A smart monitoring and control system for sorghum pests and diseases using a station-vehicle collaborative closed-loop operation.

Abstract

This invention discloses a station-vehicle collaborative closed-loop intelligent monitoring and control system for sorghum pests and diseases, achieving integrated monitoring, energy replenishment, and control. The fixed station is equipped with meteorological sensors, soil sensors, trapping devices, a detection area clearing device, and a charging pile; the robot is equipped with a tracked mobile chassis, a lifting platform, a gimbal, a camera, a dual-battery power supply system, and an automatic charging and alignment mechanism. This invention achieves autonomous robot return to recharge via automatic charging and alignment, overcoming the range bottleneck; the detection area clearing device ensures daily data reset and accurate daily statistics; and cloud server-based comprehensive analysis and coordination with drone spraying and water valve irrigation enable precise variable-rate spraying, reducing pesticide use. This invention is applicable to green pest and disease control in sorghum and other crops.

Description

Technical Field

[0001] This invention relates to the field of agricultural intelligent equipment technology, and in particular to an intelligent monitoring and control system for sorghum pests and diseases using a station-vehicle collaborative closed-loop operation. Background Technology

[0002] Sorghum, as an important food and economic crop, is susceptible to various pests and diseases during its growth, severely impacting yield and quality. Existing methods for monitoring farmland pests and diseases suffer from limited coverage and blind spots due to fixed monitoring equipment; mobile monitoring equipment lacks sufficient battery life, making 24 / 7 monitoring difficult. Mobile devices lack self-charging capabilities, requiring manual battery replacement or charging, hindering long-term continuous operation and severely restricting the realization of unmanned monitoring. Most systems only possess monitoring functions and cannot achieve coordinated monitoring and control; their reliance on chemical pesticides easily leads to environmental pollution and ecological damage. Furthermore, the lack of edge computing capabilities makes real-time response difficult. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent monitoring and control system for sorghum pests and diseases using a station-vehicle collaborative closed-loop operation, thereby solving the problems mentioned in the background art.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0005] A station-vehicle collaborative closed-loop intelligent monitoring and control system for sorghum pests and diseases includes a fixed meteorological pest observation station, a mobile intelligent inspection robot, and a cloud server.

[0006] The fixed meteorological pest observation station includes a column base, a meteorological sensor module, a soil sensor module, a trapping device, a detection area removal device, a photovoltaic power supply unit, and a charging pile assembly. An equipment box is mounted on the column base, containing a first main control board, a first edge computing motherboard, and a first wireless communication module. The meteorological sensor module, soil sensor module, trapping device, detection area removal device, and photovoltaic power supply unit are all electrically connected to the first main control board. The charging pile assembly is located at the bottom of the column base and includes charging electrodes and a positioning target; the charging electrodes are electrically connected to the photovoltaic power supply unit.

[0007] The mobile intelligent inspection robot includes a tracked chassis, a lifting platform, a cable chain mechanism, a gimbal mechanism, a camera module, a dual-battery power supply system, a control box, an automatic charging and alignment mechanism, and a harvesting box. The lifting platform is mounted on the tracked chassis and has a top support plate. The cable chain mechanism is located between the chassis and the support plate. The gimbal mechanism is mounted on the support plate. The camera module includes a first camera mounted on the support plate and a second camera mounted on the chassis. The dual-battery power supply system includes a power battery and an external battery, electrically connected via a power management module. The control box... The housing contains a second main control board and a second edge computing motherboard; the automatic charging and alignment mechanism is located at the bottom of the chassis and includes charging contacts and a positioning sensor. The charging contacts are electrically connected to the power management module of the dual-battery power supply system, the positioning sensor is electrically connected to the second main control board, the charging contacts are matched with the charging electrodes of the fixed meteorological pest observation station, and the positioning sensor is matched with the positioning target of the fixed meteorological pest observation station to realize the detachable electrical connection between the mobile intelligent inspection robot and the fixed meteorological pest observation station. The harvesting box is installed on the tracked mobile chassis.

[0008] The cloud server is communicatively connected to the first wireless communication module of the fixed meteorological pest observation station and the second wireless communication module of the mobile intelligent inspection robot.

[0009] The fixed meteorological pest observation station only activates the light trapping function at night to monitor the dynamics of adult insect populations, while the mobile intelligent inspection robot performs inspection tasks during the day, identifying pest feeding based on vegetation status and simultaneously retrieving sorghum growth parameters; the light trapping function is uniquely configured in the fixed meteorological pest observation station.

[0010] Furthermore, the detection area cleaning device includes one or more of a fan or a vibrator.

[0011] Furthermore, the lifting platform includes a telescopic mechanism, a drive motor, and limit switches; the telescopic mechanism consists of two parallel aluminum alloy telescopic rods; the limit switches are located at both ends of the travel of the telescopic mechanism, and the limit switches are electrically connected to the second main control board.

[0012] Furthermore, the charging electrode is an elastic telescopic contact, and the positioning target is an infrared reflector; there are multiple charging contacts that are symmetrically distributed, and the positioning sensor is an infrared positioning sensor disposed between the charging contacts.

[0013] Furthermore, both the power battery and the peripheral battery are rechargeable lithium batteries; the power management module is equipped with a reverse connection protection plug.

[0014] Furthermore, the cable chain mechanism is a fully enclosed structure made of nylon, and the inside of the cable chain mechanism is provided with partitions.

[0015] Furthermore, the photovoltaic power supply unit includes a solar panel and a battery. The solar panel is installed on the top of the column base, and the battery is located inside the equipment box.

[0016] Furthermore, the gimbal mechanism of the inspection robot includes a horizontal rotational servo motor and a pitch rotational servo motor, which are electrically connected to the second main control board respectively. The servo motor output shaft adopts metal gear transmission and is equipped with a precision bearing structure.

[0017] Furthermore, the system also includes a client and a drone, which are respectively connected to the cloud server.

[0018] Furthermore, the fixed meteorological pest observation station is configured to activate the light trapping unit in the trapping device during the nighttime period, and use the image acquisition equipment configured on the fixed meteorological pest observation station itself to collect images of pests in the trapping area. The trapped pests are identified by species and counted in number for nighttime pest monitoring.

[0019] The mobile intelligent inspection robot is configured to activate the camera module during the daytime to conduct field inspections for daytime pest and disease monitoring.

[0020] The light trapping unit is only installed at the fixed meteorological pest observation station, and the mobile intelligent inspection robot does not have the light trapping function; the trapping device is a statistical trap.

[0021] Beneficial effects:

[0022] This invention overcomes the battery life bottleneck by enabling robots to autonomously return to their charging dock through automatic charging alignment; it ensures accurate daily statistics by resetting data daily through a detection area clearing device; and it achieves precise variable-rate spraying by comprehensively analyzing data from cloud servers and coordinating drone spraying and water valve irrigation, thus reducing pesticide use. This invention is applicable to the green control of pests and diseases in sorghum and other crops. Attached Figure Description

[0023] Figure 1 This is a structural diagram of the fixed meteorological pest observation station in this invention;

[0024] Figure 2 This is a structural diagram of the mobile intelligent inspection robot in this invention.

[0025] The components include: 1. Column base; 2. Equipment box; 3. Wind direction sensor; 4. Wind speed sensor; 5. Photovoltaic panel; 6. Detection area clearing device; 7. Charging pile assembly; 8. Tracked mobile chassis; 9. Pan-tilt mechanism; 10. Telescopic mechanism; 11. Lifting platform; 12. Bearing plate; 13. Track. Detailed Implementation

[0026] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0027] In the description of this invention, it should be noted that the terms "installation" and "connection" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection, an indirect connection through an intermediate medium, or a connection within two components. Those skilled in the art can understand the specific meaning of these terms in this invention according to the specific circumstances.

[0028] In addition, unless otherwise specified, the components used in the following embodiments are all existing components, and their corresponding connection methods can also be achieved through conventional technical means, which will not be described in detail in this application.

[0029] Example

[0030] This embodiment provides a station-vehicle collaborative closed-loop intelligent monitoring and control system for sorghum pests and diseases, comprising a fixed meteorological pest observation station, a mobile intelligent inspection robot, a cloud server, a drone, and a client application. The fixed station is deployed at key nodes in the field, while the inspection robot moves autonomously between sorghum rows. The two systems interact via a wireless communication module and achieve autonomous charging coordination through a charging alignment mechanism. The cloud server serves as the data processing and distribution center, while the client application displays real-time monitoring data, images, and early warning information. The drone communicates with the cloud server to receive control commands and execute variable-rate spraying operations.

[0031] like Figure 1As shown, the fixed meteorological pest observation station mainly consists of a column base 1, a meteorological sensor module, a soil sensor module, a trapping device, a detection area removal device 6, a photovoltaic power supply unit, and a charging pile assembly 7. An equipment box 2 is mounted on the column base 1, containing a first main control board, a first edge computing motherboard, and a wireless communication module. The meteorological sensor module is installed at the top of the column base 1 and includes a wind speed sensor 4 and a wind direction sensor 3 using a precision cup-type anemometer and wind vane, an air temperature and humidity sensor housed in a Stevenson screen, a light intensity sensor monitoring photosynthetically active radiation, and an optical rain gauge using infrared optics to monitor rainfall, used for real-time collection of field meteorological data. The soil sensor module is a pin-type multi-functional sensor buried in the soil layer where the sorghum roots are located. It is electrically connected to the first main control board via a waterproof shielded cable and uses electrochemical principles to rapidly determine soil temperature, humidity, pH, and the content of available nitrogen, available phosphorus, and available potassium. The trapping device, installed below equipment box 2, includes a biological trap and an ultraviolet insect-attracting lamp. This trapping device is a statistical trap, designed to attract pests into the trapping area. Image acquisition equipment captures and records the data, counting the pests to monitor their population dynamics. A detection area clearing device 6 is located below the trapping device. In this embodiment, the detection area clearing device includes at least one of a fan and a vibrator, both electrically connected to the first main control board. After the trapping device attracts pests to the detection area, the first main control board activates the clearing device before the preset daily image acquisition time. The device uses airflow or vibration to drive the pests away from the detection area. The driven pests can return to the field or fall into a separate collection container, thus achieving daily data clearing for the detection area. The photovoltaic power supply unit includes a solar panel and a battery. The solar panel is a monocrystalline silicon photovoltaic panel 5, and the battery is a lead-acid battery pack. The photovoltaic panel 5 is installed above equipment box 2, and the battery pack is located inside equipment box 2. The photovoltaic panel 5 converts solar energy into electrical energy, with some directly supplying the system and the rest stored in the battery pack. The meteorological sensor module, soil sensor module, trapping device, detection area removal device 6, and photovoltaic power supply unit are all electrically connected to the first main control board and are uniformly coordinated and controlled by the first main control board.

[0032] The charging pile component 7 is located at the bottom of the column base 1 and includes a charging electrode and a positioning target. The charging electrode is electrically connected to the photovoltaic power supply unit. Specifically, the charging electrode is an elastic telescopic contact, and the positioning target is an infrared reflector, used to cooperate with the automatic charging alignment mechanism at the bottom of the inspection robot to complete the charging docking.

[0033] like Figure 2As shown, the mobile intelligent inspection robot includes a tracked mobile chassis 8, a lifting platform 11, a drag chain mechanism, a gimbal mechanism 9, a camera module, a dual-battery power supply system, a control box, an automatic charging and alignment mechanism, and a harvesting box. The mobile intelligent inspection robot integrates multiple sensor modules, such as visible light cameras and temperature and humidity sensors, enabling it to autonomously move and inspect over a wide area, achieving image acquisition and edge recognition of pests and diseases on sorghum plants in different rows and locations. When working in conjunction with fixed meteorological and pest observation stations, the fixed stations only need to be deployed in small numbers at key nodes in the field, responsible for collecting meteorological and soil data and recharging in fixed areas; the mobile intelligent inspection robot, on the other hand, covers the entire mobile area between the fixed stations, completing detailed inspections at the plant level. This architecture, with a small number of fixed stations and full coverage by mobile stations, significantly reduces the number of fixed stations while ensuring monitoring accuracy, thereby lowering the overall system cost. The tracked mobile chassis 8 measures 550mm in length, 360mm in width, and 195mm in height, weighs 6.99kg, and has a load capacity of 20kg. The chassis consists of tracks 13, load-bearing wheels, and a drive motor. Tracks 13 are made of zinc alloy, offering excellent wear resistance. The load-bearing wheels feature a bearing-type structure with wheel-plate wheels, effectively reducing bumps during travel. The drive motor is a 12V, 550W DC brushed geared motor with a 1:50 reduction ratio, providing ample torque. The operating speed is adjustable between 0 and 0.75m / s, and the included Hall effect encoder accurately reflects the travel distance and speed. The chassis has a vertical obstacle clearance of no more than 60mm, a climbing angle of no more than 15°, and a ground clearance of 60mm, providing excellent field mobility. It can easily overcome obstacles such as clods of earth and small stones, and travel stably in soft soil and narrow ridges. The equipment supports PS2 controller remote control for simple and intuitive operation.

[0034] The lifting platform 11 is mounted on a tracked mobile chassis 8, with a top support plate 12 for carrying various observation equipment. The lifting platform 11 adopts a double-bar parallel design, with two telescopic mechanisms 10 spaced 500mm apart and fixed to the chassis by four sets of M6 bolts. The telescopic mechanism 10 is made of high-strength aluminum alloy, with an outer diameter of 30mm, a wall thickness of 2mm, a single-bar weight of 1.2kg, and a load-bearing capacity of 50kg. The drive system uses a DC push rod motor with a rated voltage of 12V, a working current of 3A, a telescopic speed of 30mm / s, and a stroke range of 0 to 70cm. The outer cylinder surface of the telescopic mechanism 10 has axial guide grooves, and wear-resistant sliders are installed at corresponding positions on the inner rods, effectively reducing friction during telescopic movement and improving operational stability. The motor has a built-in limit switch, located at both ends of the telescopic mechanism 10's stroke and electrically connected to the second main control board. When the telescopic mechanism 10 reaches its retracted or extended limit position, the power is automatically cut off to prevent damage from overtravel. The top of the telescopic mechanism 10 is equipped with a 20mm×20mm aluminum profile frame for installing and supporting various expansion modules.

[0035] The cable chain mechanism is located between the chassis and the support plate 12. It features a fully enclosed nylon structure with internal dividers, measuring 18mm wide and 25mm high, and can accommodate 4 to 6 cables, including USB data cables, power cables, and control signal cables. One end of the cable chain is fixed to the rear bracket of the chassis, and the other end connects to the top support plate 12 of the telescopic mechanism 10, with a bending radius of no less than 100mm. The fully enclosed structure provides dust and water resistance, and the internal dividers separate different types of cables to prevent signal interference. The cable chain moves synchronously with the telescopic mechanism 10, and the internal cables maintain a sufficient bending radius under the protection of the cable chain, eliminating the risk of stretching, twisting, or wear, effectively ensuring the reliability of the electrical connection.

[0036] The gimbal mechanism 9 is mounted on the support plate 12 and uses an S20 series 20kg servo motor as its drive core, achieving multi-angle observation and adjustment through a dual-axis system. The lower-level first-degree-of-freedom servo motor supports 270° rotation, while the upper-level second-degree-of-freedom servo motor can complete 180° rotation, with the dual axes working together to form all-around observation coverage. The servo motor output shaft uses metal gear transmission, combined with a precision bearing structure, to ensure the accuracy and stability of angle adjustment. The gimbal mechanism 9 supports PS2 controller joystick control; the horizontal joystick adjusts the horizontal rotation angle, and the vertical joystick controls the vertical pitch angle.

[0037] The camera module includes a first camera mounted on the support plate 12 and a second camera mounted on the chassis. The first camera is a 1080P high-definition visible light camera with autofocus and wide dynamic range, used to collect images of tiny lesions and pest morphological characteristics on both sides of sorghum leaves, providing high-quality image data for pest identification. The second camera is mounted at the bottom of the lifting platform 11 with a downward viewing angle, covering the area in front of the chassis and providing real-time road condition reference for operators. An image acquisition device, such as a base station-side camera, is also configured on one side of the fixed meteorological and pest observation station, facing the area covered by the insect-attracting lamp, used to accurately identify the types and numbers of insects attracted by the light, providing data support for pest occurrence trend analysis.

[0038] The dual-battery power supply system employs an independent power supply architecture for both batteries and an intelligent power management system. Both the power battery and the peripheral battery are rechargeable lithium batteries. The power battery is a 3S model aircraft lithium battery with a nominal voltage of 11.1V, a fully charged voltage of 12.6V, and a capacity of 3200mAh. It powers the chassis drive motor via the XT60 interface, with a maximum operating current of 15A and approximately 40 minutes of flight time under moderate load. The peripheral battery is a 10300mAh safety lithium battery with a nominal voltage of 12V. It powers the second edge computing motherboard, gimbal mechanism 9, camera module, second main control board, and other peripherals via a DC interface, with a total power consumption of approximately 30W. Multiple voltage output levels can be achieved through a DC-DC module. The power management module features a reverse connection protection plug and implements dual-battery linkage. Upon power-on, the peripheral battery is connected first, and the power battery is connected only after the main control board has initialized, preventing voltage fluctuations during peripheral initialization from affecting system stability.

[0039] The automatic charging alignment mechanism is located at the bottom of the chassis and includes multiple symmetrically distributed charging contacts and infrared positioning sensors, with the infrared positioning sensors positioned between the charging contacts. The charging contacts are electrically connected to the power management module of the dual-battery power supply system, and the infrared positioning sensors are electrically connected to the second main control board. The charging contacts match the elastic telescopic contacts of the fixed station, and the infrared positioning sensors cooperate with the infrared reflectors of the fixed station to achieve a detachable electrical connection between the robot and the fixed station.

[0040] To facilitate the collection of samples from suspected diseased plants during field inspections, this embodiment includes a collection box fixedly mounted on the rear of the tracked chassis 8 of the mobile intelligent inspection robot. The collection box is made of weather-resistant ABS plastic, has a sealed top cover, and can hold ice packs to keep samples fresh. The collection box is detachably connected to the rear crossbeam of the chassis via four sets of bolts, allowing for easy removal of samples for laboratory testing.

[0041] When the inspection robot's battery level drops below a preset threshold or it completes its inspection task in a preset area, the infrared positioning sensor automatically searches for the positioning target at the bottom of the fixed station and detects the alignment signal. The second main control board then controls the chassis motor to adjust the robot's posture based on the signal from the positioning sensor, ensuring accurate alignment between the charging contacts and the charging electrodes. After alignment, the power management module initiates charging, automatically disconnecting after recharging, thus achieving a closed-loop energy system where the inspection robot autonomously returns to the fixed station for recharging. This forms a complete closed loop from operation to low battery, return to station, charging, and continued operation, enabling the robot to operate continuously without human intervention around the clock.

[0042] The visual recognition and edge computing system is centered around a second edge computing motherboard, which deploys a YOLO deep learning model, specifically YOLOv8, optimized using TensorRT model acceleration technology. This supports accurate detection of 12 common pests and diseases, including Asian corn borer, peach fruit borer adults, aphids, and smut. When the inspection robot is in inspection mode, the lifting platform 11 automatically adjusts to be level with the sorghum canopy, with a positioning error controlled within ±5cm. Image data collected by the first camera is processed and transmitted uniformly by the second edge computing motherboard. Pest and disease identification images are preprocessed before target detection and result overlay, followed by encoding and compression. Road condition camera data is prioritized for lightweight processing, rapid encoding, and low-latency transmission. Trapping images collected by base station-side cameras are also identified locally and then uploaded. After identification, the system uploads the detection results to the cloud server in real time via the WebSocket protocol.

[0043] The cloud server communicates with the first wireless communication module of the fixed meteorological and pest observation station and the second wireless communication module of the mobile intelligent inspection robot. The client communicates with the cloud server. The server acts as the data relay and scheduling center of the image transmission system, receiving multiple image data streams from the streaming end, classifying and caching them, and then distributing them according to the client's subscription requirements. It also maintains a stable connection between the equipment and the client, supporting multi-user collaborative observation. The client is available in two versions: a web page and a QWidget interface. Users can subscribe to target camera data through simple connection operations, enabling image visualization, viewing detection results, and other functions. Users can view real-time field meteorological data, soil moisture, pest and disease identification results, and early warning information through the client, achieving remote monitoring and intelligent management of sorghum growth.

[0044] The following section, in conjunction with the above system structure, details the specific working process of this embodiment in achieving the integrated coordination of monitoring, energy replenishment, and governance:

[0045] During the monitoring phase, the system operates collaboratively day and night to achieve uninterrupted monitoring around the clock.

[0046] Nighttime Monitoring: Taking advantage of its continuous power supply, the fixed meteorological pest observation station automatically activates the ultraviolet insect-attracting lamps (light trapping units) in its trapping device during nighttime. Simultaneously, the image acquisition equipment on the base station side camera begins to periodically or continuously capture images of the area covered by the insect-attracting lamps. The first edge computing motherboard performs local identification on the nighttime trapping images, counting the types and quantities of nocturnal pests. After each image capture and identification, the detection area clearing device activates, driving away or blowing the pests from the trapping area into the collection container, ensuring independent data for the next time point. The fixed station thus completes its nighttime monitoring task for major pest infestations.

[0047] Daytime monitoring:

[0048] The mobile intelligent inspection robot performs the main inspection tasks during the day; the second main control board automatically starts after sunrise according to the preset schedule or cloud server instructions, and moves autonomously along the preset path; during the movement, the second main control board controls the drive motor of the lifting platform to adjust the height of the support plate according to the height of the sorghum plants at different growth stages, so that the first camera maintains the best observation distance with the plant canopy; the gimbal mechanism drives the first camera to rotate horizontally and tilt, and collects images of sorghum plants one by one or row by row.

[0049] The second edge computing motherboard calls the YOLO deep learning model to identify the type, severity and location of pests and diseases in the collected images in real time, and uploads the identification results to the cloud server.

[0050] The first camera supports single-frame image acquisition and continuous image sequence acquisition; the acquired images are used for real-time edge computing recognition on the one hand, and uploaded to the cloud along with the recognition results on the other hand as model training data to continuously optimize the detection model.

[0051] It should be noted that in this system, the light trapping function and its associated insect-attracting lamps are only configured at fixed meteorological pest observation stations. The mobile intelligent inspection robot does not carry any light trapping devices, which reduces the robot's hardware cost and power consumption, and also avoids interference from the light emitted by the robot during movement on the insect-attracting effect at the fixed station, thus achieving functional decoupling and synergistic complementarity.

[0052] During the recharging phase, the mobile intelligent inspection robot supports two motion control methods: one is manual control of the robot's movement via mobile phone or remote control, and the other is automatic movement according to a preset inspection path or mode. The power management module in the dual-battery power supply system monitors the remaining battery power in real time. When the power battery's charge falls below a preset threshold, the power management module sends a low-battery signal to the second main control board. The second main control board immediately interrupts the current inspection task and plans the optimal path back to the fixed station. After the robot autonomously navigates to the vicinity of the fixed station, it initiates an automatic charging alignment procedure: the infrared positioning sensor detects the infrared reflector at the bottom of the fixed station, and the second main control board adjusts the robot's posture to ensure precise alignment between the charging contacts and the charging electrodes. After alignment, the power management module starts charging, automatically disconnecting once the power reaches the preset upper limit, and the robot resumes the interrupted inspection task. This forms a complete closed loop from operation to low battery, return to station, charging, and then resuming operation, enabling the robot to operate continuously without human intervention around the clock.

[0053] During the control phase, the cloud server receives data uploaded from fixed stations and robots, performs spatiotemporal alignment and fusion analysis, and generates a heat map of the spatial distribution of pests and diseases and predictions of their occurrence trends. Based on the analysis results, the cloud server generates corresponding control instructions: if the pest density exceeds the control threshold, a spraying control signal is generated and sent wirelessly to the plant protection drone. The drone then performs variable-rate spraying according to a grid-based precision spraying plan to reduce pesticide use; if the soil moisture is below the crop's lower water requirement limit, an irrigation control signal is generated and sent to the field water valve to automatically activate irrigation. The client obtains all real-time data, historical statistical charts, and early warning information from the cloud server and displays them to agricultural technicians in a visual format. It also supports manual issuance of instructions to achieve human-machine collaboration.

[0054] In one specific implementation, the drone uses a modified DJI MG-1P model. The modification involves simplifying and optimizing the trained pest and disease identification model using the MCU-level AI inference framework Tengine-Lite, migrating it to an embedded edge computing platform based on Baidu's open-source edge computing framework OpenEdge, which has limited computing and storage resources. This platform is then mounted on the open-source Pixhawk quadcopter drone. The cloud server generates task instructions containing the work area and control thresholds based on monitoring results from fixed stations and the robot, and sends these instructions to the drone via wireless communication. During operation, the drone first conducts aerial survey flights over the entire sorghum field area to determine the field's extent and divide it into several virtual grid areas, assigning a number to each grid. The edge computing platform on the drone analyzes the pest and disease occurrence in each grid in real time during flight, such as disease severity and pest density, and compares this data with the thresholds issued by the cloud server. Based on edge computing analysis, agricultural drones automatically fly to designated grid locations carrying appropriate pesticides. They perform variable-rate spraying according to the severity of pests and diseases and a preset flight path. Grids with high severity levels receive increased spraying or use higher concentrations of pesticides, while grids with mild or no pests and diseases receive less spraying or are skipped. This solution achieves precise, on-demand, targeted, and quantitative pesticide application, significantly reducing pesticide usage and environmental pollution. Although the embodiments of this invention are described in the specification, these embodiments are merely illustrative and should not limit the scope of protection of this invention. Various omissions, substitutions, and modifications made without departing from the spirit of this invention should be included within the scope of protection of this invention.

Claims

1. A smart monitoring and control system for sorghum pests and diseases using a station-vehicle collaborative closed-loop operation, characterized in that: This includes fixed meteorological and pest observation stations, mobile intelligent inspection robots, and cloud servers. The fixed meteorological pest observation station includes a column base, a meteorological sensor module, a soil sensor module, a trapping device, a detection area removal device, a photovoltaic power supply unit, and a charging pile assembly. An equipment box is mounted on the column base, containing a first main control board, a first edge computing motherboard, and a first wireless communication module. The meteorological sensor module, soil sensor module, trapping device, detection area removal device, and photovoltaic power supply unit are all electrically connected to the first main control board. The charging pile assembly is located at the bottom of the column base and includes charging electrodes and a positioning target; the charging electrodes are electrically connected to the photovoltaic power supply unit. The mobile intelligent inspection robot includes a tracked chassis, a lifting platform, a cable chain mechanism, a gimbal mechanism, a camera module, a dual-battery power supply system, a control box, an automatic charging and alignment mechanism, and a harvesting box. The lifting platform is mounted on the tracked chassis and has a top support plate. The cable chain mechanism is located between the chassis and the support plate. The gimbal mechanism is mounted on the support plate. The camera module includes a first camera mounted on the support plate and a second camera mounted on the chassis. The dual-battery power supply system includes a power battery and an external battery, electrically connected via a power management module. The control box... The housing contains a second main control board and a second edge computing motherboard; the automatic charging alignment mechanism is located at the bottom of the chassis and includes charging contacts and a positioning sensor. The charging contacts are electrically connected to the power management module of the dual-battery power supply system, the positioning sensor is electrically connected to the second main control board, the charging contacts are matched with the charging electrodes of the fixed meteorological pest observation station, and the positioning sensor is matched with the positioning target of the fixed meteorological pest observation station to realize a detachable electrical connection between the mobile intelligent inspection robot and the fixed meteorological pest observation station. The harvesting box is installed on the tracked mobile chassis. The cloud server is communicatively connected to the first wireless communication module of the fixed meteorological pest observation station and the second wireless communication module of the mobile intelligent inspection robot. The fixed meteorological pest observation station only activates the light trapping function at night to monitor the dynamics of adult insect populations, while the mobile intelligent inspection robot performs inspection tasks during the day, identifying pest feeding based on vegetation status and simultaneously retrieving sorghum growth parameters; the light trapping function is uniquely configured in the fixed meteorological pest observation station.

2. The intelligent monitoring and control system for sorghum pests and diseases in a station-vehicle collaborative closed-loop operation according to claim 1, characterized in that: The detection area cleaning device includes one or more of a fan or a vibrator.

3. The intelligent monitoring and control system for sorghum pests and diseases using a station-vehicle collaborative closed-loop operation as described in claim 1, characterized in that: The lifting platform includes a telescopic mechanism, a drive motor, and limit switches; the telescopic mechanism consists of two parallel aluminum alloy telescopic rods; the limit switches are located at both ends of the travel of the telescopic mechanism and are electrically connected to the second main control board.

4. The intelligent monitoring and control system for sorghum pests and diseases in a station-vehicle collaborative closed-loop operation according to claim 1, characterized in that: The charging electrode is an elastic telescopic contact, and the positioning target is an infrared reflector; there are multiple charging contacts that are symmetrically distributed, and the positioning sensor is an infrared positioning sensor. The infrared positioning sensor cooperates with the positioning target to guide the charging contacts to dock with the charging electrode.

5. The intelligent monitoring and control system for sorghum pests and diseases in a station-vehicle collaborative closed-loop operation according to claim 1, characterized in that: Both the power battery and the peripheral battery are rechargeable lithium batteries, and the power management module is equipped with a reverse connection protection plug.

6. The intelligent monitoring and control system for sorghum pests and diseases in a station-vehicle collaborative closed-loop operation according to claim 1, characterized in that: The cable chain mechanism is a fully enclosed structure made of nylon, and the inside of the cable chain mechanism is equipped with partitions.

7. The intelligent monitoring and control system for sorghum pests and diseases in a station-vehicle collaborative closed-loop operation according to claim 1, characterized in that: The photovoltaic power supply unit includes a solar panel and a battery. The solar panel is installed on the top of the column base, and the battery is installed inside the equipment box.

8. The intelligent monitoring and control system for sorghum pests and diseases in a station-vehicle collaborative closed-loop operation according to claim 1, characterized in that: The inspection robot's gimbal mechanism includes a horizontal rotational servo motor and a pitch rotational servo motor, which are electrically connected to the second main control board. The servo motor output shaft adopts metal gear transmission and is equipped with a precision bearing structure.

9. The intelligent monitoring and control system for sorghum pests and diseases in a station-vehicle collaborative closed-loop operation according to claim 1, characterized in that: The system also includes a client and a drone, which are respectively connected to the cloud server.

10. The intelligent monitoring and control system for sorghum pests and diseases in a station-vehicle collaborative closed-loop operation according to claim 1, characterized in that: The fixed meteorological pest observation station is configured to activate the light trapping unit in the trapping device during the nighttime period, and use the image acquisition equipment configured on the fixed meteorological pest observation station itself to collect images of pests in the trapping area, identify the species and count the number of trapped pests, and use them for nighttime pest monitoring. The mobile intelligent inspection robot is configured to activate the camera module during the daytime to conduct field inspections for daytime pest and disease monitoring. The light trapping unit is only installed at the fixed meteorological pest observation station, and the mobile intelligent inspection robot does not have the light trapping function; the trapping device is a statistical trap.

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