Logistics storage environment adjusting method and system based on Internet of Things

Abstract

The invention relates to the technical field of environment adjustment, and discloses a logistics storage environment adjustment method and system based on the Internet of Things. The method comprises the following steps: acquiring the types of articles in a warehouse, and setting the maximum value of the quality attribute of the articles as a reference attribute; searching an article environment mapping table according to the article types and the reference attributes, and setting the environment parameter corresponding to the maximum weight value as a target environment parameter; periodically collecting external temperature data, calculating internal and external temperature difference, calculating a first adjusting coefficient of the environment control equipment based on the temperature difference, calculating first operation power according to the first adjusting coefficient, and controlling operation of the environment control equipment; periodically collecting current environment data in the warehouse, and performing error compensation on the data in the current environment data to generate corrected environment data; and searching a storage state mapping table based on the corrected environment data, extracting a storage state corresponding to the maximum weight value, judging whether the corrected environment data is abnormal or not according to the storage state, and adjusting the environment control equipment when the corrected environment data is abnormal. According to the invention, the accuracy, flexibility and intelligent level of storage environment adjustment are improved.

Description

Technical Field

[0001] The present application relates to the field of environmental regulation technology, and in particular to a logistics warehousing environment regulation method and system based on the Internet of Things. Background Art

[0002] In the field of modern logistics and warehousing, the regulation of the storage environment is crucial to ensure the quality and safety of goods. Traditional storage environment regulation methods mainly rely on manual inspections and manually operated equipment, which have problems such as low efficiency of manual inspections and limited regulation accuracy. With the rapid development of Internet of Things technology, its application in the field of warehousing has gradually attracted attention. The Internet of Things can achieve real-time monitoring and automatic regulation of the storage environment through sensor networks, data transmission and intelligent control technology.

[0003] Similar prior art includes a Chinese patent application with publication number CN118113089A, which discloses a warehouse environment control method, an air conditioner and a storage medium, which obtain preset temperature information and / or humidity information, temperature information and / or humidity information inside the warehouse, and temperature information and / or humidity information outside the warehouse; compare the temperature information and / or humidity information inside the warehouse, and the temperature information and / or humidity information outside the warehouse with the preset temperature information and / or humidity information, respectively, and obtain comparison results; and according to the comparison results, control the air conditioner to execute an air circulation plan inside the warehouse, or an air circulation plan inside and outside the warehouse. There is also a Chinese patent application with publication number CN115291655A, which discloses a warehouse environment adjustment system, method and storage medium, including a monitoring system, an environment adjustment device and a background system; the monitoring system is used to collect environmental information of the warehouse, and send control instructions to the environment adjustment device according to the environmental information to control the operation of the environment adjustment device; if an alarm is required based on the environmental information, the alarm is processed and the alarm information is sent to the background system; the environment adjustment device is used to perform corresponding operations according to the control instructions to adjust the environment of the warehouse; the background system is used to provide users with alarm information query services based on the alarm information, and perform management and maintenance processing.

[0004] The above-mentioned existing technologies only consider environmental factors when adjusting environmental control equipment, and the adjustment method is single, the degree of intelligence is low, and there is a lack of in-depth processing and comprehensive analysis capabilities for environmental data. Therefore, it is an urgent problem to provide a logistics warehousing environment adjustment method and system based on the Internet of Things to improve the accuracy, flexibility and intelligence level of warehousing environment adjustment. Summary of the invention

[0005] The present application provides a logistics warehousing environment adjustment method and system based on the Internet of Things, which are used to improve the efficiency, accuracy and responsiveness of logistics warehousing environment adjustment.

[0006] In a first aspect, the present application provides a method for adjusting a logistics storage environment based on the Internet of Things, the method comprising:

[0007] Step 1: Obtain the types of items in the warehouse, identify the quality attributes of all items, and set the maximum value of the quality attribute as the reference attribute;

[0008] Step 2: search the item environment mapping table based on the item type and reference attribute, extract the maximum weight value corresponding to the reference attribute, define it as the first reference weight, and use the environment parameter corresponding to the first reference weight as the target environment parameter;

[0009] Step 3: Periodically collect external temperature data, calculate the temperature difference between the external temperature data and the target temperature data, execute a first predetermined algorithm on the temperature difference, obtain a first adjustment coefficient of the environment control device, calculate a first operating power of the environment control device based on the first adjustment coefficient, and control the environment control device to operate according to the first operating power;

[0010] Step 4: Periodically collect the current environmental data in the warehouse, extract any current environmental data, define it as the first data, determine whether the first data is within the corresponding preset range, and if so, perform error compensation on the first data to generate new environmental data. After traversing all current environmental data, generate corrected environmental data;

[0011] Step 5: Search the storage status mapping table based on the corrected environmental data, extract the maximum weight value corresponding to the corrected environmental data, define it as the second reference weight, take the storage status corresponding to the second reference weight as the target storage status, and determine whether there is an abnormality in the corrected environmental data based on the target storage status. If so, adjust the environmental control equipment.

[0012] In combination with the first aspect, in a first implementation method of the first aspect of the present application, step 3 also includes: when the warehouse door is open, obtaining the exposed area of ​​the warehouse, executing a second predetermined algorithm on the exposed area and the temperature difference, obtaining the second adjustment coefficient of the environmental control device, defining the sum of the first adjustment coefficient and the second adjustment coefficient as a third adjustment coefficient, calculating the second operating power of the environmental control device based on the third adjustment coefficient, and controlling the environmental control device to operate according to the second operating power.

[0013] In combination with the first aspect, in a second implementation method of the first aspect of the present application, the time interval for collecting environmental data in the warehouse is adjusted based on environmental disturbance factors, including: real-time monitoring of the environmental disturbance factors in the warehouse, when the environmental disturbance factors change, calculating the disturbance intensity within a first preset time, and adjusting the time interval according to preset rules based on the disturbance intensity.

[0014] In combination with the first aspect, in a third implementation of the first aspect of the present application, when the disturbance intensity increases, the time interval is reduced according to a first preset ratio;

[0015] When the disturbance intensity decreases, the time interval is increased according to a second preset ratio.

[0016] In combination with the first aspect, in a fourth implementation of the first aspect of the present application, in step 4, performing error compensation on the first data to generate new environmental data includes:

[0017] Step 41: extract historical environmental data corresponding to the first data within a second preset time, combine the historical environmental data and the first data to generate an environmental data sequence, and convert the environmental data sequence into a preset numerical type to obtain a first data sequence;

[0018] Step 42: Perform a spatial transformation operation on the first data sequence through the first transformation module to generate linear transformation data, and at the same time, perform a third predetermined algorithm on the first data sequence through the second transformation module to obtain a prediction value corresponding to the first data;

[0019] Step 43, performing a preset periodic function calculation on the transformed data and the predicted value to obtain an adjustment value, feeding the adjustment value back to the first transformation module and the second transformation module, and returning to step 42, repeating steps 42 to 43 until the transformed data and the predicted value converge;

[0020] Step 44: Correct the first data based on the transformed data and the predicted value to generate new environmental data.

[0021] In combination with the first aspect, in a fifth implementation of the first aspect of the present application, in step 42, performing a spatial transformation operation on the first data sequence by a first transformation module to generate linear transformation data includes:

[0022] A nonlinear function of the environmental monitoring device corresponding to the first data is obtained, a first-order partial derivative matrix is ​​constructed based on the nonlinear function, and the first data sequence is multiplied by the first-order partial derivative matrix to generate transformed data.

[0023] In combination with the first aspect, in a sixth implementation of the first aspect of the present application, adjusting the device operating parameters of the environment control device based on the moving object includes:

[0024] Real-time monitoring of whether there are moving objects in the warehouse. If there are, identify the area where the moving objects are located and define it as the target area;

[0025] Extract the maximum temperature and minimum humidity in the target environmental parameters, adjust the equipment operating parameters of the first environmental control device based on the maximum temperature and minimum humidity, and adjust the blowing mode of the first environmental control device, wherein the first environmental control device is the environmental control device corresponding to the target area.

[0026] In combination with the first aspect, in a seventh implementation of the first aspect of the present application, adjusting the blowing mode of the first environment control device includes:

[0027] Obtaining the positions of the first environment control device, the mobile object, and all items in the target area, identifying a reference plane perpendicular to the ground where the first environment control device and the mobile object are located, and obtaining items that are not located on the reference plane, which are defined as first items;

[0028] The surface temperatures of all first objects are obtained, the objects corresponding to the maximum surface temperatures are defined as selected objects, and the first environmental control device is controlled to blow air toward the selected objects.

[0029] In a second aspect, the present application provides a logistics warehousing environment adjustment system based on the Internet of Things, the system comprising: a data acquisition module, a parameter setting module, an equipment control module, a data collection module and an environment adjustment module;

[0030] The data acquisition module is used to obtain the types of items in the warehouse, identify the quality attributes of all items, and set the maximum value of the quality attribute as the reference attribute;

[0031] A parameter setting module is used to search the item environment mapping table according to the item type and reference attribute, extract the maximum weight value corresponding to the reference attribute, define it as the first reference weight, and use the environment parameter corresponding to the first reference weight as the target environment parameter;

[0032] an equipment control module, configured to periodically collect external temperature data, calculate a temperature difference between the external temperature data and the target temperature data, execute a first predetermined algorithm on the temperature difference, obtain a first adjustment coefficient of the environment control device, calculate a first operating power of the environment control device based on the first adjustment coefficient, and control the environment control device to operate at the first operating power;

[0033] The data collection module is used to periodically collect the current environmental data in the warehouse, extract any current environmental data, define it as the first data, determine whether the first data is within the corresponding preset range, and if so, perform error compensation on the first data to generate new environmental data, and after traversing all the current environmental data, generate the corrected environmental data;

[0034] The environmental adjustment module is used to search the storage status mapping table according to the corrected environmental data, extract the maximum weight value corresponding to the corrected environmental data, define it as the second reference weight, take the storage status corresponding to the second reference weight as the target storage status, and judge whether there is an abnormality in the corrected environmental data based on the target storage status. If so, adjust the environmental control equipment.

[0035] Compared with the prior art, the beneficial effects of the technical solution of the present application are at least as follows:

[0036] 1. By identifying the types of items and reference attributes, the target environmental parameters corresponding to the item attributes are accurately set to ensure that the storage environment meets the storage requirements of the items, which can extend the shelf life of the items and reduce energy consumption.

[0037] 2. Periodically collect external and internal environmental data, and calculate the temperature difference between the external temperature data and the target temperature data. Based on the temperature difference, dynamically adjust the operating power of the environmental control equipment to improve the flexibility of warehouse environment adjustment, achieve energy saving and consumption reduction, and reduce operating costs.

[0038] 3. Periodically collect the current environmental data in the warehouse, perform error compensation and correction on the environmental data to improve data accuracy, judge abnormal conditions based on the corrected environmental data, and adjust the environmental control equipment in a timely manner to quickly respond to environmental changes, avoid environmental control errors caused by data deviations, and maintain the stability of the storage environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0040] Figure 1 This is a schematic diagram of an embodiment of a method for adjusting a logistics storage environment based on the Internet of Things in an embodiment of the present application;

[0041] Figure 2 A schematic diagram of an embodiment of a new method for generating environmental data in an embodiment of the present application;

[0042] Figure 3 This is a schematic diagram of an embodiment of a logistics warehousing environment adjustment system based on the Internet of Things in the embodiment of the present application. DETAILED DESCRIPTION

[0043] The embodiment of the present application provides a method and system for regulating the logistics warehousing environment based on the Internet of Things. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0044] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 In the embodiments of the present application, an embodiment of the method for adjusting the logistics storage environment based on the Internet of Things includes:

[0045] Step 1: Get the types of items in the warehouse, identify the quality attributes of all items, and set the maximum value of the quality attribute as the reference attribute.

[0046] Specifically, item information is obtained through automatic identification through IoT technology (such as RFID, barcode scanning, sensors, etc.) or input by managers, which may include the name, type, quantity, etc. Item types include vegetables, seafood, meat products, medicines, electronic products, etc. Different types of items require different storage environments.

[0047] The quality attribute is the freshness of the item (for example, it can be divided into three levels: high, medium, and low). It can be obtained through image recognition technology or input into the system by staff. In particular, for perishable items such as vegetables, seafood, and meat products, there will be different degrees of loss during transportation, and the loss cannot be repaired, resulting in changes in the freshness of the items. Different quality attributes can correspond to different storage conditions. For example, for items with the highest quality attributes, stricter storage conditions are required to maintain the freshness of the items for a long time; for items with medium quality attributes, general storage conditions are required to keep the items at their current freshness. Stricter storage conditions (such as temperature 2°C and humidity 70%) require more energy consumption by the environmental control device. Compared with stricter storage conditions, general storage conditions (such as temperature 4°C and humidity 65%) require lower resources and costs. Providing storage conditions corresponding to the quality attributes of items can reduce energy consumption while ensuring their quality.

[0048] Step 2: Search the item environment mapping table based on the item type and reference attribute, extract the maximum weight value corresponding to the reference attribute, define it as the first reference weight, and use the environment parameter corresponding to the first reference weight as the target environment parameter.

[0049] Specifically, environmental parameters include temperature, humidity, light, air quality, etc. The item environment mapping table is a mapping table between item types, quality attributes, and optimal storage environments. The weight value between each environmental parameter and the item type and reference attribute is obtained through training based on historical data, and the relationship strength (i.e., weight value) between the environmental parameter and the item type and reference attribute can be directly quantified. Exemplarily, the item type is vegetable A, the reference attribute is high, and the environmental parameter B1 has a probability of 0.8 to keep the quality attribute of vegetable A high, and the environmental parameter B2 has a probability of 0.95 to keep the quality attribute of vegetable A high, then the environmental parameter B2 corresponding to the maximum weight value of 0.95 is selected as the target environmental parameter.

[0050] Step 3: periodically collect external temperature data, calculate the temperature difference between the external temperature data and the target temperature data, execute a first predetermined algorithm on the temperature difference, obtain a first adjustment coefficient of the environmental control device, calculate a first operating power of the environmental control device based on the first adjustment coefficient, and control the environmental control device to operate according to the first operating power.

[0051] Specifically, the environmental control equipment is air conditioning, cooling equipment, etc. The walls of the warehouse are in contact with the outside world. When the temperature inside the warehouse is lower than the outside temperature, heat loss will occur due to heat dissipation. When the temperature difference between the inside and outside of the warehouse is large, there will be a large heat loss. In order to ensure the target temperature in the warehouse, the environmental control equipment needs a larger operating power. When the temperature difference between the inside and outside of the warehouse is small, the heat loss is small, and the environmental control equipment needs a smaller operating power to maintain the target temperature in the warehouse.

[0052] To achieve the above target temperature, the operating power of the environmental control equipment is PW, and the heat load generated is HL1, HL1=W×C1, where W is the adjustment coefficient and C1 is the cooling capacity provided by the environmental control equipment under the operating power PW; when the warehouse door is not opened, the first heat loss caused by heat exchange between the inside and outside of the warehouse is HL2, HL2=T D ×W H ×S W , where T D is the above temperature difference, W H is the heat loss coefficient of the warehouse exterior wall, S W is the outer wall area of ​​the warehouse. To maintain the temperature in the warehouse, HL1 needs to be greater than or equal to HL2. The first adjustment coefficient W1 is further derived as the ratio of the heat loss HL2 to C1.

[0053] The operating power of the environmental control equipment in the entire warehouse is controlled based on the external temperature, which achieves precise control of equipment operation, improves the accuracy of environmental regulation, and avoids unnecessary energy waste.

[0054] Preferably, the environmental equipment mapping table is searched based on the inventory and the target environmental parameters, the maximum weight value corresponding to the inventory is extracted and defined as the third reference weight, the equipment operating parameters corresponding to the third reference weight are used as target operating parameters, and the operating power of the environmental control equipment required to reach the above-mentioned target temperature is calculated based on the target operating parameters.

[0055] Specifically, the above target operating parameters include (current, voltage, vibration frequency, etc.).

[0056] Step 4: Periodically collect the current environmental data in the warehouse, extract any current environmental data, define it as the first data, determine whether the first data is within the corresponding preset range, and if so, perform error compensation on the first data to generate new environmental data. After traversing all current environmental data, generate corrected environmental data.

[0057] Specifically, due to the physical characteristics and working principle of environmental monitoring equipment, it exhibits nonlinear characteristics within certain measurement ranges. Nonlinear characteristics mean that the output and input of the sensor are not in a simple linear relationship, resulting in errors between the detected data and the actual value. When the environmental data monitored by the environmental monitoring equipment is within its corresponding preset range, these errors can be reduced and the accuracy of the data can be improved through correction.

[0058] Step 5: Search the storage status mapping table based on the corrected environmental data, extract the maximum weight value corresponding to the corrected environmental data, define it as the second reference weight, take the storage status corresponding to the second reference weight as the target storage status, and determine whether there is an abnormality in the corrected environmental data based on the target storage status. If so, adjust the environmental control equipment.

[0059] Specifically, the storage status includes normal, high temperature, high humidity, high temperature and humidity, etc. The internal environment of the warehouse is relatively complex. The change of a certain environmental parameter may also be caused by other environmental parameters. Machine learning of historical data (such as through a neural network model) can quantify the relationship between environmental data and storage status through weights. Exemplarily, the environmental parameter is B3, which corresponds to two storage states C1 and C2. The weight value of C1 is 0.9, and the weight value of C2 is 0.3. Then C1 is defined as the target storage state. If the above-mentioned corrected environmental data does not exist in the storage state mapping table, the target storage state is obtained based on the historical environmental data with the greatest similarity to the corrected environmental data.

[0060] Obtaining the storage status through the storage status mapping table can comprehensively consider multiple factors and reduce misjudgments. It is also highly interpretable and can determine whether there are abnormalities in the storage environment even if there is a lack of experience.

[0061] Specifically, when the corrected environmental data indicates that there is an abnormality in the storage environment, the operating power, wind force or wind direction, etc. of the environmental control equipment are adjusted according to the corrected environmental data.

[0062] In a specific embodiment, step 3 also includes: when the warehouse door is opened, obtaining the exposed area of ​​the warehouse, executing a second predetermined algorithm on the exposed area and the temperature difference, obtaining the second adjustment coefficient of the environmental control device, defining the sum of the first adjustment coefficient and the second adjustment coefficient as a third adjustment coefficient, calculating the second operating power of the environmental control device based on the third adjustment coefficient, and controlling the environmental control device to operate according to the second operating power.

[0063] Specifically, opening the warehouse door will also cause heat exchange between the inside and outside of the warehouse, resulting in heat loss inside the warehouse. The second heat loss caused is HL3, HL3=TD×SE, where SE is the exposed area of ​​the warehouse, and the second adjustment coefficient is the ratio of the heat loss HL3 to C1.

[0064] The technical solution of the present invention not only takes into account the external temperature changes, but also takes into account the impact of the opening of the warehouse door on the environment, making the environmental regulation more comprehensive and accurate; dynamically adjusts the operating power of the environmental control equipment according to actual conditions, avoids temperature fluctuations caused by the opening of the warehouse door, and improves the stability and reliability of environmental regulation.

[0065] In a specific embodiment, the time interval for collecting environmental data in the warehouse is adjusted based on environmental disturbance factors, including: real-time monitoring of the environmental disturbance factors in the warehouse, when the environmental disturbance factors change, calculating the disturbance intensity within a first preset time, and adjusting the time interval according to preset rules based on the disturbance intensity.

[0066] Specifically, the above-mentioned environmental disturbance factors include access control status and / or inventory. When the warehouse door is opened, it will cause heat loss inside the warehouse and change the environment inside the warehouse; the items in the warehouse will undergo physical or chemical changes, which will also affect the environment inside the warehouse. The amount of inventory is directly related to the magnitude of the impact. Exemplarily, when the warehouse door is opened, the number of times the warehouse door is opened within a first preset time (such as 2 hours) is calculated, and the number is used as the disturbance intensity value; when goods are stored or taken out, the amount of goods in the warehouse after the first preset time (such as 10 minutes) is calculated, and the amount of goods is used as the disturbance intensity value.

[0067] Dynamically adjusting the data collection time interval based on environmental disturbance factors can improve the system's response speed and adaptability, ensure the safe storage of items, and improve warehouse management level.

[0068] In a specific embodiment, when the disturbance intensity increases, the time interval is reduced according to a first preset ratio; when the disturbance intensity decreases, the time interval is increased according to a second preset ratio.

[0069] Specifically, when the intensity of environmental disturbance is low, the time interval for data collection is appropriately increased according to a preset ratio to reduce unnecessary data collection and processing, thereby saving computing resources and energy consumption; when the intensity of environmental disturbance is high, the time interval for data collection is appropriately reduced according to a preset ratio, so that the environmental monitoring equipment can measure changes in environmental conditions without omissions.

[0070] In a specific embodiment, the remaining power of all environmental monitoring devices is obtained, and the time interval for data collection is adjusted based on the above-mentioned disturbance intensity and the remaining power of the environmental monitoring devices.

[0071] Exemplarily, when the environmental disturbance factor is the access control status and the disturbance intensity is 5 times and the remaining power of the environmental monitoring device is 90%, the time interval is set to 10 minutes; when the remaining power of the environmental monitoring device is 70%, the time interval is set to 15 minutes.

[0072] The technical solution of the present invention accurately controls the data collection frequency so that the system can respond quickly when the environment changes, while reducing unnecessary data collection when the environment is stable, thereby improving the overall stability of the system and extending the life of the environmental monitoring equipment.

[0073] In a specific embodiment, performing error compensation on the first data in step 4 to generate new environmental data includes:

[0074] Step 41: extract historical environmental data corresponding to the first data within a second preset time, combine the historical environmental data and the first data to generate an environmental data sequence, and convert the environmental data sequence into a preset numerical type to obtain a first data sequence.

[0075] Step 42: Perform spatial transformation operation on the first data sequence through the first transformation module to generate linear transformation data. At the same time, execute the third predetermined algorithm on the first data sequence through the second transformation module to obtain the prediction value corresponding to the first data.

[0076] Step 43, perform preset periodic function calculation on the transformed data and the predicted value, obtain the adjustment value, feed back the adjustment value to the first transformation module and the second transformation module, and return to step 42, repeating steps 42 to 43 until the transformed data and the predicted value converge.

[0077] Step 44: Correct the first data based on the transformed data and the predicted value to generate new environmental data.

[0078] The flowchart of the new environmental data generation method is as follows Figure 2 shown.

[0079] Specifically, the preset data type is a floating point type data, so as to perform subsequent mathematical operations. In the second transformation module, the prediction value corresponding to the first data is estimated by least square method, moving average filtering, Euler integration or Kalman filtering. The preset periodic function is a sine function, a cosine function, a tangent function, a cotangent function, a secant function or a cosecant function.

[0080] In a specific embodiment, in step 42, performing a spatial transformation operation on the first data sequence by a first transformation module to generate linear transformation data includes:

[0081] A nonlinear function of the environmental monitoring device corresponding to the first data is obtained, a first-order partial derivative matrix is ​​constructed based on the nonlinear function, and the first data sequence is multiplied by the first-order partial derivative matrix to generate transformed data.

[0082] Specifically, the nonlinear function of the environmental monitoring equipment is constructed based on its performance and characteristics, and is used to describe the relationship between the detected data and the actual physical quantity. A first-order partial derivative matrix is ​​constructed based on the nonlinear function, and the nonlinear system relationship is linearized through differential operations. The first-order partial derivative matrix is ​​a Jacobian matrix, and the order of the matrix is ​​consistent with the number of data in the first data sequence. Exemplarily, the first data sequence contains 3 values, and the first-order partial derivative matrix is ​​a 3rd-order matrix.

[0083] For example, taking a temperature sensor as an example, the nonlinear function may be a polynomial function: , find the first-order partial derivative of the nonlinear function, and the constructed first-order partial derivative matrix is Assume that a is 0.1, b is 0.2, and the first data sequence is 22, 22.5, 24, where 24 is the first data. The transformed data obtained by the first transformation module is , the predicted value corresponding to the first data obtained by the second transformation module is 23. Then, the sine function calculation is performed on the transformation data and the predicted value respectively (the transformation data and the predicted value are respectively used as the input values ​​of the sine function), the results after the sine function calculation are multiplied, and the first adjustment value is obtained (the first adjustment value is a matrix at this time), and the average value of each value on the diagonal of the first adjustment value is used as the adjustment value, and it is fed back to the first transformation module and the second transformation module.

[0084] Exemplarily, the transformed data after convergence is , the predicted value is 23. Calculate the trace of the transformed data (14.3) and the difference between the predicted value and the first data (1), use the ratio of the difference to the trace (1 / 14.3) as the error weight, and use the sum of the predicted value and the error weight (23.1) as the new environmental data.

[0085] The technical solution of the present invention linearizes nonlinear data in a local area through a first transformation module, calculates the predicted value at the current moment through a second transformation module, estimates the dynamic change trend of the data, and then dynamically adjusts parameters according to the state (such as temperature) through a preset periodic function to compensate for nonlinear characteristics. Finally, the data, predicted value and detected value are comprehensively transformed to eliminate nonlinear errors and output accurate correction results, which can effectively solve the complexity of nonlinear data correction and improve the accuracy and reliability of data.

[0086] In a specific embodiment, adjusting the device operating parameters of the environment control device based on the moving object includes:

[0087] (1) Monitor in real time whether there are moving objects in the warehouse. If there are, identify the area where the moving objects are located and define it as the target area.

[0088] (2) extracting the maximum temperature and the minimum humidity from the target environmental parameters, adjusting the equipment operating parameters of the first environmental control device based on the maximum temperature and the minimum humidity, and adjusting the blowing mode of the first environmental control device, wherein the first environmental control device is the environmental control device corresponding to the target area.

[0089] Specifically, sensors (such as cameras, infrared sensors, lidar, etc.) are used to monitor in real time whether there are moving objects (such as people or transport machinery) in the warehouse. If a moving object is detected, the area where it is located is identified and defined as the target area. The above-mentioned moving objects are people or transport machinery, etc. When the moving object is a person, the temperature and humidity in the warehouse are too low, which will cause discomfort. When the moving object is a transport machinery, the humidity is too high, which will cause corrosion of the equipment and performance degradation. When the moving object enters the warehouse, the equipment operating parameters of the environmental control equipment in the area where it is located are adjusted based on the target environmental parameters, which can improve the comfort and safety of the moving object while ensuring that the environmental conditions in the target area are always in the best state.

[0090] In a specific embodiment, adjusting the blowing mode of the first environmental control device includes:

[0091] (1) Obtain the positions of the first environmental control device, the mobile object, and all items in the target area, identify a reference plane perpendicular to the ground where the first environmental control device and the mobile object are located, and obtain items that are not located on the reference plane, which are defined as first items.

[0092] (2) Obtaining the surface temperatures of all first objects, defining the object corresponding to the maximum surface temperature as a selected object, and controlling the first environmental control device to blow air toward the selected object.

[0093] Specifically, the objects on the reference plane are all located on the horizontal line between the first environmental control device and the moving object. If air is blown towards these objects, the moving object will be affected (the human body feels cold and the moisture contacted by mechanical equipment increases). Blowing air towards the selected objects corresponding to the maximum surface temperature can quickly reduce the temperature of the selected objects while increasing the comfort and safety of the moving objects.

[0094] The beneficial effects of the technical solution of the present invention are verified from five aspects: environmental adjustment accuracy, energy efficiency, abnormal response speed, data accuracy and comprehensive benefits.

[0095] (1) Environmental adjustment accuracy experiment

[0096] Experimental design: a. Three warehouses of the same specifications (1000 m³) were selected, and the traditional method, the existing IoT method and the method of this application were used respectively; b. Storage items: fresh fruits and vegetables (the most stringent storage conditions: temperature 2±0.5℃, humidity 70±5%); c. The monitoring period was 7 days (168 hours).

[0097] The result data is as follows:

[0098] Conclusion: Through error compensation and target parameter optimization, the proposed method can improve the environmental parameter compliance rate by 12.7-30.1 percentage points and reduce the average deviation by 40-75%.

[0099] (2) Energy efficiency comparison experiment

[0100] Experimental design: a. Same external conditions (average daily temperature difference of 10°C); b. The warehouse door is opened 8 times a day, each time for 5 minutes; c. The energy consumption of environmental control equipment (air conditioning) is monitored.

[0101] The result data is as follows:

[0102] Conclusion: The dynamic power regulation and exposed area compensation algorithm of this application can save an additional 20.1% energy compared with the existing IoT method and 37.1% energy compared with the traditional method.

[0103] (3) Abnormal response speed test

[0104] Experimental design: a. Simulate abnormal opening of the warehouse door (30 minutes); b. Monitor system response time and environmental recovery time.

[0105] The result data is as follows:

[0106] Conclusion: The disturbance intensity monitoring and adaptive sampling interval of this application improve the response speed by 67-87% and significantly reduce the impact of abnormalities.

[0107] (4) Data accuracy verification

[0108] Experimental design: a. Under a known standard environment (25.0℃, 50.0%); b. Compare the sensor data correction effects of different methods.

[0109] The result data is as follows:

[0110] Conclusion: The nonlinear correction algorithm of this application improves data accuracy by about 80%, which is significantly better than other methods.

[0111] (5) Comprehensive benefit analysis

[0112] Long-term operation data (6 months):

[0113] Conclusion: The technology in this application shows significant advantages in terms of item preservation, equipment maintenance and operating costs, and the overall energy efficiency ratio is improved by 35-83%.

[0114] The above experimental data confirm that the logistics warehousing environment adjustment method based on the Internet of Things described in this application has significant advantages in adjustment accuracy, energy efficiency, response speed and data accuracy, and can realize intelligent and precise warehousing environment management.

[0115] The above describes the logistics warehousing environment adjustment method based on the Internet of Things in the embodiment of the present application. The following describes the logistics warehousing environment adjustment system based on the Internet of Things in the embodiment of the present application. Figure 3 In the embodiment of the present application, an embodiment of the logistics warehousing environment adjustment system based on the Internet of Things includes: a data acquisition module 10, a parameter setting module 20, a device control module 30, a data acquisition module 40 and an environment adjustment module 50.

[0116] The data acquisition module 10 is used to acquire the types of items in the warehouse, identify the quality attributes of all items, and set the maximum value of the quality attribute as the reference attribute.

[0117] The parameter setting module 20 is used to search the object environment mapping table according to the object type and reference attribute, extract the maximum weight value corresponding to the reference attribute, define it as the first reference weight, and use the environment parameter corresponding to the first reference weight as the target environment parameter.

[0118] The device control module 30 is used to periodically collect external temperature data, calculate the temperature difference between the external temperature data and the target temperature data, execute a first predetermined algorithm on the temperature difference, obtain a first adjustment coefficient of the environmental control device, calculate a first operating power of the environmental control device based on the first adjustment coefficient, and control the environmental control device to operate according to the first operating power.

[0119] The data acquisition module 40 is used to periodically collect the current environmental data in the warehouse, extract any current environmental data, define it as the first data, and determine whether the first data is within the corresponding preset range. If so, perform error compensation on the first data to generate new environmental data. After traversing all the current environmental data, the corrected environmental data is generated.

[0120] The environmental adjustment module 50 is used to search the storage status mapping table according to the corrected environmental data, extract the maximum weight value corresponding to the corrected environmental data, define it as the second reference weight, take the storage status corresponding to the second reference weight as the target storage status, and judge whether there is an abnormality in the corrected environmental data based on the target storage status. If so, adjust the environmental control equipment.

[0121] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0122] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0123] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A logistics warehousing environment adjustment method based on the Internet of Things, characterized in that: The method comprises: Step 1: Obtain the types of items in the warehouse, identify the quality attributes of all items, and set the maximum value of the quality attribute as the reference attribute; Step 2: search the item environment mapping table based on the item type and the reference attribute, extract the maximum weight value corresponding to the reference attribute, define it as the first reference weight, and use the environment parameter corresponding to the first reference weight as the target environment parameter; Step 3: periodically collect external temperature data, calculate the temperature difference between the external temperature data and the target temperature data, execute a first predetermined algorithm on the temperature difference, obtain a first adjustment coefficient of the environmental control device, calculate a first operating power of the environmental control device based on the first adjustment coefficient, and control the environmental control device to operate according to the first operating power; Step 4: Periodically collect the current environment data in the warehouse, extract any current environment data, define it as the first data, determine whether the first data is within the corresponding preset range, and if so, perform error compensation on the first data to generate new environment data, and after traversing all the current environment data, generate the corrected environment data; Step 5: Search the storage status mapping table based on the corrected environmental data, extract the maximum weight value corresponding to the corrected environmental data, define it as the second reference weight, take the storage status corresponding to the second reference weight as the target storage status, and determine whether there is an abnormality in the corrected environmental data based on the target storage status. If so, adjust the environmental control equipment.

2. The method for adjusting the logistics storage environment based on the Internet of Things according to claim 1 is characterized in that: The step 3 also includes: when the warehouse door is opened, obtaining the exposed area of ​​the warehouse, executing a second predetermined algorithm on the exposed area and the temperature difference, obtaining the second adjustment coefficient of the environmental control device, defining the sum of the first adjustment coefficient and the second adjustment coefficient as a third adjustment coefficient, calculating the second operating power of the environmental control device based on the third adjustment coefficient, and controlling the environmental control device to operate according to the second operating power.

3. The method for adjusting the logistics storage environment based on the Internet of Things according to claim 1 is characterized in that: Adjusting the time interval for collecting environmental data in the warehouse based on environmental disturbance factors includes: real-time monitoring of the environmental disturbance factors in the warehouse, calculating the disturbance intensity within a first preset time when the environmental disturbance factors change, and adjusting the time interval according to preset rules based on the disturbance intensity.

4. The method for adjusting the logistics storage environment based on the Internet of Things according to claim 3 is characterized in that: When the disturbance intensity increases, reducing the time interval according to a first preset ratio; When the disturbance intensity decreases, the time interval is increased according to a second preset ratio.

5. The method for adjusting the logistics warehousing environment based on the Internet of Things according to claim 1 is characterized in that: In step 4, performing error compensation on the first data to generate new environmental data includes: Step 41: extract historical environmental data corresponding to the first data within a second preset time, combine the historical environmental data and the first data to generate an environmental data sequence, and convert the environmental data sequence into a preset numerical type to obtain a first data sequence; Step 42: Perform a spatial transformation operation on the first data sequence through a first transformation module to generate linear transformation data, and at the same time, perform a third predetermined algorithm on the first data sequence through a second transformation module to obtain a prediction value corresponding to the first data; Step 43, performing a preset periodic function calculation on the transformed data and the predicted value to obtain an adjustment value, feeding the adjustment value back to the first transformation module and the second transformation module, and returning to step 42, repeating steps 42 to 43 until the transformed data and the predicted value converge; Step 44: Correct the first data based on the transformed data and the predicted value to generate new environmental data.

6. The method for adjusting the logistics storage environment based on the Internet of Things according to claim 5 is characterized in that: In step 42, performing a spatial transformation operation on the first data sequence by a first transformation module to generate linear transformation data includes: Acquire a nonlinear function of the environmental monitoring device corresponding to the first data, construct a first-order partial derivative matrix based on the nonlinear function, multiply the first data sequence by the first-order partial derivative matrix, and generate the transformed data.

7. The method for adjusting the logistics storage environment based on the Internet of Things according to claim 1 is characterized in that: Adjusting the device operating parameters of the environment control device based on the moving object includes: Real-time monitoring of whether there are moving objects in the warehouse. If there are, the area where the moving objects are located is identified and defined as the target area; Extract the maximum temperature and minimum humidity in the target environmental parameters, adjust the device operating parameters of the first environmental control device based on the maximum temperature and the minimum humidity, and adjust the blowing mode of the first environmental control device, wherein the first environmental control device is the environmental control device corresponding to the target area.

8. The method for adjusting the logistics storage environment based on the Internet of Things according to claim 7 is characterized in that: The adjusting the blowing mode of the first environmental control device comprises: Acquire the positions of the first environment control device, the mobile object, and all items in the target area, identify a reference plane perpendicular to the ground where the first environment control device and the mobile object are located, and acquire items that are not located on the reference plane, which are defined as first items; The surface temperatures of all first objects are obtained, the objects corresponding to the maximum surface temperatures are defined as selected objects, and the first environmental control device is controlled to blow air toward the selected objects.

9. The logistics warehousing environment adjustment system based on the Internet of Things is characterized by: The system includes: a data acquisition module, a parameter setting module, an equipment control module, a data collection module and an environment adjustment module; The data acquisition module is used to acquire the types of items in the warehouse, identify the quality attributes of all items, and set the maximum value of the quality attribute as the reference attribute; The parameter setting module is used to search the item environment mapping table according to the item type and the reference attribute, extract the maximum weight value corresponding to the reference attribute, define it as a first reference weight, and use the environment parameter corresponding to the first reference weight as the target environment parameter; The device control module is used to periodically collect external temperature data, calculate the temperature difference between the external temperature data and the target temperature data, execute a first predetermined algorithm on the temperature difference, obtain a first adjustment coefficient of the environment control device, calculate a first operating power of the environment control device based on the first adjustment coefficient, and control the environment control device to operate according to the first operating power; The data acquisition module is used to periodically collect current environmental data in the warehouse, extract any current environmental data, define it as first data, determine whether the first data is within the corresponding preset range, and if so, perform error compensation on the first data to generate new environmental data, and generate corrected environmental data after traversing all current environmental data; The environmental adjustment module is used to search the storage status mapping table according to the corrected environmental data, extract the maximum weight value corresponding to the corrected environmental data, define it as the second reference weight, take the storage status corresponding to the second reference weight as the target storage status, and judge whether there is an abnormality in the corrected environmental data based on the target storage status. If so, adjust the environmental control equipment.

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