CN113435316A - Intelligent bird repelling method and device, electronic equipment and storage medium - Google Patents
Intelligent bird repelling method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the field of intelligent decision making, and provides an intelligent bird repelling method, which comprises the steps of firstly obtaining a monitoring image, preprocessing the monitoring image based on an image locking algorithm to form a target image, then carrying out analogy on the target image and pre-stored sample data to obtain a similarity value, starting bird repelling sounding to finish bird repelling if the similarity value is not lower than a preset threshold value, thus being compatible with image identification, placing a plurality of devices at intervals, preventing the influence of birds in a large area in an all-round way and monitoring a crop production field, facilitating the management of workers, having lower manufacturing cost, being suitable for mass production and placement, having wide coverage range, greatly reducing the difficulty of bird repelling outdoors, being less influenced by natural disasters and severe weather, being recycled by self-integrated electric energy, having longer service life, and being capable of being combined with other outdoor agricultural implements, such as irrigator, outdoor lighting lamp, crops support etc. very big convenience and expanded placing of equipment and restrict in the place influence.
Description
Technical Field
The invention relates to the field of intelligent decision making, relates to an intelligent method, and particularly relates to an intelligent bird repelling method, an intelligent bird repelling device, electronic equipment and a computer-readable storage medium.
Background
The agriculture of the existing market is developed faster, particularly the planting industry is developed by being concerned with the livelihood, but the planting industry has various requirements on the development period and has certain requirements on the growth environment, and the external environment is interfered when crops grow and mature, so that the crop yield is influenced. The factors of birds are obvious, most of crops in the planting industry are planted in outdoor plains or mountainous regions, so that excessive birds fly to peck, a large number of birds consume the yield of the crops in the period, and meanwhile, due to the life tracks of the birds, the problems that germs, worm eggs and the like are carried with a certain probability indirectly affect the growth and the yield of the crops.
Therefore, a corresponding method for expelling birds is available, and according to the inquiry of market products, the market also has a plurality of bird expelling methods and devices, such as sonar bird expelling, wind bird expelling, sunshine colored band bird expelling, ornament bird expelling and the like. Moreover, the bird equipment that drives among the prior art receives the influence of natural disasters and meteorological big, very easily causes the destruction of equipment, increases cost of maintenance.
Therefore, there is a need for an intelligent bird repelling method and device which can improve bird repelling efficiency, facilitate modification and disassembly, reduce equipment loss and use, and integrate themselves.
Disclosure of Invention
The invention provides an intelligent bird repelling method, a device, electronic equipment and a computer readable storage medium which can improve bird repelling efficiency, are convenient to modify and disassemble and reduce equipment loss and use, and are integrated into a whole, and the intelligent bird repelling method, the device, the electronic equipment and the computer readable storage medium mainly aim at solving the problems that the existing bird repelling device is not strong in effect, high in cost, single in function, incompatible with each other, large in loss, low in matching degree with crop delivery aids, difficult to manage due to more site limitations, incapable of better mastering the overall situation of outdoor crops, greatly influenced by natural disasters and weather, easy to damage equipment and capable of increasing maintenance cost.
In order to achieve the purpose, the invention provides an intelligent bird repelling method, which comprises the following steps:
monitoring an agricultural environment in real time to obtain a monitoring image;
preprocessing the monitoring image based on an image locking algorithm to form a target image;
carrying out analogy on the target image and pre-stored sample data to obtain a similarity value;
and if the similarity value is not lower than a preset threshold value, starting bird repelling sounding to finish bird repelling.
Optionally, the monitoring the agricultural environment in real time to obtain a monitoring image includes:
detecting whether a flying object exists in the acquisition gradient through an object sensor in a preset radiation range; wherein the acquisition gradients comprise a first acquisition gradient, a second acquisition gradient and a third acquisition gradient;
if the flying object is detected to exist in the radiation range, judging the acquisition gradient of the flying object, and judging whether the brightness of the agricultural environment reaches a light source threshold value corresponding to the acquisition gradient through a light source sensor; if the brightness does not reach the light source threshold value, the brightness reaches the light source threshold value through a light supplement lamp, and if the brightness reaches the light source threshold value, monitoring data are obtained through an imaging element; the light supplement lamp comprises a first light supplement lamp, a second light supplement lamp and a third light supplement lamp; the first light supplement lamp corresponds to the first acquisition gradient, the second light supplement lamp corresponds to the second acquisition gradient, and the third light supplement lamp corresponds to the third acquisition gradient;
carrying out standardization processing on the monitoring data to form characteristic information;
and carrying out imaging processing on the characteristic information to form a monitoring image.
Optionally, the imaging the feature information to form a monitoring image includes:
preliminarily locking the characteristic information to lock black pixel points included in the characteristic information in a first region;
intercepting the first area to form first data;
and converting the first data into an image mode to form a monitoring image.
Optionally, the preprocessing the monitoring image based on an image locking algorithm to form a target image includes:
carrying out geometric position standardization processing on the monitoring image based on an image locking algorithm to form a standard image with a preset size; wherein the image locking algorithm is as follows: taking a black pixel point set in the monitoring image as a bird embryonic set through a preset rule in a processor; cutting the bird embryonic form by taking the geometric shape of the bird embryonic form as a center and radiating outwards according to a preset size;
and carrying out image gray scale normalization processing on the standard image to form a target image.
Optionally, the analogizing the target image with pre-stored sample data to obtain a similarity value includes:
pre-training a flyer recognition model through a convolutional neural network;
storing sample data to the flying object identification model to form a flying bird identification model;
inputting the target image into the flying bird recognition model, so that the flying bird recognition model forms a similarity value with the sample data by analogy with the set of the flying bird embryonic forms in the target image.
Optionally, the pre-training of the flying object recognition model by the convolutional neural network includes:
receiving an input flyer image sample;
carrying out normalization processing on the flying object image sample to obtain a flying object image set with a preset size;
processing the flying object image set by sequentially passing through a preset number of convolution layers and full-connection layers to form a flying object identification model; wherein a preset number of filters are arranged in the roll base layer; the filter comprises an activation function and a sliding step length; and a preset number of neurons are arranged in the full connection layer.
Optionally, the method further comprises: transmitting the monitoring image to a client; wherein the transmitting the monitoring image to a client includes:
sending, by the client, a connection request to the imaging element;
analyzing a matched password according to the connection request, and if the matched password is consistent with a pre-stored password, establishing connection between the client and the imaging element through the connection request;
and if the imaging element acquires monitoring data, sending a bird repelling prompt to the client based on the connection, and sending a monitoring image to the client.
In order to solve the above problems, the present invention also provides an intelligent bird repelling device, comprising:
the image recognizer is used for monitoring the agricultural environment in real time to obtain a monitoring image;
the target image unit is used for preprocessing the monitoring image based on an image locking algorithm to form a target image;
the similarity value calculation unit is used for carrying out analogy on the target image and pre-stored sample data to obtain a similarity value;
and the sounding triggering unit is used for judging the size of the similarity value, and starting the bird-driving sounding to drive birds if the similarity value is not lower than a preset threshold value.
In order to solve the above problem, the present invention also provides an electronic device, including:
a memory storing at least one instruction; and
and the processor executes the instructions stored in the memory to realize the steps of the intelligent bird repelling method.
In order to solve the above problem, the present invention further provides a computer-readable storage medium, where at least one instruction is stored in the computer-readable storage medium, and the at least one instruction is executed by a processor in an electronic device to implement the intelligent bird repelling method.
The embodiment of the invention firstly monitors the agricultural environment in real time to obtain a monitoring image, then preprocesses the monitoring image based on an image locking algorithm to form a target image, then compares the target image with pre-stored sample data to obtain a similarity value, if the similarity value is not lower than a preset threshold value, starts the bird repelling sound to finish bird repelling, is compatible with image identification, a plurality of devices are placed at intervals, can comprehensively prevent the influence of birds in a large area and monitor the production field of crops, supports the transmission of a data background mobile phone end of an image identifier and a PC (personal computer), is convenient for the management of workers, has lower manufacturing cost, is suitable for mass production and placement, has wide coverage range, greatly reduces the difficulty of outdoor bird repelling, and repeeling in a targeted manner, has simple method placement, is less influenced by natural disasters and severe weather, and can be recycled by self-integrated electric energy, possess longer life, can combine together with other outdoor agricultural implements simultaneously, like irrigator, outdoor light, crops support etc. very big convenience and expanded placing of equipment and restrict in the place influence.
Drawings
Fig. 1 is a schematic flow chart of an intelligent bird repelling method according to an embodiment of the present invention;
fig. 2 is a schematic block diagram of an intelligent bird repelling device according to an embodiment of the present invention;
fig. 3 is a schematic view of an internal structure of an electronic device for implementing an intelligent bird repelling method according to an embodiment of the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
At present, a plurality of bird repelling methods and devices are available in the market, such as sonar bird repelling, wind bird repelling, sunshine colored belt bird repelling, ornament bird repelling and the like, but the method is not strong in effect, high in cost, single in function, incompatible with each other, high in loss, low in matching degree with crop midwifery tools, difficult to manage outdoor equipment, large in site limitation and incapable of better mastering the overall situation of outdoor crops. Moreover, the prior art and the equipment device are greatly influenced by natural disasters and weather, so that the equipment is easy to damage, and the maintenance cost is increased; in particular, the method comprises the following steps of,
1. most of bird repelling devices in the market are data separation, and the bird repelling efficiency is low;
2. without client tracking, the bird repelling condition is difficult to adjust in time;
3. the mutual incompatibility results in large loss;
4. the influence of natural disasters and severe weather is large;
5. the multi-position large-scale bird drying equipment is greatly influenced by the field.
In order to solve the problems, the invention provides an intelligent bird repelling method. Fig. 1 is a schematic flow chart of an intelligent bird repelling method according to an embodiment of the present invention. The method may be performed by an apparatus, which may be implemented by software and/or hardware.
In this embodiment, the intelligent bird repelling method includes:
s1: monitoring an agricultural environment in real time to obtain a monitoring image;
s2: preprocessing the monitoring image based on an image locking algorithm to form a target image;
s3: carrying out analogy on the target image and pre-stored sample data to obtain a similarity value;
s4: and if the similarity value is not lower than the preset threshold value, starting bird repelling sounding to finish bird repelling.
In the embodiment shown in fig. 1, step S1 is to perform real-time monitoring on the agricultural environment to obtain a monitoring image; wherein, carry out real time monitoring to agricultural environment in order to obtain the step of control image, include:
s11: detecting whether a flying object exists in the acquisition gradient through an object sensor in a preset radiation range; wherein the acquisition gradient comprises a first acquisition gradient, a second acquisition gradient and a third acquisition gradient;
s12: if the flying object is detected to exist in the radiation range, judging the acquisition gradient of the flying object, and judging whether the brightness of the agricultural environment reaches a light source threshold value corresponding to the acquisition gradient through a light source sensor; if the brightness of the LED reaches the light source threshold value, the brightness of the LED reaches the light source threshold value through a light supplement lamp, and if the brightness of the LED reaches the light source threshold value, monitoring data are obtained through an imaging element; the light supplementing lamp comprises a first light supplementing lamp, a second light supplementing lamp and a third light supplementing lamp; a first light supplement lamp corresponds to the first acquisition gradient, a second light supplement lamp corresponds to the second acquisition gradient, and a third light supplement lamp corresponds to the third acquisition gradient;
s13: carrying out standardization processing on the monitoring data to form characteristic information;
s14: and imaging the characteristic information to form a monitoring image.
Specifically, in step S11, during the process of detecting whether the flying object exists in the acquisition gradient by the object sensor within the preset radiation range,
the radiation range takes a central point of an imaging element when acquiring monitoring data as an origin point and takes the diameter of a lens of the imaging element as a diameter;
the first acquisition gradient, the second acquisition gradient and the third acquisition gradient are the connecting line distances with the central point of the radiation range; for example, the first acquisition gradient is 0 to 5 meters away from the center point of the radiation range, the second acquisition gradient is 5 to 10 meters away from the center point of the radiation range, and the third acquisition gradient is 10 to 20 meters away from the center point of the radiation range;
in step S12, the light source threshold corresponds to the acquisition gradient, and the longer the distance of the acquisition gradient, the higher the light source threshold;
in step S13, the characteristic information is the monitoring data including the flying object, that is, the monitoring data including black pixels;
in step S14, the step of performing an imaging process on the feature information to form a monitoring image includes:
s141: preliminarily locking the characteristic information to lock black pixel points included in the characteristic information in a first region;
s142: intercepting the first area to form first data;
s143: converting the first data into an image mode to form a monitoring image;
for example, when a flying object appears in a crop field, firstly, an object sensor detects that the flying object enters, then, the distance of the flying object is confirmed, and whether light supplement is needed is judged by a light source sensor, when light is satisfied, a shutter is triggered to be an imaging element to shoot the flying object so as to acquire monitoring data, wherein the imaging element is arranged on an image collector, the object sensor and the light source sensor can be arranged on the image collector, or can be separately arranged and connected with the image collector so as to accurately capture a monitoring image.
In the embodiment shown in fig. 1, step S2 is to pre-process the monitoring image based on the image locking algorithm to form the target image; the method comprises the following steps of preprocessing a monitoring image based on an image locking algorithm to form a target image, wherein the steps comprise:
s21: carrying out geometric position standardization processing on the monitoring image based on an image locking algorithm to form a standard image with a preset size; wherein, the image locking algorithm is as follows: taking a black pixel point set in the monitoring image as a bird embryonic set through a preset rule in a processor; cutting the bird embryonic form by taking the geometric shape as the center and radiating outwards according to the preset size;
s22: carrying out image gray scale normalization processing on the standard image to form a target image;
in this embodiment, the width of the preprocessed target image is 100, the height is 120, the distance between the leftmost side and the rightmost side of the bird nests set and the leftmost edge and the rightmost edge of the target image is 10, and the distance between the center of the bird nests set and the uppermost edge and the lowermost edge of the target image is 20 and 40, respectively.
Specifically, in step S1, after the monitoring image is acquired by the imaging element, the monitoring image is normalized, so that the pattern including the flying object is identified.
In the embodiment shown in fig. 1, step S3 is to analogize the target image with pre-stored sample data to obtain a similarity value; wherein, the step of analogizing the target image and the pre-stored sample data to obtain a similarity value comprises:
s31: pre-training a flyer recognition model through a convolutional neural network;
s32: storing the sample data to the flying object identification model to form a flying bird identification model;
s33: and inputting the target image into the bird recognition model so that the bird recognition model forms a similarity value by analogy with the bird embryonic set in the target image and the sample data.
The method comprises the following steps of pre-training a flyer recognition model through a convolutional neural network, wherein the steps comprise:
s311: receiving an input flyer image sample;
s312: carrying out normalization processing on the flyer image sample to obtain a flyer image set with a preset size;
s313: processing the flyer image set by sequentially passing through a preset number of convolution layers and full-connection layers to form a flyer identification model; wherein a preset number of filters are arranged in the roll of base layer; the filter includes an activation function, and a sliding step size; and, a preset number of neurons are provided in the full junction layer.
In step S32, storing the sample data in the flying object recognition model to form a flying bird recognition model, that is, inputting pictures of flying birds frequently flying into the crop field into the flying object recognition model, wherein the input is not only traditional input, and if the flying object image sample includes images of flying birds, the pictures of flying birds frequently flying into the crop field can be pre-selected in the flying object recognition model by means of a network connection to form the flying bird recognition model;
in step S33, when the bird model is a mature model capable of identifying birds and the target image obtained in step S2 is input into the bird identification model, the bird model may correspond to a template of the bird (image of sample data) according to the trained neural network parameters, and then the template of the bird is analogized to the target data to obtain a similarity value.
In the embodiment shown in fig. 1, in step S4, if the similarity value is not lower than the preset threshold, the bird-driving sounding is started to complete bird driving; wherein, if the similarity value is not lower than the preset threshold value, the step of starting the bird-repelling singing to finish the bird-repelling is carried out, and the method comprises the following steps:
s41: judging whether the similarity value is not lower than a preset threshold value or not; the specific numerical value of the preset threshold is not limited, and may be determined according to the bird situation of the crop field on the spot, in the embodiment, if too many birds, the value of the preset threshold is set to be lower, so that the trace of the birds can be comprehensively captured, and if too few birds, the value of the threshold is set to be higher, so that the calculation amount is reduced;
s42: if the similarity value is not lower than the preset threshold value, triggering the audio frequency prestored in the memory through a trigger instruction to start bird repelling and sounding to finish bird repelling; the audio is the audio (such as the sound of a corresponding natural enemy) downloaded or recorded aiming at different birds according to the body sizes, species and the like of the birds, or is the bird-repelling audio directly using firecrackers, dog sounds, gunshots and other types and is uniformly stored in a memory.
In addition, the method further comprises the following steps:
s5: transmitting the monitoring image to a client; the client is a terminal, can be a mobile phone terminal or a PC terminal, so that a crop field owner can monitor the condition of the crop field in real time;
wherein, the step of transmitting the monitoring image to the client comprises:
s51: sending a connection request to the imaging element through the client; the wireless connection mode or the wired connection mode can be adopted;
s52: analyzing the matched password according to the connection request, and if the matched password is consistent with the pre-stored password, establishing connection between the client and the imaging element through the connection request;
s53: on the basis of establishing the connection, if the imaging element acquires the monitoring data, sending a bird repelling prompt to the client and sending a monitoring image to the client;
in step S51, the connection request is not a simple character, and when the connection request is generated, an input password of the client needs to be acquired, where the password is a password corresponding to the imaging elements one to one;
in step S52, the client and the imaging element are always connected, and if disconnection is required, a disconnection application needs to be made at the client.
Moreover, the client may also collect the audio of the crop field when sending the monitoring data, and the specific implementation method is not described herein.
The intelligent bird repelling method provided by the invention comprises the steps of monitoring an agricultural environment in real time to obtain a monitoring image, preprocessing the monitoring image based on an image locking algorithm to form a target image, comparing the target image with pre-stored sample data to obtain a similarity value, starting bird repelling sounding to finish bird repelling if the similarity value is not lower than a preset threshold value, thus being compatible with image identification, placing a plurality of devices at intervals, preventing the influence of birds in an all-round and large-area manner, monitoring a crop production field, supporting the transmission of a data background mobile phone end of an image identifier and a PC (personal computer), facilitating the management of workers, having low manufacturing cost, being suitable for mass production and placement, having wide coverage range, greatly reducing the difficulty of repelling birds outdoors, repelling birds in a targeted manner, and having simple placement method and less influence by natural disasters and severe weather, from the electric energy recycling of integral type, possess longer life, can combine together with other outdoor agricultural implements simultaneously, like irrigator, outdoor light, crops support etc. very big convenience and expanded placing of equipment and be restricted to the place influence.
As described above, in the embodiment shown in fig. 1, the intelligent bird repelling method provided by the invention has the following advantages: detecting whether a flying object exists in the acquisition gradient through an object sensor in a preset radiation range, and capturing and judging whether the flying object exists in a specific distance; if the flying object is detected to exist in the radiation range, judging the acquisition gradient of the flying object, judging whether the brightness of the agricultural environment reaches a light source threshold corresponding to the acquisition gradient through a light source sensor, if the brightness of the agricultural environment does not reach the light source threshold, enabling the brightness to reach the light source threshold through a light supplement lamp, and enabling each frame of image to be clearly visible through a light supplement mode so as to conveniently identify whether the flying object is a bird; thirdly, pre-storing the audio frequency into a memory, triggering the audio frequency through a trigger instruction to start bird repelling and sounding to finish bird repelling if the similarity value is not lower than a preset threshold value, namely automatically performing sounding and repelling if the flyer is judged to be a bird, wherein the whole process is free of manual participation, the full-automatic operation is realized, and the repelling precision is high after multiple judgments; and fourthly, automatically preprocessing the target image according to three dimensions, thereby improving the bird identification precision and preventing the birds from being waited by buzzing endlessly when aerial agricultural sprinklers or irrigators fly over.
As shown in fig. 2, the present invention provides an intelligent bird repelling device 100, which can be installed in an electronic device. According to the realized functions, the intelligent bird repelling device 100 can comprise an image recognizer 101, a target image unit 102, a similarity value calculation unit 103 and a sounding trigger unit 104. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the image recognizer 101 is used for monitoring the agricultural environment in real time to obtain a monitoring image;
the target image unit 102 is used for preprocessing the monitoring image based on an image locking algorithm to form a target image;
a similarity value calculation unit 103 for performing an analogy between the target image and pre-stored sample data to obtain a similarity value;
and the sounding triggering unit 104 is used for judging the size of the similarity value, and starting the bird-driving sounding to drive birds if the similarity value is not lower than a preset threshold value.
The step of monitoring the agricultural environment in real time by the image recognizer 101 to obtain a monitoring image includes:
s11: detecting whether a flying object exists in the acquisition gradient through an object sensor in a preset radiation range; wherein the acquisition gradient comprises a first acquisition gradient, a second acquisition gradient and a third acquisition gradient;
s12: if the flying object is detected to exist in the radiation range, judging the acquisition gradient of the flying object, and judging whether the brightness of the agricultural environment reaches a light source threshold value corresponding to the acquisition gradient through a light source sensor; if the brightness of the LED reaches the light source threshold value, the brightness of the LED reaches the light source threshold value through a light supplement lamp, and if the brightness of the LED reaches the light source threshold value, monitoring data are obtained through an imaging element; the light supplementing lamp comprises a first light supplementing lamp, a second light supplementing lamp and a third light supplementing lamp; the first light supplement lamp corresponds to the first acquisition gradient, the second light supplement lamp corresponds to the second acquisition gradient, and the third light supplement lamp corresponds to the third acquisition gradient;
carrying out standardization processing on the monitoring data to form characteristic information;
and imaging the characteristic information to form a monitoring image.
The target image unit 102 is used for preprocessing the monitoring image based on an image locking algorithm to form a target image, and comprises the following steps:
carrying out geometric position standardization processing on the monitoring image based on an image locking algorithm to form a standard image with a preset size; wherein, the image locking algorithm is as follows: taking a black pixel point set in the monitoring image as a bird embryonic set through a preset rule in a processor; cutting the bird embryonic form by taking the geometric shape as the center and radiating outwards according to the preset size;
performing image gray scale normalization processing on the standard image to form a target image
The step of the similarity value calculating unit 103 analogizing the target image with pre-stored sample data to obtain a similarity value includes:
pre-training a flyer recognition model through a convolutional neural network;
storing the sample data to the flying object identification model to form a flying bird identification model;
and inputting the target image into the bird recognition model so that the bird recognition model forms a similarity value by analogy with the bird embryonic set in the target image and the sample data.
Receiving an input flyer image sample;
carrying out normalization processing on the flyer image sample to obtain a flyer image set with a preset size;
processing the flyer image set by sequentially passing through a preset number of convolution layers and full-connection layers to form a flyer identification model; wherein a preset number of filters are arranged in the roll of base layer; the filter includes an activation function, and a sliding step size; and, a preset number of neurons are provided in the full junction layer.
The sounding triggering unit 104 is configured to determine a similarity value, and if the similarity value is not lower than a preset threshold, start a bird-driving sounding to drive birds, including:
judging whether the similarity value is not lower than a preset threshold value or not; the specific numerical value of the preset threshold is not limited, and may be determined according to the bird situation of the crop field on the spot, in the embodiment, if too many birds, the value of the preset threshold is set to be lower, so that the trace of the birds can be comprehensively captured, and if too few birds, the value of the threshold is set to be higher, so that the calculation amount is reduced;
if the similarity value is not lower than the preset threshold value, triggering the audio frequency prestored in the memory through a trigger instruction to start bird repelling and sounding to finish bird repelling; the audio is the audio (such as the sound of a corresponding natural enemy) downloaded or recorded aiming at different birds according to the body sizes, species and the like of the birds, or is the bird-repelling audio directly using firecrackers, dog sounds, gunshots and other types and is uniformly stored in a memory.
The system also comprises a real-time monitoring unit, wherein the monitoring unit is used for transmitting the monitoring image to the client, and the step of transmitting the monitoring image to the client comprises the following steps:
sending a connection request to the imaging element through the client; the wireless connection mode or the wired connection mode can be adopted;
analyzing the matched password according to the connection request, and if the matched password is consistent with the pre-stored password, establishing connection between the client and the imaging element through the connection request;
on the basis of establishing the connection, if the imaging element acquires the monitoring data, sending a bird repelling prompt to the client and sending a monitoring image to the client.
In addition, the intelligent bird repelling device provided by the invention comprises a bird-shaped shell, wherein the image recognizer 101 is arranged on the bird-shaped shell; a processor is further arranged on the bird-shaped shell, and the target image unit 102, the similarity value calculation unit 103 and the sounding trigger unit 104 are integrated in the processor, and the processor is connected with a loudspeaker device; moreover, grooves are arranged on the wings at the two sides of the bird-shaped shell, and a solar charging panel is arranged in the grooves; the solar charging panel is used for providing power for the image recognizer 101 and the speaker device.
Specifically, in the present embodiment, the bird-shaped mold is an eagle-shaped mold, but the shape of the eagle is not limited to placing the mold, the shape can be changed according to the actual situation, and the changed shape is generally the natural enemy of common birds: owl, hawk, sparrow hawk, bald eagle and other species; the material of the mould can be plastic, wood, rubber, stainless steel, heavy metal and other materials which are preserved for a long time; the wings at two sides of the bird model (eagle-shaped shell) are provided with corresponding grooves for placing or binding the purchased solar charging panel, the electric wire can be placed in the hollow part of the abdomen of the model and is directly connected with the neck image recognizer to provide the needed power supply for the bird model, and the integrated electric energy can be recycled; a loudspeaker or a small-sized sound box and the like are arranged below the tail feather of the bird model and used for being connected with an imager at the neck to identify and play out the sound, and a power supply can be provided for the solar charging panel through a wire of the hollow solar charging panel at the belly so as to support the bird repelling sound or the audio amplification play out when the flying bird comes; the rear of the two feet of the bird mould is provided with a vertical metal long stick, the stick body can adopt a solid or hollow mode, the solid stick supports the wireless information transmission of the image recognizer, the hollow stick supports the limited information transmission of the image recognizer, the whole long stick is used for fixing the position and placement of the whole mould, and can also be integrated or installed in other appliances or tree fields, the length of the fixed support stick can be adjusted and designed, and the bird mould is relatively flexible;
this fixed unified standardization drives bird mould (hawk type shell), can the compatible relevant props bird props thing and equipment of placing, can be better place multiple equipment and devices such as image recognizer, public address utensil, solar charging panel, and the circuit of each equipment is placed in bird mould cavity belly, effectively protect the safety of electric wire and do not receive external environment's influence, this has formed bright contrast with the device of market single function, and in the aspect of other devices or the equipment of protection equipment, can form the circulation of oneself in the interior, accomplish full-automatic bird that drives.
As described above, the intelligent bird repelling device 100 provided by the invention firstly monitors the agricultural environment in real time through the image recognizer 101 to obtain a monitoring image, then preprocesses the monitoring image based on an image locking algorithm through the target image unit 102 to form a target image, then analogizes the target image with pre-stored sample data through the similarity value calculation unit 103 to obtain a similarity value, judges the size of the similarity value through the whistle trigger unit 104, if the similarity value is not lower than a preset threshold value, starts the whistle of the whistle dispelling to finish the whistle of the bird dispelling, so that the image recognition is compatible, a plurality of devices are placed at intervals, the influence of the birds can be prevented in an all-round large area, the crop production field can be monitored, the data background mobile phone end of the image recognizer is supported to be sent by a PC, the management of workers is convenient, the manufacturing cost is low, and the intelligent bird repelling device is suitable for mass production and placement, coverage is wide, greatly reduce the outdoor degree of difficulty of driving the bird, it is pointed to drive the bird, and the method is placed simply, it is less with bad weather influence to receive natural disasters, from the electric energy cyclic utilization of integral type, possess longer life, simultaneously can combine together with other outdoor agricultural implements, if irrigator, outdoor lighting lamp, crops support etc., very big convenient and expanded placing of equipment is restricted to the place influence, have in addition to drive bird appearance mould container (bird type mould), can greatly limit compatible current drive bird technique and equipment, the set of multi-functional kludge, make things convenient for staff's modification and dismantlement, reduce equipment loss and use.
The intelligent bird repelling device 100 provided by the invention has the following advantages: detecting whether a flying object exists in the acquisition gradient through an object sensor in a preset radiation range, and capturing and judging whether the flying object exists in a specific distance; if the flying object is detected to exist in the radiation range, judging the acquisition gradient of the flying object, judging whether the brightness of the agricultural environment reaches a light source threshold corresponding to the acquisition gradient through a light source sensor, if the brightness of the agricultural environment does not reach the light source threshold, enabling the brightness to reach the light source threshold through a light supplement lamp, and enabling each frame of image to be clearly visible through a light supplement mode so as to conveniently identify whether the flying object is a bird; thirdly, pre-storing the audio frequency into a memory, triggering the audio frequency through a trigger instruction to start bird repelling and sounding to finish bird repelling if the similarity value is not lower than the preset threshold value, namely automatically performing sounding and repelling if the flyer is judged to be a bird, wherein the whole process is free of manual participation, the full-automatic operation is realized, and the repelling precision is high after multiple judgments; automatically preprocessing the target image according to three dimensions, thereby improving the bird identification precision and preventing the birds from being buzzed and caught without end when aerial agricultural sprinklers or irrigators fly over; the bird repelling appearance mold container can be compatible with the existing bird repelling technology and equipment to the maximum extent, and a multifunctional assembling machine is integrated, so that workers can conveniently modify and disassemble the bird repelling appearance mold container, and equipment loss and use are reduced.
As shown in fig. 3, the present invention provides an electronic device 1 for an intelligent bird repelling method.
The electronic device 1 may include a processor 10, a memory 11 and a bus, and may further include a computer program, such as an intelligent bird repelling program 12, stored in the memory 11 and operable on the processor 10.
The memory 11 includes at least one type of readable storage medium, which includes flash memory, removable hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used to store not only application software installed in the electronic device 1 and various types of data, such as codes of the intelligent bird repelling program, but also temporarily store data that has been output or will be output.
The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the whole electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device 1 by operating or executing programs or modules (e.g., an intelligent bird repelling program, etc.) stored in the memory 11 and calling data stored in the memory 11.
The bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
Fig. 3 only shows an electronic device with components, and it will be understood by a person skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or a combination of certain components, or a different arrangement of components.
For example, although not shown, the electronic device 1 may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so as to implement functions of charge management, discharge management, power consumption management, and the like through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device 1 may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
Further, the electronic device 1 may further include a network interface, and optionally, the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a bluetooth interface, etc.), which are generally used for establishing a communication connection between the electronic device 1 and other electronic devices.
Optionally, the electronic device 1 may further comprise a user interface, which may be a Display (Display), an input unit (such as a Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable for displaying information processed in the electronic device 1 and for displaying a visualized user interface, among other things.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The intelligent bird repelling program 12 stored in the memory 11 of the electronic device 1 is a combination of instructions, and when running in the processor 10, can realize:
monitoring an agricultural environment in real time to obtain a monitoring image;
preprocessing the monitoring image based on an image locking algorithm to form a target image;
carrying out analogy on the target image and pre-stored sample data to obtain a similarity value;
and if the similarity value is not lower than the preset threshold value, starting bird repelling sounding to finish bird repelling.
Specifically, the specific implementation method of the processor 10 for the instruction may refer to the description of the relevant steps in the embodiment corresponding to fig. 1, which is not described herein again. It should be emphasized that, in order to further ensure the privacy and security of the intelligent bird repelling, the data of the intelligent bird repelling is stored in the node of the block chain where the server cluster is located.
Further, the integrated modules/units of the electronic device 1, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. The computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
An embodiment of the present invention further provides a computer-readable storage medium, where the storage medium may be nonvolatile or volatile, and the storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements:
monitoring an agricultural environment in real time to obtain a monitoring image;
preprocessing the monitoring image based on an image locking algorithm to form a target image;
carrying out analogy on the target image and pre-stored sample data to obtain a similarity value;
and if the similarity value is not lower than the preset threshold value, starting bird repelling sounding to finish bird repelling.
Specifically, the specific implementation method of the computer program when being executed by the processor may refer to the description of the relevant steps in the intelligent bird repelling method in the embodiment, which is not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. An intelligent bird repelling method is characterized by comprising the following steps:
monitoring an agricultural environment in real time to obtain a monitoring image;
preprocessing the monitoring image based on an image locking algorithm to form a target image;
carrying out analogy on the target image and pre-stored sample data to obtain a similarity value;
and if the similarity value is not lower than a preset threshold value, starting bird repelling sounding to finish bird repelling.
2. An intelligent bird repelling method according to claim 1, wherein the real-time monitoring of the agricultural environment to obtain the monitoring image comprises:
detecting whether a flying object exists in the acquisition gradient through an object sensor in a preset radiation range; wherein the acquisition gradients comprise a first acquisition gradient, a second acquisition gradient and a third acquisition gradient;
if the flying object is detected to exist in the radiation range, judging the acquisition gradient of the flying object, and judging whether the brightness of the agricultural environment reaches a light source threshold value corresponding to the acquisition gradient through a light source sensor; if the brightness does not reach the light source threshold value, the brightness reaches the light source threshold value through a light supplement lamp, and if the brightness reaches the light source threshold value, monitoring data are obtained through an imaging element; the light supplement lamp comprises a first light supplement lamp, a second light supplement lamp and a third light supplement lamp; the first light supplement lamp corresponds to the first acquisition gradient, the second light supplement lamp corresponds to the second acquisition gradient, and the third light supplement lamp corresponds to the third acquisition gradient;
carrying out standardization processing on the monitoring data to form characteristic information;
and carrying out imaging processing on the characteristic information to form a monitoring image.
3. An intelligent bird repelling method according to claim 2, wherein the imaging the characteristic information to form a monitoring image comprises:
preliminarily locking the characteristic information to lock black pixel points included in the characteristic information in a first region;
intercepting the first area to form first data;
and converting the first data into an image mode to form a monitoring image.
4. An intelligent bird repelling method according to claim 3, wherein the pre-processing of the monitoring image based on an image locking algorithm to form a target image comprises:
carrying out geometric position standardization processing on the monitoring image based on an image locking algorithm to form a standard image with a preset size; wherein the image locking algorithm is as follows: taking a black pixel point set in the monitoring image as a bird embryonic set through a preset rule in a processor; cutting the bird embryonic form by taking the geometric shape of the bird embryonic form as a center and radiating outwards according to a preset size;
and carrying out image gray scale normalization processing on the standard image to form a target image.
5. An intelligent bird repelling method according to claim 4, wherein the analogizing the target image with pre-stored sample data to obtain a similarity value comprises:
pre-training a flyer recognition model through a convolutional neural network;
storing sample data to the flying object identification model to form a flying bird identification model;
inputting the target image into the flying bird recognition model, so that the flying bird recognition model forms a similarity value with the sample data by analogy with the set of the flying bird embryonic forms in the target image.
6. An intelligent bird repelling method according to claim 5, wherein the pre-training of the flying object recognition model by the convolutional neural network comprises:
receiving an input flyer image sample;
carrying out normalization processing on the flying object image sample to obtain a flying object image set with a preset size;
processing the flying object image set by sequentially passing through a preset number of convolution layers and full-connection layers to form a flying object identification model; wherein a preset number of filters are arranged in the roll base layer; the filter comprises an activation function and a sliding step length; and a preset number of neurons are arranged in the full connection layer.
7. An intelligent bird repelling method according to claim 6, further comprising: transmitting the monitoring image to a client; wherein the transmitting the monitoring image to a client includes:
sending, by the client, a connection request to the imaging element;
analyzing a matched password according to the connection request, and if the matched password is consistent with a pre-stored password, establishing connection between the client and the imaging element through the connection request;
and if the imaging element acquires monitoring data, sending a bird repelling prompt to the client based on the connection, and sending a monitoring image to the client.
8. The utility model provides an intelligence bird repellent device which characterized in that, the device includes:
the image recognizer is used for monitoring the agricultural environment in real time to obtain a monitoring image;
the target image unit is used for preprocessing the monitoring image based on an image locking algorithm to form a target image;
the similarity value calculation unit is used for carrying out analogy on the target image and pre-stored sample data to obtain a similarity value;
and the sounding triggering unit is used for judging the size of the similarity value, and starting the bird-driving sounding to drive birds if the similarity value is not lower than a preset threshold value.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the steps in the intelligent bird repelling method of any one of claims 1-7.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the intelligent bird repelling method according to any one of claims 1 to 7.
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