27 results about "Plant factory" patented technology

The application discloses a kind of based on selective spectral regulation agricultural photoelectric conversion film synthesis method and application, belong to the cross field of agricultural technology and new energy.It is quantum dot as core spectral selective absorption material in the synthesis method, by the standardization steps of substrate pretreatment, transparent electrode preparation, photoelectric conversion layer coating, quantum dot layer integration, back electrode evaporation and packaging, the functional film comprising "substrate-transparent electrode-photoelectric conversion layer-quantum dot spectral selective absorption layer-back electrode" is prepared.The quantum dot layer can efficiently absorb the ultraviolet light, green light and near-infrared light with low photosynthesis utilization rate of plant, and energy is transferred to photoelectric conversion layer to realize power generation;At the same time, the transmittance of blue light and red light necessary for plants is greater than or equal to 85%.The synthesis process of the application has strong compatibility and high repeatability, solves the contradiction between power generation and planting in traditional "agri-photovoltaic", realizes light energy hierarchical utilization and agri-photovoltaic synergy, and can be widely applied to greenhouse, greenhouse, plant factory and other agricultural facilities cover.

This invention provides a comprehensive energy-saving system and control method for plant factories, comprising: a liquid CO2 energy storage and release subsystem for compressing and storing gaseous CO2 generated in the plant factory into liquid CO2 and controlling the release of the liquid CO2; a refrigeration subsystem for vaporizing the liquid CO2 released by the liquid CO2 energy storage and release subsystem to obtain CO2 gas; an electricity generation system for expanding the vaporized CO2 gas to generate electricity for use in the plant factory; and a CO2 gas supply and recovery subsystem for processing the generated CO2 gas and transporting it to the plant cultivation area of ​​the plant factory, and recovering the CO2 gas that is not absorbed and utilized by the plants. This invention reduces the operating cost and energy consumption of plant factories.

This invention discloses an AIoT-based containerized modular intelligent sprout cultivation device. The device collects environmental data in real time through multiple sensors deployed within the container, which is then uploaded to the platform layer via an edge computing gateway. The platform layer uses an LSTM predictive control module to analyze the data, predict environmental trends, and generate optimized environmental control and growth agent dispensing strategies, which are then sent to the edge gateway to drive actuators. Simultaneously, an intelligent circulating water system integrates multi-stage treatment and recycling devices to achieve efficient water resource recycling. This invention solves the problems of lagging environmental control, low resource utilization efficiency, and poor coordination among subsystems in existing plant factory systems through integrated closed-loop intelligent regulation of sensing, prediction, and control, achieving precise and automated management of the entire plant growth cycle.

The utility model discloses a kind of strawberry plant factory three-dimensional soilless strawberry cultivation frame, including hydroponic box, the upper portion of the hydroponic box is provided with planting frame, the through slot is set on the planting frame, the through slot is provided with planting plate, the sidewall of the planting plate is set with a plurality of planting device, the sidewall of the planting frame is set with two limiting devices, the top of the greenhouse at corresponding position is vertically fixedly connected with two fixed columns downwards, the sidewall of the hydroponic box and the sidewall of planting frame are all fixedly connected with connecting plate, the sidewall of two the connecting plate is all set with positioning device with the through. The utility model has the benefit that operator can replace water sample at any time, clean inside dirt conveniently, and flush rhizome conveniently.

This invention relates to a plant care device and method for plant factories, belonging to the technical field of indoor care devices. It includes: multiple mounting frames, each equipped with a care collection unit; mounting platforms arranged from bottom to top on the mounting frames; a lifting assembly installed between the mounting frames and the mounting platforms for adjusting the height between adjacent mounting platforms; a moving track installed under the mounting platforms; a shuttle trolley moving on the moving track and equipped with a monitoring unit for comparing and screening plants; and a harvesting assembly installed on the shuttle trolley for harvesting plants marked by the care collection units. This invention addresses the technical problems of existing plant factories that still use shuttle trolley tracks between adjacent shelves for transportation, reducing space utilization and increasing production costs, and failing to simultaneously perform plant detection, secondary screening, sampling, and removal operations during the production process.

The present invention relates to a polygonal, underground, and protected prismatic plant factory for the production of vegetables, characterized by comprising a support structure that defines a polygonal base of "n" sides, configured to fix and vertically support a cultivation panel, which together define a polygonal plant growth chamber; wherein each cultivation panel comprises on its inner face, multiple levels of plant supports and growth, with a hydroponic irrigation system; said base centrally comprises an automated system for regulating the distance of panels with LED lighting means for providing light to the plants, configured to extend or retract from the respective inner faces of the cultivation panels, and wherein between the automated distance regulation system and the plurality of cultivation panels there is a service corridor;further comprising a central control and processing unit configured to control and operate a user interface, a plurality of sensors such as temperature, relative humidity, luminosity, flow, water level, distance of lighting panels and machine vision cameras; actuators for controlling the LED luminaires, at least one irrigation pump, temperature regulation means, the linear stroke actuator and an electrical power supply for the operation of the system as a whole.

The present application relates to the field of plant factory water culture, and specifically discloses a kind of plant factory three-dimensional cultivation automatic liquid supply equipment and hierarchical compensation control method, including independent liquid supply unit, comprising: a pneumatic sensing assembly, with a closed flexible sensing capsule inside encapsulating low-boiling working medium, the sensing capsule is configured to respond to the microenvironment humidity change caused by crop transpiration in the cultivation layer. The plant factory three-dimensional cultivation automatic liquid supply equipment and hierarchical compensation control method, through the mechanical combination of transpiration-condensation sensing capsule and nonlinear cam differential proportional valve, realizes the passive, real-time, independent compensation of the different water and fertilizer requirements of each layer of three-dimensional cultivation, and gets rid of the dependence on expensive and frequently maintained online ion selective electrode.

This invention provides an automated logistics collaborative operation system and scheduling method for plant factories. The system includes a three-dimensional cultivation storage area, a horizontal shuttle subsystem, a vertical transfer subsystem, a central processing station subsystem, and an intelligent scheduling and control station, forming a relay-style logistics topology combining multi-level shuttles and stacker cranes. The multi-level shuttles are responsible for horizontal storage and retrieval of overall cultivation units between cultivation rack layers; the stacker cranes are responsible for vertical collection and layer changing at the ends of the aisles. The two systems achieve spatiotemporal coordination through the intelligent scheduling and control station. Lateral flexible clamping mechanisms and anti-drip transport modes ensure the safety and cleanliness of live crops during high-speed transport. Combined with scheduling algorithms, the entire process from sowing, germination, and transplanting to harvesting and cleaning is automated, significantly improving the production efficiency and logistics throughput of plant factories and solving the problem of efficient and stable transport of massive cultivation units in high-density plant factories.

The present application relates to a kind of control method of whole artificial light plant factory illumination temperature coordination based on daily cumulative light quantity control, and the DLI of different varieties and growth period is set to light supplement, and the temperature between cultivation layer is monitored in real time. Once temperature exceeds the upper limit threshold of set illumination adjustment temperature, system will automatically adjust the illumination intensity to 2 / 3 of original setting, and recalculate the light supplement duration;After a period of time after adjusting light supplement, if temperature still exceeds the upper limit threshold, illumination intensity is further reduced to 1 / 2, until temperature returns to the ideal range;This process will be repeated continuously in the whole photoperiod, to ensure the best coordination of illumination and temperature, so as to prevent the phenomenon of burning tip of plant.

This invention discloses a plant factory control system and method based on dual-modal monitoring using sensors and machine vision, belonging to the field of smart agriculture technology. The system includes a central server, a monitoring module, an actuator module, and an information display terminal. The monitoring module comprises multiple monitoring units, each including an edge microcontroller, a wireless communication module, an image acquisition device, and a sensor group, used to collect parameter data of the plant growth environment and image data of the plant growth status and upload them to the server. The actuator module comprises multiple actuator units, each including an edge microcontroller, a wireless communication module, and at least one actuator, used to receive instructions from the central server and drive the actuator actions. The information display terminal is used to receive and display alarm information. Methodically, the central server performs threshold comparisons on the plant growth environment parameters received by the sensor group, and simultaneously uses an image semantic segmentation pre-trained model to identify the image data. Based on the dual-modal combination state of the plant growth environment parameter data and the image data, it generates differentiated control instructions or alarm information. When there are no abnormalities, a preset scheme is executed; when there are abnormalities, logs are recorded and pushed to the information display terminal, and instructions are issued to adjust the environment. This invention provides dual-modal monitoring for timely detection of environmental parameters and physiological abnormalities in plant growth, enabling real-time monitoring and timely regulation, and improving the reliability and automation of regulation.

The application discloses a plant factory light intensity integrated control system, which comprises an environment sensing module, a central control unit and a partition light adjusting driving module. The core of the application is that a Bayesian optimization module and a digital PID controller are integrated in the central control unit. The Bayesian optimization module takes PID parameters as optimization variables, and a comprehensive performance index as a target function, and automatically optimizes through a Bayesian optimization algorithm. The target function comprises a function for improving response speed and accuracy, a function for suppressing light overshoot, and a function for protecting equipment and reducing energy consumption. The application realizes adaptive setting of PID parameters, solves the problem of insufficient control precision of a traditional method, and improves the control quality of a plant factory light environment.

The application discloses a container plant factory energy-saving regulation and control method based on fuzzy reinforcement learning and distributed collaborative optimization, and relates to the technical field of industrial automation control. The method comprises the following steps: collecting in-box environment, equipment energy consumption, external environment, time-of-use electricity price and crop canopy image data; performing core derived feature calculation based on the data to construct a comprehensive state vector; inputting the comprehensive state vector into an intelligent decision-making model based on a deep Q network; using a fuzzy reward calculator, obtaining an instant reward value according to a crop stress index and an electricity price pressure level through fuzzy rule base reasoning, training the model based on the value and making a decision, and outputting macro joint action instructions containing temperature, light and ventilation intentions; inputting the instructions into a hierarchical rule collaborative optimization layer, sequentially checking and refining through safety and boundary rules, energy efficiency optimization rules and economic dispatching rules, generating device-level control instructions and executing the instructions, and effectively reducing system energy consumption and electricity cost on the premise of ensuring the stability of the crop growth environment.

Addressing electrical leakage in lighting systems applied to plant factories. [Solution] The lighting system applied to the plant factory comprises a lighting device including LED elements and a single-phase two-wire power supply circuit that supplies power to the lighting device from an external power source. The power supply circuit comprises a power transmission unit that constitutes a power supply path that sends power from the external power source to the lighting device, and a ground fault circuit breaker provided in the power supply path that cuts off the power supply to the lighting device when a ground fault is detected. The power transmission unit comprises a plurality of cables provided in the section between the ground fault circuit breaker and the lighting device in the power supply path, and a connector that connects the plurality of cables. The lighting system comprises a grounding unit that grounds the connector.

The utility model discloses a multifunctional integral plant lighting lamp relates to plant lighting lamp technical field, the utility model discloses a lamp outer casing body, the upper end of lamp outer casing body is open -mouthed and is located, and the closed support mechanism is arranged in lamp outer casing body, the lower end distribution of lamp outer casing body is provided with the lighting lamp, the whole of lamp outer casing body is square structure and is located, and the both ends of lamp outer casing body are provided with the inclined shape, and one of the inclined surface of lamp outer casing body is provided with the integrated air inlet of going in and out, and the inner wall of lamp outer casing body is provided with the integrated fan of positive and negative rotation on one side of integrated air inlet of going in and out. The utility model replaces the conventional plant lighting, ventilation, dehumidification separate arrangement, makes installation construction more convenient, greatly saves the construction and maintenance cost of planting factory, can also be convenient for staff to operate construction, and then can save manpower construction cost.

The application belongs to the field of plant factory control, and discloses an AI-based intelligent plant factory control method and system, which obtains environment data and crop cultivation data of each subzone in the plant factory, pre-processes to form a multi-subzone and multi-crop spatiotemporal data set, constructs a subzone interaction relationship representation containing a dynamic adjacency graph and transpiration agent characteristics, outputs environment and crop data prediction results of a future prediction window by using a spatiotemporal sequence fusion model, constructs a multi-objective function containing steady-state, production and cost targets, and optimizes and controls each subzone based on the prediction results and the multi-objective function. The application can accurately depict cross-crop interaction, improve prediction accuracy, realize multi-objective optimization and subzone differentiated control, and improve resource utilization rate and production efficiency of the plant factory.

The application relates to the technical field of planting tools, in particular to a container plant factory layer rack type three-dimensional planting module, which comprises a base, and the upper side of the base is fixedly connected with a vertical plate. The chain wheel, the chain, the limiting block, the U-shaped block and the planting assembly are arranged, when the planting assembly on the lower side needs to be operated, the handheld locking pin is slid in the movable port, is separated from the limiting hole, one limiting block is pulled down, the two U-shaped blocks are exchanged positions under the action of the chain, the U-shaped block originally on the lower side is moved to the upper side, the locking pin is inserted into the limiting hole on the lower side, is fixed, the U-shaped block on the lower side is moved to the upper side, a person can keep a standing state to operate, the operation of bending over is avoided, and the comfort of planting operation is improved.

This application relates to the field of rice seedling cultivation technology, and discloses a method and system for rice seedling cultivation based on a plant factory. The method includes: constructing a fully intelligent plant factory seedling cultivation system; placing seedling trays in a storage facility and maintaining their fixed position throughout the entire process; performing dark germination and three-dimensional microenvironment-based synergistic dehumidification; inducing root and crown growth through reverse coupling of water temperature during the greening stage; constructing wind-light synergistic seedling hardening using reconstructed spectra and pneumatic pulses; and removing the finished seedling trays after verifying that the growth indicators are qualified. The system includes: a multi-layer three-dimensional cultivation rack, a seed soaking system, a drying system, a sowing system, a seedling storage system, an air conditioning system, a plant LED lighting system, an irrigation system, a carbon dioxide control system, and a central control system. This invention maintains the physical position of the seedling trays fixed throughout the entire seedling cultivation cycle by using a seedling storage system in conjunction with dynamic switching logic of environmental parameters, thereby eliminating the mechanical costs and manual labor input of transporting seedling trays across regions.

This invention relates to the field of controlled environment agricultural environmental control technology, and more particularly to a precise environmental control system and method for plant factories. The system and method include: an integrated air handling unit with cooling, heating, dehumidification, humidification, and carbon dioxide mixing functions; a multi-stage air distribution network connected to the unit's air outlet; the network comprising a primary main air duct, a secondary branch air duct, and a tertiary micro-jet duct connected sequentially; and an array of micro-jet orifices on the tertiary micro-jet duct. This invention utilizes the high momentum characteristics of micro-jet flow to break the air stagnant layer on the leaf surface, enhancing heat, mass, and carbon dioxide exchange. Combined with computational fluid dynamics simulation optimization and zoned linkage control, it achieves precise targeted control of the plant microenvironment, maintaining the temperature uniformity of the entire workshop within ±1.5℃, significantly improving crop growth consistency and commercial quality, while substantially reducing system operating energy consumption.

This invention discloses a method and system for optimizing environmental control strategies in facility agriculture based on a large language model, relating to the fields of smart agriculture and environmental control technology. The invention constructs a four-layer closed-loop architecture: "data layer - simulation layer - evaluation layer - optimization layer," achieved through the following steps: S1 Constructing a hybrid simulator including a gray-box physical model, residual correction, and periodic state reset; S2 Establishing a six-dimensional weighted scoring function; S3 Configuring a safety verification mechanism; S4 Executing the large language model structure discovery phase, retrieving domain experience from pre-trained knowledge through structured experimental loops and transforming it into a control strategy framework; S5 Fine-tuning the continuous parameters in the strategy framework using Bayesian optimization; S6 Outputting the final controller. This invention is applicable to various facility agriculture scenarios such as poultry houses, greenhouses, plant factories, and aquaculture, achieving safe, efficient, and reproducible automatic optimization of environmental control strategies.

This invention discloses a wind-lighting module for plant factories, comprising a mounting frame, a light module, and multiple wind modules. Each light module includes a side-illuminated reflector and a light source. The side-illuminated reflector includes a first reflector, a second reflector, and a third reflector. The first and second reflectors are connected to the left and right sides of the third reflector, and the light source is connected to the lower end of the third reflector. Each wind module includes a wind deflector, blades, and a fan. The wind deflector is located at the lower end of the fan, and the blades are located inside the wind deflector. The blades include at least one set of vertically placed blades and at least one set of inclined blades. This wind-lighting module achieves uniform ventilation in the planting area. When used in conjunction with a side-illuminated lighting module, it combines lighting and ventilation to provide plants with a light energy and ventilation environment suitable for photosynthesis, and has a large market potential.

This invention discloses a plant factory planting device, belonging to the field of factory planting technology. It includes a conveying mechanism for conveying planting trays, a rolling hole-pressing mechanism, and a corresponding rolling sowing mechanism. The rolling hole-pressing mechanism includes a cylinder, a first end cap, and a second end cap. A hole-pressing control component is installed inside the cylinder. The rolling sowing mechanism includes a feeding cylinder and a feeding end cap. Multiple outlets are evenly spaced along the length of the feeding cylinder's wall, and each outlet contains a discharging component. This invention enables the creation of holes of different depths based on seed type without replacing the hole-pressing rollers, avoiding downtime for adjustments, improving the continuity of the planting line, and allowing for simultaneous and precise hole pressing and sowing operations. This significantly improves seed utilization, prevents seed scattering outside the holes, ensures precise plant spacing, and further optimizes the automation and standardization of plant factory planting.

1. Name of the product in this design: Graphical User Interface for a Smart Virtual Plant Factory for Electronic Devices. 2. Application of this design: The graphical user interface of this design is applied to an electronic device. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: the front view. 5. Purpose of the graphical user interface: This graphical user interface is used for interactive teaching and planting training in agricultural virtual simulation of smart virtual plant factories. 6. Description of the changing states of the graphical user interface: The main view is the "Smart Virtual Plant Factory" main interface. After logging in, you will see screen transition diagram 1, which is the factory creation interface. Click the "Create" button in screen transition diagram 1 to create a factory, then see screen transition diagram 2, which shows the successfully created factory interface. Click the created "factory icon" in screen transition diagram 2 to see screen transition diagram 3, where you can view the current factory planting tasks. Click the "Start Training" button for planting plan task number 1 in the list in screen transition diagram 3 to see screen transition diagram 4, the planting plan task interface. Complete the planting plan task in screen transition diagram 4 and click the "OK" button. The system will then display screen transition diagram 5, the current task results interface. Click the "OK" button in screen transition diagram 5 to see screen transition diagram 6. Click "Continue Task" in screen transition diagram 6 to see screen transition diagram 7, which displays the basic information for the next task. Click the "OK" button in screen transition diagram 7 to see screen transition diagram 8, the theoretical test interface. After completing the theoretical test in screen transition diagram 8, click the "OK" button to see screen transition diagram 9. The task training interface; in interface change state diagram 9, click the "Environmental Control Management" button at the bottom to enter the environmental control system interface in interface change state diagram 10, which is the training operation interface; click "Lighting System" at the top of interface change state diagram 10 to enter interface change state diagram 11, which is the training operation interface; click "Nutrient Solution Configuration" at the top of interface change state diagram 11 to enter interface change state diagram 12, which is the training operation interface; after completing the nutrient solution settings in interface change state diagram 12, click the "Save" button to enter the material list interface in interface change state diagram 13, where you can view the relevant information for this nutrient solution replenishment; click the "OK" button in the material list in interface change state diagram 13 to enter the factory roaming interface in interface change state diagram 14, where you can browse the 3D virtual scene and perform training operations; after completing the 3D virtual scene browsing and training operations in the factory roaming scene in interface change state diagram 14, you will enter the sales interface in interface change state diagram 15; click on interface change state diagram 15... Click "Confirm Sale" to proceed to the interface change state diagram 16 after the sale is completed, where you can view the current factory operation statistics and training results; click the "×" close button in the interface change state diagram 16 to proceed to the interface change state diagram 17; click "End Training" at the bottom of the interface change state diagram 17 to complete the lettuce planting training.

The present application relates to the technical field of plant factory light environment regulation, and discloses a light period regulation method and system based on dynamic adaptation of plant growth stages, which comprises the following steps: executing an interlayer spectral crosstalk calibration sequence to generate an interlayer spectral crosstalk transmission coefficient tensor; identifying the growth stages of plants in each layer, retrieving growth stage adaptation target light period parameter groups; collecting chlorophyll fluorescence kinetic parameters and decomposing direct and crosstalk spectral components to generate a photosynthetic response dataset grouped by varieties; independently training a spectral sensing Gaussian process regression model for each variety; executing multi-objective constraint Bayesian optimization to generate a set of Pareto optimal light period candidate schemes; and outputting the scheduling scheme to each layer of light controllers for synchronous execution; the present application solves the technical problem of light period parameter misalignment caused by interlayer light crosstalk in multi-layer vertical planting racks.

The application relates to the technical field of intelligent agriculture and wireless sensor networks, in particular to a plant factory plant growth data monitoring system based on Zigbee technology, which comprises a data acquisition module, a reference reconstruction module, a coupling verification module and a state judgment module; the data acquisition module is used for collecting environmental growth data and communication link characteristic data in real time and performing data validity preprocessing; the reference reconstruction module is used for constructing an ideal non-interference growth model and generating theoretical plant shape parameters; the coupling verification module is used for generating theoretical signal attenuation data by using biomass radio frequency attenuation logic, and calculating real and theoretical residual error vectors respectively; the state judgment module is used for performing residual error vector topological form comparison, and determining normal growth, growth stagnation or equipment fault state according to the coincidence degree and the attenuation amplitude; the application solves the pain point that signal interference and equipment failure are difficult to distinguish, and realizes low-cost monitoring of plant recessive growth stagnation by using physical layer characteristics.

This invention provides a soybean leaf-specific promoter Pcab1 and its applications, belonging to the field of plant bio-breeding technology. The soybean leaf-specific promoter Pcab1 provided by this invention has the nucleotide sequence shown in SEQ ID NO.4. This promoter-driven target gene can achieve specific expression in soybean leaves, providing a core molecular component for improving crop photosynthetic efficiency and constructing efficient biosynthetic systems for plant factories. It has high application value in research on plant gene expression regulation and the use of genetic engineering to improve soybean varieties.

This invention relates to the field of intelligent equipment and environmental control technology for facility agriculture, and discloses a method for sensing the growth status and adaptive supplemental lighting control of leafy vegetables in plant factories. The method includes the following steps: Step S1: Multimodal data acquisition; Step S2: Multimodal data fusion and growth status assessment; Step S3: Intelligent identification of growth stages and prediction of growth trends; Step S4: Adaptive optimization of multi-dimensional supplemental lighting parameters, etc. This method for sensing the growth status and adaptive supplemental lighting control of leafy vegetables in plant factories, through the fusion of hyperspectral, RGB-D, and chlorophyll fluorescence multimodal data plus attention mechanism feature weighting, can achieve comprehensive perception of leafy vegetable morphology, physiology, and spectral information, significantly improving the accuracy of growth status assessment. Through growth stage identification, LSTM trend prediction, and improved particle swarm optimization, it can achieve synchronous adaptive control of spectrum, light intensity, and photoperiod, while simultaneously improving leafy vegetable yield and quality, and significantly reducing supplemental lighting energy consumption, making the control more intelligent and energy-efficient.