An image recognition-based aedes albopictus trapping and density monitoring device
By using an image recognition-based Aedes albopictus mosquito trapping and density monitoring device, combined with fiber optic sensors and high-definition cameras, and utilizing the YOLO algorithm, the automatic integration of mosquito trapping and species identification is achieved. This solves the problems of low efficiency and high cost in existing mosquito species identification technologies, and realizes efficient and accurate mosquito species identification and trapping.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Utility models(China)
- Current Assignee / Owner
- SUZHOU HUIQIAO INTELLIGENT TECHNOLOGY CO LTD
- Filing Date
- 2025-08-26
- Publication Date
- 2026-07-24
AI Technical Summary
Existing mosquito trapping devices are unable to effectively identify the species of mosquitoes captured, and existing identification methods are either inefficient or involve complex and costly equipment, making them difficult to apply widely.
Design an image recognition-based Aedes albopictus mosquito trapping and density monitoring device, including mosquito trapping, detection, image acquisition, control and processing parts. Utilize fiber optic sensors and high-definition cameras combined with the YOLO algorithm to achieve automated integration of mosquito trapping and species identification, and employ inexpensive electronic components and structural design.
It achieves automated integration of mosquito trapping and species identification, improving work efficiency, with an identification accuracy rate of over 95%, controllable cost, and easy to widely apply to public health and disease vector monitoring.
Smart Images
Figure CN224539216U_ABST
Abstract
Description
Technical Field
[0001] This utility model relates to the field of insect trapping and identification technology, specifically to a device for trapping and monitoring the density of Aedes albopictus mosquitoes based on image recognition. Background Technology
[0002] Most common mosquito trapping devices can only trap mosquitoes and cannot effectively identify the species of the captured mosquitoes. Existing identification methods either require a large amount of manual operation, making them inefficient, or involve complex and expensive equipment, hindering widespread application. Therefore, developing an efficient, accurate, and cost-effective integrated mosquito trapping and species identification device is of significant practical importance. Utility Model Content
[0003] This invention provides an image recognition-based device for trapping and monitoring the density of Aedes albopictus mosquitoes. It integrates mosquito trapping and species identification, completing the entire process from trapping to identification without manual intervention. This improves work efficiency, enhances the accuracy of mosquito species identification, keeps costs under control, and is easy to implement for widespread application.
[0004] To achieve the above objectives, an image recognition-based device for trapping and monitoring the density of Aedes albopictus mosquitoes is provided. The device includes a mosquito-attracting section, a detection section, an image acquisition section, a control section, and a processing section. The mosquito-attracting section includes an upper mosquito-suction fan, an escape-prevention funnel net, and mosquito-attracting components. The detection section includes a fiber optic sensor with a transmitter and a receiver. The image acquisition section includes an observation chamber, a high-definition camera, an observation board, and a lower mosquito-suction fan. A mosquito outlet is located on one side of the observation chamber. The control section includes an STM32F103C8T6 chip, a relay module, and a motor drive module. The processing section includes a transmission channel, a brushless motor, a mosquito collection bag, a mosquito outlet baffle, and a servo motor. The upper mosquito-suction fan is fixedly connected to the top of the escape-prevention funnel net. The escape funnel net has a conical mesh structure. The observation chamber is fixedly connected to the bottom of the escape funnel net. The fiber optic sensor transmitter and receiver are symmetrically installed on both sides of the channel at the lower outlet of the escape funnel net. The high-definition camera is fixedly connected to the top of the observation chamber and is located directly above the observation plate. The observation plate is fixedly connected to the inner surface of the observation chamber. The lower suction fan is fixedly connected to the bottom of the observation chamber. A partition groove is provided near the mosquito outlet in the transmission channel. The servo motor is fixedly connected to the outer surface of the observation chamber near the end of the transmission channel. The mosquito outlet baffle is fixedly connected to the output end of the servo motor. The brushless motor is fixedly connected to the end of the transmission channel away from the observation chamber. The mosquito collection bag is installed below the brushless motor. The mosquito collection bag is connected to the transmission channel, and the transmission channel is connected to the mosquito outlet.
[0005] Preferably, the mosquito-attracting component is placed at the top of the device, and the power cord of the upper mosquito-suction fan is connected to the motor drive module of the control section.
[0006] Preferably, the fiber optic sensor is model FT-20ML-2, and the signal line of the fiber optic sensor is connected to the PB1 pin of the core chip STM32F103C8T6 of the control section.
[0007] Preferably, the high-definition camera is model MV-CS200-10UC. The DC power supply line and the optocoupler isolated input signal line of the high-definition camera are connected in series through a 2kΩ pull-up resistor, and the leads are respectively connected to the NO1 and COM1 interfaces of the relay. The control line IN1 of the relay is connected to the PB0 pin of the STM32F103C8T6 chip.
[0008] Preferably, the motor drive module is a TB6612FNG, and the AIN1 and AIN2 pins of the motor drive module are connected to the PB14 and PB15 pins of the STM32F103C8T6 chip, respectively. The BIN1 and BIN2 pins of the motor drive module are connected to the PA4 and PA5 pins of the STM32F103C8T6 chip, respectively. The WMA and PWMB pins of the motor drive module are connected to the PA1 and PA0 pins of the STM32F103C8T6 chip, respectively.
[0009] Preferably, the servo motor is an S20F, the servo motor power ground wire and the STM32F103C8T6 chip ground wire are common, and the servo motor signal line is connected to the PA6 pin of the STM32F103C8T6 chip.
[0010] Preferably, the mosquito collection bag has a mesh structure.
[0011] Preferably, the observation plate is provided with a plurality of vertically penetrating holes, and the diameter of the holes in the observation plate is between 0.5 mm and 1.5 mm.
[0012] Preferably, the color of the observation plate is any one of white, blue, or green.
[0013] Preferably, the mosquito-attracting component includes a carbon dioxide generator, a human body temperature simulator, and a human sweat odor simulator.
[0014] The beneficial effects of this invention are: it integrates mosquito trapping and species identification, completing the process from trapping to identification without manual intervention, thus improving work efficiency; it uses the YOLO algorithm for species identification, achieving an accuracy rate of over 95%, thereby enhancing the precision of mosquito species identification; the device has a reasonable structural design, the components used are cost-effective, and it is easy to implement in a wide range of applications; it is beneficial for playing an important role in public health and epidemic prevention, mosquito vector monitoring, and other fields, and has high practical value.
[0015] Additional aspects and advantages of this invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description
[0016] The present invention will be further described below with reference to the accompanying drawings and embodiments; Figure 1 This is a schematic diagram of the structure of an image recognition-based Aedes albopictus mosquito trapping and density monitoring device proposed in this invention; Figure 2 This is a front view of the structure of an image recognition-based Aedes albopictus mosquito trapping and density monitoring device proposed in this invention; Figure 3 This is a structural diagram of the mosquito species identification and processing part of an image recognition-based Aedes albopictus mosquito trapping and density monitoring device proposed in this invention; Figure 4 This is a bottom view of the structure of an image recognition-based Aedes albopictus mosquito trapping and density monitoring device proposed in this invention; Figure 5 The left view shows the mosquito species identification and processing part of the image recognition-based Aedes albopictus mosquito trapping and density monitoring device proposed in this invention. Figure 6 This is a top view of the structure of an image recognition-based Aedes albopictus mosquito trapping and density monitoring device proposed in this invention; Figure 7 This is a side-view (bottom view) of the mosquito species identification and processing section of an image recognition-based Aedes albopictus mosquito trapping and density monitoring device proposed in this invention. Figure 8 This is a side view of the mosquito species identification and processing section of an image recognition-based Aedes albopictus mosquito trapping and density monitoring device proposed in this invention; Figure 9 This is a structural diagram of the mosquito outlet baffle of an image recognition-based Aedes albopictus mosquito trapping and density monitoring device proposed in this invention.
[0017] The components include: 1. Upper mosquito suction fan; 2. Anti-escape funnel net; 3. High-definition camera; 4. Observation board; 5. Brushless motor; 6. Mosquito collection bag; 7. Lower mosquito suction fan; 8. Fiber optic sensor transmitter; 9. Fiber optic sensor receiver; 10. Mosquito outlet; 11. Mosquito outlet baffle; and 12. Servo motor. Detailed Implementation
[0018] This section will describe in detail the specific embodiments of the present utility model. The preferred embodiments of the present utility model are shown in the accompanying drawings. The purpose of the drawings is to supplement the textual description with graphics, so that people can intuitively and vividly understand each technical feature and the overall technical solution of the present utility model, but they should not be construed as limiting the scope of protection of the present utility model.
[0019] Reference Figures 1 to 9 This utility model discloses an image recognition-based device for trapping and monitoring the density of Aedes albopictus mosquitoes. It includes a mosquito-attracting section, a detection section, an image acquisition section, a control section, and a processing section. The mosquito-attracting section includes an upper mosquito-suction fan 1, an escape-prevention funnel net 2, and mosquito-attracting components. The detection section includes a fiber optic sensor with a transmitter 8 and a receiver 9. The image acquisition section includes an observation chamber, a high-definition camera 3, an observation board 4, and a lower mosquito-suction fan 7. A mosquito outlet 10 is located on one side of the observation chamber. The control section includes an STM32F103C8T6 chip, a relay module, and a motor drive module. The processing section includes a transmission channel, a brushless motor 5, a mosquito collection bag 6, an outlet baffle 11, and a servo motor 12. The upper mosquito-suction fan 1 is fixedly connected to the top of the escape-prevention funnel net 2. The escape-proof funnel net 2 has a conical mesh structure. The observation chamber is fixedly connected to the bottom of the escape-proof funnel net 2. The fiber optic sensor transmitter 8 and the fiber optic sensor receiver 9 are symmetrically installed on both sides of the channel at the lower outlet of the escape-proof funnel net 2. The high-definition camera 3 is fixedly connected to the top of the observation chamber, located directly above the observation plate 4. The observation plate 4 is fixedly connected to the inner surface of the observation chamber. The lower mosquito-suction fan 7 is fixedly connected to the bottom of the observation chamber. A partition groove is provided in the transmission channel near the mosquito outlet 10. The servo motor 12 is fixedly connected to the outer surface of the observation chamber near the end of the transmission channel. The mosquito outlet baffle 11 is fixedly connected to the output end of the servo motor 12. The brushless motor 5 is fixedly connected to the end of the transmission channel away from the observation chamber. The mosquito collection bag 6 is installed below the brushless motor 5 and is connected to the transmission channel. The transmission channel is connected to the mosquito outlet 10. The upper mosquito-suction fan 1 can generate a downward airflow, which blows the mosquitoes attracted to the entrance through the escape-proof funnel net 2 to the detection and image acquisition area below. When a mosquito passes through the detection area, the sensor's optical path is blocked, and the signal line outputs a low-level signal to the control unit, triggering subsequent actions. After passing through the detection area, the mosquito falls onto the observation plate 4, where it is held in place by the downward suction fan 7, thus completing image acquisition.
[0020] The mosquito-attracting component is placed at the top of the device, and the power cords of the upper mosquito-suction fan 1 and the lower mosquito-suction fan 7 are connected to the motor drive module of the control section.
[0021] The fiber optic sensor is model FT-20ML-2. The signal line of the fiber optic sensor is connected to the PB1 pin of the core chip STM32F103C8T6 of the control section to receive the trigger signal when a mosquito passes by.
[0022] The HD camera 3, model MV-CS200-10UC, has its DC power supply line and optocoupler-isolated input signal line connected in series via a 2kΩ pull-up resistor. The leads are then connected to the NO1 and COM1 interfaces of the relay, respectively. The relay's control line IN1 is connected to the PB0 pin of the STM32F103C8T6 chip. By controlling the high and low levels of the PB0 pin using the STM32F103C8T6 chip, the relay is activated and deactivated, thereby controlling the camera's startup and image acquisition.
[0023] The motor drive module uses a TB6612FNG. The AIN1 and AIN2 pins of the motor drive module are connected to the PB14 and PB15 pins of the STM32F103C8T6 chip, respectively, to control the forward and reverse rotation of the upper mosquito suction fan 1 in the mosquito-attracting section. The BIN1 and BIN2 pins of the motor drive module are connected to the PA4 and PA5 pins of the STM32F103C8T6 chip, respectively, to control the operation of the lower mosquito suction fan 7 in the processing section. The WMA and PWMB pins of the motor drive module are connected to the PA1 and PA0 pins of the STM32F103C8T6 chip, respectively, to adjust the speed of the upper mosquito suction fan 1 and the lower mosquito suction fan 7 through the PWM signal.
[0024] Servo motor 12 is an S20F. The power ground of servo motor 12 shares a common ground with the ground of the STM32F103C8T6 chip. The signal line of servo motor 12 is connected to pin PA6 of the STM32F103C8T6 chip. The shaft of servo motor 12 can drive the baffle 11 to rotate 180 degrees, controlling the opening and closing of the mosquito outlet 10. After the mosquitoes are photographed, the mosquito outlet baffle 11 opens under the control of servo motor 12. The brushless motor 5, driven by the control unit, sucks out the observed mosquitoes and places them into the mosquito collection bag 6 for processing.
[0025] The mosquito collection bag 6 has a mesh structure.
[0026] The observation plate 4 has multiple vertically penetrating holes, with the diameter of the holes ranging from 0.5 mm to 1.5 mm.
[0027] The color of observation board 4 is any one of white, blue, or green.
[0028] The mosquito-attracting components include a carbon dioxide generator, a human body temperature simulator, and a human sweat odor simulator.
[0029] The processing section of the entire device uses an algorithm based on the YOLO V8X framework to process photos taken by the high-definition camera 3 and identify the types of mosquitoes.
[0030] Under normal conditions, the servo motor 12, brushless motor 5, downdraft mosquito fan 7, and high-definition camera 3 do not work. When a mosquito is detected passing through the detection area between the fiber optic sensor transmitter 8 and the fiber optic sensor receiver 9, the pre-programmed actions of each component are performed in sequence.
[0031] Working Principle: The mosquito-attracting section attracts mosquitoes by simulating human scent, drawing them close to the top inlet of the device. The upper suction fan 1 generates a downward airflow, blowing the mosquitoes through the escape-proof funnel net 2 towards the detection area. When a mosquito passes through the detection area between the fiber optic sensor transmitter 8 and the fiber optic sensor receiver 9, the fiber optic sensor outputs a low-level signal to the STM32F103C8T6 chip, initiating the detection trigger phase. Upon receiving the trigger signal, the STM32F103C8T6 chip controls a relay to activate the high-definition camera 3, continuously capturing five images of the mosquitoes landing on the observation board 4, completing the image acquisition phase. The algorithm module then processes the images based on the YOLO algorithm to identify the mosquito species, entering the species recognition phase. After recognition, the STM32F103C8T6 chip controls the servo motor 12 to open the mosquito outlet baffle 11, simultaneously controlling the brushless motor 5 to open. The mosquitoes, aided by the airflow from the brushless motor 5 and the lower suction fan 7, fall into the mosquito collection bag 6, completing the entire trapping and recognition process.
[0032] The embodiments of the present utility model have been described in detail above with reference to the accompanying drawings. However, the present utility model is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present utility model.
Claims
1. A device for trapping and monitoring the density of Aedes albopictus mosquitoes based on image recognition, characterized in that: The system includes a mosquito-attracting section, a detection section, an image acquisition section, a control section, and a processing section. The mosquito-attracting section includes an upper mosquito-suction fan (1), an escape-proof funnel net (2), and mosquito-attracting components. The detection section includes a fiber optic sensor, which is equipped with a fiber optic sensor transmitter (8) and a fiber optic sensor receiver (9). The image acquisition section includes an observation chamber, a high-definition camera (3), an observation board (4), and a lower mosquito-suction fan (7). A mosquito outlet (10) is provided on one side of the observation chamber. The control section includes an STM32F103C8T6 chip, a relay module, and a motor drive module. The processing section includes a transmission channel, a brushless motor (5), a mosquito collection bag (6), a mosquito outlet baffle (11), and a servo motor (12). The upper mosquito-suction fan (1) is fixedly connected to the top of the escape-proof funnel net (2), which has a conical mesh structure. The observation chamber is fixedly connected to... At the bottom of the escape-proof funnel net (2), the fiber optic sensor transmitter (8) and the fiber optic sensor receiver (9) are symmetrically installed on both sides of the channel at the lower outlet of the escape-proof funnel net (2). The high-definition camera (3) is fixedly connected to the top of the observation chamber. The high-definition camera (3) is located directly above the observation plate (4). The observation plate (4) is fixedly connected to the inner surface of the observation chamber. The mosquito suction fan (7) is fixedly connected to the bottom of the observation chamber. A partition groove is provided near the mosquito outlet (10) of the transmission channel. The servo motor (12) is fixedly connected to the outer surface of the observation chamber near the end of the transmission channel. The mosquito outlet baffle (11) is fixedly connected to the output end of the servo motor (12). The brushless motor (5) is fixedly connected to the end of the transmission channel away from the observation chamber. The mosquito collection bag (6) is installed below the brushless motor (5). The mosquito collection bag (6) is connected to the transmission channel. The transmission channel is connected to the mosquito outlet (10).
2. The image recognition-based Aedes albopictus mosquito trapping and density monitoring device according to claim 1, characterized in that: The mosquito-attracting component is placed at the top of the device, and the power cords of the upper mosquito-suction fan (1) and the lower mosquito-suction fan (7) are connected to the motor drive module of the control section.
3. The image recognition-based Aedes albopictus mosquito trapping and density monitoring device according to claim 1, characterized in that: The fiber optic sensor is model FT-20ML-2, and its signal line is connected to the PB1 pin of the core chip STM32F103C8T6 in the control section.
4. The image recognition-based Aedes albopictus mosquito trapping and density monitoring device according to claim 1, characterized in that: The high-definition camera (3) is model MV-CS200-10UC. The DC power supply line of the high-definition camera (3) and the optocoupler isolated input signal line are connected in series through a 2kΩ pull-up resistor. The lead wires are connected to the NO1 and COM1 interfaces of the relay respectively. The control line IN1 of the relay is connected to the PB0 pin of the STM32F103C8T6 chip.
5. The image recognition-based Aedes albopictus mosquito trapping and density monitoring device according to claim 1, characterized in that: The motor drive module uses a TB6612FNG. The AIN1 and AIN2 pins of the motor drive module are connected to the PB14 and PB15 pins of the STM32F103C8T6 chip, respectively. The BIN1 and BIN2 pins of the motor drive module are connected to the PA4 and PA5 pins of the STM32F103C8T6 chip, respectively. The WMA and PWMB pins of the motor drive module are connected to the PA1 and PA0 pins of the STM32F103C8T6 chip, respectively.
6. The image recognition-based Aedes albopictus mosquito trapping and density monitoring device according to claim 1, characterized in that: The servo motor (12) is an S20F. The power ground of the servo motor (12) is the same as the ground of the STM32F103C8T6 chip. The signal line of the servo motor (12) is connected to the PA6 pin of the STM32F103C8T6 chip.
7. The image recognition-based Aedes albopictus mosquito trapping and density monitoring device according to claim 1, characterized in that: The mosquito collection bag (6) has a mesh structure.
8. The image recognition-based Aedes albopictus mosquito trapping and density monitoring device according to claim 1, characterized in that: The observation plate (4) is provided with a plurality of vertically penetrating holes, the diameter of which ranges from 0.5 mm to 1.5 mm.
9. The image recognition-based Aedes albopictus mosquito trapping and density monitoring device according to claim 1, characterized in that: The color of the observation plate (4) is any one of white, blue, or green.
10. The image recognition-based Aedes albopictus mosquito trapping and density monitoring device according to claim 1, characterized in that: The mosquito-attracting component includes a carbon dioxide generator, a human body temperature simulator, and a human sweat odor simulator.