CN110139080B - A method for obtaining and identifying types of high-definition images of remote micro-vectors - Google Patents

Abstract

The invention relates to a method for acquiring and identifying types of high-definition images of remote tiny vector organisms based on the Internet of Things. The present invention firstly installs a network camera and a wireless terminal with macro photography function at the monitoring point, and is connected to a designated server, and the on-site monitoring point is arranged with white gauze in front of the camera head as a background. The macro camera video data is uploaded to the server in real time through the mobile Internet. The server analyzes the video to determine whether there are tiny vector organisms appearing in front of the camera, and if so, activates the macro photography function and uploads the photos to the server in real time; the server uses image recognition software to process the received high-definition photos Vector organism species identification. The invention can monitor the tiny vector organisms all-weather, and monitor multiple monitoring points at the same time, which greatly improves the monitoring efficiency.

Description

A method for obtaining and identifying types of high-definition images of remote micro-vectors

technical field

The invention relates to the field of microscopic vector organism monitoring, in particular to a method for remotely controlling a high-definition macro camera through the Internet of Things to acquire images of microscopic vector organisms in real time and identify their types.

Background technique

At present, the microscopic vector organisms (such as mosquitoes) at outdoor monitoring points are captured on-site by humans, and then brought back to the laboratory for photo analysis for species identification. This method has high labor costs and low efficiency, and is not convenient for timely species identification and timely identification. Early warning to take preventive measures.

SUMMARY OF THE INVENTION

In order to solve the above problems, the present invention provides a method for real-time acquisition of high-definition images of remote tiny vector organisms (mosquitoes) based on the Internet of Things and identifying their types.

The present invention includes the following steps:

Step 1: Build a monitoring network: Install network cameras and wireless terminals with macro photography functions at the monitoring points, and connect to the designated server through the mobile Internet; one server can be connected to multiple monitoring points through the mobile Internet.

Step 2: In the field monitoring point, a white gauze is arranged in front of the macro camera as the background, and the light is sufficient, and the camera is focused on the designated area on the white gauze; this area is used as a place to attract tiny vector organisms, and there are lights and smells. measures; rain protection devices are installed on cameras and lure points.

Step 3: Start the macro camera for macro video shooting, and upload the video data to the designated background server through the mobile Internet in real time.

Step 4: The background server judges whether there are tiny vector organisms (mosquitoes) appearing in front of the camera by analyzing the pictures in the video. The background server is installed with video behavior analysis software, which can determine whether tiny organisms appear in front of the camera.

Step 5: If there are tiny vector organisms appearing in the lens area, activate the macro high-definition zoom-in photo function to take a photo; this step includes three sub-steps:

1) Receive the start signal sent by the backend server through the mobile Internet, and start the camera to zoom in and take pictures. The magnification depends on the size of the tiny vector organisms, generally 50 to 100 times;

2) After zooming in, the tiny vector organisms are still in the lens, and auto-focus is performed to ensure that the target is clear; if the tiny vector organisms move quickly when taking pictures, the photo effect is not ideal;

3) Start taking pictures, if the light is not enough, start flashing pictures; in order to ensure the effect of taking pictures, you can take two or more high-definition pictures in succession, and the magnification and resolution equipment can be adjusted automatically without human intervention;

Step 6: Upload the captured high-definition photos to the designated background server in real time through the mobile Internet;

Step 7: The server uses special image recognition software to identify the types of micro vector organisms on the received high-definition photos.

Preferably, the network macro camera described in step 1 is a network camera with a high-magnification photographing function;

Preferably, the mobile Internet described in step 1 can adopt 3G/4G network, and can be upgraded to 5G network in the future;

Preferably, the background white gauze described in step 2 is similar to a patterned net, and there are certain light sources or smells to attract tiny vector organisms (mosquitoes) to attach.

Preferably, the macro video monitoring described in steps 3 and 4 refers to capturing video through a macro camera and transmitting the data to a background server for video analysis to determine whether there are tiny vector organisms appearing in a designated area.

Preferably, the zoomed-in shooting described in step 5 is different from macro video shooting, and the zoomed-in shooting is a static high-definition photo.

Preferably, the image recognition software described in step 7 is image recognition software dedicated to tiny vector organisms.

The beneficial effects of the present invention are:

1: No need for professionals to observe and sample on-site, and it can monitor micro-vector organisms around the clock.

2: Multiple monitoring points can be monitored at the same time, which greatly improves the efficiency.

3: By taking pictures and sampling in this way, high-definition photos can be obtained at the first time, without disturbing the tiny vector organisms, and the obtained mosquito information is more reliable.

4: Quick identification. Image recognition technology can quickly identify the species of microscopic vector organisms in photos, which can be used by health and epidemic prevention departments as a reference for disease prevention and control.

Description of drawings

FIG. 1 is a specific flow chart of the present invention.

Detailed ways

In order to facilitate the understanding and implementation of the present invention by those skilled in the art, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the embodiments described herein are only used to illustrate and explain the present invention, but not for The invention is limited.

With the rapid development of information technology, macro video image processing technology and macro photography technology have provided a technical means not available in the past for the development of modern science and technology, and have been widely used in various disciplines. At the same time, it also provides a feasible way for the real-time monitoring and evaluation of microscopic vector organisms (mosquitoes), and provides early warning and prevention and control functions for the spread of diseases in real time.

On-site tiny vector organisms (mosquitoes) are easy to appear in the places where the monitoring points are set, and macro cameras cannot accurately capture them, and a certain lure device is required to lure them to the camera for shooting; there are many ways to lure them. , such as light source lure and smell lure.

Multiple monitoring points and background servers can be networked through 3G/4G/5G mobile Internet, and multiple other types of sensors can be assembled on site to form a micro-vector organism (mosquito) monitoring Internet of Things;

See Figure 1 for details: the present invention provides a method for obtaining high-definition images of remote microscopic vector organisms (mosquitoes) based on the Internet of Things; the steps are as follows:

Step 1: Build a monitoring network: Install network cameras and wireless terminals with macro photography functions at the monitoring points, and connect to the designated server through the mobile Internet; a server can be connected to multiple monitoring points through the mobile Internet.

Step 2: In the field monitoring point, white gauze is arranged in front of the macro camera as the background, and the light is sufficient, and the camera is focused on the designated area on the white gauze; this area is used as a place to attract tiny vector organisms (mosquitoes), with lights and Scent and other lure measures; rainproof devices are installed on cameras and lure points.

Step 3: Start the macro camera for macro video shooting, and upload the video data to the designated background server through the mobile Internet in real time.

Step 4: The back-end server judges whether there are tiny vector organisms (mosquitoes) appearing in front of the camera by analyzing the pictures in the video. The back-end server is installed with the video behavior analysis software independently developed by the cooperative company, which can determine whether it is a tiny organism ( Mosquitoes) appear in front of the camera.

Step 5: If there are tiny vector organisms (mosquitoes) appearing in the lens area, activate the macro high-definition zoom-in photo function to take a photo; this step includes three sub-steps:

1) After receiving the start signal sent by the background server through the mobile Internet, start the camera to zoom in and take pictures. The magnification depends on the size of the tiny vector organisms (mosquitoes), generally 50 to 100 times;

2) After zooming in, the tiny vector organisms (mosquitoes) are still in the lens, and auto-focus is performed to ensure that the target is clear; if the tiny vector organisms (mosquitoes) move quickly when taking pictures, the photo effect is not ideal;

3) Start taking pictures, if the light is not enough, start flashing pictures; in order to ensure the effect of taking pictures, two or more high-definition pictures can be taken continuously, and the magnification and resolution equipment can be adjusted automatically without human intervention;

Step 6: Upload the captured high-definition photos to the designated background server in real time through the mobile Internet;

Step 7: The server uses special image recognition software to identify the species of microscopic vector organisms (mosquitoes) on the received high-definition photos.

The invention can quickly identify the tiny vector organisms (mosquitoes) in the field monitoring point online, thereby determining the imminent epidemic situation of the disease near the monitoring point, and taking measures to prevent the spread of the disease. Compared with the traditional manual trapping brought back to the laboratory for analysis and identification, the first is fast, low cost, all-weather, and secondly, multiple monitoring points can be established at the same time, and the obtained photos are also rich, which can be monitored in a large area.

It should be understood that the above description of the preferred embodiments is relatively detailed, and therefore should not be considered as a limitation on the scope of the patent protection of the present invention. In the case of the protection scope, substitutions or deformations can also be made, which all fall within the protection scope of the present invention, and the claimed protection scope of the present invention shall be subject to the appended claims.

Claims (3)

1. The method for obtaining high-definition images of remote tiny disease vectors and identifying types, is characterized in that, comprises the following steps: Step 1: Build a monitoring network: Install network cameras and wireless terminals with macro photography functions at the monitoring points, and connect to the designated server through the mobile Internet; one server can be connected to multiple monitoring points through the mobile Internet; Step 2: In the field monitoring point, a white gauze is arranged in front of the macro camera as the background, and the light is sufficient, and the camera is focused on the designated area on the white gauze; this area is used as a place to attract tiny vector organisms, and there are lights and smells. Rainproof devices are installed on cameras and lure points; Step 3: Start the macro camera for macro video shooting, and upload the video data to the designated background server through the mobile Internet in real time; Step 4: The background server judges whether there are tiny vector organisms appearing in front of the camera by analyzing the images in the video, and the background server is installed with video behavior analysis software, which can determine whether tiny organisms appear in front of the camera; Step 5: If there are tiny vector organisms appearing in the lens area, activate the macro high-definition zoom-in photo function to take a photo; this step includes three sub-steps: 1) After receiving the start signal sent by the backend server through the mobile Internet, start the camera to zoom in and take pictures, and the magnification is 50 to 100 times depending on the size of the tiny vector organisms; 2) After zooming in, the tiny vector organisms are still in the lens, and auto-focus is performed to ensure that the target is clear; if the tiny vector organisms move quickly when taking pictures, the photo effect is not ideal; 3) Start taking pictures, if the light is not enough, start flashing pictures; in order to ensure the effect of taking pictures, two or more high-definition pictures can be taken continuously, and the magnification and resolution equipment can be adjusted automatically without human intervention; Step 6: Upload the captured high-definition photos to the designated background server in real time through the mobile Internet; Step 7: The server uses special image recognition software to identify the types of micro vector organisms on the received high-definition photos. 2 . The method for acquiring and identifying types of high-definition images of remote tiny disease vectors according to claim 1 , wherein the network camera in step 1 is a network camera with a high-magnification photographing function. 3 . 3 . The method for obtaining and identifying types of high-definition images of remote tiny disease vectors according to claim 1 , wherein the step 5 in which the camera is activated to zoom in and take pictures is to take static high-definition pictures. 4 .

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