Carbon neutral smart seeding device, system and method

Abstract

This invention discloses a carbon-neutral intelligent seeding device, system, and method, belonging to the field of agricultural intelligent equipment technology. It includes a machine body with a leveling structure at the front, a furrowing and seeding structure and a soil covering structure sequentially arranged along the travel direction in the middle section, a watering structure at the rear, and a steering structure at the bottom. The machine body integrates a central control system and a clean energy supply module. The central control system is equipped with a multi-sensor fusion processing subunit and a carbon footprint calculation subunit, simultaneously collecting multi-dimensional operational data such as leveling flatness, seeding depth, soil compaction, soil moisture, terrain slope, equipment energy consumption, and solar power generation. The clean energy supply module is equipped with an MPPT intelligent energy management submodule to achieve dynamic tracking and optimization of solar power generation. The steering structure adopts a composite steering structure of front wheel oscillation and rear wheel differential, dynamically adjusting steering parameters according to real-time terrain parameters.

Description

Technical Field

[0001] This invention relates to a carbon-neutral intelligent seeding device, system, and method, belonging to the field of agricultural intelligent equipment technology. Background Technology

[0002] With the advancement of global carbon neutrality goals, agriculture, as a significant sector of carbon emissions, urgently needs a green transformation. Traditional sowing methods have numerous drawbacks: high labor input and low operational efficiency, making it difficult to meet the needs of large-scale planting; poor sowing uniformity and inaccurate control of sowing depth and irrigation volume, leading to seed waste and uneven crop growth; and most equipment relies on fuel power, resulting in high carbon emissions, which is inconsistent with the concept of low-carbon development. These problems restrict the sustainability of agricultural production, necessitating an efficient, precise, and low-carbon sowing solution.

[0003] Furthermore, while some existing mechanized seeding equipment can replace manual labor to a certain extent, it generally suffers from fragmented functionality. Most only integrate the single processes of ditching and sowing, while subsequent key steps such as leveling and removing obstacles, covering and compacting the soil, and precise watering still require additional manual labor or separate equipment. This results in a fragmented workflow and time-consuming process connections, making it difficult to form a complete and efficient seeding loop. At the same time, these devices mostly use traditional fuel-powered systems, which not only emit large amounts of pollutants such as carbon dioxide and nitrogen oxides during operation, contradicting the requirements of low-carbon agricultural transformation, but also incur high long-term fuel purchase and maintenance costs, increasing the economic burden on growers. Moreover, their terrain adaptability is limited. In non-plain scenarios such as hilly slopes and small, irregular plots, problems such as bumpy travel and excessive deviations in sowing depth often occur, making it impossible to guarantee sowing quality. They also lack effective integration of clean energy. Even if some devices attempt to be equipped with simple solar panels, the lack of an intelligent energy management system results in an energy conversion efficiency of less than 60%, making it difficult to support continuous and stable operation of the equipment, further restricting the advancement of large-scale, low-carbon agricultural production.

[0004] Some related sowing device solutions already exist in existing publicly available technologies. For example, Chinese invention patent CN112913394A discloses an intelligent experimental seedling sowing device that uses a push rod motor to drive a plate to automatically dig holes and sow seeds, replacing manual labor in seedling sowing and reducing labor input. However, this solution is only suitable for small-scale laboratory seedling cultivation scenarios, integrating only the two processes of digging holes and sowing seeds. It lacks functions such as leveling, covering and compacting soil, and precise watering, and cannot meet the complete operational needs of large-scale field sowing. Furthermore, it uses a mains power supply mode, lacking clean energy supply and carbon footprint management capabilities, and does not meet the requirements of low-carbon agricultural production.

[0005] Chinese invention patent application CN117652237A discloses a multi-functional sandy land seeder. It employs a tracked walking mechanism adapted to complex sandy terrain, integrating the entire process of tilling, ditching, quantitative sowing, covering, and irrigation. It uses a gyroscope for self-calibration of motion posture and a light curtain sensor to detect seed placement, enabling automated sowing operations in sandy environments and reducing manual labor. However, this solution still has significant technical limitations: First, it lacks a clean energy supply system and a carbon footprint accounting module, thus lacking carbon neutrality control capabilities. Energy consumption and carbon emissions during operation are not dynamically optimized, failing to meet the requirements of low-carbon agricultural transformation. Second, the parameters for each process are controlled independently, without a multi-sensor fusion collaborative control algorithm. Parameters for leveling, sowing, covering, and irrigation cannot be dynamically matched based on real-time operational status, resulting in significant fluctuations in operational accuracy in non-sandy farmland and hilly slopes. Third, it lacks cloud data interaction and parameter self-iteration mechanisms, preventing continuous optimization of operational parameters based on historical data. It is only suitable for a single sandy operation scenario and cannot meet the needs of large-scale planting for different terrains and crops.

[0006] None of the aforementioned existing technologies can simultaneously meet the complex requirements of "multi-process integrated closed-loop operation, efficient utilization of low-carbon energy, precise adaptation to complex terrain, and full-process carbon footprint management," and are therefore insufficient to support the actual production requirements of large-scale, low-carbon, and intelligent transformation of agriculture. Summary of the Invention

[0007] To address the shortcomings of existing seeding equipment, such as high energy consumption, large carbon emissions, poor coordination of multi-process parameters, weak adaptability to complex terrain, and inability to achieve carbon footprint control throughout the entire operation process, this invention provides a carbon-neutral intelligent seeding device, system, and method that improves the accuracy and terrain adaptability of seeding operations while achieving the goal of carbon neutrality throughout the entire operation process.

[0008] The present invention discloses a carbon-neutral intelligent seeding device, comprising a body, a soil leveling structure at the front end of the body, a furrowing and seeding structure and a soil covering structure sequentially arranged in the middle section along the direction of travel, a watering structure at the rear of the body, and a steering structure at the bottom of the body. The body integrates a central control system and a clean energy supply module. The central control system is equipped with a multi-sensor fusion processing subunit and a carbon footprint calculation subunit, simultaneously collecting multi-dimensional operational data such as soil leveling flatness, seeding depth, soil compaction, soil moisture, terrain slope, equipment energy consumption, and solar power generation. The clean energy supply module is equipped with an energy management submodule to achieve dynamic tracking and optimization of solar power generation. The steering structure adopts a composite steering structure of front wheel oscillation and rear wheel differential, dynamically adjusting steering parameters according to real-time terrain parameters.

[0009] Preferably, the leveling structure includes a height-adjustable front shovel, an adjustable horizontal bar, an adjustable vertical bar, and a laser leveling sensor. The adjustable horizontal bar and the adjustable vertical bar form a lifting and adjusting structure connected to the front shovel. The height of the front shovel off the ground can be automatically adjusted according to the detection results of surface obstacles. The laser leveling sensor uploads the surface leveling data after the operation to the central control system in real time as input parameters for subsequent sowing depth adjustment.

[0010] Preferably, the furrowing and sowing structure includes a furrowing shovel, a conveying pipe, a lower sowing box, a bearing, an optical shaft, an upper sowing box, a bevel gear, a bevel gear, a DC geared motor, a sowing wheel, and a soil depth sensor. The furrowing shovel is fixed to the end of the conveying pipe. The lower sowing box and the upper sowing box are connected to form a seed-containing cavity. The sowing wheel is set in the cavity and mounted on the optical shaft. The optical shaft is fixed to the side wall of the sowing box through the bearing. The output end of the DC geared motor is connected to the bevel gear. The bevel gear meshes with the bevel gear mounted on the end of the optical shaft. The surface of the sowing wheel is provided with a quantitative seed-containing groove whose capacity can be adjusted according to the seed particle size. The soil depth sensor collects soil thickness data of the working area in real time. The central control system dynamically adjusts the ground clearance of the furrowing shovel and the output speed of the DC geared motor based on the data.

[0011] Preferably, the soil covering structure includes a compaction wheel, a second optical shaft, a compaction wheel bracket, a bearing bracket, a slider, a lead screw, a third optical shaft, an aluminum alloy base, a stepper motor bracket, a stepper motor, and a compaction sensor. The compaction wheel is mounted on the second optical shaft, which is fixed to the compaction wheel bracket via the bearing bracket. The top of the compaction wheel bracket is fixed to the bottom of the slider. The slider is mounted on the lead screw and the third optical shaft, both of which are fixed to the aluminum alloy base. The stepper motor is fixed to the side of the aluminum alloy base via a stepper motor bracket, and the output end of the stepper motor is connected to the lead screw. The compaction sensor collects real-time soil compaction data after soil covering. The central control system drives the stepper motor to rotate based on this data, thereby raising and lowering the slider to adjust the height of the compaction wheel above the ground and the compaction pressure.

[0012] Preferably, the watering structure includes a water supply pipe, a water storage tank, an impeller pump, and a soil moisture sensor. The inlet of the impeller pump is connected to the water storage tank, and the outlet is connected to the atomizing nozzle in the work area through the water supply pipe. The soil moisture sensor collects soil moisture data in real time after covering with soil, and the central control system dynamically adjusts the output flow of the impeller pump based on the data.

[0013] Preferably, the motion steering structure includes wheels, a second bearing, a gear, a second DC geared motor, a sprocket, a chain, a third DC geared motor, a pad, a rack, and a slope sensor. The output end of the second DC geared motor is connected to the differential, and power is transmitted to the rear wheel drive unit via the sprocket and chain. The front wheel steering axle is fixed to the machine body via the second bearing, and a gear is fixed to the top of the front wheel steering axle. The third DC geared motor is fixed to the machine body via the pad, and its output end is connected to a rack that meshes with the gear. The slope sensor collects the slope data of the plot in real time, and the central control system dynamically adjusts the rear wheel differential output of the second DC geared motor and the steering amplitude of the third DC geared motor based on the data.

[0014] Preferably, the energy management submodule of the clean energy supply module has built-in disturbance observation method / conductivity increment method control logic. The execution logic is as follows: read the current voltage V(k) and current current I(k) of the solar panel at a certain time period, calculate the current power P(k), compare it with the power P(k-1) and voltage V(k-1) of the previous period, and automatically adjust the adjustment direction and step size of the PWM duty cycle in the next period. The algorithm has built-in step size adaptive mechanism and anti-oscillation judgment logic, which can maintain the stability of power tracking under sudden change in light intensity.

[0015] The carbon-neutral intelligent seeding system of this invention includes a carbon-neutral intelligent seeding device, a cloud data platform, and a user terminal. The central control system of the carbon-neutral intelligent seeding device interacts bidirectionally with the cloud data platform via a wireless communication module. The cloud data platform stores a database of optimal operating parameters for different crops and different plots. The user terminal can remotely access the cloud data platform to obtain operating data and issue operating instructions. The central control system has the following built-in control modules: The DC motor dual closed-loop PID control module calculates the actual speed through the encoder value, takes the deviation between the target speed and the actual speed as input, and outputs the target torque command through the digital PID controller with integral limiting and output limiting. The current loop samples the motor drive current detection signal, fine-tunes the PWM duty cycle to limit the maximum current, and finally outputs the PWM duty cycle to control the operation of DC geared motor 1, DC geared motor 2, and DC geared motor 3. Stepper motor S-curve acceleration and deceleration control module: After receiving the target position command, it pre-plans an S-curve speed curve including acceleration, constant speed and deceleration segments. It dynamically adjusts the pulse frequency through a high-priority timer interrupt to generate a pulse sequence with variable frequency and precise quantity to drive the stepper motor and achieve precise adjustment of the press wheel height. Multi-sensor data fusion and filtering module: It uses median averaging filtering to remove extreme values ​​for the raw sensor data, and uses complementary filtering to fuse the inertial measurement unit and ultrasonic sensor data for terrain slope and body tilt angle data, and outputs smooth and stable state estimates. Adaptive decision-making module: Built-in tables of sowing depth and spacing parameters for different crops and soil textures. It looks up the table based on crop type and soil moisture parameters and calculates the target operation parameters through linear interpolation. Optional configuration of fuzzy logic irrigation decision-making submodule: Taking soil moisture deviation and moisture change trend as input, it outputs irrigation demand intensity through fuzzy rule reasoning and defuzzifies it into irrigation duration or water volume.

[0016] The carbon-neutral intelligent seeding method of this invention is based on the aforementioned carbon-neutral intelligent seeding system and incorporates two core algorithms to optimize the entire operation process: ① a PID algorithm for dynamic matching of seeding parameters based on multi-sensor fusion, and ② a real-time optimization and control algorithm for net carbon emissions. Specifically, it includes the following steps: S1: Pre-operation initialization: Complete the no-load self-check of each module of the device, upload the crop type and basic attribute parameters of the plot to the cloud data platform, match the optimal initial operation parameters, the clean energy supply module detects the energy storage battery power, and automatically starts solar charging when the power is lower than the preset threshold until the power meets the operation requirements. S2: Coordinated operation of the entire process: The device moves at a preset operating speed, and the leveling structure, trenching and sowing structure, soil covering structure and watering structure are started in sequence according to preset time delays. The operating parameters of each process are adjusted in real time by dynamically matching the sowing parameters with the PID algorithm. S3: Dynamic optimization of carbon footprint: During the operation, the energy supply strategy and equipment power consumption are dynamically adjusted through the real-time optimization and control algorithm of net carbon emissions to maintain the net carbon emissions of the entire operation process not higher than the carbon neutrality threshold. S4: Post-operation data synchronization: The device uploads all operation data to the cloud data platform, updates the optimal operation parameter library, and pushes an operation report containing operation volume, resource consumption, and carbon emission reduction to the user terminal.

[0017] Preferably, the execution logic of the PID algorithm for dynamic matching of sowing parameters based on multi-sensor fusion is as follows: Using the flatness error e1 from the leveling structure, the soil thickness error e2 from the soil depth sensor of the furrowing and sowing structure, and the soil moisture error e3 from the soil moisture sensor of the irrigation structure as input variables, the adjustment parameters are output through the PID control formula: ; in, The total weighted error is represented by w1, w2, and w3, which are pre-configured error weight coefficients, and K. p T is the proportionality coefficient. i Let T be the integration time constant. d The time constant is the differential; the output adjustment parameters correspond to the sowing depth compensation, the press wheel height adjustment, and the impeller pump flow rate adjustment, realizing the dynamic coordination and matching of the operation parameters of each process.

[0018] The execution logic of the real-time optimization and control algorithm for net carbon emissions is as follows: Real-time data collection of three types of data from the clean energy supply module: solar power generation Ws, total energy consumption We, and soil carbon sequestration increment Wc. The real-time net carbon emission value C is calculated using the following formula: ; Where α is the carbon emission coefficient per unit of energy consumption, β is the carbon emission reduction coefficient per unit of solar power generation, and γ is the carbon emission reduction coefficient per unit of soil carbon sequestration. When the calculated net carbon emission value C > 0, an energy-saving control strategy is automatically triggered: reduce the power consumption of non-core functional modules and increase the priority of solar power supply until the net carbon emission value returns to a carbon-neutral state of ≤ 0.

[0019] Preferably, step S2 further includes terrain adaptive adjustment logic: the slope sensor of the motion steering structure collects plot slope data at a fixed frequency. When the slope reaches a preset threshold, it automatically triggers parameter adjustment of the hilly operation mode: increasing the height of the front shovel off the ground, expanding the differential adjustment range of the rear wheels, and reducing the spring clamping force of the press wheel to avoid equipment jamming and sowing depth deviation on slopes. In step S4, the cloud data platform uses the K-means clustering algorithm to label the parameter data of this operation, calculates the cosine similarity between the feature vector of the current operation parameters and the feature vector of the historical operation parameters, and matches the historical parameter group with the highest similarity to update the optimal operation parameter library. The next time the same plot and the same crop are operated, the matched optimal parameter group can be directly called without repeated setting.

[0020] Compared with existing technologies, the intelligent harvesting device and method based on visual recognition and motion control of the present invention exhibits the following beneficial effects in terms of technical performance and practical application: 1. Closed-loop integration of the entire process significantly improves operational efficiency. This invention integrates five core sowing processes: leveling, ditching, sowing, covering, and watering. A single device can complete the entire sowing process in one go, eliminating the need for multiple devices or manual supplementary steps. The work chain is shortened by 60% compared to the traditional model, and labor input is reduced by 70%. The daily work efficiency of a single device can reach 15 acres / day, greatly simplifying the sowing process, avoiding time losses and labor costs associated with process connections, and meeting the high-efficiency operation requirements of large-scale planting.

[0021] 2. Clean energy provides efficient power supply with significant carbon neutrality benefits. By using solar panels in conjunction with the MPPT intelligent energy management system for power supply, the solar energy conversion efficiency can reach over 95%, which is 60% higher than that of traditional simple solar seeding equipment. The net carbon emissions throughout the entire operation process can be stably controlled at ≤0, reducing carbon emissions by more than 82% compared to fuel-fired seeding equipment of the same power. It can reduce carbon emissions by about 12.7 kg per acre per year, which is in line with the concept of carbon-neutral agriculture development. It has outstanding green and environmentally friendly attributes and can be connected to the agricultural carbon sink accounting system to help growers obtain additional carbon emission reduction benefits.

[0022] 3. Multi-dimensional intelligent control significantly improves operational accuracy and resource utilization. Equipped with a multi-sensor fusion central control system, it can achieve full-dimensional adjustment of core operating parameters: the sowing spacing supports custom adjustment from 5cm to 15cm, the sowing depth supports stepless adjustment from 2cm to 5cm, the irrigation volume can be dynamically adapted according to soil moisture, the overall sowing accuracy is stable at ±1cm, reducing seed waste by more than 15% compared with traditional sowing equipment, improving irrigation water resource utilization by 40%, avoiding unnecessary loss of seeds and water resources, and increasing the average seed germination rate by 12%, directly improving crop planting quality and yield.

[0023] 4. Adapts to all terrains and covers a wide operational range. Employing a combined steering mode of front wheel oscillation and rear wheel differential, along with a height-adjustable working machinery structure, it can adapt to various terrains such as plains, hills, and sandy areas, with an all-terrain passability of ≥92% and a minimum turning radius of only 1.2m. It can meet the operational needs of small, irregular plots and corner plots, and the field coverage rate is increased by more than 25% compared to traditional seeding equipment. It solves the pain points of existing equipment that can only adapt to a single terrain and has poor operation quality in complex plots, and can meet the operational needs of different regions and different planting scenarios.

[0024] 5. User-friendly human-computer interaction, significantly reducing the barrier to entry. It supports Bluetooth remote control and real-time operation data feedback on the device display screen. Operators can complete parameter adjustments, start and stop operations without following the equipment. A single person can manage 3-5 devices simultaneously. The operation process is simple and easy to learn, and no professional technical background is required to use it proficiently, which lowers the threshold for using intelligent seeding equipment and adapts to the different operational needs of small and medium-sized growers and large-scale farms.

[0025] This invention eliminates the need for fuel procurement costs, reducing annual energy consumption costs by more than 85% compared to fuel-powered seeding equipment. Its modular design lowers annual maintenance costs by 40% compared to traditional equipment, resulting in a reduction of approximately 80 yuan per acre in annual planting costs. Furthermore, it supports integration with agricultural smart management platforms, enabling remote viewing of operational data and unified scheduling of equipment clusters. This aligns with the large-scale management upgrade needs of digital agriculture and smart farms, resulting in significant overall benefits. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the overall structure of the carbon-neutral intelligent seeding device of the present invention; Figure 2 This is a schematic diagram of the leveling structure in the carbon-neutral intelligent seeding device of the present invention; Figure 3 This is a schematic diagram of the furrowing and sowing structure in the carbon-neutral intelligent sowing device of the present invention; Figure 4 This is a schematic diagram of the seeding wheel structure in the carbon-neutral intelligent seeding device of the present invention; Figure 5 This is a schematic diagram of the soil covering structure in the carbon-neutral intelligent seeding device of the present invention; Figure 6 This is a schematic diagram of the watering structure in the carbon-neutral intelligent seeding device of the present invention; Figure 7 This is a schematic diagram of the impeller pump in the carbon-neutral intelligent seeding device of the present invention; Figure 8 This is a schematic diagram of the motion steering structure in the carbon neutrality intelligent seeding device of the present invention; Figure 9 This is a schematic diagram of the rack structure in the carbon-neutral intelligent seeding device of the present invention; Figure 10 This is a schematic diagram of the central control system in the carbon-neutral intelligent seeding device of the present invention; Figure 11 This is a schematic diagram of the clean energy supply module in the carbon-neutral intelligent seeding device of the present invention; In the diagram: 1. Leveling structure; 101. Front shovel plate; 102. Adjustable crossbar; 103. Adjustable vertical bar; 2. Furrowing and sowing structure; 201. Furrowing shovel; 202. Conveying pipe; 203. Lower part of the sowing box; 204. Bearing 1; 205. Optical shaft 1; 206. Upper part of the sowing box; 207. Bevel gear 1; 208. Bevel gear 2; 209. DC geared motor 1; 210. Sowing wheel; 3. Covering structure; 301. Pressing wheel; 302. Optical shaft 2; 303. Pressing wheel bracket; 304. Bearing bracket; 305. Sliding block 306. Lead screw; 307. Optical shaft three; 308. Aluminum alloy base; 309. Stepper motor frame; 310. Stepper motor; 4. Watering structure; 401. Water supply pipe; 402. Water storage tank; 403. Impeller pump; 5. Motion steering structure; 501. Wheel; 502. Bearing two; 503. Gear; 504. DC geared motor two; 505. Sprocket; 506. Chain; 507. DC geared motor three; 508. Pad; 509. Rack; 6. Machine body; 7. Central control system; 8. Clean energy supply module. Detailed Implementation

[0027] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0028] Example 1: like Figure 1 , 10 As shown in Figure 11, the carbon-neutral intelligent seeding device of the present invention includes a body 6. A leveling structure 1 is provided at the front end of the body 6. A furrowing and seeding structure 2 and a soil covering structure 3 are provided sequentially along the direction of travel in the middle section of the body 6. A watering structure 4 is provided at the rear of the body 6. A motion steering structure 5 is provided below the body 6. A central control system 7 and a clean energy supply module 8 are integrated on the body 6. The central control system 7 is equipped with a multi-sensor fusion processing subunit and a carbon footprint accounting subunit, which simultaneously collects multi-dimensional operating data such as leveling flatness, seeding depth, soil compaction, soil moisture, terrain slope, equipment energy consumption, and solar power generation. The clean energy supply module 8 is equipped with an MPPT intelligent energy management submodule to realize dynamic tracking and optimization of solar power generation. The motion steering structure 5 adopts a composite steering structure of front wheel swing + rear wheel differential, which dynamically adjusts the steering parameters according to real-time terrain parameters.

[0029] like Figure 2 As shown, the leveling structure 1 includes a height-adjustable front shovel 101, an adjustable horizontal bar 102, an adjustable vertical bar 103, and a laser flatness sensor. The adjustable horizontal bar 102 and the adjustable vertical bar 103 form a lifting and adjusting structure connected to the front shovel 101. The height of the front shovel 101 off the ground can be automatically adjusted according to the detection results of surface obstacles. The laser flatness sensor uploads the surface flatness data after the operation to the central control system 7 in real time as input parameters for subsequent sowing depth adjustment.

[0030] like Figures 3-4As shown, the furrowing and sowing structure 2 includes a furrowing shovel 201, a conveying pipe 202, a lower sowing box 203, a bearing 204, an optical shaft 205, an upper sowing box 206, a bevel gear 207, a bevel gear 208, a DC geared motor 209, a sowing wheel 210, and a soil depth sensor. The furrowing shovel 201 is fixed to the end of the conveying pipe 202. The lower sowing box 203 and the upper sowing box 206 are connected to form a seed-containing cavity. The sowing wheel 210 is set in the cavity and mounted on the optical shaft 205. 205 is fixed to the side wall of the seed box by bearing 204. The output end of DC geared motor 209 is connected to bevel gear 207. Bevel gear 207 meshes with bevel gear 208 mounted on the end of optical shaft 205. The surface of seeding wheel 210 is provided with a quantitative seed trough whose capacity can be adjusted according to the seed size. Soil depth sensor collects soil thickness data of the working area in real time. The central control system 7 dynamically adjusts the ground clearance of furrowing shovel 201 and the output speed of DC geared motor 209 according to the data.

[0031] like Figure 5 As shown, the soil covering structure 3 includes a compaction wheel 301, a second optical axis 302, a compaction wheel bracket 303, a bearing bracket 304, a slider 305, a lead screw 306, a third optical axis 307, an aluminum alloy base 308, a stepper motor bracket 309, a stepper motor 310, and a compaction sensor. The compaction wheel 301 is mounted on the second optical axis 302, and the second optical axis 302 is fixed to the compaction wheel bracket 303 via the bearing bracket 304. The top of the compaction wheel bracket 303 is fixed to the bottom of the slider 305, and the slider 305 is mounted on... The screw 306 and the optical axis 307 are mounted on the lead screw 306 and the optical axis 307, respectively. Both the lead screw 306 and the optical axis 307 are fixed on the aluminum alloy base 308. The stepper motor 310 is fixed to the side of the aluminum alloy base 308 through the stepper motor frame 309. The output end of the stepper motor 310 is connected to the lead screw 306. The compaction sensor collects the soil compaction data after the soil is covered in real time. The central control system 7 drives the stepper motor 310 to rotate according to the data, thereby driving the slider 305 to rise and fall to adjust the ground clearance of the compaction wheel 301 and the compaction pressure.

[0032] like Figures 6-7 As shown, the watering structure 4 includes a water supply pipe 401, a water storage tank 402, an impeller pump 403, and a soil moisture sensor. The inlet of the impeller pump 403 is connected to the water storage tank 402, and the outlet is connected to the atomizing nozzle in the work area through the water supply pipe 401. The soil moisture sensor collects soil moisture data after covering the soil in real time, and the central control system 7 dynamically adjusts the output flow of the impeller pump 403 according to the data. like Figures 8-9As shown, the motion steering structure 5 includes a wheel 501, a second bearing 502, a gear 503, a second DC geared motor 504, a sprocket 505, a chain 506, a third DC geared motor 507, a pad 508, a rack 509, and a slope sensor. The output end of the second DC geared motor 504 is connected to the differential, and power is transmitted to the rear wheel drive unit via the sprocket 505 and the chain 506. The front wheel steering axle is fixed to the body 6 via the second bearing 502, and the gear 503 is fixed to the top of the front wheel steering axle. The third DC geared motor 507 is fixed to the body 6 via the pad 508, and its output end is connected to the rack 509 that meshes with the gear 503. The slope sensor collects the slope data of the plot in real time, and the central control system 7 dynamically adjusts the rear wheel differential output of the second DC geared motor 504 and the steering amplitude of the third DC geared motor 507 based on the data.

[0033] The MPPT intelligent energy management submodule of the clean energy supply module 8 has built-in disturbance observation method / conductivity increment method control logic. The execution logic is as follows: read the current voltage V(k) and current current I(k) of the solar panel with a period of 100ms, calculate the current power P(k), compare it with the power P(k-1) and voltage V(k-1) of the previous period, and automatically adjust the adjustment direction and step size of the PWM duty cycle in the next period. The algorithm has built-in step size adaptive mechanism and anti-oscillation judgment logic, which can maintain the stability of power tracking under sudden change in light intensity.

[0034] The present invention will be further illustrated below with specific examples. These examples are implemented based on the technical solution of the present invention and provide detailed operation procedures and specific parameters. However, the scope of protection of the present invention is not limited to the following embodiments. The core hardware selection involved in this example is as follows: the central control system uses an STM32F103C8T6 microcontroller, the DC motor drive module uses an L298N, the stepper motor drive module uses a TB6600, and the clean energy supply module uses a 100W monocrystalline silicon solar panel paired with a 12V 20Ah polymer lithium battery. The sampling accuracy of all sensors meets the requirements of agricultural operations.

[0035] Main control chip: STM32F103C8T6 is used as the core processor. Its peripheral circuitry includes: Power supply circuit: A two-stage voltage regulator design is adopted. The first stage uses an LM2596S to stabilize the external input voltage (12-24V) to 5V; the second stage uses an AMS1117-3.3 to convert 5V to 3.3V to power the MCU and core chip. Each power input stage is equipped with a π-type filter circuit and a TVS transient suppression diode.

[0036] Clock circuit: An 8MHz high-speed crystal oscillator and a 32.768kHz low-speed crystal oscillator are connected to serve as the system master clock and real-time clock reference, respectively.

[0037] Reset and Debugging Circuit: Design power-on reset and manual reset circuits, and bring out the standard SWD debugging interface.

[0038] Isolation Interface: All external GPIOs (except for debug ports) are electrically isolated through high-speed optocouplers (such as 6N137) or digital isolation chips (such as ADuM1201), with an isolation voltage of not less than 2500Vrms.

[0039] Case 1: Winter wheat sowing operations in plain loam soil This embodiment is applicable to loamy land plots in the North China Plain with a slope of ≤2°, where winter wheat is planted, and the operating area is 15 mu (approximately 1 hectare). The specific implementation process is as follows: (a) Preparation stage before the operation 1. Equipment Inspection and Initialization Before operation, the core components of the equipment were pre-tested: First, the battery level was confirmed to be 85% through the display screen of the clean energy supply module 8, which meets the operation requirements; second, the connection was established with the mobile control program through the Bluetooth module of the central control system 7, and a "self-test command" was sent. The microcontroller drove each module to complete the no-load test: the DC geared motor 209 of the furrowing and sowing structure 2 drove the sowing wheel 210 to rotate 10 times, and the quantitative seed trough was unobstructed; the lead screw 306 of the soil covering structure 3 drove the press wheel 301 to complete the height adjustment from 5cm to 15cm, and the stepper motor 310 had an operating accuracy error of ≤0.1cm; the impeller pump 403 of the watering structure 4 started for 10 seconds, and the water flow was uniform and unobstructed, with a self-test pass rate of 100%.

[0040] 2. Setting operating parameters Based on the characteristics of winter wheat planting and soil properties, the core parameters are input through the control terminal: Sowing parameters: Set the sowing spacing to 8cm and the sowing depth to 3cm. The central control system 7 converts the parameters into electrical signals to control the speed of DC geared motor 209 to 1r / s (corresponding to the speed of sowing wheel 210) and the height of furrowing shovel 201 from the ground to 3cm. Irrigation parameters: Set the soil moisture threshold to 18%-22%. The moisture sensor collects soil data at a frequency of 1 time / second. When the soil moisture is below the threshold, the watering structure 4 is automatically triggered. Terrain adaptation parameters: The plot is a plain, the motion steering structure 5 is set to "normal mode", and the transmission sensitivity of the front wheel gear 503-rack 509 is adjusted to medium.

[0041] (II) On-site operation phase The DC geared motor 504 of the motion steering structure 5 drives the differential through a coupling. Power is transmitted to the wheels 501 via sprocket 505 and chain 506, and the machine body 6 moves at a constant speed of 0.8 m / s. Leveling-furrowing and sowing coordinated operation: The front shovel plate 101 of the leveling structure 1 is kept 3cm off the ground, pushing stones and crop residues with a diameter ≤5cm on the surface of the plot to both sides, forming a leveling operation zone with a width of 1.2m; the soil signal after leveling is fed back to the central control system 7, and after a delay of 0.5 seconds, the furrowing and sowing structure 2 is started: DC geared motor 209 drives the optical shaft 205 to rotate through bevel gear 207 and bevel gear 208, and the sowing wheel 210 rotates at a speed of 1r / s. Winter wheat seeds fall into the quantitative seed trough with a single trough capacity of 0.5g, and rotate with the sowing wheel 210 to the inlet of the conveying pipe 202, and fall naturally into the sowing furrow opened by the furrowing shovel 201 (shovel head angle 30°), and the sowing depth is stably maintained at 3cm±0.7cm.

[0042] Covering and watering connection operation: After the furrowing and sowing structure 2 is in operation, the machine body 6 continues to move 0.3m (about 0.4 seconds), and the covering structure 3 is started: the stepper motor 310 drives the lead screw 306 to adjust the height of the pressing wheel 301 to 8cm. Under the action of the 50N spring buffer force, the rubber protrusions on the surface of the pressing wheel 301 push the soil on both sides of the sowing furrow into the furrow to complete the covering and compaction. The soil compaction degree is stable at 1.2g / cm³, which meets the requirements for wheat germination. At the same time, the humidity sensor is inserted into the soil surface layer 1cm deep after covering and collects the initial humidity of 16% (below the threshold). The central control system 7 immediately triggers the impeller pump 403 to pump water at a flow rate of 50ml / min and sprays it into the covered area through the 0.8mm aperture atomizing nozzle (connected to the water supply pipe 401) until the humidity reaches 20% and then automatically stops the pump. The irrigation volume error is ≤4%.

[0043] Real-time monitoring and early warning: The central control system displays data such as travel distance, sowing density, soil moisture, and battery level in real time. During operation, when the infrared sensor of the sowing box (206 on top of the sowing box + 203 on the bottom of the sowing box) detects that the seed quantity is insufficient, it immediately triggers an audible and visual warning and sends a "re-sowing prompt" to the control terminal. The equipment automatically slows down to 0.2m / s. After re-sowing is completed, it automatically resumes normal operating speed, with no fault-free shutdown throughout the process.

[0044] (III) Dynamic Management of Clean Energy Supply The operation period is sunny at noon with a light intensity of ≥8000 lux. The MPPT intelligent energy management system equipped in the clean energy power supply module 8 prioritizes solar power supply, and excess energy is stored in the lithium battery. The battery charge increases from 85% to 92% during the entire operation without the need for external charging, and the energy conversion efficiency reaches 95.3%.

[0045] (iv) Post-operation finishing stage Equipment cleaning and maintenance: After the operation is completed, send a "cleaning command". The impeller pump 403 of the watering structure 4 will start for 30 seconds and use the remaining clean water in the water storage tank 402 to rinse the delivery pipe 202 and the trenching shovel 201 to prevent soil caking. Raise the front shovel plate 101 to the highest position and manually remove surface weeds and gravel. Disassemble the seeding box (upper seeding box 206 + lower seeding box 203) to clean up the remaining wheat seeds to prevent mold.

[0046] Data storage and backup: The central control system 7 automatically stores the data for this operation: operation area 15.2 acres, seed usage 27.4 kg, total irrigation 32.6 L, carbon emission reduction 8.7 kg. The data can be exported to the control terminal via Bluetooth. The system automatically backs up the winter wheat sowing parameters for this operation, which can be directly called up for the next operation on the same plot without repeated settings.

[0047] Case 2: Spring Maize Planting Operations in Hilly Sandy Loam Fields This embodiment is applicable to sandy loam soil in hilly areas of southern China with a slope of ≤12°, where spring corn is planted, and the operating area is 8 mu (approximately 0.33 hectares). The specific implementation process is as follows: (a) Preparation stage before the operation The equipment self-check confirmed that the battery power was 90%, and the parameters were set as follows: sowing spacing 12cm, sowing depth 4cm, soil moisture threshold set to 15%-18%, motion steering structure 5 switched to "terrain adaptation mode", the rear wheel differential speed difference adjustment range was expanded to ±15%, and the height of the front shovel 101 of leveling structure 1 was increased by 2cm to 5cm.

[0048] (II) On-site operation phase The aircraft 6 is moving at a speed of 0.6 m / s, and the terrain adaptation function is automatically activated: Smooth steering and obstacle avoidance: When the front wheel encounters a protrusion with a height of ≤8cm, the pressure sensor of the front wheel support linkage sends a signal to the central control system 7. The system controls the gear 503-rack 509 structure (the DC geared motor 507 is fixed to the body 6 through the pad 508, and the output end is connected to the rack 509) to fine-tune the steering angle (single adjustment range ±3°). At the same time, the differential increases the speed difference between the left and right rear wheels (0.6m / s for the left rear wheel and 0.75m / s for the right rear wheel). The minimum turning radius is controlled at 1.2m, with no side tilt or jamming throughout the entire process.

[0049] Dynamic adjustment of sowing parameters: The depth sensor of the furrowing shovel 201 detects the soil thickness in real time. When the soil thickness in a certain area is only 8cm, the central control system 7 immediately reduces the speed of the DC geared motor 209 from 1r / s to 0.7r / s and finely adjusts the height of the furrowing shovel 201 to reduce the sowing depth from 4cm to 2cm, so as to avoid the furrowing shovel 201 touching the underground hard layer; the spring force of the pressing wheel 301 of the soil covering structure 3 is adjusted to 40N to avoid the seeds from being deprived of oxygen due to excessive soil compaction on the slope. The screw 306 automatically calibrates the height of the pressing wheel 301 every 10m of travel, and the soil covering thickness error is ≤±0.5cm.

[0050] Watering adaptation adjustment: The humidity sensor detects that the initial humidity of the sandy soil is 14%. The central control system 7 increases the flow rate of impeller pump 403 to 65ml / min until the humidity reaches 17% and then stops the pump to adapt to the poor water retention of sandy soil.

[0051] (III) Dynamic Management of Clean Energy Supply During the operation period, the daytime was cloudy with a light intensity of 2500 lux. The MPPT intelligent energy management system of the clean energy power supply module 8 automatically switched to "battery power mode". At the same time, the brightness of the display screen was adjusted to 50% and the sampling frequency of the humidity sensor was reduced to 1 time / 2 seconds. During the entire operation, the battery level dropped from 90% to 62%, which can support continuous operation for more than 2.5 hours.

[0052] (iv) Post-operation finishing stage After the equipment was cleaned, the central control system 7 stored the operation data: operation area 8.1 acres, seed usage 12.2 kg, total irrigation 21.8 L, carbon emission reduction 4.6 kg, and the pass rate for hilly terrain operation reached 98%.

[0053] Implementation effect verification The operational data from the two cases were statistically analyzed, and the results were compared with those of the existing publicly available technology (CN117652237A multi-functional sand seeder) as follows:

[0054] Verification results show that this invention fully achieves its design goals of integrated operation across all processes, low-carbon and high-efficiency energy supply, all-terrain adaptability, and high-precision control, meeting the needs of large-scale, low-carbon, and intelligent agricultural production. Those skilled in the art can adjust the parameters according to the needs of different crops and plots, all of which fall within the scope of protection of this invention. Example 2: The carbon-neutral intelligent seeding system of the present invention is based on the carbon-neutral intelligent seeding device, cloud data platform, and user terminal described in Example 1. The central control system 7 of the carbon-neutral intelligent seeding device interacts bidirectionally with the cloud data platform through a wireless communication module. The cloud data platform stores a database of optimal operating parameters for different crops and different plots. The user terminal can remotely access the cloud data platform to obtain operating data and issue operating instructions.

[0055] The central control system 7 has four built-in control modules: ① DC motor dual closed-loop PID control module: Using a 10ms control cycle, the speed loop calculates the actual speed through the encoder value, takes the deviation between the target speed and the actual speed as input, and outputs the target torque command through the digital PID controller with integral limiting and output limiting; the current loop samples the motor drive current detection signal, fine-tunes the PWM duty cycle to limit the maximum current, and finally outputs the PWM duty cycle to control the operation of DC geared motor 1-209, DC geared motor 2-504, and DC geared motor 3-507; ② Stepper motor S-curve acceleration and deceleration control module: After receiving the target position command, the module pre-plans an S-curve speed curve including acceleration, constant speed and deceleration segments. It dynamically adjusts the pulse frequency through a high-priority timer interrupt to generate a pulse sequence with variable frequency and precise quantity to drive the stepper motor 310 to run, thereby achieving precise adjustment of the height of the press wheel 301. ③ Multi-sensor data fusion and filtering module: The raw sensor data collected by the ADC is filtered by median average to remove extreme values. The terrain slope and body tilt angle data are fused by complementary filtering to fuse the inertial measurement unit and ultrasonic sensor data, and output a smooth and stable state estimate. ④ Adaptive decision-making module: It has built-in tables of sowing depth and spacing parameters for different crops and soil textures. It can look up the table according to crop type and soil moisture parameters and calculate the target operation parameters through linear interpolation. An optional fuzzy logic irrigation decision-making submodule is configured. It takes soil moisture deviation and moisture change trend as input, and outputs irrigation demand intensity through fuzzy rule reasoning. It is defuzzified into irrigation duration or water volume.

[0056] Carbon-neutral intelligent seeding device: that is, the hardware device described in Example 1. The central control system 7 is equipped with a 4G wireless communication module with a sampling frequency of 1Hz. It can upload operation data to the cloud in real time and receive parameter instructions sent from the cloud. The data transmission delay is ≤0.5 seconds.

[0057] Cloud-based data platform: Deployed on Alibaba Cloud servers, it has a built-in optimal operation parameter library for 27 mainstream crops and 12 typical plots, storing over 10,000 historical operation data entries; it supports three major functions: automatic parameter matching, operation data storage and analysis, and parameter library self-iteration, with a single device parameter matching response time of ≤2 seconds.

[0058] User terminal: WeChat mini program / tablet management APP, which supports users to remotely upload plot information (location, slope, soil type, crops planted), issue work instructions, and view real-time work progress and work reports, with data synchronization delay ≤1 second.

[0059] Example 3: This embodiment describes a carbon-neutral intelligent sowing method, using spring maize sowing in hilly sandy loam soil as a scenario. The core algorithm parameters are pre-configured as follows: PID algorithm error weights w1=0.2 (flatness error weight), w2=0.5 (soil thickness error weight), w3=0.3 (humidity error weight); carbon emission coefficients α=0.583kgCO2 / kWh, β=0.583kgCO2 / kWh, γ=1.8kgCO2 / kg; and the K-means clustering parameter similarity threshold is 0.95. The specific execution process is as follows: S1: Pre-operation initialization After the device is started, it first completes a no-load self-check: the trenching and sowing structure 2, the soil covering structure 3, and the watering structure 4 are all operating normally. The clean energy supply module 8 detects that the battery power is 90%, which meets the operation requirements. The user uploads the planting crop as spring corn and the plot as a sandy loam plot with a slope of 10° through the terminal. The cloud data platform matches the optimal initial parameters: sowing spacing 12cm, depth 4cm, humidity threshold 15%-18%, and terrain mode as hilly adaptation mode, and sends them to the central control system 7 to take effect.

[0060] S2: Collaborative operation across all processes The device travels at a speed of 0.6 m / s. The leveling structure 1, furrowing and sowing structure 2, soil covering structure 3, and watering structure 4 are activated sequentially with delays of 0.5 seconds, 0.9 seconds, and 1.3 seconds, respectively. The parameters are dynamically adjusted through a multi-sensor fusion PID algorithm. The input errors collected for a certain work section are: flatness error e1=1cm, soil thickness error e2=2cm, and moisture error e3=3%. The weighted total error e(t) is calculated to be 0.2×1+0.5×2+0.3×3=2.1. The output adjustment parameters are calculated by the PID formula: sowing depth compensation amount -2cm (from 4cm to 2cm), press wheel 301 height adjustment amount +0.5cm, impeller pump 403 flow rate adjustment amount +15ml / min. After parameter adjustment, the sowing depth error is reduced from 2cm to 0.8cm, and the irrigation amount error is reduced from 7% to 3%, realizing dynamic coordination and matching of each process. At the same time, the slope sensor detected that the slope of the plot was 10°, reaching the preset threshold, and automatically triggered the hill mode parameter adjustment: the height of the front shovel 101 off the ground was increased to 5cm, the differential adjustment range of the rear wheel was expanded to ±15%, and the spring clamping force of the pressure wheel 301 was reduced to 40N, with no jamming or tilting problems throughout the process.

[0061] S3: Dynamic Optimization of Carbon Footprint During the operation, three types of data were collected in real time: total equipment energy consumption We = 1.8 kWh, solar power generation Ws = 3.2 kWh, and soil carbon sequestration increment Wc = 0.6 kg. These data were then substituted into the net carbon emission formula for calculation. C=0.583×1.8 - 0.583×3.2 - 1.8×0.6 = 1.05 - 1.87 - 1.08 = -1.9kg.

[0062] The net carbon emissions are negative, which meets the carbon neutrality requirements, and there is no need to trigger the energy-saving strategy. If there is insufficient sunlight on a cloudy day, and the calculated C=0.3kg>0, the system will automatically trigger the energy-saving strategy: reduce the brightness of the display screen to 30%, reduce the sampling frequency of the humidity sensor to 1 time / 2 seconds, and turn off non-core lighting modules. After the adjustment, C will return to the carbon neutrality state of ≤0 within 10 minutes.

[0063] S4: Post-task data synchronization After the operation is completed, the device uploads all operation data to the cloud data platform: operation area 8.1 mu, seed usage 12.2 kg, total irrigation 21.8 L, carbon emission reduction 4.6 kg. The cloud uses the K-means clustering algorithm to label the parameters of this operation. The calculated cosine similarity between the feature vector of this parameter and the historical parameters of the same type is 0.92, which is lower than the threshold of 0.95. Therefore, the parameter set of this operation is updated to the optimal operation parameter library. The parameter set can be directly called when spring corn operation with the same slope and soil in the future without repeated setting. At the same time, the cloud pushes the operation report to the user terminal, which includes the operation amount, resource consumption, and carbon emission reduction certificate, which can be directly used for agricultural carbon sink declaration.

[0064] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A carbon-neutral intelligent seeding device, comprising a body (6), wherein a leveling structure (1) is provided at the front end of the body (6), a furrowing and seeding structure (2) and a soil covering structure (3) are provided sequentially along the direction of travel in the middle section of the body (6), a watering structure (4) is provided at the rear side of the body (6), a motion steering structure (5) is provided below the body (6), and a central control system (7) and a clean energy supply module (8) are integrated on the body (6), characterized in that: The central control system (7) is equipped with a multi-sensor fusion processing subunit and a carbon footprint accounting subunit, which simultaneously collect multi-dimensional operation data such as soil flatness, sowing depth, soil compaction, soil moisture, terrain slope, equipment energy consumption, and solar power generation; the clean energy supply module (8) is equipped with an energy management submodule to realize dynamic tracking and optimization of solar power generation; the motion steering structure (5) adopts a composite steering structure of front wheel swing + rear wheel differential, which dynamically adjusts the steering parameters according to real-time terrain parameters.

2. The carbon-neutral intelligent seeding device according to claim 1, characterized in that: The leveling structure (1) includes a height-adjustable front shovel (101), an adjustable crossbar (102), an adjustable vertical bar (103), and a laser flatness sensor. The adjustable crossbar (102) and the adjustable vertical bar (103) form a lifting and adjusting structure connected to the front shovel (101). The height of the front shovel (101) off the ground can be automatically adjusted according to the detection results of surface obstacles. The laser flatness sensor uploads the surface flatness data after the operation to the central control system (7) in real time as the input parameter for subsequent sowing depth adjustment.

3. The carbon-neutral intelligent seeding device according to claim 1, characterized in that: The furrowing and sowing structure (2) includes a furrowing shovel (201), a conveying pipe (202), a lower part of the sowing box (203), a bearing (204), an optical axis (205), an upper part of the sowing box (206), a bevel gear (207), a bevel gear (208), a DC geared motor (209), a sowing wheel (210), and a soil depth sensor. The furrowing shovel (201) is fixed to the end of the conveying pipe (202). The lower part of the sowing box (203) and the upper part of the sowing box (206) are connected to form a seed-containing cavity. The sowing wheel (210) is set in the cavity and mounted on the optical axis (205). The optical axis (205) is fixed to the side wall of the seed box by bearing (204). The output end of the DC geared motor (209) is connected to the bevel gear (207). The bevel gear (207) meshes with the bevel gear (208) mounted on the end of the optical axis (205). The surface of the seed wheel (210) is provided with a quantitative seed trough whose capacity can be adjusted according to the seed particle size. The soil depth sensor collects the soil thickness data of the working area in real time. The central control system (7) dynamically adjusts the ground clearance of the trenching shovel (201) and the output speed of the DC geared motor (209) according to the data.

4. The carbon-neutral intelligent seeding device according to claim 1, characterized in that: The soil covering structure (3) includes a compaction wheel (301), a second optical axis (302), a compaction wheel bracket (303), a bearing bracket (304), a slider (305), a lead screw (306), a third optical axis (307), an aluminum alloy base (308), a stepper motor bracket (309), a stepper motor (310), and a compaction sensor; the compaction wheel (301) is mounted on the second optical axis (302), the second optical axis (302) is fixed to the compaction wheel bracket (303) via the bearing bracket (304), the top of the compaction wheel bracket (303) is fixed to the bottom of the slider (305), and the slider (305) 305) is mounted on the lead screw (306) and the optical axis three (307). The lead screw (306) and the optical axis three (307) are both fixed on the aluminum alloy base (308). The stepper motor (310) is fixed on the side of the aluminum alloy base (308) through the stepper motor frame (309). The output end of the stepper motor (310) is connected to the lead screw (306). The compaction sensor collects the soil compaction data after the soil is covered in real time. The central control system (7) drives the stepper motor (310) to rotate according to the data, and drives the slider (305) to rise and fall to adjust the ground clearance of the compaction wheel (301) and the compaction pressure.

5. The carbon-neutral intelligent seeding device according to claim 1, characterized in that: The watering structure (4) includes a water supply pipe (401), a water storage tank (402), an impeller pump (403), and a soil moisture sensor. The inlet of the impeller pump (403) is connected to the water storage tank (402), and the outlet is connected to the atomizing nozzle of the work area through the water supply pipe (401). The soil moisture sensor collects soil moisture data after covering the soil in real time, and the central control system (7) dynamically adjusts the output flow of the impeller pump (403) according to the data. The motion steering structure (5) includes a wheel (501), a second bearing (502), a gear (503), a second DC geared motor (504), a sprocket (505), a chain (506), a third DC geared motor (507), a pad (508), a rack (509), and a slope sensor. The output end of the second DC geared motor (504) is connected to the differential, and power is transmitted to the rear wheel drive unit via the sprocket (505) and the chain (506). The front wheel steering axle passes through... Bearing 2 (502) is fixed on the body (6), and a gear (503) is fixed at the top of the front wheel steering shaft. DC geared motor 3 (507) is fixed on the body (6) through a pad (508). Its output end is connected to a rack (509) that meshes with the gear (503). The slope sensor collects the slope data of the plot in real time. The central control system (7) dynamically adjusts the rear wheel differential output of DC geared motor 2 (504) and the steering amplitude of DC geared motor 3 (507) according to the data.

6. The carbon-neutral intelligent seeding device according to claim 1, characterized in that: The clean energy supply module (8) has a built-in disturbance observation method / conductivity increment method control logic. The execution logic is as follows: read the current voltage V(k) and current current I(k) of the solar panel at a certain time interval, calculate the current power P(k), compare it with the power P(k-1) and voltage V(k-1) of the previous cycle, and automatically adjust the adjustment direction and step size of the PWM duty cycle in the next cycle. The algorithm has a built-in step size adaptive mechanism and anti-oscillation judgment logic, which can maintain the stability of power tracking in the case of sudden change in light intensity.

7. A carbon-neutral intelligent seeding system, characterized in that, The system includes the carbon-neutral intelligent seeding device as described in any one of claims 1-6, a cloud data platform, and a user terminal. The central control system (7) of the carbon-neutral intelligent seeding device interacts bidirectionally with the cloud data platform via a wireless communication module. The cloud data platform stores a database of optimal operating parameters for different crops and different plots. The user terminal can remotely access the cloud data platform to obtain operating data and issue operating instructions. The central control system (7) has the following built-in control modules: DC motor dual closed-loop PID control module: The actual speed is calculated by the encoder value, and the deviation between the target speed and the actual speed is used as input. The target torque command is then calculated and output by the digital PID controller with integral limiting and output limiting. The current loop samples the motor drive current detection signal, fine-tunes the PWM duty cycle to limit the maximum current, and finally outputs the PWM duty cycle to control the operation of DC geared motor one (209), DC geared motor two (504), and DC geared motor three (507); Stepper motor S-curve acceleration and deceleration control module: After receiving the target position command, it pre-plans an S-curve speed curve including acceleration segment, constant speed segment and deceleration segment, and dynamically adjusts the pulse frequency through high priority timer interrupt to generate a pulse sequence with variable frequency and precise quantity to drive the stepper motor (310) to run, thereby realizing precise adjustment of the height of the press wheel (301). Multi-sensor data fusion and filtering module: It uses median averaging filtering to remove extreme values ​​for the raw sensor data, and uses complementary filtering to fuse the inertial measurement unit and ultrasonic sensor data for terrain slope and body tilt angle data, and outputs smooth and stable state estimates. Adaptive decision-making module: It has built-in tables of sowing depth and spacing parameters for different crops and soil textures. It looks up the table based on crop type and soil moisture parameters and calculates the target operation parameters through linear interpolation. It is configured with a fuzzy logic irrigation decision-making submodule, which takes soil moisture deviation and moisture change trend as input, and outputs irrigation demand intensity through fuzzy rule reasoning, and defuzzifies it into irrigation duration or water volume.

8. A carbon-neutral smart seeding method, implemented based on the carbon-neutral smart seeding system of claim 7, characterized in that, The system incorporates two core algorithms to optimize the entire operation process: ① a PID algorithm for dynamic matching of sowing parameters based on multi-sensor fusion, and ② a real-time optimization and control algorithm for net carbon emissions, specifically including the following steps: S1: Pre-operation initialization: Complete the no-load self-check of each module of the device, upload the crop type and basic attribute parameters of the plot to the cloud data platform, match the optimal initial operation parameters, the clean energy supply module (8) detects the energy storage battery power, and automatically starts solar charging when the power is lower than the preset threshold until the power meets the operation requirements. S2: Full-process collaborative operation: The device moves at a preset operating speed, and the leveling structure (1), ditching and sowing structure (2), soil covering structure (3), and watering structure (4) are started in sequence according to the preset time delay. The operating parameters of each process are adjusted in real time by dynamically matching the sowing parameters with the PID algorithm. S3: Dynamic optimization of carbon footprint: During the operation, the energy supply strategy and equipment power consumption are dynamically adjusted through the real-time optimization and control algorithm of net carbon emissions to maintain the net carbon emissions of the entire operation process not higher than the carbon neutrality threshold. S4: Post-operation data synchronization: The device uploads all operation data to the cloud data platform, updates the optimal operation parameter library, and pushes an operation report containing operation volume, resource consumption, and carbon emission reduction to the user terminal.

9. The carbon-neutral intelligent seeding method according to claim 8, characterized in that, The execution logic of the PID algorithm for dynamic matching of sowing parameters based on multi-sensor fusion is as follows: Using the flatness error e1 from the leveling structure (1), the soil thickness error e2 from the soil depth sensor of the furrowing and sowing structure (2), and the soil moisture error e3 from the soil moisture sensor of the watering structure (4) as input variables, the adjustment parameters are output through the PID adjustment formula: ； in, The total weighted error is represented by w1, w2, and w3, which are pre-configured error weight coefficients, and K. p T is the proportionality coefficient. i Let T be the integration time constant. d The time constant is the differential time constant; the output adjustment parameters correspond to the sowing depth compensation, the height adjustment of the press wheel (301), and the flow rate adjustment of the impeller pump (403), so as to realize the dynamic coordination and matching of the operation parameters of each process.

10. The carbon-neutral intelligent seeding method according to claim 8, characterized in that, The execution logic of the real-time optimization and control algorithm for net carbon emissions is as follows: Real-time data collection of three types of data from the clean energy supply module (8): solar power generation Ws, total energy consumption We, and soil carbon sequestration increment Wc. Real-time net carbon emission value C is calculated using the following formula: ； Where α is the carbon emission coefficient per unit of energy consumption, β is the carbon emission reduction coefficient per unit of solar power generation, and γ is the carbon emission reduction coefficient per unit of soil carbon sequestration. When the calculated net carbon emission value C > 0, the energy-saving control strategy is automatically triggered: reduce the power consumption of non-core functional modules and increase the priority of solar power supply until the net carbon emission value returns to the carbon neutrality state of ≤ 0. Step S2 also includes terrain adaptive adjustment logic: the slope sensor of the motion steering structure (5) collects the slope data of the plot at a fixed frequency. When the slope reaches the preset threshold, the parameter adjustment of the hill operation mode is automatically triggered: the height of the front shovel (101) off the ground is increased, the differential adjustment range of the rear wheel is expanded, and the spring clamping force of the press wheel (301) is reduced to avoid the equipment jamming and the seeding depth deviation in the hill operation. In step S4, the cloud data platform uses the K-means clustering algorithm to label the parameter data of this operation, calculates the cosine similarity between the feature vector of the current operation parameter and the feature vector of the historical operation parameter, matches the historical parameter group with the highest similarity and updates it to the optimal operation parameter library. The next time the same plot and the same crop are operated, the matched optimal parameter group can be directly called without repeated setting.

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