Composting methods and intelligent composting systems based on garden waste

Abstract

This invention discloses a composting method and intelligent composting system based on garden waste. The composting method based on garden waste provides a homogeneous and optimized material basis for efficient fermentation through intelligent pretreatment and dynamic formulation of raw materials. During fermentation, a three-dimensional sensor network is deployed and a synchronized digital twin model is constructed. The model is used to predict the future evolution of internal temperature, oxygen, and microbial activity within the compost pile. The degree of composting is intelligently determined by a multi-source information fusion model. The matured material undergoes multi-stage screening to produce a series of products, and a unique traceability code links the entire process to a digital archive, achieving quality traceability. This invention also provides an integrated system for implementing this method. This invention achieves predictive intelligent control and clean production in the composting process, significantly improving processing efficiency, product quality, and resource utilization, while effectively controlling operating costs and environmental pollution.

Description

Technical Field

[0001] This invention relates to the field of solid waste resource utilization technology, and in particular to a composting method based on garden waste and an intelligent composting system. Background Technology

[0002] Garden waste mainly includes branches, fallen leaves, and lawn clippings generated from urban greening pruning, and its output continues to increase with urbanization. Traditional disposal methods mainly involve landfill and incineration, which not only occupy land resources but also generate secondary pollution and fail to achieve resource utilization.

[0003] Composting is an effective way to utilize garden waste as a resource. Through microbial action, organic matter is converted into stable humus, which can be used as a soil conditioner or organic fertilizer. However, existing composting technologies still have the following problems in practical applications: 1. The fermentation process is poorly controlled: it relies heavily on manual experience for turning, adding water and aerating, and lacks real-time monitoring and precise control of key parameters such as temperature, humidity and oxygen concentration, resulting in long fermentation cycles, low efficiency and unstable product quality.

[0004] 2. Significant environmental pollution issues: Composting produces malodorous gases such as ammonia and hydrogen sulfide, as well as greenhouse gases such as methane and carbon dioxide. Current technologies lack systematic gas collection and treatment measures, which easily leads to pollution of the surrounding environment.

[0005] 3. Low level of process intelligence: From raw material pretreatment to fermentation control and then to finished product processing, each link is relatively independent, lacking closed-loop optimization and intelligent decision support based on data feedback, and the overall operating efficiency and economy need to be improved.

[0006] Therefore, it is necessary to provide a composting method based on garden waste to solve the above-mentioned technical problems. Summary of the Invention

[0007] In order to overcome the shortcomings of existing technologies, this invention provides a composting method and an intelligent composting system based on garden waste, so as to achieve predictive intelligent control of the fermentation process, solve environmental pollution problems, and achieve product quality traceability and operating cost optimization.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows: Composting methods based on garden waste include the following steps: S1. Intelligent pretreatment of raw materials and dynamic formulation adjustment: Garden waste is crushed and screened; near-infrared spectroscopy and microwave moisture technology are used to detect the moisture content, organic matter content and initial carbon-nitrogen ratio of the crushed material online; based on the detection results, the central control platform dynamically calculates and generates a precise formulation containing microbial agents, nutrient conditioners and physical conditioners, combined with preset cost optimization targets and material characteristic databases; through an automatic batching and mixing system, the auxiliary materials and main materials measured according to the formula are evenly mixed to obtain the material to be fermented; S2. Intelligent Stacking, Three-Dimensional Monitoring, and Digital Twin Initialization: The mixed materials are stacked in a fermentation tank or stockpile using a layered distribution and synchronous precision spraying method to control the initial stack structure and moisture content within a set range; a three-dimensional wireless sensor network is deployed in the stack to collect parameters such as temperature, oxygen concentration, ammonia concentration, and hydrogen sulfide concentration in real time; based on the initial material parameters and the real-time data collected by the sensor network, a digital twin model corresponding to the physical stack is created and calibrated in the central control platform. S3. Multi-stage adaptive fermentation control based on digital twin prediction: The digital twin model is used to simulate and predict the temperature field, oxygen field, and microbial activity trends inside the compost pile in real time. Based on the prediction results, with the goals of maximizing composting efficiency, minimizing odor emissions, and optimizing energy consumption and auxiliary material costs, the optimization algorithm dynamically makes decisions and automatically executes turning, ventilation, and spraying operations. The control process, based on model prediction, supports the dynamic planning and execution of adding new materials and supplementing corresponding auxiliary materials after assessing the compost pile's degradation capacity during the high-temperature fermentation period. S4. Full-process negative pressure gas collection and multi-stage synergistic purification: During the fermentation process, a covering system is used to seal or semi-close the pile, and a negative pressure fan is used to continuously collect the escaping gas; the collected gas passes through a biological filter for main deodorization, and a chemical washing unit is connected in series as an emergency and deep treatment guarantee; the carbon dioxide in the purified gas is enriched and utilized as a resource. S5. Intelligent Determination of Maturity and Refined Gradient Processing: When the comprehensive maturity index calculated by the digital twin model based on the temperature history, oxygen consumption rate, predicted carbon-nitrogen ratio change, and apparent image characteristics of the pile reaches the threshold, fermentation is determined to be complete; the matured material is subjected to secondary crushing and multi-stage screening to produce a series of products with different particle size specifications; the products are automatically packaged and assigned a unique traceability code, which is linked to a digital archive including raw material information, dynamic formula, full-process process parameters, and quality inspection reports.

[0009] Preferably, in step S1, the dynamically calculated and generated precise formula specifically includes: Based on the initial carbon-nitrogen ratio detected, one or more of urea and poultry and livestock manure are dynamically determined and added as nitrogen source conditioners to make the carbon-nitrogen ratio of the mixed material reach 25:1-35:1. Based on the lignin content and structural characteristics of the material, determine and add a compound microbial agent containing lignocellulose degradation function, with an addition amount of 0.5-2.0% of the total dry weight of the material; Add one or more of crushed rice husks, wheat bran, corn cobs, or peanut shells as a physical conditioner at a rate of 5%-15% to improve the porosity of the pile. The formulation model integrates a cost optimization algorithm to achieve the goal of controlling the total cost of adding excipients.

[0010] Preferably, the addition of the microbial agent adopts a phased strategy: a basic compound microbial agent is added during the initial mixing; during the high-temperature fermentation period, based on the prediction of microbial community succession by the digital twin model, a microbial agent with specific decomposition-promoting function is added through a precision spraying system.

[0011] Preferably, in step S2, the layered material laying and synchronous precision spraying pile building refers to laying material according to the preset thickness of each layer by an automated material laying equipment, while the spraying device integrated on the material laying equipment sprays water on each layer of material according to the real-time moisture content detection data of the material and the target moisture content set by the model, so that the overall moisture content is uniformly maintained at 55%-60% after the pile building is completed.

[0012] Preferably, in step S3, the dynamic planning and execution of adding new materials specifically includes: during the high-temperature fermentation period, when the digital twin model assesses and determines that the current pile still has sufficient microbial activity and physical space to accommodate new materials, and the addition behavior will not have a negative impact on the core fermentation process, the central control platform plans to add new garden waste pretreated in step S1, and simultaneously calculates and supplements a small amount of nitrogen source conditioner and microbial agent required to balance the overall carbon-nitrogen ratio.

[0013] Preferably, in step S3, the timing, depth, and frequency of the turning operation are entirely determined by the temperature uniformity, oxygen distribution defect risk, and structural compaction trend inside the pile predicted by the digital twin model. The first turning condition is that the model predicts the core temperature of the pile to reach 55-60℃ and at the same time predicts that oxygen deficit will occur in a local area, rather than relying solely on a single temperature threshold.

[0014] Preferably, in step S4, the covering system is a polymer biofilm or composite membrane with controllable air permeability; the phosphorus- or nitrogen-containing waste liquid generated by the chemical washing unit is treated and reused as a nutrient solution for composting or made into liquid fertilizer.

[0015] Preferably, in step S5, the multi-stage screening separates the composted material into at least: coarse particles with a particle size greater than 10 mm, suitable for forest cover and soil improvement; medium particles with a particle size of 2-10 mm, suitable for landscaping substrates; and fine particles with a particle size less than 2 mm, suitable for seedling nutrient soil or high-quality organic fertilizer.

[0016] Preferably, the central control platform has a built-in historical data analysis and machine learning module, which is used to continuously optimize the parameters of the digital twin model, the generation rules of the dynamic recipe, and the multi-stage control strategy, so as to realize the self-evolution of the processing technology and the continuous reduction of long-term operating costs.

[0017] An intelligent composting system for implementing a composting method based on garden waste includes: The intelligent pretreatment and dynamic batching unit is connected in sequence to crushing and screening equipment, online rapid detection equipment, multiple auxiliary material storage bins and automatic metering and dosing devices, and high-efficiency mixing equipment; The intelligent fermentation and control unit includes fermentation tanks / stacks, automated layered material distribution and spraying stacking equipment, a three-dimensional wireless sensor network, an intelligent compost turner, a precise and controllable ventilation system, and a spraying system; The gas collection and resource recovery unit includes an openable and closable membrane system, negative pressure collection pipelines and fans, a biofilter, a chemical scrubbing tower, and an optional carbon dioxide enrichment device. The intelligent processing and traceability unit for composted materials includes a secondary crusher, a multi-stage screening machine, an automated packaging line, and an identification code assignment system. The central control platform includes a data acquisition and storage module, a dynamic formulation model with integrated cost optimization objectives, a digital twin simulation and prediction module, a multi-objective optimization decision-making module, and a human-computer interaction interface, which are used to coordinate the control of all the aforementioned units and execute the composting treatment method.

[0018] Compared with the prior art, the present invention has the following beneficial effects: (1) This invention uses predictive control of digital twins to keep the composting process in or close to the optimal operating state, effectively solving the difficulties of garden waste fermentation, greatly shortening the composting cycle, and making the product more fully composted and of more stable and uniform quality. (2) This invention uses a closed negative pressure collection and biological and chemical combined purification process to ensure high efficiency in removing odorous gases and meet emission standards, thereby thoroughly improving the factory area and surrounding environment. (3) This invention avoids unnecessary turning and excessive ventilation through intelligent and precise control, thus saving energy; adding auxiliary materials as needed reduces waste; and automated production reduces dependence on manual labor and labor costs. (4) This invention makes management transparent and efficient through automatic data collection, model optimization, and closed-loop control throughout the entire process. The digital traceability system for product quality enhances market trust, and the accumulated big data provides a solid foundation for continuous process optimization; (5) This invention is not only applicable to garden waste, but can also be extended to the resource utilization of other organic wastes such as agricultural straw and kitchen waste, and has broad prospects for promotion and application. Detailed Implementation

[0019] The present invention will be further described below with reference to the embodiments. The embodiments of the present invention include, but are not limited to, the following embodiments.

[0020] Example 1: The following is an example of the renovation of a municipal garden waste treatment station. The station is designed to process 30 tons per day and was technically renovated using the method of this invention.

[0021] System configuration and process integration design: Fusion design of preprocessing units: Optimization of preliminary preparations: The requirement of selecting a flat, hardened site is retained, serving as the foundation for the construction of the intelligent fermentation tank. The traditional pre-drying process of spreading the material out to sun for a week is integrated into the online rapid detection and intelligent decision-making process of this invention. The system monitors the moisture content of the incoming materials in real time using a microwave moisture meter. If the moisture content is too high (e.g., >65%), it instructs that a portion of the material be sent to a reserved sun-drying area for short-term spreading (the drying process can be monitored by deploying temperature and humidity sensors). The system also predicts the required drying time using a model, rather than a fixed week, thus improving pre-treatment efficiency.

[0022] Precision and automation in substrate mixing: Traditional processes involve mixing substrates according to a fixed formula (e.g., 15 kg of inoculant, 100 kg of rice bran, 10 kg of brown sugar, and 50 kg of urea per 10 tons of air-dried substrate). This invention upgrades this process. a. Dynamic formulation: The system dynamically adjusts the auxiliary material formulation based on the actual composition (carbon-nitrogen ratio, lignin content) of each batch of raw materials detected online by NIRS. For example, for pure branches and leaves with a high carbon-nitrogen ratio, the model will calculate and increase the amount of urea added; for lawn clippings with a high soil content, the amount of rice bran may be reduced.

[0023] b. Automated Dosing: The system includes microbial agent storage, rice bran / wheat bran storage, nitrogen / phosphorus nutrient storage (urea, superphosphate, etc.), and carbon source storage (brown sugar, cornmeal substitutes). A central control system automatically measures and adds various auxiliary materials to the mixer based on a dynamic formula, replacing manual mixing and ensuring accuracy and hygiene.

[0024] c. Refined Functions of Microbial Agents: The traditional concepts of Fermentation Bacteria No. 1 and No. 2 are integrated and optimized into the compound microbial agent strategy described in this invention. A basic compound microbial agent containing both room-temperature and thermophilic strains is added during initial mixing, its functions encompassing rapid start-up and high-temperature degradation. After the system determines that it has entered the high-temperature stable period (rather than simply after the final addition), specific decomposition-promoting microbial agents (similar to Bacteria No. 2) can be automatically supplemented through a precision spraying system based on the model's predicted changes in the microbial community, thereby enhancing the decomposition of recalcitrant substances such as lignocellulose and achieving a more scientific synergistic effect of the microbial agent.

[0025] Intelligent upgrade of fermentation regulation: Standardization and controllability of material stacking and mulching: The process adopts the reasonable experience of layering, watering layer by layer, piling into a mound shape, and covering with film from traditional methods, but is executed by an intelligent system. The material-laying vehicle lays the material in layers according to a preset program (e.g., 0.5 meters per layer). Simultaneously, the spray heads integrated on the vehicle provide precise watering based on the initial moisture content of the material and the model settings, ensuring that the initial moisture content is uniformly controlled within the optimized range of 55%-60%, rather than relying solely on experience. The mulching operation uses an automatically rolled-up high-polymer breathable membrane, whose breathability and heat insulation performance are superior to ordinary plastic greenhouse films, and it can be easily connected to a negative pressure extraction system.

[0026] Modeling and Precision of Turning Decisions: This invention fundamentally changes the traditional experience-based approach of turning compost when temperatures rise above 55°C. In this invention, turning decisions are entirely driven by a digital twin model. The model comprehensively considers factors such as temperature field uniformity, oxygen distribution, peak microbial activity, and changes in compost structure to predict the optimal timing, frequency, and depth of turning. For example, the model might suggest the first turning when the temperature reaches 58°C and local oxygen deficit is predicted, rather than simply waiting for a fixed temperature point. The turning equipment uses an automated turning machine that can precisely execute commands.

[0027] Integrated cost optimization strategy for dynamic material addition: Traditional processes suggest that each addition of garden waste only requires a small amount of microbial agent, with higher additions resulting in lower costs. This invention incorporates this economic principle into the cost function of the optimization algorithm. When the treatment facility has continuous feeding capabilities, the system can plan a dynamic addition mode: During the high-temperature fermentation period, the model assesses the degradation capacity of the pile and remaining space. If it determines that new material can be accepted without affecting the main fermentation process, it will prompt and plan the addition of new pretreated waste, while accurately calculating the required small amount of microbial agent and conditioner (mainly supplementing nitrogen source to balance the C / N ratio). This achieves incremental processing and cost reduction while ensuring quality, making the economic target of approximately 40-50 yuan / ton for material input more controllable and achievable.

[0028] Refinement of decomposition determination and processing: Traditional processes involve natural drying, sieving, or crushing. This invention builds upon this by using a sensor network and model to determine the maturity endpoint, avoiding insufficient or excessive natural drying. During processing, multi-stage sieving replaces single-stage sieving or screenless crushing, producing products with different particle sizes (e.g., coarse material for forestry, fine material for seedling cultivation), thus increasing product value. Processing data (such as particle size distribution) is automatically entered into the traceability file for that batch of products.

[0029] Process operation: A batch of 15 tons of garden waste arrived at the site with a moisture content of 62%. The system instructed that 30% of it be spread out to dry for 4 hours. During mixing, based on the detected C / N ratio of 52:1, urea, compound basic microbial agent, rice bran, and a small amount of brown sugar were automatically added. Layered fabric and spraying were used to build the pile, and the initial moisture content was controlled at 58%.

[0030] After fermentation started, the model predicted a rapid drop in oxygen levels at the bottom on the 45th hour (core temperature 56℃), so bottom ventilation was initiated ahead of schedule and the first turning of the pile was performed. During the entire high-temperature period (days 3-12), three turnings were performed based on the model's predictions. On day 8, the model assessment indicated that 5 tons of new pretreated material could be added, and the system automatically performed this, replenishing the corresponding microbial agent and a small amount of urea.

[0031] On day 20, the system determined the material to be fully decomposed. Approximately 9 tons of finished product were obtained after processing. Calculations showed that the direct cost of processing this batch of material was approximately 45 yuan per ton. The entire process involved gas collection and treatment, resulting in no significant odor within the plant area.

[0032] Example 2: Taking a comprehensive processing center within an eco-industrial park as an example, this center processes garden waste and agricultural straw, further enhancing resource utilization. Based on the intelligent system of this invention, it further integrates the principles of economy and resource utilization from traditional processes.

[0033] Energy and resource cycles: The gas collected by the gas processing unit is used for energy recovery and carbon resource recycling, as described above.

[0034] The addition of superphosphate or diammonium phosphate in traditional processes is combined with the treatment of phosphorus-containing wastewater generated by chemical scrubbing towers. After safe treatment, it can be reused as a phosphorus nutrient supplement for composting or made into liquid fertilizer, thus achieving phosphorus recycling.

[0035] Intelligent guarantee for low-cost operation: Utilizing the data advantages of the system of this invention, the consumption of microbial agent excipients is monitored and optimized in real time to find the lowest cost addition scheme under different seasons and different raw material ratios. The model is continuously optimized through historical data to keep the long-term average material cost stable in a low range (such as 40-50 yuan / ton) and ensure better quality.

[0036] Product diversification and high-value development: Combining the different uses of traditional direct return to the field and fertilizer application, we utilize intelligent screening systems to produce coarse-particle organic matter for direct return to the field, medium-grade substrate for landscaping, and fine organic fertilizer for high-end agriculture, thereby meeting diversified market demands and improving overall profitability.

[0037] Implementation results: The center not only achieves efficient and low-cost waste conversion, but also ensures that the advantages of traditional processes are brought into play while overcoming their shortcomings through intelligent management, thus building a more complete circular economy chain. The environmental, economic, and social benefits are significant.

Claims

1. A composting method based on garden waste, characterized in that, Includes the following steps: S1. Intelligent pretreatment of raw materials and dynamic formulation adjustment: Garden waste is crushed and screened; near-infrared spectroscopy and microwave moisture technology are used to detect the moisture content, organic matter content and initial carbon-nitrogen ratio of the crushed material online; based on the detection results, the central control platform dynamically calculates and generates a precise formulation containing microbial agents, nutrient conditioners and physical conditioners, combined with preset cost optimization targets and material characteristic databases; through an automatic batching and mixing system, the auxiliary materials and main materials measured according to the formula are evenly mixed to obtain the material to be fermented; S2. Intelligent Stacking, Three-Dimensional Monitoring, and Digital Twin Initialization: The mixed materials are stacked in a fermentation tank or stockpile using a layered distribution and synchronous precision spraying method to control the initial stack structure and moisture content within a set range; a three-dimensional wireless sensor network is deployed in the stack to collect parameters such as temperature, oxygen concentration, ammonia concentration, and hydrogen sulfide concentration in real time; based on the initial material parameters and the real-time data collected by the sensor network, a digital twin model corresponding to the physical stack is created and calibrated in the central control platform. S3. Multi-stage adaptive fermentation control based on digital twin prediction: The digital twin model is used to simulate and predict the temperature field, oxygen field, and microbial activity trends inside the compost pile in real time. Based on the prediction results, with the goals of maximizing composting efficiency, minimizing odor emissions, and optimizing energy consumption and auxiliary material costs, the optimization algorithm dynamically makes decisions and automatically executes turning, ventilation, and spraying operations. The control process, based on model prediction, supports the dynamic planning and execution of adding new materials and supplementing corresponding auxiliary materials after assessing the compost pile's degradation capacity during the high-temperature fermentation period. S4. Full-process negative pressure gas collection and multi-stage synergistic purification: During the fermentation process, a covering system is used to seal or semi-close the pile, and a negative pressure fan is used to continuously collect the escaping gas; the collected gas passes through a biological filter for main deodorization, and a chemical washing unit is connected in series as an emergency and deep treatment guarantee; the carbon dioxide in the purified gas is enriched and utilized as a resource. S5. Intelligent Determination of Maturity and Refined Gradient Processing: When the comprehensive maturity index calculated by the digital twin model based on the temperature history, oxygen consumption rate, predicted carbon-nitrogen ratio change, and apparent image characteristics of the pile reaches the threshold, fermentation is determined to be complete; the matured material is subjected to secondary crushing and multi-stage screening to produce a series of products with different particle size specifications; the products are automatically packaged and assigned a unique traceability code, which is linked to a digital archive including raw material information, dynamic formula, full-process process parameters, and quality inspection reports.

2. The composting method based on garden waste according to claim 1, characterized in that, In step S1, the dynamically calculated and generated precise formula specifically includes: Based on the initial carbon-nitrogen ratio detected, one or more of urea and poultry and livestock manure are dynamically determined and added as nitrogen source conditioners to make the carbon-nitrogen ratio of the mixed material reach 25:1-35:

1. Based on the lignin content and structural characteristics of the material, determine and add a compound microbial agent containing lignocellulose degradation function, with an addition amount of 0.5-2.0% of the total dry weight of the material; Add one or more of crushed rice husks, wheat bran, corn cobs, or peanut shells as a physical conditioner at a rate of 5%-15% to improve the porosity of the pile. The formulation model integrates a cost optimization algorithm to achieve the goal of controlling the total cost of adding excipients.

3. The composting method based on garden waste according to claim 2, characterized in that, The addition of the microbial agent adopts a phased strategy: a basic compound microbial agent is added during the initial mixing; during the high-temperature fermentation period, based on the prediction of microbial community succession by the digital twin model, a microbial agent with specific decomposition-promoting function is added through a precision spraying system.

4. The composting method based on garden waste according to claim 1, characterized in that, In step S2, the layered material laying and synchronous precision spraying pile building refers to the use of automated material laying equipment to lay material according to the preset thickness of each layer, while the spraying device integrated on the material laying equipment sprays water on each layer of material according to the real-time moisture content detection data of the material and the target moisture content set by the model, so that the overall moisture content is uniformly maintained at 55%-60% after the pile building is completed.

5. The composting method based on garden waste according to claim 1, characterized in that, In step S3, the dynamic planning and execution of adding new materials specifically includes: during the high-temperature fermentation period, when the digital twin model assesses and determines that the current pile still has sufficient microbial activity and physical space to accommodate new materials, and the addition behavior will not have a negative impact on the core fermentation process, the central control platform plans to add new garden waste that has been pretreated in step S1, and simultaneously calculates and supplements a small amount of nitrogen source conditioner and microbial agent required to balance the overall carbon-nitrogen ratio.

6. The composting method based on garden waste according to claim 1, characterized in that, In step S3, the timing, depth, and frequency of the turning operation are entirely determined by the temperature uniformity, oxygen distribution defect risk, and structural compaction trend inside the pile predicted by the digital twin model. The first turning condition is that the model predicts the core temperature of the pile to reach 55-60℃ and at the same time predicts that oxygen deficit will occur in a local area, rather than relying solely on a single temperature threshold.

7. The composting method based on garden waste according to claim 1, characterized in that, In step S4, the covering system is a polymer biofilm or composite membrane with controllable air permeability; the phosphorus- or nitrogen-containing waste liquid generated by the chemical washing unit is treated and reused as a nutrient solution for composting or made into liquid fertilizer.

8. The composting method based on garden waste according to claim 1, characterized in that, In step S5, the multi-stage screening separates the composted material into at least the following: coarse particles with a particle size greater than 10 mm, suitable for forest cover and soil improvement; medium particles with a particle size between 2 and 10 mm, suitable for landscaping substrates; and fine particles with a particle size less than 2 mm, suitable for seedling nutrient soil or high-quality organic fertilizer.

9. A composting method based on garden waste according to claim 1, characterized in that, The central control platform has a built-in historical data analysis and machine learning module, which is used to continuously optimize the parameters of the digital twin model, the generation rules of the dynamic recipe, and the multi-stage control strategy, so as to achieve the self-evolution of the processing technology and the continuous reduction of long-term operating costs.

10. An intelligent composting system for implementing the composting method based on garden waste according to any one of claims 1-9, characterized in that, include: The intelligent pretreatment and dynamic batching unit is connected in sequence to crushing and screening equipment, online rapid detection equipment, multiple auxiliary material storage bins and automatic metering and dosing devices, and high-efficiency mixing equipment; The intelligent fermentation and control unit includes fermentation tanks / stacks, automated layered material distribution and spraying stacking equipment, a three-dimensional wireless sensor network, an intelligent compost turner, a precise and controllable ventilation system, and a spraying system; The gas collection and resource recovery unit includes an openable and closable membrane system, negative pressure collection pipelines and fans, a biofilter, a chemical scrubbing tower, and an optional carbon dioxide enrichment device. The intelligent processing and traceability unit for composted materials includes a secondary crusher, a multi-stage screening machine, an automated packaging line, and an identification code assignment system. The central control platform includes a data acquisition and storage module, a dynamic formulation model with integrated cost optimization objectives, a digital twin simulation and prediction module, a multi-objective optimization decision-making module, and a human-computer interaction interface, which are used to coordinate the control of all the aforementioned units and execute the composting treatment method.