Packaging method and system for garment processing based on Internet of Things control
Through the Internet of Things-controlled clothing processing and packaging method, weight set analysis and image recognition technology are used to solve the problem of weight inaccurate in traditional packaging methods, accurate packaging and abnormal detection are achieved, and product quality and inventory management efficiency are improved.
Patent Information
- Application Number
- CN202510508304.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-22
- Publication Date
- 2025-07-08
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
During the process of clothing processing, traditional packaging methods cannot accurately know the weight of each garment, resulting in mispacking and missing packaging, affecting product quality, and the express bag blocks the field of view, making it impossible to judge the correctness of packaging.
Through IoT control, we obtain customer order information, analyze clothing weight collection, combine historical packaging data and image recognition, predict packaging bag weight, set weight deviation values, and detect clothing weight deviations in real time to ensure packaging accuracy.
It realizes precise control of the weight of clothing packaging, timely discover abnormalities, avoid misinstallation or misinstallation, ensure product quality, improve customer satisfaction and optimize inventory management.
Smart Images
Figure CN120270592A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of clothing packaging management, and specifically, to a packaging method and system for clothing processing based on Internet of Things control. Background Art
[0002] In the e-commerce era, many factories cooperate with express delivery parties to start e-commerce operations. The factories pack the products independently and then the express delivery parties pick them up for transportation, so that the clothing is already packaged for express delivery when it leaves the factory. Currently, most of the clothing processing and packaging work in factories is carried out in the traditional production workshop environment. Generally, workers take the corresponding clothing according to the order requirements for packaging and sending. However, in the process of batch packaging, due to the inability to accurately know the weight of each piece of clothing, it is easy to have the situations of mis-packaging and missing packaging, mixing clothing of different weight specifications, which affects the product quality and often leads to the situation of wrong product delivery in the market. At the same time, express delivery bags are generally disposable and dark in color, which causes visual obstruction to the internal clothing, resulting in the inability to judge the correctness of packaging based on external observation after packaging. Therefore, a packaging method and system for clothing processing based on Internet of Things control are proposed. Summary of the Invention
[0003] The purpose of the present invention is to provide a packaging method and system for clothing processing based on Internet of Things control to solve the problems raised in the above background art.
[0004] To achieve the solution of the above technical problems, one of the purposes of the present invention is to provide a packaging method for clothing processing based on Internet of Things control, including the following steps: S1. Obtain customer order information and extract clothing style and size requirements according to the customer order information; S2. Collect clothing processing data, and at the same time screen the clothing processing data online according to the clothing stored in the warehouse, and analyze the clothing weight sets of different clothing styles and different sizes according to the online clothing processing data; S3. Send the data obtained in S1 and S2 to the packaging inspection device through the Internet of Things, and at the same time obtain historical packaging data in the packaging inspection device, and analyze the weight range of the packaging bag according to the historical packaging data combined with the corresponding clothing weight set; S4. Collect the real-time packaging data of the clothing, and at the same time determine the customer to which it belongs. Predict the weight of the packaging bag according to the real-time packaging data combined with the weight range analysis of the packaging bag and image recognition, and extract the real-time clothing weight by combining the predicted packaging bag weight with the real-time packaging data; S5. Set the weight deviation value according to the predicted weight of the packaging bag, combine the real-time clothing weight with the weight deviation value to predict the weight of the packaging bag and calculate the deviation of the clothing weight set. When the calculation result fails to match in the clothing weight set, an abnormal packaging will be displayed through the packaging inspection device.
[0005] As a further improvement of this technical solution, in S1, a data connection is established between the packaging inspection device, the factory production device, and the sales order management terminal through the Internet of Things, enabling data sharing among packaging, production, and sales.
[0006] As a further improvement of this technical solution, the steps of S1 are as follows: S1.1. When a new sales order is added to the sales order management terminal, extract the new sales order in real time to obtain the customer order information of this sales order. S1.2. Extract the customer delivery address, clothing style, size requirements, and other remarks according to the customer order information.
[0007] As a further improvement of this technical solution, the steps of S2 are as follows: S2.1. Collect clothing processing data through factory production equipment, and at the same time obtain the current quantity of clothing stored in the factory warehouse. Combine each piece of stored clothing with the clothing processing data for corresponding online allocation. According to the allocation result, use the clothing processing data corresponding to the stored clothing as online clothing processing data, and use the clothing processing data of the stored clothing that fails to match successfully as historical clothing processing for reference. S2.2. Analyze the clothing weight sets of different clothing styles and different sizes according to the online clothing processing data to obtain the clothing weight sets corresponding to different clothing styles and different sizes in the warehouse.
[0008] As a further improvement of this technical solution, when collecting clothing processing data in S2.1, the clothing processing data includes clothing processing styles, clothing processing sizes, and weight data obtained by weighing after the clothing production is completed. Data of each piece of clothing is recorded through factory production equipment during the production process and uploaded through the Internet of Things.
[0009] As a further improvement of this technical solution, the steps of S3 are as follows: S3.1. Send the customer order information and clothing-related information to the packaging inspection device through the Internet of Things, enabling the packaging inspection device to generate a to-be-inspected link according to the customer order information until the clothing corresponding to this customer order information passes the packaging inspection, and then adjust the to-be-inspected link generated by the packaging inspection device this time to passed. S3.2. Extract the historical packing data recorded by the packing inspection device for passed packing, screen the historical packing data in combination with the clothing styles and sizes corresponding to the customer information, and then perform subtraction calculations by combining the screened historical packing data with the corresponding clothing weight data uploaded by the factory production equipment to obtain the weight of the packaging bag corresponding to each packed clothing, and summarize it as the packaging bag weight range.
[0010] As a further improvement of this technical solution, the steps of S4 are as follows: S4.1. Collect the real-time packing data of the clothing. At the same time, determine the customer to which the clothing belongs according to the real-time packing data, and then perform image recognition on the packaging bag size based on the real-time packing data to obtain the image data of the clothing packed this time. S4.2. Perform similarity analysis on the image data of the clothing packed this time in combination with the image data in the historical data of the same style and size, and select the packaging bag with the highest similarity to extract the corresponding weight within the packaging bag weight range as the predicted packaging bag weight. S4.3. Extract the real-time clothing weight by combining the predicted packaging bag weight with the real-time packing data to obtain the real-time clothing weight corresponding to the clothing packed this time minus the predicted packaging bag weight.
[0011] As a further improvement of this technical solution, the steps of S5 are as follows: S5.1. Set the weight deviation value according to the image difference rate between the predicted packaging bag weight and the packaging bag with the highest corresponding similarity. The larger the image difference rate, the higher the weight deviation value. Conversely, the smaller the image difference rate, the lower the weight deviation value. S5.2. Perform subtraction calculations by combining the real-time clothing weight, the weight deviation value, and the predicted packaging bag weight, and then perform deviation calculations by combining the calculation results with the clothing weight set. When the calculation results fail to match in the clothing weight set, the packing inspection device displays abnormal packing to remind the staff to check. Conversely, when the calculation results match successfully in the clothing weight set, the packing inspection device displays that the packing has passed, and the successfully matched value is deleted from the clothing weight set.
[0012] The second object of the present invention is to provide a packing system for clothing processing based on Internet of Things control, including a packing method for clothing processing based on Internet of Things control as described in any one of the above, including a basic data acquisition module, a weight calculation module, and a packing inspection module; The basic data acquisition module is used to obtain customer order information, extract clothing style and size requirements according to the customer order information, collect clothing processing data, and at the same time perform online screening on the clothing processing data according to the clothing stored in the warehouse, and perform clothing weight set analysis for different clothing styles and different sizes according to the online clothing processing data. The weight calculation module is used to obtain historical packing data in the packing inspection device, analyze the weight range of the packaging bag according to the historical packing data combined with the corresponding clothing weight set, collect the real-time packing data of the clothing, and determine the customer to which it belongs at the same time. According to the real-time packing data, combined with the weight range analysis of the packaging bag and image recognition, predict the weight of the packaging bag, and extract the real-time clothing weight by combining the predicted packaging bag weight with the real-time packing data; The packing inspection module is used to set a weight deviation value according to the predicted packaging bag weight, calculate the deviation by combining the real-time clothing weight, the weight deviation value, the predicted packaging bag weight and the clothing weight set. When the calculation result fails to match in the clothing weight set, display abnormal packing through the packing inspection device.
[0013] Compared with the prior art, the beneficial effects of the present invention are: 1. A packing method and system for clothing processing based on Internet of Things control. By comprehensively collecting clothing processing data, covering styles, sizes and weights, and combining with the clothing stored in the warehouse for online screening, deeply analyzing the weight sets of different styles and sizes of clothing. In the packing inspection link, use historical packing data and clothing weight set to determine the weight range of the packaging bag, then predict the weight of the packaging bag through real-time packing data and image recognition, and then accurately extract the real-time clothing weight. This series of operations can accurately control the packing weight of clothing, timely detect weight abnormalities, avoid mispacking and missing packing, ensure product quality, and improve customer satisfaction.
[0014] 2. A packing method and system for clothing processing based on Internet of Things control. By setting a weight deviation value according to the image difference rate between the predicted packaging bag weight and the packaging bag with the highest similarity, comprehensively calculate and compare the real-time clothing weight, the weight deviation value, the predicted packaging bag weight and the clothing weight set. When the calculation result exceeds the acceptable deviation range of the clothing weight set, it is determined as abnormal packing and prompt the staff to handle it. This intelligent judgment mechanism can timely detect packing abnormalities, ensure the stability of product quality, optimize inventory management at the same time, reasonably control the inventory level, and reduce the operation cost of the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] Figure 1 is the overall flow block diagram of the present invention; Figure 2 is the flow block diagram of the present invention for obtaining the customer order information of the sales order; Figure 3 is the flow block diagram of the present invention for obtaining the clothing weight sets corresponding to different clothing styles and different sizes in the warehouse; Figure 4 is the flow block diagram of the present invention for summarizing the weight range of the packaging bag; Figure 5It is a flowchart for the present invention to obtain the image data of the packaged clothing this time; Figure 6 It is a flowchart for the present invention to set the weight deviation value. Detailed implementation manners
[0016] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
[0017] As Figure 1 - Figure 6 shown, one of the purposes of the present invention is to provide a packaging method for clothing processing based on Internet of Things control, including the following steps: S1. Obtain customer order information, and extract clothing style and size requirements according to the customer order information; S1 establishes a data connection between the packaging inspection device, the factory production device and the sales order management terminal through the Internet of Things, so that data sharing can be carried out for packaging, production and sales. The specific steps are as follows: Hardware device preparation and network construction: Equip the packaging inspection device with an Internet of Things communication module, such as a Wi-Fi module, a 4G / 5G module, etc., to ensure its ability to access the network. The factory production device also installs the corresponding Internet of Things communication module, and the server of the sales order management terminal also needs to have a network connection function, such as connecting to the enterprise internal local area network or accessing through the Internet; Internet of Things platform construction and configuration: Select an Internet of Things platform according to the enterprise, register an account on the platform, create corresponding projects and device groups, and develop data sharing interfaces at the same time, so that the packaging inspection device, the factory production device and the sales order management terminal can perform data interaction through the Internet of Things platform; Implementation of data interaction and sharing: When a new order is generated in the sales order management terminal, the order data is transmitted to the factory production device and the packaging inspection device in real time through the Internet of Things platform. The factory production device arranges production according to the order information and feeds back the production progress data to the sales order management terminal and the packaging inspection device.
[0018] The steps of S1 are as follows: S1.1. When a new sales order is added in the sales order management terminal, extract the new sales order in real time to obtain the customer order information of the sales order; Set an event listener in the sales order management terminal software to monitor the new order event. After the new order is monitored, immediately make a response and record the order-related information.
[0019] S1.2. Extract the customer's delivery address, clothing style, size requirements, and other remarks according to the customer order information.
[0020] According to the newly monitored order identifier, query the detailed information of the order from the database, and extract the customer order information from the query results, including fields such as the customer's delivery address, clothing style, size requirements, and other remarks.
[0021] S2. Collect clothing processing data, and at the same time perform online screening of the clothing processing data according to the clothing stored in the warehouse, and perform an analysis of the clothing weight sets of different clothing styles and different sizes according to the online clothing processing data; The steps of S2 are as follows: S2.1. Collect clothing processing data through the factory production equipment, and at the same time obtain the current quantity of clothing stored in the factory warehouse, and perform corresponding online allocation of each stored clothing in combination with the clothing processing data. According to the allocation results, the clothing processing data corresponding to the stored clothing is used as the online clothing processing data, and the clothing processing data of the stored clothing that fails to match successfully is used as the historical clothing processing for reference; When S2.1 collects clothing processing data, the clothing processing data includes the clothing processing style, clothing processing size, and weight data obtained by weighing after the clothing production is completed; Data of each piece of clothing is recorded through the factory production equipment during the production process and uploaded through the Internet of Things. The specific steps are as follows: Style and size recording: In each link of clothing processing, such as cutting and sewing, record the processing style and size information of the clothing by scanning the barcodes or QR codes on the clothing, or using RFID technology. For example, in the cutting link, the cutting machine can automatically identify the labels on the fabric to obtain the clothing style and size data; Obtaining weight data: After the clothing production is completed, use an electronic scale to weigh each piece of clothing, and associate the weight data with the style and size information of the clothing. The factory production equipment uploads the collected clothing processing data (style, size, weight) to the server through the Internet of Things; Obtaining the quantity of clothing in the warehouse: Use the factory's inventory management system to obtain the current quantity of clothing stored in the warehouse in real time. The inventory management system can update the inventory data through barcode scanning, RFID inventory counting, etc., and synchronize the inventory data in the inventory management system to the server for integration with the clothing processing data; Online allocation of clothing data: According to the style and size information of the clothing, set matching rules. For example, for clothing of the same style and size, associate their corresponding processing data, and then compare the style and size information of each stored clothing with the collected clothing processing data for online allocation; Take the clothing processing data corresponding to the successfully matched stored clothing as the online clothing processing data for subsequent production analysis and decision-making; Take the clothing processing data of the stored clothing that fails to match as historical clothing processing data for reference.
[0022] S2.2. Analyze the clothing weight sets of different clothing styles and different sizes according to the online clothing processing data, and obtain the clothing weight sets corresponding to different clothing styles and different sizes in the warehouse.
[0023] Group the online clothing processing data according to clothing style and clothing size. The purpose of grouping is to group the clothing data of the same style and size together for subsequent weight set analysis of each group. For each group, extract the weight data of all clothing in the group to form the clothing weight set corresponding to the style and size, and then store the obtained clothing weight sets of different clothing styles and different sizes. The formula is as follows: ; Among them, W(s, m) is the clothing weight set corresponding to clothing style s and clothing size m, d i is each data record, D is the set of online clothing processing data, s i is the clothing style, m i is the clothing size, w i is the clothing weight, S3. Send the data obtained in S1 and S2 to the packing and inspection device through the Internet of Things. At the same time, obtain the historical packing data in the packing and inspection device, and analyze the weight range of the packing bag according to the historical packing data combined with the corresponding clothing weight set; The steps of S3 are as follows: S3.1. Send both the customer order information and the clothing-related information to the packing and inspection device through the Internet of Things, so that the packing and inspection device generates a to-be-inspected link according to the customer order information until the clothing packing corresponding to the customer order information passes, and then adjust the to-be-inspected link generated by the packing and inspection device this time to passed; The packing and inspection device creates a corresponding to-be-inspected task according to the received customer order information. A to-be-inspected task table can be created in the local database to record the order ID, clothing information, inspection status, etc. The staff performs the clothing packing operation according to the to-be-inspected task and conducts quality inspection during the packing process. The inspection content includes whether the style, size, and quantity of the clothing are consistent with the order.
[0024] S3.2. Extract the historical packing data recorded by the packing inspection device for passed packings, screen the historical packing data in combination with the clothing styles and sizes corresponding to the customer information, and then perform subtraction calculations based on the screened historical packing data and the corresponding clothing weight data uploaded by the factory production equipment to obtain the weight of the packaging bag corresponding to each passed packing clothing, and summarize it as the packaging bag weight range; For the screened data, according to each record of passed packing, subtract the weight of the corresponding clothing from the total packing weight to obtain the weight of the packaging bag corresponding to each passed packing clothing; ; Among them, W bag is the weight of the packaging bag, W total is the total packing weight, and W clothing is the weight of the clothing; Summarize all the calculated packaging bag weights to obtain their minimum and maximum values as the packaging bag weight range.
[0025] S4. Collect the real-time packing data of the clothing, and at the same time determine the belonging customer. Predict the packaging bag weight based on the real-time packing data in combination with the analysis of the packaging bag weight range and image recognition, and extract the real-time clothing weight by combining the predicted packaging bag weight with the real-time packing data; The steps of S4 are as follows: S4.1. Collect the real-time packing data of the clothing, and at the same time determine the customer to which the clothing belongs according to the real-time packing data, and then perform image recognition on the packaging bag size based on the real-time packing data to obtain the image data of the clothing being packed this time; Install a weight sensor and an image acquisition device (such as an industrial camera) at the packing station. The weight sensor is used to measure the total weight after packing, and the industrial camera is used to take pictures of the packaging bag and the clothing. When performing the clothing packing operation, the image acquisition device and the weight sensor collect data in real time.
[0026] S4.2. Perform similarity analysis on the image data of the clothing being packed this time in combination with the image data in the historical data of the same style and size, and select the packaging bag with the highest similarity to extract the corresponding weight within the packaging bag weight range as the predicted packaging bag weight. The specific steps are as follows: Historical data acquisition: Retrieve the historical packing image data of clothing of the same style and size from the database. The database should store the clothing images and related packaging bag information from previous packings. Extract the features of the image data of the clothing being packed this time and the historical image data respectively, and use a suitable similarity measurement method (such as cosine similarity, Euclidean distance, etc.) to calculate the similarity between the image being packed this time and the historical image. The formula is as follows: ; Among them, K( ) is the cosine similarity, is the feature vector of the image packed this time, is the feature vector of the historical image.
[0027] Predict the weight of the packaging bag: According to the calculated similarity value, sort the historical image data, find the packaging bag with the highest similarity, and then within the known weight range of the packaging bag, find the weight value corresponding to the packaging bag with the highest similarity, and use it as the predicted weight of the packaging bag. For example, if the weight range of the packaging bag is stored in a list or a database table, obtain the corresponding weight by matching the information of the packaging bag with the highest similarity.
[0028] S4.3. Combine the predicted weight of the packaging table with the real-time packing data to extract the real-time clothing weight, and obtain the real-time clothing weight corresponding to subtracting the predicted weight of the packaging bag from the clothing packed this time. The formula is as follows: Among them, W sf is the real-time clothing weight, W zg is the total weight after packing in the real-time packing data, W yc is the predicted weight of the packaging bag; S5. Set the weight deviation value according to the predicted weight of the packaging bag, combine the real-time clothing weight with the weight deviation value, the predicted weight of the packaging bag and the clothing weight set for deviation calculation. When the calculation result fails to match in the clothing weight set, an abnormal packing is displayed through the packing inspection device.
[0029] The steps of S5 are as follows: S5.1. Set the weight deviation value according to the image difference rate between the predicted weight of the packaging bag and the packaging bag with the highest corresponding similarity; The greater the image difference rate, the higher the weight deviation value. On the contrary, the smaller the image difference rate, the lower the weight deviation value. According to the positive correlation between the image difference rate and the weight deviation value, establish a mapping rule. The specific formula is as follows: ; Among them, P is the image difference rate between the predicted packaging bag image and the packaging bag image with the highest similarity, c j is the j-th feature vector of the predicted packaging bag image, d j is the j-th feature vector of the packaging bag image with the highest similarity, and j is the number of feature vectors; ; Among them, P max is the maximum image difference rate, ΔW is the weight deviation value, and ΔW max is the maximum weight deviation value.
[0030] S5.2. Combine the real-time clothing weight with the weight deviation value to predict the packaging bag weight for subtraction calculation, and then combine the calculation result with the clothing weight set for deviation calculation. When the calculation result fails to match in the clothing weight set, the packaging inspection device will display abnormal packaging to remind the staff to check. Otherwise, when the calculation result matches successfully in the clothing weight set, the packaging inspection device will display that the packaging has passed, and the successfully matched value will be deleted from the clothing weight set; In the case of a small inventory quantity and a large difference in weight data, a deviation range can be added for matching operations. The steps are as follows: Compare the adjusted weight with each value in the clothing weight set, calculate the deviation, and determine whether the adjusted weight is within the acceptable deviation range of the clothing weight set, that is, perform the matching operation. If the adjusted weight is not within the acceptable deviation range of the clothing weight set, the packaging inspection device will display abnormal packaging to remind the staff to check. If the adjusted weight is within the acceptable deviation range of the clothing weight set, the packaging inspection device will display that the packaging has passed, and the successfully matched value will be deleted from the clothing weight set.
[0031] Another object of the present invention is to provide a clothing processing packaging system based on Internet of Things control, including a clothing processing packaging method based on Internet of Things control as described in any one of the above, including a basic data acquisition module, a weight calculation module, and a packaging inspection module; The basic data acquisition module is used to obtain customer order information, extract clothing style and size requirements according to the customer order information, collect clothing processing data, and at the same time perform online screening of the clothing processing data according to the clothing stored in the warehouse, and analyze the clothing weight sets of different clothing styles and different sizes according to the online clothing processing data; The weight calculation module is used to obtain historical packaging data in the packaging inspection device, analyze the packaging bag weight range according to the historical packaging data combined with the corresponding clothing weight set, collect the real-time packaging data of the clothing, and at the same time determine the customer to which it belongs. Predict the packaging bag weight according to the real-time packaging data combined with the packaging bag weight range analysis and image recognition, and extract the real-time clothing weight by combining the predicted packaging bag weight with the real-time packaging data; The packaging inspection module is used to set a weight deviation value according to the predicted packaging bag weight, and perform deviation calculation by combining the real-time clothing weight, the weight deviation value, the predicted packaging bag weight, and the clothing weight set. When the calculation result fails to match in the clothing weight set, the packaging inspection device will display abnormal packaging.
[0032] The foregoing has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and the above embodiments and the descriptions in the specification are only preferred examples of the present invention, and are not used to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of the present invention claimed is defined by the appended claims and their equivalents.
Claims
1. A packaging method for clothing processing based on Internet of Things control, characterized in that: It includes the following steps: S1. Obtain customer order information, and extract clothing style and size requirements according to the customer order information; S2. Collect clothing processing data, and at the same time screen the clothing processing data online according to the clothing stored in the warehouse, and analyze the clothing weight sets of different clothing styles and different sizes according to the online clothing processing data; S3. Send the data obtained in S1 and S2 to the packing inspection device through the Internet of Things. At the same time, obtain historical packing data in the packing inspection device, and analyze the packaging bag weight range according to the historical packing data combined with the corresponding clothing weight set; S4. Collect the real-time packing data of the clothing, and at the same time determine the belonging customer. Predict the packaging bag weight according to the real-time packing data combined with the packaging bag weight range analysis and image recognition, and extract the real-time clothing weight by combining the predicted packaging bag weight with the real-time packing data; S5. Set a weight deviation value according to the predicted packaging bag weight, and perform deviation calculation by combining the real-time clothing weight with the weight deviation value, the predicted packaging bag weight and the clothing weight set. When the calculation result fails to match in the clothing weight set, an abnormal packing will be displayed through the packing inspection device.
2. The packaging method for clothing processing based on Internet of Things control according to claim 1, wherein: In S1, a data connection is established between the packing inspection device, the factory production device and the sales order management terminal through the Internet of Things, so that data sharing can be carried out for packing, production and sales.
3. A packaging method for clothing processing based on Internet of Things control according to claim 1, characterized in that: The steps of S1 are as follows: S1.
1. When a new sales order is added to the sales order management terminal, extract the new sales order in real time to obtain the customer order information of the sales order; S1.
2. Extract the customer delivery address, clothing style, size requirements, and other remarks according to the customer order information.
4. A packing method for clothing processing based on Internet of Things control according to claim 1, characterized in that: The steps of S2 are as follows: S2.
1. Collect clothing processing data through factory production equipment, and at the same time obtain the current quantity of clothing stored in the factory warehouse. Combine each piece of stored clothing with the clothing processing data for corresponding online allocation. According to the allocation result, use the clothing processing data corresponding to the stored clothing as the online clothing processing data, and use the clothing processing data of the stored clothing that fails to match successfully as the historical clothing processing for reference; S2.
2. Analyze the clothing weight sets of different clothing styles and different sizes according to the online clothing processing data, and obtain the clothing weight sets corresponding to different clothing styles and different sizes in the warehouse.
5. A packing method for garment processing based on Internet of Things control according to claim 1, characterized in that: When collecting clothing processing data in S2.1, the clothing processing data includes the clothing processing style, clothing processing size, and weight data obtained by weighing after the clothing production is completed; Each piece of clothing records data through factory production equipment during the production process and uploads it through the Internet of Things.
6. A packing method for garment processing based on Internet of Things control according to claim 1, characterized in that: The steps of S3 are as follows: S3.
1. Send the customer order information and clothing-related information to the packing inspection device through the Internet of Things, so that the packing inspection device generates a to-be-inspected link according to the customer order information until the clothing corresponding to the customer order information passes the packing. Then, adjust the to-be-inspected link generated by the packing inspection device this time to passed; S3.
2. Extract the historical packing data recorded by the packing inspection device for passed packings, screen the historical packing data in combination with the clothing styles and sizes corresponding to the customer information, and then perform subtraction calculations based on the screened historical packing data and the corresponding clothing weight data uploaded by the factory production equipment to obtain the weight of the packaging bag corresponding to each passed packing clothing, and summarize it as the packaging bag weight range.
7. A packing method for garment processing based on Internet of Things control according to claim 1, characterized in that: The steps of S4 are as follows: S4.
1. Collect the real-time packing data of the clothing. At the same time, determine the customer to which the clothing belongs according to the real-time packing data, and then perform image recognition on the packaging bag size based on the real-time packing data to obtain the image data of the clothing packed this time. S4.
2. Perform similarity analysis on the image data of the clothing packed this time in combination with the image data in the historical data of the same style and size, and select the packaging bag with the highest similarity to extract the corresponding weight within the packaging bag weight range as the predicted packaging bag weight. S4.
3. Extract the real-time clothing weight by combining the predicted packaging bag weight with the real-time packing data to obtain the real-time clothing weight corresponding to the clothing packed this time minus the predicted packaging bag weight.
8. A packing method for clothing processing based on Internet of Things control according to claim 1, characterized in that: The steps of S5 are as follows: S5.
1. Set the weight deviation value according to the image difference rate between the predicted packaging bag weight and the packaging bag with the highest corresponding similarity. The larger the image difference rate, the higher the weight deviation value. Conversely, the smaller the image difference rate, the lower the weight deviation value. S5.
2. Perform subtraction calculations by combining the real-time clothing weight, the weight deviation value, and the predicted packaging bag weight, and then perform deviation calculations by combining the calculation results with the clothing weight set. When the calculation results fail to match in the clothing weight set, the packing inspection device will display an abnormal packing to remind the staff to check. Conversely, when the calculation results match successfully in the clothing weight set, the packing inspection device will display that the packing has passed, and the successfully matched value will be deleted from the clothing weight set.
9. A packing system for clothing processing based on Internet of Things control, which is used to implement a packing method for clothing processing based on Internet of Things control according to any one of claims 1-8, characterized in that: It includes a basic data acquisition module, a weight calculation module, and a packing inspection module. The basic data acquisition module is used to obtain customer order information, extract clothing style and size requirements according to the customer order information, collect clothing processing data, and at the same time perform online screening on the clothing processing data according to the clothing stored in the warehouse, and analyze the clothing weight set of different clothing styles and sizes according to the online clothing processing data. The weight calculation module is used to obtain historical packing data in the packing inspection device, analyze the packaging bag weight range according to the historical packing data in combination with the corresponding clothing weight set, collect the real-time packing data of the clothing, and at the same time determine the belonging customer. Predict the packaging bag weight according to the real-time packing data in combination with the packaging bag weight range analysis and image recognition, and extract the real-time clothing weight by combining the predicted packaging bag weight with the real-time packing data. The packing inspection module is used to set the weight deviation value according to the predicted packaging bag weight, perform deviation calculations by combining the real-time clothing weight, the weight deviation value, the predicted packaging bag weight, and the clothing weight set. When the calculation results fail to match in the clothing weight set, the packing inspection device will display an abnormal packing.