1. An unmanned aerial vehicle-based livestock and poultry breeding pollution source monitoring system is characterized by comprising an infrared detection module, a radar detection module, an audio identification module, an image identification module, a wireless transmission module, a processing module and a pollution source identification module;

the infrared detection module is used for converting an infrared radiation signal detected from a region to be detected into an infrared thermal imaging graph and transmitting the infrared thermal imaging graph to the processing module through the wireless transmission module;

the radar detection module is used for sending a pulse signal to the area to be detected, processing the received reflection signal to obtain a differential circuit signal, and sending the differential circuit signal to the processing module through the wireless transmission module;

the audio identification module is used for collecting the sound wave signals of the area to be detected and sending the collected sound wave signals to the processing module through the wireless transmission module;

the image identification module is used for shooting the image of the area to be detected, carrying out image identification on the image according to a preset program to obtain image identification information, and sending the image identification information to the processing module through the wireless transmission module;

the processing module is used for obtaining pollution source information of the area to be detected according to the infrared thermal imaging image, the differential circuit signal, the sound wave signal and the image identification information respectively and sending the pollution source information to the pollution source identification module;

and the pollution source identification module obtains the types, the quantity and the longitude and latitude coordinates of the livestock and poultry in the area to be detected according to the obtained pollution source information.

2. The system according to claim 1, wherein the obtaining of the pollution source information of the region to be measured according to the infrared thermal imaging graph, the differential circuit signal, the acoustic wave signal and the image identification information respectively comprises:

obtaining the types, the number and the longitude and latitude coordinates of the livestock and poultry in the area to be detected according to the infrared thermal imaging graph;

obtaining the types of the livestock and poultry in the area to be detected according to the differential circuit signal;

obtaining the types of the livestock and poultry in the area to be detected according to the sound wave signals;

and obtaining the types and the quantity of the livestock and poultry in the area to be detected according to the image identification information.

3. The system of claim 2, wherein obtaining the type, the number and the longitude and latitude coordinates of the livestock and poultry in the area to be detected according to the infrared thermal imaging map comprises:

analyzing and determining the types of the livestock and poultry in the region to be detected according to the heat quantity in the infrared thermal imaging image and the imaging area;

determining the number of livestock and poultry in the area to be detected according to the imaging number in the infrared thermal imaging image;

and calculating the longitude and latitude coordinates of the area to be detected according to the infrared detection position of the area to be detected.

4. The system according to claim 2, wherein obtaining the types of livestock and poultry in the region to be tested according to the differential circuit signal comprises:

differential circuit output signal templates of all livestock and poultry types are prestored in the processing module;

and matching the differential circuit signal with the differential circuit output signal template to determine the types of the livestock and poultry in the area to be detected.

5. The system according to claim 2, wherein obtaining the types of the livestock and poultry in the region to be detected according to the sound wave signal comprises:

the processing module is pre-stored with acoustic frequency templates of all livestock and poultry types;

and matching the sound wave signals with the sound wave frequency template to determine the types of the livestock and poultry in the area to be detected.

6. The system of claim 1, wherein the preset program comprises a livestock matching model program and a quantity identification program, wherein:

the livestock and poultry matching model program is used for identifying the types of livestock and poultry in the images;

and the quantity identification program is used for identifying the quantity of the livestock and poultry in the image.

7. The system of claim 1, wherein the infrared detection module is configured to convert the infrared radiation signals detected from the region under test into an infrared thermal image, and comprises:

converting the infrared radiation signal detected by the region to be detected into an electric signal through an infrared sensor; and obtaining the infrared thermal imaging graph according to the electric signal.

8. The system of claim 1, wherein the radar detection module, configured to send a pulse signal to the area under test, comprises:

and controlling a pulse oscillator to generate a narrow pulse signal through an encoder, and transmitting the narrow pulse signal to the area to be detected through a transmitting antenna.

9. The system of claim 1, wherein the audio recognition module comprises a noise filter and a sound wave sensor;

the noise filter is used for filtering the flight noise of the unmanned aerial vehicle and other non-target background noise;

the sound wave sensor is used for collecting the filtered sound.

10. The system of claim 1, further comprising: and the storage module is used for storing the obtained infrared thermal imaging graph, the differential circuit signal, the sound wave signal, the image identification information and the pollution source information of the area to be detected.

Background

With the rapid development of the economic society of China and the continuous acceleration of the urbanization process, water pollution becomes an important factor for restricting the sustainable development of the national economy. The water pollution is mainly from agricultural non-point source pollution, livestock and poultry breeding pollution, aquaculture pollution, rural life pollution, river endogenous pollution and the like, wherein the livestock and poultry breeding pollution has great influence on the water environment in various pollution sources, so that the pollution source investigation work has important significance on water pollution prevention and control.

The traditional livestock and poultry breeding pollution source investigation working method mainly comprises an on-site investigation method and an unmanned aerial vehicle aerial photography method. The on-site investigation method is a method for investigating and recording by investigators according to the situation of a breeding site, although the method is high in accuracy, time and labor are consumed, and investigation efficiency is low, while the traditional unmanned aerial vehicle aerial photography method is a method for shooting and recording near a livestock breeding area by using an unmanned aerial vehicle, manpower and material resources are saved, but when the aerial photographs are analyzed in a post-processing mode, livestock breeding pollution sources need to be screened out from numerous photographs, and breeding pollution sources of different livestock and poultry types cannot be accurately distinguished, so that the efficiency and the accuracy of livestock breeding pollution source investigation work are influenced.

Disclosure of Invention

Based on this, this application embodiment provides a beasts and birds are bred pollution sources monitoring system based on unmanned aerial vehicle, can satisfy monitoring accuracy when, has higher efficiency.

An unmanned aerial vehicle-based livestock and poultry breeding pollution source monitoring system comprises an infrared detection module, a radar detection module, an audio identification module, an image identification module, a wireless transmission module, a processing module and a pollution source identification module;

the infrared detection module is used for converting an infrared radiation signal detected from a region to be detected into an infrared thermal imaging graph and transmitting the infrared thermal imaging graph to the processing module through the wireless transmission module;

the radar detection module is used for sending a pulse signal to the area to be detected, processing the received reflection signal to obtain a differential circuit signal, and sending the differential circuit signal to the processing module through the wireless transmission module;

the audio identification module is used for collecting the sound wave signals of the area to be detected and sending the collected sound wave signals to the processing module through the wireless transmission module;

the image identification module is used for shooting the image of the area to be detected, carrying out image identification on the image according to a preset program to obtain image identification information, and sending the image identification information to the processing module through the wireless transmission module;

the processing module is used for obtaining pollution source information of the area to be detected according to the infrared thermal imaging image, the differential circuit signal, the sound wave signal and the image identification information respectively and sending the pollution source information to the pollution source identification module;

and the pollution source identification module obtains the types, the quantity and the longitude and latitude coordinates of the livestock and poultry in the area to be detected according to the obtained pollution source information.

In one embodiment, the obtaining the pollution source information of the region to be measured according to the infrared thermal imaging graph, the differential circuit signal, the acoustic wave signal, and the image identification information respectively includes:

obtaining the types, the number and the longitude and latitude coordinates of the livestock and poultry in the area to be detected according to the infrared thermal imaging graph;

obtaining the types of the livestock and poultry in the area to be detected according to the differential circuit signal;

obtaining the types of the livestock and poultry in the area to be detected according to the sound wave signals;

and obtaining the types and the quantity of the livestock and poultry in the area to be detected according to the image identification information.

In one embodiment, obtaining the type, the number, and the longitude and latitude coordinates of the livestock and poultry in the area to be detected according to the infrared thermal imaging diagram includes:

analyzing and determining the types of the livestock and poultry in the region to be detected according to the heat quantity in the infrared thermal imaging image and the imaging area;

determining the number of livestock and poultry in the area to be detected according to the imaging number in the infrared thermal imaging image;

and calculating the longitude and latitude coordinates of the area to be detected according to the infrared detection position of the area to be detected.

In one embodiment, obtaining the types of the livestock and poultry in the region to be detected according to the differential circuit signal includes:

differential circuit output signal templates of all livestock and poultry types are prestored in the processing module;

and matching the differential circuit signal with the differential circuit output signal template to determine the types of the livestock and poultry in the area to be detected.

In one embodiment, obtaining the types of the livestock and poultry in the region to be detected according to the sound wave signal includes:

the processing module is pre-stored with acoustic frequency templates of all livestock and poultry types;

and matching the sound wave signals with the sound wave frequency template to determine the types of the livestock and poultry in the area to be detected.

In one embodiment, the preset program includes a livestock and poultry matching model program and a quantity identification program, wherein:

the livestock and poultry matching model program is used for identifying the types of livestock and poultry in the images;

and the quantity identification program is used for identifying the quantity of the livestock and poultry in the image.

In one embodiment, the infrared detection module is configured to convert an infrared radiation signal detected from an area to be detected into an infrared thermal image, and includes:

converting the infrared radiation signal detected by the region to be detected into an electric signal through an infrared sensor; and obtaining the infrared thermal imaging graph according to the electric signal.

In one embodiment, the radar detection module is configured to send a pulse signal to the region to be detected, and includes:

and controlling a pulse oscillator to generate a narrow pulse signal through an encoder, and transmitting the narrow pulse signal to the area to be detected through a transmitting antenna.

In one embodiment, the audio recognition module comprises a noise filter and an acoustic wave sensor;

the noise filter is used for filtering the flight noise of the unmanned aerial vehicle and other non-target background noise;

the sound wave sensor is used for collecting the filtered sound.

In one embodiment, the system further comprises: and the storage module is used for storing the obtained infrared thermal imaging graph, the differential circuit signal, the sound wave signal, the image identification information and the pollution source information of the area to be detected.

The beneficial effects brought by the technical scheme provided by the embodiment of the application at least comprise:

the type, the number and the longitude and latitude coordinates of the livestock and poultry in the livestock and poultry breeding pollution source are detected through the infrared radiation signals, the reflection signals, the sound wave signals and the image information in the area to be detected, so that the monitoring precision is met, and meanwhile, the efficiency is high.

Drawings

Fig. 1 is a schematic view of a pollution source monitoring system for livestock and poultry breeding based on an unmanned aerial vehicle provided in an embodiment of the present application;

fig. 2 is a flowchart illustrating an operation of an infrared detection module according to an embodiment of the present disclosure;

fig. 3 is a flowchart illustrating the operation of a radar detection module according to an embodiment of the present disclosure;

fig. 4 is a flowchart illustrating the operation of an audio recognition module according to an embodiment of the present disclosure;

fig. 5 is a schematic diagram of pollution source identification by the system according to an embodiment of the present disclosure.

Detailed Description

To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

In the description of the embodiments of the present application, it should also be noted that, unless otherwise explicitly stated or limited, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. Specific meanings of the above terms in the embodiments of the present application can be understood in specific cases by those of ordinary skill in the art.

The application provides a beasts and birds are bred pollution sources monitoring system based on unmanned aerial vehicle, as shown in figure 1, this system includes: the device comprises an infrared detection module, a radar detection module, an audio identification module, an image identification module, a wireless transmission module, a processing module and a pollution source identification module.

In this embodiment of the application, the infrared detection module is configured to convert an infrared radiation signal detected from a region to be detected into an infrared thermal imaging graph, and transmit the infrared thermal imaging graph to the processing module through the wireless transmission module.

Specifically, as shown in fig. 2, the infrared detection module incorporates an infrared detection technology into the unmanned aerial vehicle system. When unmanned aerial vehicle flies near beasts and birds breed region, infrared sensor is gathered to the infrared radiation energy of being surveyed beasts and birds, and infrared radiation is received to pyroelectric element among the infrared sensor, can outwards release electric charge during the change that the temperature takes place, and release electric charge can convert the output signal of telecommunication into, transmits the signal of telecommunication to processing module through wireless transmission module after internal processing to show infrared thermal imaging picture in the aerial photography monitor that processing module connects again. Investigators find suspicious livestock and poultry breeding pollution sources from the infrared thermal imaging images, press a photographing key of the unmanned aerial vehicle remote controller, and record the imaging images of the livestock and poultry pollution sources.

In the embodiment of the application, the processing module analyzes and determines the types of livestock and poultry in the area to be detected according to the heat quantity and the imaging area in the infrared thermal imaging image; determining the number of livestock and poultry in the area to be detected according to the imaging number in the infrared thermal imaging image; and calculating the longitude and latitude coordinates of the area to be detected according to the infrared detection position of the area to be detected.

And the radar detection module is used for sending a pulse signal to the area to be detected, processing the received reflected signal to obtain a differential circuit signal, and sending the differential circuit signal to the processing module through the wireless transmission module.

In the embodiment of the application, the radar detection module is composed of an encoder, a pulse oscillator, a transmitting antenna and a receiver.

Referring to fig. 3, the radar detection module utilizes the reflection principle of electromagnetic waves, and the encoder controls the pulse oscillator to generate a narrow pulse signal, which is radiated by the transmitting antenna. The reflected signal is sent to a sampling head of a receiver through an antenna, a signal generated by a pulse oscillator generates a narrow pulse through a delay circuit to be used as a range gate, the received signal is selected, a signal output by the sampling head passes through an integrating circuit to accumulate the received signal, an amplifying and filtering circuit amplifies and filters the signal, a differentiating circuit in a detection circuit differentiates the amplified signal, if no livestock and poultry moving target exists, the output of the differentiating circuit is a fixed value, and if the livestock and poultry moving target exists, the output of the differentiating circuit slightly changes. The differential circuit output signal is sent to the processing module through the wireless transmission module.

The processing module is pre-stored with differential circuit output signal templates of all livestock and poultry types, namely the change rule of the differential circuit output signal corresponding to each livestock and poultry type is fixed, the differential circuit output signal templates of all livestock and poultry types are input into the processing module, the collected differential circuit output signals are matched with the input template signals according to the maximum similarity principle, and the livestock and poultry types in the region to be detected are determined.

And the audio recognition module is used for collecting the sound wave signals of the area to be detected and sending the collected sound wave signals to the processing module through the wireless transmission module.

In the embodiment of the present application, the audio recognition module includes a noise filter and a sound wave sensor, as shown in fig. 4, the noise filter is used for filtering out the flight noise of the unmanned aerial vehicle itself and other non-target background noise; the sound wave sensor is used for collecting the filtered sound.

When unmanned aerial vehicle flies near the region of awaiting measuring, carry out omnidirectional sound wave information collection, noise filter filters unmanned aerial vehicle flight noise itself and other non-target's background interference wave, collects the beasts and birds sound production sound wave that uses the air as the carrier through sound wave sensor after filtering to the sound wave signal that will collect sends to processing module through wireless transmission module.

The processing module is pre-stored with acoustic frequency templates of all livestock and poultry types, namely the acoustic frequency corresponding to each livestock and poultry type,

and matching the collected sound wave signals with a sound wave frequency template, and determining the types of the livestock and poultry in the area to be detected according to the maximum similarity principle.

The image identification module is used for shooting the image of the area to be detected, carrying out image identification on the image according to a preset program to obtain image identification information, and sending the image identification information to the processing module through the wireless transmission module.

In the embodiment of the application, the preset program comprises a livestock and poultry matching model program and a quantity identification program, wherein: the livestock and poultry matching model program is used for identifying the types of livestock and poultry in the images; and the quantity identification program is used for identifying the quantity of the livestock and poultry in the image.

Specifically, the image recognition module in the unmanned aerial vehicle takes an aerial photograph of the livestock breeding area to obtain a basic image, the livestock matching model program matches the basic image with the livestock matching model to recognize the basic image as the livestock of a specific type, the quantity recognition program calculates the quantity of the livestock according to the livestock image in the basic image, and the image recognition information is sent to the processing module through the wireless transmission module.

And the processing module is used for obtaining the pollution source information of the area to be detected according to the infrared thermal imaging image, the differential circuit signal, the sound wave signal and the image identification information respectively and sending the pollution source information to the pollution source identification module.

The pollution source information of the area to be detected can be the types, the number and the longitude and latitude coordinates of the livestock and poultry in the area to be detected, which are obtained according to the infrared thermal imaging graph;

or the types of the livestock and poultry in the area to be detected are obtained according to the differential circuit signals;

or obtaining the types of the livestock and poultry in the area to be detected according to the sound wave signals;

or obtaining the types and the quantity of the livestock and the poultry in the area to be detected according to the image identification information.

And the pollution source identification module obtains the types, the quantity and the longitude and latitude coordinates of the livestock and poultry in the area to be detected according to the obtained pollution source information.

Referring to fig. 5, an alternative contamination source identification process of the present application is given below:

the pollution source identification module sets that A can represent the types of livestock and poultry, B can represent the number of the livestock and poultry, and C can represent the longitude and latitude coordinates of the livestock and poultry; and numeral 1 represents information derived from an infrared thermal imaging chart obtained by using an infrared detection module; numeral 2 indicates information derived from a differential circuit signal obtained by a radar detection module; numeral 3 indicates information derived from the sound wave signal obtained by the audio recognition module, numeral 4 indicates information derived from the image recognition information obtained by the image recognition module,

for example, in the processing module, the types A1, the quantity B1 and the longitude and latitude coordinates C1 of the livestock and poultry in the area to be detected are obtained according to the infrared thermal imaging graph;

obtaining the types A2 of the livestock and poultry in the area to be detected according to the differential circuit signal;

obtaining the types A3 of the livestock and poultry in the area to be detected according to the sound wave signals;

and obtaining the type A4 and the quantity B4 of the livestock and poultry in the region to be detected according to the image identification information.

Meanwhile, the ratio of the infrared thermal imaging image, the differential circuit signal, the sound wave signal and the image identification information identification accuracy coefficient is set to be N1: n2: n3: n4 ═ 0.9: 0.8: 0.5: 1, the information obtained by the image recognition module has the highest accuracy, and the audio recognition module has the lowest accuracy.

The identification program in the pollution source identification module judges the principle of the livestock and poultry type A:

a 1-a 2-A3-a 4, and the types of livestock and poultry are distinguished as a1, a2, A3 and a 4. (specifically, it is shown that the types of the livestock and poultry in the region to be detected identified according to the infrared thermal imaging image, the differential circuit signal, the sound wave signal and the image identification information are the same, that is, a 1-a 2-A3-a 4, the types of the livestock and poultry in the region to be detected can be considered as a1, a2, A3 and a4)

A1 ═ a2 ═ A3 ≠ a4, and the types of livestock and poultry are identified as a1, a2, and A3. (specifically, it is shown that the types of the livestock and poultry in the region to be detected identified according to the infrared thermal imaging image, the differential circuit signal and the sound wave signal are the same, that is, a1 is a2 is A3, but different from a4 identified by the image identification information, the types of the livestock and poultry in the region to be detected can be considered to be distinguished as a1, a2 and A3)

A1 ═ a2 ═ a4 ≠ A3, and the types of livestock and poultry are identified as a1, a2, and a 4. (specifically, it is shown that the types of the livestock and poultry in the region to be detected identified according to the infrared thermal imaging image, the differential circuit signal and the image identification information are the same, namely A1 is A2 is A4, but different from A3 identified by the sound wave signal, the types of the livestock and poultry in the region to be detected can be considered as A1, A2 and A4)

A2 ═ A3 ═ a4 ≠ a1, and the types of livestock and poultry are identified as a2, A3, and a 4. (specifically, it is shown that the types of the livestock and poultry in the region to be detected identified according to the differential circuit signal and the image identification information are the same, that is, a2 is A3 is a4, but different from a1 identified by the infrared thermal imaging diagram, the types of the livestock and poultry in the region to be detected can be considered as a2, A3 and a4)

A1 ═ A3 ═ a4 ≠ a2, and the types of livestock and poultry are identified as a1, A3, and a 4. (specifically, it is shown that the types of the livestock and poultry in the region to be detected identified according to the infrared thermal imaging image, the sound wave signal and the image identification information are the same, that is, a1 is A3 is a4, but different from a2 identified by the differential circuit signal, the types of the livestock and poultry in the region to be detected can be considered as a1, A3 and a4)

A1 ═ a2 ≠ A3 ═ a4, N1+ N2 ═ 1.7, N3+ N4 ═ 1.5, (N1+ N2) > (N3+ N4), and the types of livestock and poultry are distinguished as a1 and a 2. (specifically, the types of livestock and poultry in the area to be detected identified according to the infrared thermal imaging graph and the differential circuit signal are the same; the types of livestock and poultry in the area to be detected identified according to the sound wave signal and the image identification information are the same but different from the types of livestock and poultry in the area to be detected identified according to the infrared thermal imaging graph and the differential circuit signal; A1 is A2 is not equal to A3 is A4; the accuracy coefficient N1 is added with the accuracy coefficient N2 of the differential circuit signal according to the infrared thermal imaging graph, namely N1+ N2 is 1.7; the accuracy coefficient N4 of the image identification information signal is added according to the sound wave signal identification accuracy coefficient N3, namely N3+ N4 is 1.5; and the comparison between the two results shows that (N1+ N2) > (N3+ N4) judges that the types of livestock and poultry are the types A1 and the type A2 of the differential circuit signal)

The following method is adopted to identify the accuracy coefficient according to the infrared thermal imaging image, the differential circuit signal, the sound wave signal and the image identification information, and the coefficient and the highest type are determined as the type of the area to be detected, and the specific process is not repeated.

A1 ═ A3 ≠ a2 ═ a4, N1+ N3 ═ 1.4, N2+ N4 ═ 1.8, (N2+ N4) > (N1+ N3), and the types of livestock and poultry are distinguished as a2 and a 4.

A1 ═ a4 ≠ a2 ═ A3, N1+ N4 ═ 1.9, N2+ N3 ═ 1.3, (N1+ N4) > (N2+ N3), and the types of livestock and poultry are distinguished as a1 and a 4.

A1 ═ a2 ≠ A3 ≠ a4, and the types of livestock and poultry are identified as a1 and a 2.

A1 ═ A3 ≠ a2 ≠ a4, and the types of livestock and poultry are identified as a1 and A3.

A1 ═ a4 ≠ a2 ≠ A3, and the types of livestock and poultry are identified as a1 and a 4.

A2 ═ A3 ≠ a1 ≠ a4, and the types of livestock and poultry are identified as a2 and A3.

A2 ═ a4 ≠ a1 ≠ A3, and the types of livestock and poultry are identified as a2 and a 4.

A3 ═ a4 ≠ a1 ≠ a2, and the types of livestock and poultry are identified as A3 and a 4.

A1 is not equal to A2 is not equal to A3 is not equal to A4, N4 is more than N1 is more than N2 is more than N3, and the type of the livestock is judged to be A4.

In the embodiment of the application, since the number of the livestock and the poultry in the region to be detected is only influenced by the infrared thermal imaging graph B1 and the identification information B4, the number of the livestock and the poultry in the region to be detected is represented as BAnd C, representing the longitude and latitude coordinates C of the livestock and poultry in the area to be detected as C-C1.

The system also comprises a storage module used for storing the obtained infrared thermal imaging image, the differential circuit signal, the sound wave signal, the image identification information and the pollution source information of the area to be detected.

The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the claims. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.