Warehouse environment adjusting method, system and equipment based on industrial Internet of Things and medium

Abstract

The invention discloses a warehouse environment adjusting method, system and device based on the industrial Internet of Things and a medium, and relates to the technical field of the industrial Internet of Things, and the method comprises the steps: obtaining image data in a warehouse, and dividing materials stacked in the warehouse into at least one stacking unit according to the image data; determining an environmental adaptation factor of the at least one stacking unit according to the stacking parameters and the material parameters; acquiring a surface environment parameter of the at least one stacking unit, and determining an internal environment parameter of the at least one stacking unit according to the environment adaptation factor and the surface environment parameter; according to the internal environment parameters, the environment compatibility of the at least one stacking unit is determined, whether the environment in the warehouse needs to be adjusted or not is determined according to the environment compatibility, and if yes, an environment adjusting instruction is generated according to the internal environment parameters. The method and the device have the effect of improving the intelligent level of warehouse management.

Description

Technical Field

[0001] The present application relates to the technical field of industrial Internet of Things, and in particular to warehouse environment adjustment methods, systems, equipment and media based on industrial Internet of Things. Background Art

[0002] With the rapid development of globalization and e-commerce, warehouse management has become more and more complex and important. Modern warehouses not only need to handle a large amount of material flow, but also need to deal with the special requirements of different materials for storage conditions. In this context, the importance of warehouse environment management has become increasingly prominent, especially in industries such as food, medicine and high-value goods, which have strict requirements on environmental conditions such as temperature, humidity and light. Therefore, maintaining a suitable warehouse environment is crucial to ensure the safety and quality of materials.

[0003] At present, many warehouse management systems rely on regular manual inspections and simple monitoring equipment, resulting in inaccurate control of environmental conditions. In addition, the lack of real-time data monitoring and intelligent analysis systems makes warehouses slow to respond to sudden environmental changes, which not only increases the risk of material loss, but also affects overall operational efficiency. Therefore, existing warehouse management methods have significant defects in environmental monitoring and regulation, and new technical means are urgently needed to improve the level of intelligent and automated management. Summary of the invention

[0004] In order to improve the intelligence level of warehouse management, the present application provides a warehouse environment adjustment method, system, equipment and medium based on industrial Internet of Things.

[0005] In the first aspect, the present application provides a warehouse environment adjustment method based on the industrial Internet of Things, which adopts the following technical solutions: The warehouse environment adjustment method based on the industrial Internet of Things is applied to the industrial Internet of Things system, wherein the industrial Internet of Things system includes a management platform, a sensor network platform and an object platform which are sequentially connected in communication. The method is executed by the management platform and includes: Acquire image data in the warehouse, and divide the materials stacked in the warehouse into at least one stacking unit according to the image data; Acquire stacking parameters of the at least one stacking unit and material parameters of the material in the at least one stacking unit, and determine an environmental adaptability factor of the at least one stacking unit according to the stacking parameters and the material parameters; Acquire the surface environmental parameters of the at least one stacking unit, and determine the internal environmental parameters of the at least one stacking unit according to the environmental adaptability factor and the surface environmental parameters; The environmental compatibility of the at least one stacking unit is determined according to the internal environmental parameters, and whether the environment in the warehouse needs to be adjusted is determined according to the environmental compatibility. If so, an environmental adjustment instruction is generated according to the internal environmental parameters to adjust the environmental parameters in the warehouse.

[0006] By adopting the above technical scheme, the image data in the warehouse is first obtained, and the materials stacked in the warehouse are divided into at least one stacking unit according to the image data, then the stacking parameters of at least one stacking unit and the material parameters of the materials in at least one stacking unit are obtained, and the environmental adaptability factor of at least one stacking unit is determined according to the stacking parameters and the material parameters, then the surface environmental parameters of at least one stacking unit are obtained, and the internal environmental parameters of at least one stacking unit are determined according to the environmental adaptability factor and the surface environmental parameters, finally the environmental compatibility of at least one stacking unit is determined according to the internal environmental parameters, and it is determined whether the environment in the warehouse needs to be adjusted according to the environmental compatibility, if the environment in the warehouse needs to be adjusted, then an environmental adjustment instruction is generated according to the internal environmental parameters to adjust the environmental parameters in the warehouse; compared with the method of regular manual inspection or simple monitoring equipment, this method can be dynamically adjusted according to real-time data to ensure the safety and quality of materials in the warehouse, improve the efficiency and reliability of overall warehouse management, and improve the intelligence and automation levels of warehouse management.

[0007] Optionally, the step of dividing the materials stacked in the warehouse into at least one stacking unit according to the image data includes: Acquire a sample image of the warehouse, and annotate the material piles in the sample image to obtain a corresponding annotated image; Performing data enhancement operation on the annotated image to obtain corresponding model training data; Training a pre-built semantic segmentation model according to the model training data to obtain a pre-trained semantic segmentation model; Determine whether the model accuracy corresponding to the pre-trained semantic segmentation model meets the preset accuracy, and if so, use the pre-trained semantic segmentation model as the pre-generated semantic segmentation model; Inputting the image data into a pre-generated semantic segmentation model to obtain a semantic segmentation map; At least one stacking unit is determined according to the semantic segmentation map.

[0008] By adopting the above technical solution, a sample image of the warehouse is first obtained, and the material piles in the sample image are annotated to obtain the corresponding annotated image, and then the annotated image is subjected to data enhancement operation to obtain the corresponding model training data, and then the pre-constructed semantic segmentation model is trained according to the model training data to obtain the pre-trained semantic segmentation model, and then it is determined whether the model accuracy corresponding to the pre-trained semantic segmentation model meets the preset accuracy. If the model accuracy meets the preset accuracy, the pre-trained semantic segmentation model is used as the pre-generated semantic segmentation model, and then the image data is input into the pre-generated semantic segmentation model to obtain a semantic segmentation map, and finally at least one stacking unit is determined according to the semantic segmentation map.

[0009] Optionally, the stacking parameters include stacking volume and stacking mode, the material parameters include particle size, standard thermal conductivity and standard moisture absorption rate, the environmental adaptability factor includes a thermal conductivity assessment coefficient and a moisture conductivity assessment coefficient, and the step of determining the environmental adaptability factor of the at least one stacking unit according to the stacking parameters and the material parameters includes: Based on the stacking method, determining an average stacking density of the at least one stacking unit according to the stacking volume and the particle size; Determining a thermal conductivity evaluation coefficient of the at least one stacking unit according to the average stacking density and the standard thermal conductivity; A moisture conductivity evaluation coefficient of the at least one stacking unit is determined according to the average stacking density and the standard moisture absorption rate.

[0010] By adopting the above technical scheme, the average stacking density of at least one stacking unit is first determined based on the stacking method, and according to the stacking volume and particle size, and then the thermal conductivity evaluation coefficient of at least one stacking unit is determined according to the average stacking density and standard thermal conductivity, and the moisture conductivity evaluation coefficient of at least one stacking unit is determined according to the average stacking density and standard moisture absorption rate.

[0011] Optionally, the step of determining the internal environmental parameters of the at least one stacking unit according to the environmental adaptability factor and the surface environmental parameters includes: Acquire scanning data of the at least one stacking unit, and generate a three-dimensional model with a geometric center of the at least one stacking unit as an origin according to the scanning data; Acquiring preset coordinate acquisition parameters, and generating a feature point set from the three-dimensional model according to the coordinate acquisition parameters; the feature point set includes a plurality of coordinate feature points; Calculate distance feature data from each of the coordinate feature points to the surface of the at least one stacking unit according to the feature point set and the three-dimensional model; Constructing a temperature distribution equation of the at least one stacking unit according to the thermal conductivity evaluation coefficient and the surface environment parameter, and constructing a humidity distribution equation of the at least one stacking unit according to the moisture conductivity evaluation coefficient and the surface environment parameter; Inputting the distance characteristic data into the temperature distribution equation to obtain the temperature of each of the coordinate characteristic points; The distance characteristic data is input into the humidity distribution equation to obtain the humidity of each of the coordinate characteristic points; the internal environment parameters include the temperature and the humidity of each of the coordinate characteristic points.

[0012] By adopting the above technical solution, the scanning data of at least one stacking unit is first obtained, and a three-dimensional model with the geometric center of at least one stacking unit as the origin is generated according to the scanning data, and then the preset coordinate acquisition parameters are obtained, and a feature point set is generated from the three-dimensional model according to the coordinate acquisition parameters. The feature point set includes a number of coordinate feature points, and then the distance feature data from each coordinate feature point to the surface of at least one stacking unit is calculated according to the feature point set and the three-dimensional model, and then the temperature distribution equation of at least one stacking unit is constructed according to the thermal conductivity evaluation coefficient and the surface environmental parameters, and the humidity distribution equation of at least one stacking unit is constructed according to the moisture conductivity evaluation coefficient and the surface environmental parameters, and finally the distance feature data is input into the temperature distribution equation to obtain the temperature of each coordinate feature point, and the distance feature data is input into the humidity distribution equation to obtain the humidity of each coordinate feature point.

[0013] Optionally, the step of determining the environmental compatibility of the at least one stacking unit according to the internal environmental parameters includes: Obtaining the optimal storage conditions of the material, the optimal storage conditions including an optimal storage temperature range and an optimal humidity storage range, and determining the temperature compatibility of each of the characteristic points according to the optimal storage temperature range and the temperature of each of the characteristic points, and determining the humidity compatibility of each of the characteristic points according to the optimal humidity storage range and the temperature of each of the characteristic points; Obtaining a preset first weight and a second weight, and determining a comprehensive compatibility of each feature point according to the first weight, the second weight, the temperature compatibility and the humidity compatibility of each feature point; A corresponding average value is calculated according to the comprehensive compatibility of each of the feature points, and the average value is used as the environmental compatibility corresponding to the at least one stacking unit.

[0014] By adopting the above technical scheme, the optimal storage conditions of the material are first obtained, and the optimal storage conditions include the optimal storage temperature range and the optimal humidity storage range, and the temperature compatibility of each characteristic point is determined according to the optimal storage temperature range and the temperature of each characteristic point, and the humidity compatibility of each characteristic point is determined according to the optimal humidity storage range and the temperature of each characteristic point, and then the preset first weight and second weight are obtained, and the comprehensive compatibility of each characteristic point is determined according to the first weight, the second weight, the temperature compatibility and the humidity compatibility of each characteristic point, and finally the corresponding average value is calculated according to the comprehensive compatibility of each characteristic point, and the average value is used as the environmental compatibility corresponding to at least one stacking unit.

[0015] Optionally, the step of determining whether it is necessary to adjust the environment in the warehouse according to the environmental compatibility includes: Determining whether the environmental compatibility is greater than a preset value according to the environmental compatibility; If yes, it is determined that the environment in the warehouse needs to be adjusted; If not, it is determined that there is no need to adjust the environment in the warehouse.

[0016] By adopting the above technical solution, it is determined whether the environmental compatibility is greater than the preset value based on the environmental compatibility. If the environmental compatibility is greater than the preset value, it is determined that the environment in the warehouse needs to be adjusted. If the environmental compatibility is less than the preset value, it is determined that the environment in the warehouse does not need to be adjusted.

[0017] Optionally, the step of generating an environmental adjustment instruction according to the internal environmental parameters to adjust the environmental parameters in the warehouse includes: Determine the corresponding maximum temperature value and minimum temperature value according to the temperature of each of the coordinate feature points, and determine the corresponding maximum humidity value and minimum humidity value according to the humidity of each of the coordinate feature points; Determining a temperature adjustment value according to the maximum temperature value, the minimum temperature value and the optimal storage temperature range; Determine a humidity adjustment value according to the maximum humidity value, the minimum humidity value and the optimal storage humidity range; An environmental adjustment instruction is generated according to the temperature adjustment value and the humidity adjustment value to adjust the environmental parameters in the warehouse.

[0018] By adopting the above technical scheme, the corresponding maximum temperature and minimum temperature are first determined according to the temperature of each coordinate feature point, and the corresponding maximum humidity and minimum humidity are determined according to the humidity of each coordinate feature point. Then, the temperature adjustment value is determined according to the maximum temperature, the minimum temperature and the optimal storage temperature range, and the humidity adjustment value is determined according to the maximum humidity, the minimum humidity and the optimal storage humidity range. Finally, the environmental adjustment instructions are generated according to the temperature adjustment values ​​and the humidity adjustment values ​​to adjust the environmental parameters in the warehouse.

[0019] In the second aspect, the present application also provides a warehouse environment adjustment system based on the industrial Internet of Things, which adopts the following technical solutions: The warehouse environment adjustment system based on the industrial Internet of Things includes a management platform, a sensor network platform and an object platform which are sequentially connected in communication, and the management platform is configured with: A stacking unit division module, used for acquiring image data in the warehouse, and dividing the materials stacked in the warehouse into at least one stacking unit according to the image data; An environmental adaptability factor generating module, used for acquiring stacking parameters of the at least one stacking unit and material parameters of the material in the at least one stacking unit, and determining the environmental adaptability factor of the at least one stacking unit according to the stacking parameters and the material parameters; An internal environment parameter generating module, used for acquiring the surface environment parameters of the at least one stacking unit, and determining the internal environment parameters of the at least one stacking unit according to the environmental adaptability factor and the surface environment parameters; The environmental adjustment module is used to determine the environmental compatibility of the at least one stacking unit according to the internal environmental parameters, and determine whether the environment in the warehouse needs to be adjusted according to the environmental compatibility. If so, an environmental adjustment instruction is generated according to the internal environmental parameters to adjust the environmental parameters in the warehouse.

[0020] In a third aspect, the present application also provides a computer device, which adopts the following technical solution: A computer device comprises a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor implements the method described in the first aspect when executing the computer program.

[0021] In a fourth aspect, the present application further provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program that can be loaded by a processor and execute the method described in the first aspect.

[0022] In summary, the present application includes at least the following beneficial technical effects: first, image data in the warehouse is obtained, and materials stacked in the warehouse are divided into at least one stacking unit according to the image data, then the stacking parameters of at least one stacking unit and the material parameters of the materials in at least one stacking unit are obtained, and the environmental adaptability factor of at least one stacking unit is determined according to the stacking parameters and the material parameters, then the surface environmental parameters of at least one stacking unit are obtained, and the internal environmental parameters of at least one stacking unit are determined according to the environmental adaptability factor and the surface environmental parameters, finally, the environmental compatibility of at least one stacking unit is determined according to the internal environmental parameters, and whether it is necessary to adjust the environment in the warehouse according to the environmental compatibility is determined, and if it is necessary to adjust the environment in the warehouse, an environmental adjustment instruction is generated according to the internal environmental parameters to adjust the environmental parameters in the warehouse; compared with the method of regular manual inspection or simple monitoring equipment, this method can be dynamically adjusted according to real-time data to ensure the safety and quality of materials in the warehouse, improve the efficiency and reliability of overall warehouse management, and improve the intelligence and automation levels of warehouse management. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of the overall process of an embodiment of the present application.

[0024] Figure 2 It is a structural diagram of one application scenario of the system of an embodiment of the present application.

[0025] Figure 3 It is a structural diagram of another application scenario of the system of an embodiment of the present application.

[0026] Figure 4 It is a structural block diagram of the computer device of the present application. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-4 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0028] The embodiment of the present application discloses a warehouse environment adjustment method based on the industrial Internet of Things.

[0029] Reference Figure 1 The method for adjusting warehouse environment based on industrial Internet of Things is applied to the industrial Internet of Things system. The industrial Internet of Things system includes a management platform, a sensor network platform and an object platform which are sequentially connected in communication. The method is executed by the management platform and includes: Step S11, acquiring image data in the warehouse, and dividing the materials stacked in the warehouse into at least one stacking unit according to the image data.

[0030] Step S12, obtaining stacking parameters of at least one stacking unit and material parameters of the material in at least one stacking unit, and determining the environmental adaptability factor of at least one stacking unit according to the stacking parameters and the material parameters.

[0031] It can be understood that the environmental adaptability factor is a quantitative indicator that represents the degree of adaptability between the environmental conditions of the stacking unit and the material characteristics. It usually needs to take into account the requirements of the material properties in the stacking unit (such as temperature, humidity, light, ventilation, oxygen concentration, etc.) for environmental conditions.

[0032] Step S13, acquiring surface environmental parameters of at least one stacking unit, and determining internal environmental parameters of at least one stacking unit according to the environmental adaptability factor and the surface environmental parameters.

[0033] It can be understood that, in this embodiment, the surface environmental parameter of at least one stacking unit includes at least one of surface temperature and surface humidity, and the internal environmental parameter of at least one stacking unit includes at least one of internal temperature and internal humidity.

[0034] Step S14, determining the environmental compatibility of at least one stacking unit according to the internal environmental parameters, and determining whether the environment in the warehouse needs to be adjusted according to the environmental compatibility, and if so, generating environmental adjustment instructions according to the internal environmental parameters to adjust the environmental parameters in the warehouse.

[0035] Specifically, the environmental compatibility of at least one stacking unit is determined according to the internal environmental parameters, and whether the environment in the warehouse needs to be adjusted is determined according to the environmental compatibility. If the environment in the warehouse needs to be adjusted, an environmental adjustment instruction is generated according to the internal environmental parameters to adjust the environmental parameters in the warehouse; if the environment in the warehouse does not need to be adjusted, execution is restarted from step S11 or step S13 after a period of time.

[0036] It can be understood that environmental compatibility is used to indicate the compatibility or matching degree between the stacking unit and the current environment in the warehouse. Specifically, environmental compatibility is used to evaluate the matching degree between the internal environment of the stacking unit and the properties of the materials in the stacking unit. It is usually reflected as a numerical value to measure the adaptability of the current environmental parameters (such as temperature, humidity, etc.) to material storage.

[0037] In the above embodiment, image data in the warehouse is first obtained, and the materials stacked in the warehouse are divided into at least one stacking unit according to the image data, then the stacking parameters of at least one stacking unit and the material parameters of the materials in at least one stacking unit are obtained, and the environmental adaptability factor of at least one stacking unit is determined according to the stacking parameters and the material parameters, then the surface environmental parameters of at least one stacking unit are obtained, and the internal environmental parameters of at least one stacking unit are determined according to the environmental adaptability factor and the surface environmental parameters, finally the environmental compatibility of at least one stacking unit is determined according to the internal environmental parameters, and it is determined whether the environment in the warehouse needs to be adjusted according to the environmental compatibility, and if the environment in the warehouse needs to be adjusted, an environmental adjustment instruction is generated according to the internal environmental parameters to adjust the environmental parameters in the warehouse; compared with the method of regular manual inspection or simple monitoring equipment, this method can be dynamically adjusted according to real-time data to ensure the safety and quality of materials in the warehouse, improve the efficiency and reliability of overall warehouse management, and improve the intelligence and automation levels of warehouse management.

[0038] As a further implementation of the adjustment method, the step of dividing the materials stacked in the warehouse into at least one stacking unit according to the image data includes: Step S21, obtaining a sample image of the warehouse, and annotating the material piles in the sample image to obtain a corresponding annotated image.

[0039] Step S22, performing data enhancement operation on the annotated image to obtain corresponding model training data.

[0040] It can be understood that data augmentation operations refer to generating new, variant data samples by performing a series of transformations or processing on the original data. Data augmentation operations generally include rotation, flipping, scaling, cropping, adjusting brightness / contrast, adding noise, color transformation, and affine transformation.

[0041] Step S23, training the pre-built semantic segmentation model according to the model training data to obtain a pre-trained semantic segmentation model.

[0042] It should be noted that the semantic segmentation model is a deep learning model that is used to assign each pixel in an image to a specific category; common semantic segmentation models include Fully Convolutional Networks (FCN), U-Net, SegNet, DeepLab, etc.

[0043] Step S24, determining whether the model accuracy corresponding to the pre-trained semantic segmentation model meets the preset accuracy, and if so, using the pre-trained semantic segmentation model as the pre-generated semantic segmentation model.

[0044] Specifically, determine whether the model accuracy corresponding to the pre-trained semantic segmentation model meets the preset accuracy. If the model accuracy meets the preset accuracy, the pre-trained semantic segmentation model is used as the pre-generated semantic segmentation model; if the model accuracy does not meet the preset accuracy, re-execute step S21.

[0045] Step S25, inputting the image data into a pre-generated semantic segmentation model to obtain a semantic segmentation map.

[0046] Step S26, determining at least one stacking unit according to the semantic segmentation map.

[0047] Specifically, it should be noted that in step S26, each pixel in the semantic segmentation map is usually marked as a certain category (such as "material pile", "blank", "other objects", etc.), and then the connectivity of the pixels (such as four-connectivity or eight-connectivity) can be used to extract independent material pile areas, and calculate the properties of each independent material pile (such as height, volume, center of gravity position, etc.), and then determine at least one stacking unit from the above-mentioned independent material piles based on the properties of the material pile.

[0048] In the above embodiment, a sample image of the warehouse is first obtained, and the material piles in the sample image are annotated to obtain the corresponding annotated image, and then the annotated image is subjected to data enhancement operation to obtain the corresponding model training data, and then the pre-constructed semantic segmentation model is trained according to the model training data to obtain the pre-trained semantic segmentation model, and then it is determined whether the model accuracy corresponding to the pre-trained semantic segmentation model meets the preset accuracy. If the model accuracy meets the preset accuracy, the pre-trained semantic segmentation model is used as the pre-generated semantic segmentation model, and then the image data is input into the pre-generated semantic segmentation model to obtain a semantic segmentation map, and finally at least one stacking unit is determined according to the semantic segmentation map.

[0049] As a further implementation of the adjustment method, the stacking parameters include stacking volume and stacking mode, the material parameters include particle size, standard thermal conductivity and standard moisture absorption rate, the environmental adaptability factor includes thermal conductivity evaluation coefficient and moisture conductivity evaluation coefficient, and the step of determining the environmental adaptability factor of at least one stacking unit according to the stacking parameters and the material parameters includes: Step S31, based on the stacking method, and according to the stacking volume and particle size, an average stacking density of at least one stacking unit is determined.

[0050] It should be noted that in step S31, the volume fraction of the at least one stacking unit is first determined according to the particle size, and the corrected volume fraction is determined according to the stacking method and the volume fraction; then the particle density of the material is obtained, and the average stacking density of at least one stacking unit is determined according to the particle density, the corrected volume fraction and the stacking volume.

[0051] Step S32: determining a thermal conductivity evaluation coefficient of at least one stacking unit according to the average stacking density and the standard thermal conductivity.

[0052] It should be noted that the thermal conductivity evaluation coefficient K can be calculated by the following formula:

[0053] Wherein, λ represents the standard thermal conductivity, ρ represents the average stacking density; k1 represents a constant, and k1 is a value determined according to experiments.

[0054] Step S33, determining a moisture conductivity evaluation coefficient of at least one stacking unit according to the average stacking density and the standard moisture absorption rate.

[0055] It should be noted that the moisture conductivity evaluation coefficient H can be calculated by the following formula:

[0056] Wherein, S represents the standard moisture absorption rate, ρ represents the average stacking density; k2 represents a constant, and k2 is a value determined according to experiments.

[0057] In the above embodiment, the average stacking density of at least one stacking unit is first determined based on the stacking method, the stacking volume and the particle size, and then the thermal conductivity evaluation coefficient of at least one stacking unit is determined based on the average stacking density and the standard thermal conductivity, and the moisture conductivity evaluation coefficient of at least one stacking unit is determined based on the average stacking density and the standard moisture absorption rate.

[0058] As a further implementation of the adjustment method, the step of determining the internal environmental parameters of at least one stacking unit according to the environmental adaptation factor and the surface environmental parameters includes: Step S41, acquiring scanning data of at least one stacking unit, and generating a three-dimensional model with the geometric center of at least one stacking unit as the origin according to the scanning data.

[0059] It can be understood that, for each stacking unit, the geometric center of gravity can be the center of gravity of the stacking unit.

[0060] Step S42, obtaining preset coordinate acquisition parameters, and generating a feature point set from the three-dimensional model according to the coordinate acquisition parameters. The feature point set includes a number of coordinate feature points.

[0061] It is understandable that the coordinate acquisition parameters may include parameters such as acquisition method and distance between acquisition points.

[0062] Step S43, calculating distance feature data from each coordinate feature point to the surface of at least one stacking unit according to the feature point set and the three-dimensional model.

[0063] It should be noted that the distance feature data may be the shortest distance between the coordinate feature point and the surface of the stacking unit.

[0064] Step S44, constructing a temperature distribution equation of at least one stacking unit according to the thermal conductivity evaluation coefficient and the surface environmental parameters, and constructing a humidity distribution equation of at least one stacking unit according to the moisture conductivity evaluation coefficient and the surface environmental parameters.

[0065] It should be noted that the surface environmental parameters include surface temperature parameters and surface humidity parameters, and the temperature distribution equation can be:

[0066] Wherein, x represents the shortest distance between the coordinate feature point and the surface of the stacking unit, T(x) represents the temperature of the coordinate feature point corresponding to x; T0 is the temperature obtained by the surface temperature parameter, such as the average surface temperature, but in actual determination, it needs to be set according to the surface temperature parameter and the actual situation; Indicates the thermal conductivity evaluation coefficient.

[0067] It should be further explained that the temperature distribution equation can be:

[0068] Wherein, x represents the shortest distance between the coordinate feature point and the surface of the stacking unit, H(x) represents the humidity of the coordinate feature point corresponding to x; H0 is the humidity obtained by the surface humidity parameter, such as the average surface humidity, but in actual determination, it needs to be set according to the surface humidity parameter and the actual situation; Indicates the moisture conductivity evaluation coefficient.

[0069] Step S45, inputting the distance characteristic data into the temperature distribution equation to obtain the temperature of each coordinate characteristic point.

[0070] Step S46, inputting the distance feature data into the humidity distribution equation to obtain the humidity of each coordinate feature point.

[0071] Among them, the internal environmental parameters include the temperature and humidity of each coordinate feature point.

[0072] In the above embodiment, the scanning data of at least one stacking unit is first obtained, and a three-dimensional model with the geometric center of at least one stacking unit as the origin is generated according to the scanning data, and then the preset coordinate acquisition parameters are obtained, and a feature point set is generated from the three-dimensional model according to the coordinate acquisition parameters. The feature point set includes a number of coordinate feature points, and then the distance feature data from each coordinate feature point to the surface of at least one stacking unit is calculated according to the feature point set and the three-dimensional model, and then the temperature distribution equation of at least one stacking unit is constructed according to the thermal conductivity evaluation coefficient and the surface environmental parameters, and the humidity distribution equation of at least one stacking unit is constructed according to the moisture conductivity evaluation coefficient and the surface environmental parameters, and finally the distance feature data is input into the temperature distribution equation to obtain the temperature of each coordinate feature point, and the distance feature data is input into the humidity distribution equation to obtain the humidity of each coordinate feature point.

[0073] As a further implementation of the adjustment method, the step of determining the environmental compatibility of at least one stacking unit according to the internal environmental parameters includes: Step S51, obtaining the optimal storage conditions of the material, the optimal storage conditions include the optimal storage temperature range and the optimal humidity storage range, and determining the temperature compatibility of each feature point based on the optimal storage temperature range and the temperature of each feature point, and determining the humidity compatibility of each feature point based on the optimal humidity storage range and the temperature of each feature point.

[0074] It should be noted that when calculating the temperature compatibility of each feature point, each feature point can be assigned a value by determining whether the temperature of each feature point is within the optimal storage temperature range, and the corresponding assigned value can be used as the temperature compatibility; the method for determining the humidity compatibility can be consistent with the method for determining the humidity compatibility.

[0075] Step S52, obtaining a preset first weight and a second weight, and determining the comprehensive compatibility of each feature point according to the first weight, the second weight, the temperature compatibility and the humidity compatibility of each feature point.

[0076] Step S53, calculating a corresponding average value according to the comprehensive compatibility of each feature point, and using the average value as the environmental compatibility corresponding to at least one stacking unit.

[0077] In the above embodiment, the optimal storage conditions of the material are first obtained, and the optimal storage conditions include the optimal storage temperature range and the optimal humidity storage range, and the temperature compatibility of each feature point is determined according to the optimal storage temperature range and the temperature of each feature point, and the humidity compatibility of each feature point is determined according to the optimal humidity storage range and the temperature of each feature point, and then the preset first weight and second weight are obtained, and the comprehensive compatibility of each feature point is determined according to the first weight, the second weight, the temperature compatibility and the humidity compatibility of each feature point, and finally the corresponding average value is calculated according to the comprehensive compatibility of each feature point, and the average value is used as the environmental compatibility corresponding to at least one stacking unit.

[0078] As a further implementation of the adjustment method, the step of determining whether the environment in the warehouse needs to be adjusted according to the environmental compatibility includes: Step S61, judging whether the environmental compatibility is greater than a preset value according to the environmental compatibility.

[0079] Step S62: If yes, it is determined that the environment in the warehouse needs to be adjusted.

[0080] Step S63: If not, it is determined that there is no need to adjust the environment in the warehouse.

[0081] In the above embodiment, it is determined whether the environmental compatibility is greater than a preset value based on the environmental compatibility. If the environmental compatibility is greater than the preset value, it is determined that the environment in the warehouse needs to be adjusted. If the environmental compatibility is less than the preset value, it is determined that the environment in the warehouse does not need to be adjusted.

[0082] As a further implementation of the adjustment method, the step of generating an environmental adjustment instruction according to the internal environmental parameters to adjust the environmental parameters in the warehouse includes: Step S71, determining the corresponding maximum temperature value and minimum temperature value according to the temperature of each coordinate feature point, and determining the corresponding maximum humidity value and minimum humidity value according to the humidity of each coordinate feature point.

[0083] Step S72, determining a temperature adjustment value according to the maximum temperature value, the minimum temperature value and the optimal storage temperature range.

[0084] Step S73, determining the humidity adjustment value according to the maximum humidity value, the minimum humidity value and the optimal storage humidity range.

[0085] Step S74, generating an environmental adjustment instruction according to the temperature adjustment value and the humidity adjustment value to adjust the environmental parameters in the warehouse.

[0086] It is understandable that, in step S74, after the environmental adjustment instruction is generated, an air conditioner or a humidifier is usually started to adjust the environmental parameters in the warehouse to make the environment in the warehouse more suitable for storing materials.

[0087] In the above embodiment, the corresponding maximum temperature and minimum temperature are first determined according to the temperature of each coordinate feature point, and the corresponding maximum humidity and minimum humidity are determined according to the humidity of each coordinate feature point. Then, the temperature adjustment value is determined according to the maximum temperature, the minimum temperature and the optimal storage temperature range, and the humidity adjustment value is determined according to the maximum humidity, the minimum humidity and the optimal storage humidity range. Finally, the environmental adjustment instructions are generated according to the temperature adjustment values ​​and the humidity adjustment values ​​to adjust the environmental parameters in the warehouse.

[0088] The embodiment of the present application also discloses a warehouse environment adjustment system based on the industrial Internet of Things.

[0089] refer to Figure 2 The warehouse environment adjustment system based on the industrial Internet of Things includes a management platform, a sensor network platform and an object platform which are connected in sequence by communication. The management platform is configured with: A stacking unit division module, used to obtain image data in the warehouse and divide the materials stacked in the warehouse into at least one stacking unit according to the image data; An environmental adaptability factor generating module, used to obtain stacking parameters of at least one stacking unit and material parameters of materials in at least one stacking unit, and determine the environmental adaptability factor of at least one stacking unit according to the stacking parameters and the material parameters; An internal environment parameter generating module, used to obtain the surface environment parameters of at least one stacking unit, and determine the internal environment parameters of at least one stacking unit according to the environmental adaptability factor and the surface environment parameters; The environmental adjustment module is used to determine the environmental compatibility of at least one stacking unit according to the internal environmental parameters, and determine whether the environment in the warehouse needs to be adjusted according to the environmental compatibility. If so, an environmental adjustment instruction is generated according to the internal environmental parameters to adjust the environmental parameters in the warehouse.

[0090] The overall framework of another application scenario of the robot management system based on industrial Internet of Things of this application is as follows Figure 3 As shown, it may include a user platform, a service platform, a management platform, a sensor network platform and an object platform that interact in sequence, forming a five-platform architecture based on the industrial Internet of Things. Among them, the management platform includes a stacking unit division module, an environmental adaptation factor generation module, an internal environmental parameter generation module and an environmental adjustment module; the sensor network platform includes a sensor general database and several sensor network sub-platforms, each of which can communicate with the sensor general database, and each sensor network sub-platform is provided with a sensor sub-database.

[0091] Specifically, in another application scenario mentioned above, the robot management system based on industrial Internet of Things includes a management platform, which is configured to: obtain image data in the warehouse, and divide the materials stacked in the warehouse into at least one stacking unit according to the image data; obtain the stacking parameters of at least one stacking unit and the material parameters of the material in at least one stacking unit, and determine the environmental adaptability factor of at least one stacking unit according to the stacking parameters and the material parameters; obtain the surface environmental parameters of at least one stacking unit, and determine the internal environmental parameters of at least one stacking unit according to the environmental adaptability factor and the surface environmental parameters; determine the environmental compatibility of at least one stacking unit according to the internal environmental parameters, and determine whether it is necessary to adjust the environment in the warehouse according to the environmental compatibility, and if so, generate environmental adjustment instructions according to the internal environmental parameters to adjust the environmental parameters in the warehouse.

[0092] Through the interaction between the various functional platforms of the industrial Internet of Things-based robot management system based on the above three platforms or five platforms, a complete closed-loop information operation logic is established, ensuring the orderly operation of perception information and control information and realizing intelligent equipment management.

[0093] The warehouse environment adjustment system based on industrial Internet of Things of the present invention can implement any one of the warehouse environment adjustment methods based on industrial Internet of Things, and the specific working process of the warehouse environment adjustment system based on industrial Internet of Things of the present invention can refer to the corresponding process in the above-mentioned warehouse environment adjustment method based on industrial Internet of Things.

[0094] The embodiment of the present application also discloses a computer device.

[0095] refer to Figure 4 A computer device includes a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, any of the above-mentioned warehouse environment adjustment methods based on the industrial Internet of Things is implemented.

[0096] The embodiment of the present application also discloses a computer-readable storage medium.

[0097] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any one of the above-mentioned warehouse environment adjustment methods based on the industrial Internet of Things.

[0098] Among them, computer-readable storage media can be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus or device; the program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0099] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A warehouse environment adjustment method based on industrial Internet of Things, characterized in that: Applied to an industrial Internet of Things system, the industrial Internet of Things system includes a management platform, a sensor network platform and an object platform that are sequentially communicatively connected, and the method is executed by the management platform, including: Acquire image data in the warehouse, and divide the materials stacked in the warehouse into at least one stacking unit according to the image data; Acquire stacking parameters of the at least one stacking unit and material parameters of the material in the at least one stacking unit, and determine an environmental adaptability factor of the at least one stacking unit according to the stacking parameters and the material parameters; Acquire the surface environmental parameters of the at least one stacking unit, and determine the internal environmental parameters of the at least one stacking unit according to the environmental adaptability factor and the surface environmental parameters; The environmental compatibility of the at least one stacking unit is determined according to the internal environmental parameters, and whether the environment in the warehouse needs to be adjusted is determined according to the environmental compatibility. If so, an environmental adjustment instruction is generated according to the internal environmental parameters to adjust the environmental parameters in the warehouse.

2. The warehouse environment adjustment method based on industrial Internet of Things according to claim 1 is characterized in that: The step of dividing the materials stacked in the warehouse into at least one stacking unit according to the image data comprises: Acquire a sample image of the warehouse, and annotate the material piles in the sample image to obtain a corresponding annotated image; Performing data enhancement operation on the annotated image to obtain corresponding model training data; Training a pre-built semantic segmentation model according to the model training data to obtain a pre-trained semantic segmentation model; Determine whether the model accuracy corresponding to the pre-trained semantic segmentation model meets the preset accuracy, and if so, use the pre-trained semantic segmentation model as the pre-generated semantic segmentation model; Inputting the image data into a pre-generated semantic segmentation model to obtain a semantic segmentation map; At least one stacking unit is determined according to the semantic segmentation map.

3. The warehouse environment adjustment method based on industrial Internet of Things according to claim 1 is characterized in that: The stacking parameters include stacking volume and stacking mode, the material parameters include particle size, standard thermal conductivity and standard moisture absorption rate, the environmental adaptability factor includes thermal conductivity evaluation coefficient and moisture conductivity evaluation coefficient, and the step of determining the environmental adaptability factor of at least one stacking unit according to the stacking parameters and the material parameters includes: Based on the stacking method, determining an average stacking density of the at least one stacking unit according to the stacking volume and the particle size; Determining a thermal conductivity evaluation coefficient of the at least one stacking unit according to the average stacking density and the standard thermal conductivity; A moisture conductivity evaluation coefficient of the at least one stacking unit is determined according to the average stacking density and the standard moisture absorption rate.

4. The warehouse environment adjustment method based on industrial Internet of Things according to claim 3 is characterized in that: The step of determining the internal environmental parameters of the at least one stacking unit according to the environmental adaptability factor and the surface environmental parameters comprises: Acquire scanning data of the at least one stacking unit, and generate a three-dimensional model with a geometric center of the at least one stacking unit as an origin according to the scanning data; Acquiring preset coordinate acquisition parameters, and generating a feature point set from the three-dimensional model according to the coordinate acquisition parameters; the feature point set includes a plurality of coordinate feature points; Calculate distance feature data from each of the coordinate feature points to the surface of the at least one stacking unit according to the feature point set and the three-dimensional model; Constructing a temperature distribution equation of the at least one stacking unit according to the thermal conductivity evaluation coefficient and the surface environment parameter, and constructing a humidity distribution equation of the at least one stacking unit according to the moisture conductivity evaluation coefficient and the surface environment parameter; Inputting the distance characteristic data into the temperature distribution equation to obtain the temperature of each of the coordinate characteristic points; The distance characteristic data is input into the humidity distribution equation to obtain the humidity of each of the coordinate characteristic points; the internal environment parameters include the temperature and the humidity of each of the coordinate characteristic points.

5. The warehouse environment adjustment method based on industrial Internet of Things according to claim 4 is characterized in that: The step of determining the environmental compatibility of the at least one stacking unit according to the internal environmental parameters comprises: Obtaining the optimal storage conditions of the material, the optimal storage conditions including an optimal storage temperature range and an optimal humidity storage range, and determining the temperature compatibility of each of the characteristic points according to the optimal storage temperature range and the temperature of each of the characteristic points, and determining the humidity compatibility of each of the characteristic points according to the optimal humidity storage range and the temperature of each of the characteristic points; Obtaining a preset first weight and a second weight, and determining a comprehensive compatibility of each feature point according to the first weight, the second weight, the temperature compatibility and the humidity compatibility of each feature point; A corresponding average value is calculated according to the comprehensive compatibility of each of the feature points, and the average value is used as the environmental compatibility corresponding to the at least one stacking unit.

6. The warehouse environment adjustment method based on industrial Internet of Things according to claim 1 is characterized in that: The step of determining whether it is necessary to adjust the environment in the warehouse according to the environmental compatibility includes: Determining whether the environmental compatibility is greater than a preset value according to the environmental compatibility; If yes, it is determined that the environment in the warehouse needs to be adjusted; If not, it is determined that there is no need to adjust the environment in the warehouse.

7. The warehouse environment adjustment method based on industrial Internet of Things according to claim 5 is characterized in that: The step of generating an environmental adjustment instruction according to the internal environmental parameters to adjust the environmental parameters in the warehouse includes: Determine the corresponding maximum temperature value and minimum temperature value according to the temperature of each of the coordinate feature points, and determine the corresponding maximum humidity value and minimum humidity value according to the humidity of each of the coordinate feature points; Determining a temperature adjustment value according to the maximum temperature value, the minimum temperature value and the optimal storage temperature range; Determine a humidity adjustment value according to the maximum humidity value, the minimum humidity value and the optimal storage humidity range; An environmental adjustment instruction is generated according to the temperature adjustment value and the humidity adjustment value to adjust the environmental parameters in the warehouse.

8. The warehouse environment adjustment system based on industrial Internet of Things is characterized by: It includes a management platform, a sensor network platform and an object platform which are connected in sequence, and the management platform is configured with: A stacking unit division module, used for acquiring image data in the warehouse, and dividing the materials stacked in the warehouse into at least one stacking unit according to the image data; An environmental adaptability factor generating module, used for acquiring stacking parameters of the at least one stacking unit and material parameters of the material in the at least one stacking unit, and determining the environmental adaptability factor of the at least one stacking unit according to the stacking parameters and the material parameters; An internal environment parameter generating module, used for acquiring the surface environment parameters of the at least one stacking unit, and determining the internal environment parameters of the at least one stacking unit according to the environmental adaptability factor and the surface environment parameters; The environmental adjustment module is used to determine the environmental compatibility of the at least one stacking unit according to the internal environmental parameters, and determine whether the environment in the warehouse needs to be adjusted according to the environmental compatibility. If so, an environmental adjustment instruction is generated according to the internal environmental parameters to adjust the environmental parameters in the warehouse.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 7.

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