CN109006652A - A kind of Tilapia mossambica production of hybrid seeds seedling system and method based on Internet of Things - Google Patents
A kind of Tilapia mossambica production of hybrid seeds seedling system and method based on Internet of Things Download PDFInfo
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- CN109006652A CN109006652A CN201811145873.6A CN201811145873A CN109006652A CN 109006652 A CN109006652 A CN 109006652A CN 201811145873 A CN201811145873 A CN 201811145873A CN 109006652 A CN109006652 A CN 109006652A
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; CARE OF BIRDS, FISHES, INSECTS; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K63/00—Receptacles for live fish, e.g. aquaria; Terraria
- A01K63/04—Arrangements for treating water specially adapted to receptacles for live fish
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; CARE OF BIRDS, FISHES, INSECTS; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K61/00—Culture of aquatic animals
- A01K61/80—Feeding devices
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; CARE OF BIRDS, FISHES, INSECTS; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K63/00—Receptacles for live fish, e.g. aquaria; Terraria
- A01K63/04—Arrangements for treating water specially adapted to receptacles for live fish
- A01K63/042—Introducing gases into the water, e.g. aerators, air pumps
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; CARE OF BIRDS, FISHES, INSECTS; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K63/00—Receptacles for live fish, e.g. aquaria; Terraria
- A01K63/06—Arrangements for heating or lighting in, or attached to, receptacles for live fish
- A01K63/065—Heating or cooling devices
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/80—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in fisheries management
- Y02A40/81—Aquaculture, e.g. of fish
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- Biodiversity & Conservation Biology (AREA)
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- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention belongs to seedling-raising technique fields, a kind of Tilapia mossambica production of hybrid seeds seedling system and method based on Internet of Things is disclosed, the Tilapia mossambica production of hybrid seeds seedling system based on Internet of Things includes: temperature detecting module, salinity measurement module, oxygen content detection module, central control module, communication module, server, mobile terminal, water supply module, sterilization module, bait throwing in module, display module.The present invention is mutually bound measuring device with mobile terminal using dynamic unique encodings by communication module, to make the two establish one-to-one communication connection, instead of the mode of direct communication between original equipment and controlling terminal.In this way, making bindings more simple and fast, matched woth no need to equipment and terminal direct communication, no distance limitation, good compatibility；The management of more convenient pair of Tilapia mossambica production of hybrid seeds nursery；Meanwhile bait throwing in can be carried out by bait throwing in module automatically, the accurate bait throwing in requirement of fishery cultivating may be implemented in high degree of automation, simple, convenient.
Description
Technical field
The invention belongs to seedling-raising technique field more particularly to a kind of Tilapia mossambica production of hybrid seeds seedling systems and side based on Internet of Things
Method.
Background technique
Tilapia mossambica is commonly called as: African crucian, non-crucian carp, Vietnam fish, Nan Yang crucian carp etc..Original refers to using Mozambique as type locality
Mouth incubates non-crucian carp category fish species: Mozambique mouthful incubates non-crucian carp (scientific name: Oreochromismossambicus), now non-for Family Cichlidae
Crucian carp category and mouth incubate non-crucian carp category etc. and belong to being commonly called as jointly for several fish；Tilapia is referred to as in English.It is world's aquatic products industry now
Emphasis scientific research culture cultured freshwater fish, and be known as one of the main source of the following animal protein.Usually life
It in fresh water, can also move in the salt water of different salt contents, can also survive in lake, river, in the shallow water in pond.It has very
Strong adaptability can also breed in the narrow waters of area, or even can grow in paddy field, and to dissolved oxygen it is less it
Water has extremely strong adaptability.Most Tilapia mossambicas are omnivorousness, often eat aquatic plant and mince.However, existing Tilapia mossambica educates
In seedling relevant device communication mode, the disadvantages of there are transmission ranges short, poor compatibility, more complex matching operation；And use sequence
Number with account binding mode in, for an equipment to more terminals in the case where, can not correctly transmit data to target end
End；Meanwhile existing fishery cultivating bait relies primarily on mechanical device for feeding fish bait and sheds, and needs to be set manually by cultivation experience
Set, that there are the degree of automation is not high, without bait throwing in algorithm, without intelligent control the problems such as, can not achieve the accurate of fishery cultivating production
Bait throwing in requirement.
In conclusion problem of the existing technology is: in existing Tilapia mossambica nursery relevant device communication mode, there is biography
It is defeated apart from short, poor compatibility, more complex matching operation the disadvantages of；And use in the mode of sequence number and account binding, for one
In the case that platform equipment is to more terminals, target terminal can not be correctly transmitted data to；Meanwhile existing fishery cultivating bait is main
It is shed by mechanical device for feeding fish bait, needs to carry out manual setting by cultivation experience, that there are the degree of automation is not high, calculates without bait throwing in
Method, without intelligent control the problems such as, can not achieve fishery cultivating production accurate bait throwing in requirement.
In the prior art, the influence for the measurement of temperature vulnerable to environment temperature, prevent temperature parameter is from accurately obtaining
, the acquisition of temperature parameter in Tilapia mossambica production of hybrid seeds nursery is influenced, the progress of Tilapia mossambica production of hybrid seeds nursery is hindered；In the prior art, right
It is insufficient in the amount of storage of the data of production of hybrid seeds nursery, it often results in the loss of data and lacks, be unfavorable for obtaining server control and believe
The storage of breath；Furthermore display does not have low noise, low damage and highlighted advantage, can not more precisely construct defect image
Background information, be unfavorable for the accurate acquisition of Tilapia mossambica living environment parameter.
Summary of the invention
In view of the problems of the existing technology, the present invention provides a kind of Tilapia mossambica production of hybrid seeds seedling system based on Internet of Things
And method.
The invention is realized in this way a kind of Tilapia mossambica production of hybrid seeds seedling system based on Internet of Things includes:
Temperature detecting module, salinity measurement module, oxygen content detection module, central control module, communication module, service
Device, mobile terminal, water supply module, sterilization module, bait throwing in module, display module；
Temperature detecting module is connect with central control module, cultivates Tilapia mossambica water body for detecting by temperature sensor
Temperature data information；
The temperature sensor, the temperature of output are Tm, extraneous link temperature Te, and temperature drift, that is, each measurement point
Measurement error E can regard T asm、TeBinary function, it may be assumed that
E=F (Tm, Te)
By 2 independent variable Tm、TeAs 2 components of training set input value, target value of the dependent variable E as training set, benefit
It is fitted modeling with IAGA-LSSVM, optimizing is carried out to regularization parameter γ and radial direction base parameter σ, utilizes resulting optimal ginseng
Number solution formula:
Function model optimized parameter α and b can be obtained, thus the temperature drift curved surface optimal models function established are as follows:
The measured value of temperature sensor is compensated using the pattern function value that the method is established, it may be assumed that
Salinity measurement module, connect with central control module, for cultivating Tilapia mossambica water body by the detection of salinity measurement instrument
Salinity Data information；
Oxygen content detection module, connect with central control module, cultivates Tilapia mossambica for detecting by oxygen measurement set
Water body oxygen content data information；
Central control module, with temperature detecting module, salinity measurement module, oxygen content detection module, communication module, confession
Water module, sterilization module, bait throwing in module, display module connection, work normally for controlling modules by single-chip microcontroller；
Communication module is connect with central control module, is communicatively coupled for being established by Internet of Things with server, and
Server control information is wirelessly obtained by mobile terminal；
The Internet of Things, the attribute value using the tagsort weight ai of cloud storage database is p, in effective database
Under access request, the datum number storage in cloud computing storing data library increases data storage capacity according to model, is conducive to obtain server
The storage for controlling information, is described as follows:
Wherein, the data initial schedule grid assignment of Tilapia mossambica production of hybrid seeds seedling system indicates in cloud computing storing data library
For；
U×A→V
The grid distributed areas fitting that cloud storage database is carried out using adaptive channel method of weighting, obtains database point
The network of cloth are as follows:
In formula: an (t) is the T/F union feature analysis on nth data memory channels；
τ n (t) is that nth data storage path extends time delay；
Fc is the data attribute weight in cloud computing storing data library；
Setting fuzzy operator is mapped to synthetic evaluation matrix, carries out initialization gridding scheduling, obtains cloud computing storing data
The mapping relations of the transmission path of library data memory node are as follows:
In formula: ai and τ i is the propagation loss of the data of Tilapia mossambica production of hybrid seeds seedling system in cloud computing storing data library respectively
And delivery lag.
Water supply module is connect with central control module, cultivates water supplying operation to Tilapia mossambica for drawing water by water pump；
Sterilization module is connect with central control module, for passing through sprinkler spray disinfectant drug to cultivation tilapia water
Body carries out disinfection operation；
Bait throwing in module, connect with central control module, carries out dispensing fish material for controlling device for feeding fish bait by bait throwing in algorithm；
Display module is connect with central control module, for showing detection Tilapia mossambica production of hybrid seeds nursery existence by display
Environmental parameter；
The display inhibits to examine using liquid crystal display for liquid crystal display spot (LCD-Mura) defect background
There is introducing property noise jamming and target defect in the background rebuild in survey, present invention proposition can be summarized simply as follows in the ideal case
Without make an uproar, it is lossless and enhancing so that display have noise reduction, it is lossless, enhancing effect, be conducive to Tilapia mossambica living environment parameter
It is accurate to obtain；Without making an uproar refer to that the background of reconstruction cannot introduce new noise jamming, quantized value L with normal background by being averaged
Gray scale difference value is defined as:
Wherein: ISB is normal background, i.e., the normal LCD image shot under the conditions of same Image Acquisition；Num is statistics
Gray scale non-zero pixels number；It is lossless to refer to that defect image does not lose Mura defects information after reconstructed background inhibits, generally from
Mura defects region area A out is evaluated:
Wherein: s (x, y) is the area of unit pixel；D representative meets the pixel domain that difference in defect area is not 0；And increase
It is strong then refer to that the Mura defects after background inhibits are more obvious, it is visual higher, then it can pass through the flat of Define defects and background
Equal contrast defines the data quantity C:
Wherein: LM is the average brightness of defect area in original image, and LB is to correspond to defect area in the background image rebuild
The average brightness at place；By the way that each quantized value is answered in the ideal situation known to analysis mode (1)~(3) are as follows: L=0, A=AMura, C →
∞；Since actual reconstruction process will receive the interference of various factors, each quantized value for obtaining at this time compared to ideal value there are error,
Therefore for the calculated L of certain Background Rebuilding Method, smaller, A and C more defecates it can be assumed that the background masses that this method is rebuild
It is higher.
Another object of the present invention is to provide a kind of, and the Tilapia mossambica production of hybrid seeds method for culturing seedlings based on Internet of Things includes following step
It is rapid:
Step 1 cultivates tilapia water temperature data information using temperature sensor detection by temperature detecting module；
Tilapia mossambica water body Salinity Data information is cultivated using the detection of salinity measurement instrument by salinity measurement module；It is detected by oxygen content
Module cultivates Tilapia mossambica water body oxygen content data information using oxygen measurement set detection；
Step 2, central control module are established using Internet of Things by communication module and are communicatively coupled with server, and
Server control information is wirelessly obtained by mobile terminal；
Step 3 is drawn water using water pump by water supply module and cultivates water supplying operation to Tilapia mossambica；Pass through sterilization module
It is carried out disinfection operation using sprinkler spray disinfectant drug to Tilapia mossambica water body is cultivated；
Step 4 controls device for feeding fish bait using bait throwing in algorithm by bait throwing in module and carries out dispensing fish material；
Step 5 utilizes display display detection Tilapia mossambica production of hybrid seeds nursery living environment parameter by display module.
Further, the communication module includes request module, generation module, uploading module, binding module；
Request module, for sending the request for generating dynamic unique encodings to server by measuring device；
Generation module, server respond the request, generate dynamic unique encodings；
Uploading module, for the dynamic unique encodings to be uploaded to the server by mobile terminal；
Binding module, for will send the measuring device of request by the server and upload the movement of dynamic unique encodings
Terminal is bound, so that the two establishes one-to-one communication connection.
Further, the bait throwing in module bait-throwing method is as follows:
(1) System Control Center establishes net connection by communication module and mobile terminal；
(2) wake-up module timing wake-up is just in the control centre of deep-sleep and control circuit；
(3) first to use, the setting of original cultivation parameter is carried out by mobile terminal, as the type of fish, specification, number and
The specification etc. of feed；
(4) when reusing, automatically into automatic control mode, control centre reads the bait throwing in environmental parameter of sensor acquisition,
And it shows on mobile terminals；
(5) the cultivation database in sensor parameters and memory is compared for control centre, is generated by bait throwing in algorithm
Daily ration, feeding quantity, and control the opening/closing time of electromagnetism sliding door；
(6) bait in device for feeding fish bait is conveyed by air-flow, and the special construction design of feed inlet makes delivery air in feed inlet
Lower section forms local decompression, sucks and carries bait to discharge port accelerated motion；
(7) the smooth guide frame of discharge port designs the pellet adjustment direction so that linear uniform motion, final equal
It is even to spray to the fan-shaped region immediately ahead of device for feeding fish bait；
(8) control centre calculates daily ration, feeding quantity according to sensor parameters, month in season, cultivation database etc., and according to bait throwing in
The bait throwing in rate of machine controls the bait throwing in time, realizes accurate bait throwing in；
(9) after bait throwing in, this bait throwing in data is recorded in memory data library by control centre, and power supply closes automatically
It closes, system enters deep sleep state and next timing node is waited to be waken up.
Further, the cultivation database in sensor parameters and memory is compared for the control centre, by bait throwing in
Algorithm generates daily ration, feeding quantity, and controls the opening/closing time of electromagnetism sliding door.
Further, the bait in the device for feeding fish bait is conveyed by air-flow, and the special construction design of feed inlet makes delivery air
Local decompression is formed below feed inlet, sucks and carries bait to discharge port accelerated motion.
Advantages of the present invention and good effect are as follows: the present invention is set measurement using dynamic unique encodings by communication module
It is standby mutually to be bound with mobile terminal, to make the two establish one-to-one communication connection, instead of original equipment and controlling terminal
Between direct communication mode.In this way, making bindings more simple and fast, matched woth no need to equipment and terminal direct communication,
It is limited without distance, good compatibility；The management of more convenient pair of Tilapia mossambica production of hybrid seeds nursery；Meanwhile it can be automatic by bait throwing in module
Bait throwing in is carried out, the accurate bait throwing in requirement of fishery cultivating may be implemented in high degree of automation, simple, convenient.
The present invention is compensated by the measured value to temperature sensor, obtains accurate temperature parameter, can record in time,
Temperature is adjusted, is conducive to obtain accurately temperature information in Tilapia mossambica production of hybrid seeds nursery；The present invention is stored using cloud computing
The datum number storage of database increases data storage capacity according to model, is conducive to the storage for obtaining server control information；The present invention
For liquid crystal display spot (LCD-Mura) defect background inhibit in detection the background rebuild exist introducing property noise jamming and
Target defect can more precisely construct the back of defect image so that display has the advantages that low noise, low damage and highlights
Scape information is conducive to the accurate acquisition of Tilapia mossambica living environment parameter.
Detailed description of the invention
Fig. 1 is that the present invention implements the Tilapia mossambica production of hybrid seeds method for culturing seedlings flow chart based on Internet of Things provided.
Fig. 2 is that the present invention implements the Tilapia mossambica production of hybrid seeds seedling system structural block diagram based on Internet of Things provided.
In Fig. 2: 1, temperature detecting module；2, salinity measurement module；3, oxygen content detection module；4, center control mould
Block；5, communication module；6, server；7, mobile terminal；8, water supply module；9, sterilization module；10, bait throwing in module；11, mould is shown
Block；.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
With reference to the accompanying drawing and specific embodiment is further described application principle of the invention.
As shown in Figure 1, a kind of Tilapia mossambica production of hybrid seeds method for culturing seedlings based on Internet of Things provided by the invention the following steps are included:
Step S101 cultivates tilapia water temperature data using temperature sensor detection by temperature detecting module and believes
Breath；Tilapia mossambica water body Salinity Data information is cultivated using the detection of salinity measurement instrument by salinity measurement module；Pass through oxygen content
Detection module cultivates Tilapia mossambica water body oxygen content data information using oxygen measurement set detection；
Step S102, central control module are established using Internet of Things by communication module and are communicatively coupled with server,
And server control information is wirelessly obtained by mobile terminal；
Step S103 is drawn water using water pump by water supply module and cultivates water supplying operation to Tilapia mossambica；By sterilizing mould
Block is carried out disinfection operation using sprinkler spray disinfectant drug to Tilapia mossambica water body is cultivated；
Step S104 controls device for feeding fish bait using bait throwing in algorithm by bait throwing in module and carries out dispensing fish material；
Step S105 utilizes display display detection Tilapia mossambica production of hybrid seeds nursery living environment parameter by display module.
As shown in Fig. 2, the Tilapia mossambica production of hybrid seeds seedling system provided by the invention based on Internet of Things includes: temperature detecting module
1, salinity measurement module 2, oxygen content detection module 3, central control module 4, communication module 5, server 6, mobile terminal 7,
Water supply module 8, sterilization module 9, bait throwing in module 10, display module 11.
Temperature detecting module 1 is connect with central control module 4, cultivates tilapia water for detecting by temperature sensor
Temperature data information；
Salinity measurement module 2 is connect with central control module 4, for cultivating tilapia water by the detection of salinity measurement instrument
Body Salinity Data information；
Oxygen content detection module 3 is connect with central control module 4, cultivates Rofe for detecting by oxygen measurement set
Fish and water body oxygen content data information；
Central control module 4, with temperature detecting module 1, salinity measurement module 2,3 communication module of oxygen content detection module
5, water supply module 8, sterilization module 9, bait throwing in module 10, display module 11 connect, for controlling modules just by single-chip microcontroller
Often work；
Communication module 5 is connect with central control module 4, carries out communication link with server 6 for establishing by Internet of Things
It connects, and server 6 is wirelessly obtained by mobile terminal 7 and controls information；
Water supply module 8 is connect with central control module 4, cultivates the behaviour that supplies water to Tilapia mossambica for drawing water by water pump
Make；
Sterilization module 9 is connect with central control module 4, for passing through sprinkler spray disinfectant drug to cultivation Tilapia mossambica
Water body carries out disinfection operation；
Bait throwing in module 10 is connect with central control module 4, carries out dispensing fish for controlling device for feeding fish bait by bait throwing in algorithm
Material；
Display module 11 is connect with central control module 4, for showing that detection Tilapia mossambica production of hybrid seeds nursery is raw by display
Dis environment parameter.
The temperature sensor, the temperature of output are Tm, extraneous link temperature Te, and temperature drift, that is, each measurement point
Measurement error E can regard T asm、TeBinary function, it may be assumed that
E=F (Tm, Te)；
By 2 independent variable Tm、TeAs 2 components of training set input value, target value of the dependent variable E as training set, benefit
It is fitted modeling with IAGA-LSSVM, optimizing is carried out to regularization parameter γ and radial direction base parameter σ, utilizes resulting optimal ginseng
Number solution formula:
Function model optimized parameter α and b can be obtained, thus the temperature drift curved surface optimal models function established are as follows:
The measured value of temperature sensor is compensated using the pattern function value that the method is established, it may be assumed that
The Internet of Things, the attribute value using the tagsort weight ai of cloud storage database is p, in effective database
Under access request, the datum number storage in cloud computing storing data library increases data storage capacity according to model, is conducive to obtain server
The storage for controlling information, is described as follows:
Wherein, the data initial schedule grid assignment of Tilapia mossambica production of hybrid seeds seedling system indicates in cloud computing storing data library
For；
U×A→V
The grid distributed areas fitting that cloud storage database is carried out using adaptive channel method of weighting, obtains database point
The network of cloth are as follows:
In formula: an (t) is the T/F union feature analysis on nth data memory channels；
τ n (t) is that nth data storage path extends time delay；
Fc is the data attribute weight in cloud computing storing data library；
Setting fuzzy operator is mapped to synthetic evaluation matrix, carries out initialization gridding scheduling, obtains cloud computing storing data
The mapping relations of the transmission path of library data memory node are as follows:
In formula: ai and τ i is the propagation loss of the data of Tilapia mossambica production of hybrid seeds seedling system in cloud computing storing data library respectively
And delivery lag.
The display inhibits to examine using liquid crystal display for liquid crystal display spot (LCD-Mura) defect background
There is introducing property noise jamming and target defect in the background rebuild in survey, present invention proposition can be summarized simply as follows in the ideal case
Without make an uproar, it is lossless and enhancing so that display have noise reduction, it is lossless, enhancing effect, be conducive to Tilapia mossambica living environment parameter
It is accurate to obtain；Without making an uproar refer to that the background of reconstruction cannot introduce new noise jamming, quantized value L with normal background by being averaged
Gray scale difference value is defined as:
Wherein: ISB is normal background, i.e., the normal LCD image shot under the conditions of same Image Acquisition；Num is statistics
Gray scale non-zero pixels number；It is lossless to refer to that defect image does not lose Mura defects information after reconstructed background inhibits, generally from
Mura defects region area A out is evaluated:
Wherein: s (x, y) is the area of unit pixel；D representative meets the pixel domain that difference in defect area is not 0；And increase
It is strong then refer to that the Mura defects after background inhibits are more obvious, it is visual higher, then it can pass through the flat of Define defects and background
Equal contrast defines the data quantity C:
C=(| LM-LB|)/LB(3)
Wherein: LM is the average brightness of defect area in original image, and LB is to correspond to defect area in the background image rebuild
The average brightness at place；By the way that each quantized value is answered in the ideal situation known to analysis mode (1)~(3) are as follows: L=0, A=AMura, C →
∞；Since actual reconstruction process will receive the interference of various factors, each quantized value for obtaining at this time compared to ideal value there are error,
Therefore for the calculated L of certain Background Rebuilding Method, smaller, A and C more defecates it can be assumed that the background masses that this method is rebuild
It is higher.
Communication module 5 provided by the invention includes request module, generation module, uploading module, binding module；
Request module, for sending the request for generating dynamic unique encodings to server by measuring device；
Generation module, server respond the request, generate dynamic unique encodings；
Uploading module, for the dynamic unique encodings to be uploaded to the server by mobile terminal；
Binding module, for will send the measuring device of request by the server and upload the movement of dynamic unique encodings
Terminal is bound, so that the two establishes one-to-one communication connection.
10 bait-throwing method of bait throwing in module provided by the invention is as follows:
(1) System Control Center establishes net connection by communication module and mobile terminal；
(2) wake-up module timing wake-up is just in the control centre of deep-sleep and control circuit；
(3) first to use, the setting of original cultivation parameter is carried out by mobile terminal, as the type of fish, specification, number and
The specification etc. of feed；
(4) when reusing, automatically into automatic control mode, control centre reads the bait throwing in environmental parameter of sensor acquisition,
And it shows on mobile terminals；
(5) the cultivation database in sensor parameters and memory is compared for control centre, is generated by bait throwing in algorithm
Daily ration, feeding quantity, and control the opening/closing time of electromagnetism sliding door；
(6) bait in device for feeding fish bait is conveyed by air-flow, and the special construction design of feed inlet makes delivery air in feed inlet
Lower section forms local decompression, sucks and carries bait to discharge port accelerated motion；
(7) the smooth guide frame of discharge port designs the pellet adjustment direction so that linear uniform motion, final equal
It is even to spray to the fan-shaped region immediately ahead of device for feeding fish bait；
(8) control centre calculates daily ration, feeding quantity according to sensor parameters, month in season, cultivation database etc., and according to bait throwing in
The bait throwing in rate of machine controls the bait throwing in time, realizes accurate bait throwing in；
(9) after bait throwing in, this bait throwing in data is recorded in memory data library by control centre, and power supply closes automatically
It closes, system enters deep sleep state and next timing node is waited to be waken up.
Cultivation database in sensor parameters and memory is compared for control centre provided by the invention, by bait throwing in
Algorithm generates daily ration, feeding quantity, and controls the opening/closing time of electromagnetism sliding door.
Bait in device for feeding fish bait provided by the invention is conveyed by air-flow, and the special construction design of feed inlet makes to convey gas
Stream forms local decompression below feed inlet, sucks and carries bait to discharge port accelerated motion.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (9)
1. a kind of Tilapia mossambica production of hybrid seeds method for culturing seedlings based on Internet of Things, which is characterized in that the Tilapia mossambica system based on Internet of Things
Planting method for culturing seedlings includes:
Step 1 cultivates tilapia water temperature data information using temperature sensor detection by temperature detecting module；Pass through
Salinity measurement module cultivates Tilapia mossambica water body Salinity Data information using the detection of salinity measurement instrument；Pass through oxygen content detection module
It is detected using oxygen measurement set and cultivates Tilapia mossambica water body oxygen content data information；
Step 2, central control module is established using Internet of Things by communication module and is communicatively coupled with server, and is passed through
Mobile terminal wirelessly obtains server control information；
Step 3 is drawn water using water pump by water supply module and cultivates water supplying operation to Tilapia mossambica；It is utilized by sterilization module
Sprinkler spray disinfectant drug carries out disinfection operation to Tilapia mossambica water body is cultivated；
Step 4 controls device for feeding fish bait using bait throwing in algorithm by bait throwing in module and carries out dispensing fish material；
Step 5 utilizes display display detection Tilapia mossambica production of hybrid seeds nursery living environment parameter by display module；
The temperature sensor of the temperature detecting module, the temperature of output are Tm, extraneous link temperature Te, and temperature drift is
The measurement error E of each measurement point can regard T asm、TeBinary function, it may be assumed that
E=F (Tm, Te)；
By 2 independent variable Tm、TeAs 2 components of training set input value, target value of the dependent variable E as training set is utilized
IAGA-LSSVM is fitted modeling, carries out optimizing to regularization parameter γ and radial direction base parameter σ, utilizes resulting optimized parameter
Solution formula:
Function model optimized parameter α and b are obtained, the temperature drift curved surface optimal models function established are as follows:
The measured value of temperature sensor is compensated using the pattern function value of foundation, it may be assumed that
2. the Tilapia mossambica production of hybrid seeds method for culturing seedlings based on Internet of Things as described in claim 1, which is characterized in that the communication module
Internet of Things, using cloud storage database tagsort weight ai attribute value be p, in effective database access request
Under, the datum number storage in cloud computing storing data library increases data storage capacity according to model:
Wherein, the data initial schedule grid assignment of Tilapia mossambica production of hybrid seeds seedling system is expressed as in cloud computing storing data library；
U×A→V；
The grid distributed areas fitting that cloud storage database is carried out using adaptive channel method of weighting, obtains database distribution
Network are as follows:
In formula: an (t) is the T/F union feature analysis on nth data memory channels；
τ n (t) is that nth data storage path extends time delay；
Fc is the data attribute weight in cloud computing storing data library；
Setting fuzzy operator is mapped to synthetic evaluation matrix, carries out initialization gridding scheduling, obtains cloud computing storing data library number
According to the mapping relations of the transmission path of memory node are as follows:
In formula: ai and τ i is the propagation loss and biography of the data of Tilapia mossambica production of hybrid seeds seedling system in cloud computing storing data library respectively
Pass time delay.
3. the Tilapia mossambica production of hybrid seeds method for culturing seedlings based on Internet of Things as described in claim 1, which is characterized in that the display module
The make an uproar background of reconstruction of nothing of display liquid crystal display cannot introduce new noise jamming, quantized value L by with standard
The average gray difference value of background is defined as:
Wherein: ISB is normal background, i.e., the normal LCD image shot under the conditions of same Image Acquisition；Num is the gray scale of statistics
Non-zero pixels number；It is lossless to refer to that defect image does not lose Mura defects information after reconstructed background inhibits, from the Mura obtained
Defect area area A is evaluated:
Wherein: s (x, y) is the area of unit pixel；D representative meets the pixel domain that difference in defect area is not 0；By fixed
The average contrast of adopted defect and background defines the data quantity C:
C=(| LM-LB|)/LB；
Wherein: LM is the average brightness of defect area in original image, and LB is corresponded at defect area in the background image rebuild
Average brightness；By analysis mode, each quantized value is answered in the ideal situation are as follows: L=0, A=AMura, C → ∞；Due to actual reconstruction mistake
Journey will receive the interference of various factors, and there are errors compared to ideal value for each quantized value obtained at this time, for certain Background Reconstruction
The calculated L of method is smaller, A and C are bigger.
4. the Tilapia mossambica production of hybrid seeds method for culturing seedlings based on Internet of Things as described in claim 1, which is characterized in that the bait throwing in module
Bait-throwing method is as follows:
(1) System Control Center establishes net connection by communication module and mobile terminal；
(2) wake-up module timing wake-up is just in the control centre of deep-sleep and control circuit；
(3) first to use, the setting of original cultivation parameter is carried out by mobile terminal, such as the type of fish, specification, number and feed
Specification；
(4) when reusing, automatically into automatic control mode, the bait throwing in environmental parameter that control centre's reading sensor acquires, and
It is shown on mobile terminal；
(5) the cultivation database in sensor parameters and memory is compared for control centre, generates bait throwing in by bait throwing in algorithm
Amount, and control the opening/closing time of electromagnetism sliding door；
(6) bait in device for feeding fish bait is conveyed by air-flow, and the special construction design of feed inlet makes delivery air below feed inlet
Local decompression is formed, suck and carries bait to discharge port accelerated motion；
(7) the smooth guide frame of discharge port designs the pellet adjustment direction so that linear uniform motion, final uniformly spray
It is spread to the fan-shaped region immediately ahead of device for feeding fish bait；
(8) control centre calculates daily ration, feeding quantity according to sensor parameters, month in season, cultivation database, and according to the throwing of device for feeding fish bait
Bait rate controls the bait throwing in time, realizes accurate bait throwing in；
(9) after bait throwing in, this bait throwing in data is recorded in memory data library by control centre, and power supply is automatically closed, and is
System enters deep sleep state and next timing node is waited to be waken up.
5. a kind of Tilapia mossambica based on Internet of Things for the Tilapia mossambica production of hybrid seeds method for culturing seedlings realized described in claim 1 based on Internet of Things
Production of hybrid seeds seedling system, which is characterized in that the Tilapia mossambica production of hybrid seeds seedling system based on Internet of Things includes:
Temperature detecting module is connect with central control module, cultivates tilapia water temperature for detecting by temperature sensor
Data information；
Salinity measurement module, connect with central control module, for cultivating Tilapia mossambica water salinity by the detection of salinity measurement instrument
Data information；
Oxygen content detection module, connect with central control module, cultivates Tilapia mossambica water body for detecting by oxygen measurement set
Oxygen content data information；
Central control module, with temperature detecting module, salinity measurement module, oxygen content detection module, communication module, water supply mould
Block, sterilization module, bait throwing in module, display module connection, work normally for controlling modules by single-chip microcontroller；
Communication module is connect with central control module, is communicatively coupled for being established by Internet of Things with server, and pass through
Mobile terminal wirelessly obtains server control information；
Water supply module is connect with central control module, cultivates water supplying operation to Tilapia mossambica for drawing water by water pump；
Sterilization module is connect with central control module, for by sprinkler spray disinfectant drug to cultivate Tilapia mossambica water body into
Row sterilizing operation；
Bait throwing in module, connect with central control module, carries out dispensing fish material for controlling device for feeding fish bait by bait throwing in algorithm；
Display module is connect with central control module, for showing detection Tilapia mossambica production of hybrid seeds nursery living environment by display
Parameter.
6. the Tilapia mossambica production of hybrid seeds seedling system based on Internet of Things as claimed in claim 5, which is characterized in that the communication module
Including request module, generation module, uploading module, binding module；
Request module, for sending the request for generating dynamic unique encodings to server by measuring device；
Generation module, server respond the request, generate dynamic unique encodings；
Uploading module, for the dynamic unique encodings to be uploaded to the server by mobile terminal；
Binding module, for will send the measuring device of request by the server and upload the mobile terminal of dynamic unique encodings
It is bound, so that the two establishes one-to-one communication connection.
7. the Tilapia mossambica production of hybrid seeds seedling system based on Internet of Things as claimed in claim 5, which is characterized in that the control centre
Cultivation database in sensor parameters and memory is compared, daily ration, feeding quantity is generated by bait throwing in algorithm, and control electromagnetism and push away
The opening/closing time of sliding door.
8. the Tilapia mossambica production of hybrid seeds seedling system based on Internet of Things as claimed in claim 5, which is characterized in that in the device for feeding fish bait
Bait conveyed by air-flow, the design of the special construction of feed inlet makes delivery air form local decompression below feed inlet, inhales
Enter and carry bait and is accelerated to discharge port.
9. a kind of Information Number using the Tilapia mossambica production of hybrid seeds method for culturing seedlings described in Claims 1 to 4 any one based on Internet of Things
According to processing terminal.
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| CN114296487A (en) * | 2022-03-07 | 2022-04-08 | 广东省农业科学院动物科学研究所 | Intelligent culture pond salinity parameter regulation and control method and system |
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