a third threshold; the system also comprises a fresh water container, wherein the brine container is used for containing fresh water; the fresh water release device is arranged between the crab-choking pickling container and the fresh water container; when the fresh water releasing device is started, fresh water flows to the crab-choking pickling container. In the scheme, when the crab-choking pickling monitoring module finds that the actual pickling time is smaller than the predicted pickling time and the absolute value of the difference between the actual pickling time and the predicted pickling time is larger than a third threshold value, the actual required pickling time is too short, and the salty degree of the crab-choking is too high when the pickling is completed according to the predicted pickling time, a measure of releasing fresh water to a crab-choking pickling container to reduce the salt water concentration is adopted to prevent the salty degree from being too salty, and early warning information is sent to a terminal to remind related personnel to treat in time; the third threshold may be obtained from personal experience or experimentation and is preset in the system, for example, by setting for 5 hours, i.e., when the actual curing time period is shortened by 5 hours, indicating that curing is too salty.
The fresh water releasing device is in communication connection with the crab choking curing monitoring module, and can be in limited connection or wireless connection. The fresh water releasing device is started after receiving the fresh water starting instruction, and fresh water flows into the crab-choking pickling container at the moment. The instruction may include a release duration, the fresh water release means being activated only for the release duration and then being closed. In one embodiment, the fresh water release device is an intelligent water valve, a water outlet of the intelligent water valve is arranged above the crab-choking pickling container, when the intelligent water valve is started after receiving a fresh water starting instruction with the release time of 5 minutes, fresh water flows to the crab-choking pickling container, and after 5 minutes, the fresh water is automatically closed. According to the scheme, based on a large number of data sets in the crab choking curing database, the actual curing time is judged in time, so that the risk of oversalty is judged, and the means of autonomously reducing the salt water concentration is adopted, so that the actual curing time is prolonged.
Meanwhile, the crab choking pickling monitoring module sends early warning information to the terminal so as to remind the risk of oversalty, and people can conveniently decide to take proper countermeasures. The terminal can be a display, a mobile phone, a computer screen, an alarm device and the like, and when people find out the reminding of the terminal, the people can make a decision in time to adopt proper measures, such as reducing the concentration of pickling brine, taking out the pickled crabs in advance, cooling, pickling and the like.
In a more preferable scheme, a concentration monitoring module is arranged in a crab-choking pickling container to monitor the actual brine concentration in consideration of the fact that personnel do not see early warning reminding or oversalty information and a fresh water release device is controlled by a crab-choking pickling monitoring module for a plurality of times to reduce the brine concentration; the crab-choking curing monitoring module receives the actual brine concentration, and obtains new actual curing time from a crab-choking curing database according to the average curing temperature and the actual brine concentration. The concentration monitoring module is in communication connection with the crab choking curing monitoring module, and the concentration monitoring module can be a brine concentration meter and a salinity sensor.
In accordance with the above-mentioned scheme, the present invention provides an embodiment, which is an intelligent decision method based on big data, and it is to be noted that the meaning of the first threshold, the second threshold, the third threshold and other custom words in the method are the same as those in the system description. The method comprises the following steps:
s10: and receiving order information of the crabs to be choked, wherein the order information comprises order quantity, ordering time and order taking time, when the order quantity is smaller than the stock quantity of the crabs choked in the day before the order taking time, the temperature information of the day before the order taking time is called, the temperature information of the day before the order taking time comprises the highest temperature and a predicted average temperature, the highest temperature and a first threshold are compared, and the stock quantity of the crabs choked in the day before the order taking time is updated.
In one embodiment, when the order quantity is greater than the stock quantity of the crabs choking the day before the order taking time, the stock quantity of the crabs choking the day before the order taking time is zeroed and the replenishment information is sent to the terminal.
In one embodiment, the predicted curing time period is obtained from the crab-choking curing database according to a preset temperature and the preset brine concentration when the highest temperature is greater than the first threshold value and the predicted average temperature is greater than a second threshold value. In a more specific embodiment, when the time is the pickling start time, sending a refrigeration instruction to the cooling device; the cooling device executes the refrigeration instruction, and the refrigeration instruction comprises the preset temperature.
S20: when the highest temperature is smaller than the first threshold value, obtaining predicted pickling time from a crab-choking pickling database according to the predicted average temperature and the preset brine concentration; determining the pickling starting time according to the predicted pickling time length and the picking time; the crab choking curing database comprises corresponding curing time under the conditions of corresponding temperature and corresponding salt water concentration;
s30: monitoring the temperature in real time after starting pickling, calculating the average pickling temperature, and obtaining the actual pickling time from the crab choking pickling database according to the average pickling temperature and the preset brine concentration; and when the actual pickling time is longer than the predicted pickling time, sending a brine starting instruction to a brine releasing device and sending timeout information to a terminal. It should be noted that the specific curing step or process is not a subject or an inventive point of the present invention, and is not described herein.
In one embodiment, when the actual pickling time period is less than the predicted pickling time period and the absolute value of the difference between the two is greater than a third threshold value, the method further includes step S40: and sending a fresh water starting instruction to the fresh water releasing device and sending early warning information to the terminal.
The above examples are provided for convenience of description of the present invention and are not to be construed as limiting the invention in any way, and any person skilled in the art will make partial changes or modifications to the invention by using the disclosed technical content without departing from the technical features of the invention.
Claims (10)
1. An intelligent decision making system based on big data, the system comprising:
a crab choking curing database containing corresponding curing time under the conditions of corresponding temperature and corresponding salt water concentration;
the crab-choking order processing module is used for receiving crab-choking order information, and comprises order quantity, order placing time and order taking time, and when the order quantity is smaller than the crab-choking inventory quantity of the day before the order taking time, the temperature information of the day before the order taking time is called, the temperature information of the day before the order taking time comprises the highest temperature and a predicted average temperature, the highest temperature and a first threshold are compared, and the crab-choking inventory quantity of the day before the order taking time is updated;
the crab-choking pickling determination module is used for obtaining predicted pickling duration from the crab-choking pickling database according to the predicted average temperature and the preset brine concentration when the highest temperature is smaller than the first threshold value; determining the pickling starting time according to the predicted pickling time length and the picking time;
the temperature monitoring module is used for monitoring the temperature;
the crab choking curing monitoring module is connected with the temperature monitoring module and is used for calculating the average curing temperature according to the real-time monitoring temperature after curing begins; obtaining actual pickling time from the crab choke pickling database according to the average pickling temperature and the preset brine concentration; when the actual pickling time is longer than the predicted pickling time, a brine starting instruction is sent to a brine releasing device, and timeout information is sent to a terminal;
a crab-choking curing container for curing the crab-choking; the brine container is used for containing strong brine; the brine releasing device is arranged between the crab-choking pickling container and the brine container; when the brine releasing device is started, the concentrated brine flows to the crab-choking pickling container.
2. The big data based intelligent decision system of claim 1, wherein the crab choke order processing module is configured to zero the number of crab choke inventory on the day before the order taking time and send replenishment information to a terminal when the number of orders is greater than the number of crab choke inventory on the day before the order taking time.
3. The big data based intelligent decision system of claim 1, wherein the crab choke curing determination module is configured to obtain the predicted curing time period from the crab choke curing database based on a preset temperature and the preset brine concentration when the maximum temperature is greater than the first threshold and the predicted average temperature is greater than a second threshold.
4. A big data based intelligent decision system according to claim 3, further comprising a cooling device in communication with the crab-chocking curing determination module;
when the time is the pickling starting time, the crab choking pickling determining module sends a refrigerating instruction to the cooling device; the cooling device executes the refrigeration instruction, and the refrigeration instruction comprises the preset temperature.
5. The big data-based intelligent decision-making system according to claim 1, wherein the crab-choking pickling monitoring module is configured to send a fresh water start instruction to a fresh water release device and send early warning information to a terminal when the actual pickling time is less than the predicted pickling time and an absolute value of a difference between the actual pickling time and the predicted pickling time is greater than a third threshold;
the system further comprises a fresh water container for holding fresh water; the fresh water release device is arranged between the crab-choking pickling container and the fresh water container; when the fresh water releasing device is started, the fresh water flows to the crab-choking pickling container.
6. An intelligent decision method based on big data is characterized by comprising the following steps:
s10: receiving order information of crabs, wherein the order information comprises order quantity, ordering time and order taking time, and when the order quantity is smaller than the stock quantity of crabs choked on the day before the order taking time, calling the temperature information on the day before the order taking time, wherein the temperature information on the day before the order taking time comprises a highest temperature and a predicted average temperature, comparing the highest temperature with a first threshold value and updating the stock quantity of crabs choked on the day before the order taking time;
s20: when the highest temperature is smaller than the first threshold value, obtaining predicted pickling time from a crab-choking pickling database according to the predicted average temperature and the preset brine concentration; determining the pickling starting time according to the predicted pickling time length and the picking time; the crab choking curing database comprises corresponding curing time under the conditions of corresponding temperature and corresponding salt water concentration;
s30: monitoring the temperature in real time after starting pickling, calculating the average pickling temperature, and obtaining the actual pickling time from the crab choking pickling database according to the average pickling temperature and the preset brine concentration; and when the actual pickling time is longer than the predicted pickling time, sending a brine starting instruction to a brine releasing device and sending timeout information to a terminal.
7. The intelligent decision-making method based on big data according to claim 6, wherein in the step S10, when the order quantity is greater than the crab-choking stock quantity one day before the order taking time, the crab-choking stock quantity one day before the order taking time is zeroed and a replenishment message is sent to a terminal.
8. The intelligent big data-based decision method according to claim 6, wherein in the step S20, the predicted pickling duration is obtained from the crab-choking pickling database according to a preset temperature and the preset brine concentration when the maximum temperature is greater than the first threshold value and the predicted average temperature is greater than a second threshold value.
9. The intelligent decision-making method based on big data according to claim 8, wherein when the time is the pickling start time, a refrigeration instruction is sent to the cooling device; the cooling device executes the refrigeration instruction, and the refrigeration instruction comprises the preset temperature.
10. The big data based intelligent decision method according to claim 6, wherein when the actual pickling time period is smaller than the predicted pickling time period and the absolute value of the difference between the two is larger than a third threshold value, the method further comprises step S40: and sending a fresh water starting instruction to the fresh water releasing device and sending early warning information to the terminal.
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