Food safety intelligent scale with infrared short waves and millimeter waves and operation mode

Abstract

The invention relates to a food safety intelligent scale with infrared short waves and millimeter waves and an operation mode. An infrared short wave device and a millimeter wave device are used for achieving nondestructive testing on food ingredients, freshness and safety. When the scale is used in a food acceptance check link, the scale not only can accurately record the weight, quantity and image information of food, but also can detect the maturity of vegetables and fruits, whether the interior of the food is rotted or not and the pesticide residue condition on the surface. The system is wide in application scene and suitable for various occasions such as school canteens, enterprise and public institution canteens, government agency canteens, social catering canteens, central kitchens and food supply chain enterprises. Through detailed data analysis of the vegetable food consumption, a using unit not only can better monitor fund expenditure, but also can optimize a purchase plan, improve the efficiency of a supply chain and adjust an internal consumption mode, and finally achieves the goals of cost saving and reasonable resource allocation.

Description

Technical Field

[0001] The invention belongs to the technical field of food safety acceptance equipment, and in particular relates to a food safety intelligent scale with infrared shortwave and millimeter wave and an operation method. Background Art

[0002] In today's era, modern logistics services are facing unprecedented demands and development backgrounds. With the continuous advancement of science and technology, logistics centers are undergoing a profound transformation, gradually moving from traditional management models to digital intelligence and digital governance. The past model that relied on a large amount of manpower management and strict control is gradually being replaced by more intelligent supervision methods. Some advanced logistics centers have begun to invest in the construction of intelligent food safety supervision systems, committed to realizing a comprehensive "human defense + technical defense" management system. In this management system, the food acceptance link is particularly important.

[0003] The existing technical solutions have some obvious shortcomings, as follows:

[0004] First, the existing smart scales have relatively simple functions, mainly limited to the two basic functions of weighing and taking pictures. This means that they can only record the weight, quantity and picture information of food. However, these devices cannot effectively monitor and manage the variety of dishes provided by suppliers. In addition, these smart scales cannot detect the maturity of vegetables and fruits, cannot identify whether the food has rotted inside, and cannot detect the pesticide residues on the surface of vegetables and fruits. The lack of these functions makes smart scales have great limitations in food safety and quality monitoring.

[0005] Second, in terms of data processing and analysis, existing smart scales also have obvious limitations. Although these devices can record and store data, they often lack the ability to conduct deep learning and big data analysis. This makes it impossible for the equipment to effectively monitor and manage the dishes provided by suppliers, and it is impossible to provide deeper data analysis and decision support. Therefore, the existing smart scales have relatively limited capabilities in data processing and analysis and cannot meet more complex needs.

[0006] Third, although existing smart scales are convenient in terms of weighing and recording, they are not convenient for statistical analysis. For example, it is not convenient for the user to conduct statistical analysis on the amount of vegetables and other foods used over a period of time, which leads to inaccurate monitoring of the user's funds. In addition, existing smart scales are unable to provide a comparison of the quality of food provided by various suppliers, and cannot provide users with a better selection strategy.

[0007] Fourth, previous smart scale equipment did not have complete purchase data records, which made it impossible for procurement managers to conduct multi-dimensional comparative analysis. Due to the lack of understanding of historical data, procurement managers could not accurately evaluate the performance of suppliers, nor provide data strategy support for subsequent procurement activities. This not only affected the accuracy of procurement decisions, but also increased the risks in the procurement process.

[0008] In summary, future smart scale equipment should develop in the direction of multi-functional integration, intelligence, enhanced data processing capabilities, and improved statistical analysis functions to meet the growing needs of food safety and quality monitoring and provide users with more comprehensive, safer, more convenient, and smarter solutions.

[0009] The existence of these problems has resulted in obvious deficiencies in the existing smart scale equipment in terms of food safety supervision, and further technological innovation and functional upgrades are urgently needed. Summary of the invention

[0010] In view of this, the present invention aims to solve the defects in the prior art and proposes a food safety intelligent scale with infrared shortwave and millimeter wave and its operation method. Its purpose is that in the food acceptance link, the scale can not only accurately record the weight, quantity and image information of the food, but also detect the maturity of vegetables and fruits, whether the food is rotten inside, and the pesticide residue on the surface. Through this equipment, modern logistics services can realize a digital and intelligent supervision model and build a full-range management system of "combining manual prevention with technical prevention". This has become a key measure to ensure food safety.

[0011] In order to achieve the above-mentioned object, the first aspect of the present invention provides a food safety intelligent scale with infrared shortwave and millimeter wave, which at least includes a base, a weighing platform, a pressure sensor, a supporting structure, a display device, an image acquisition device, an infrared shortwave device, a millimeter wave device and a main control circuit board; wherein

[0012] The weighing platform is located on the base; the pressure sensor is fixed between the base and the weighing platform, and the pressure sensor is responsible for converting the weight on the weighing platform into an electrical signal;

[0013] One end of the supporting structure is connected to one side of the base; the display device is directly or indirectly arranged on the supporting structure; the infrared shortwave device and the millimeter wave device are used to realize non-destructive detection of food ingredients, freshness and safety; the main control circuit board is placed inside the supporting structure; the pressure sensor, the display device, the image acquisition device, the external shortwave device, and the millimeter wave device are electrically connected to the active circuit board respectively.

[0014] Furthermore, it also includes a height-adjustable lifting rod, which is arranged above the supporting structure and has an adjustable height; the display device is fixed on the height-adjustable lifting rod;

[0015] The image acquisition unit includes a first image acquisition unit and a second image acquisition unit. The first image acquisition unit is arranged at the free end of the height-adjustable lifting rod and is used to capture images of the surrounding environment, people and objects; the second image acquisition unit is arranged on the supporting structure and is used to photograph the weighed goods.

[0016] Furthermore, it also includes a wireless communication unit, which is electrically connected to the main control circuit board; the built-in Wi-Fi or Bluetooth module in the wireless communication unit can transmit weighing data and image information to a cloud server or mobile device.

[0017] The second aspect of the present invention provides an operation method of a food safety smart scale with infrared shortwave and millimeter wave, wherein the method at least uses the above-mentioned food safety smart scale and at least comprises the following steps:

[0018] Step S1: The user unit sends a purchase order to one or more suppliers through the ordering module of the smart logistics support system;

[0019] Step S2: The smart logistics support system pushes the purchase order information to the supplier. After the supplier accepts the order, the smart logistics support system generates an acceptance form for each purchasing unit.

[0020] Step S3: The supplier brings the goods and the printed acceptance form to the purchasing unit for delivery, and the user unit uses the above-mentioned food safety smart scale to inspect the goods delivered by the supplier.

[0021] Furthermore, in step S3, the staff will use the food safety smart scale to conduct acceptance work as follows:

[0022] Step S31: The staff will use a barcode scanner to scan the QR code on the acceptance form, or manually enter the acceptance form number. At this time, the product information list of the order will be displayed on the display screen of the smart scale.

[0023] Step S32: The staff clicks on the product name in turn to weigh the product, take photos of the product and the surrounding environment, and use the infrared shortwave device and millimeter wave device of the smart scale to inspect the product to detect the maturity of the product, the pesticide residue on the surface, and whether there is rot inside the product.

[0024] Furthermore, after the acceptance work is completed, all data will be uploaded to the smart logistics support system; the system will automatically generate corresponding data charts based on these data. The data charts cover classification statistics, summarization and comparison based on multiple dimensions of product name, category, purchasing unit, supplier, date, and perform in-depth data analysis. The analysis methods include at least one or more of cluster analysis, factor analysis, correlation analysis, correspondence analysis, regression analysis and variance analysis; procurement management personnel can flexibly set different search conditions according to their specific needs, thereby realizing multi-dimensional analysis and comparison of data.

[0025] Furthermore, the content of data analysis at least includes statistical analysis of vegetable food usage in order to more accurately grasp the needs of the user units, classify and count by vegetable type, analyze which vegetables are most popular and which vegetables are increasing or decreasing in usage; this helps the user units optimize procurement plans and ensure sufficient inventory.

[0026] Furthermore, the content of data analysis at least includes helping users evaluate the performance of suppliers through data analysis; by comparing the quality, price and delivery time of vegetables provided by different suppliers, users can optimize supply chain management and select the most cost-effective supplier, thereby reducing procurement costs while ensuring food quality.

[0027] Furthermore, it also includes revealing the consumption patterns within the user units through data analysis;

[0028] By conducting a detailed analysis of vegetable usage in different departments or at different time periods, it is possible to reveal abnormally high or low usage in certain departments. This analysis result can help to take appropriate measures to deal with these abnormal situations. For example, if the vegetable usage in a department is abnormally high, it is necessary to conduct an in-depth investigation to see if there is waste so that timely measures can be taken to reduce waste and improve resource utilization efficiency. On the contrary, if the usage in a department is abnormally low, it is necessary to further investigate whether it is because employees are dissatisfied with the variety of vegetables provided, which leads to a reduction in usage. In this case, the menu can be adjusted to add more vegetable varieties that meet the tastes and needs of employees to improve employee satisfaction and dining experience.

[0029] The present invention adopts the above technical solution, which has at least the following beneficial effects:

[0030] First of all, the food safety smart scale provided by the present invention can play an important role in the food acceptance link. The scale can not only accurately record the weight, quantity and image information of food, but also detect the maturity of vegetables and fruits, whether the food is rotten inside, and the pesticide residue on the surface. Compared with traditional scales, the present invention not only has the function of recording the weight, quantity and commodity picture information of food, but also can shoot the surrounding environment of the acceptance site and the people and objects around it through the camera on the top of the smart scale. In addition, it also has infrared shortwave and millimeter wave detection technology, which can detect the maturity of food, pesticide residues on the surface, and whether the inside is rotten. Through the wireless communication unit of the smart scale, the weighed weight, quantity, picture and detection data are uploaded to the cloud server or mobile device, which is convenient for relevant personnel to view and manage in real time.

[0031] Secondly, through the smart logistics support system, regulatory authorities, leaders of user units, canteen students or diners can view detailed information on the food purchased by the canteen. This information includes supplier information, food pictures, maturity, surface pesticide residues, and whether there is rot, etc. This transparent information display not only enhances the traceability of food safety, but also improves the transparency and credibility of canteen management. The application scenarios of the present invention are wide, and it is suitable for various occasions such as school canteens, enterprise canteens, government agency canteens, social catering canteens, central kitchens, food supply chain companies, etc., and can meet the needs of food safety and management in different occasions.

[0032] Finally, through detailed data analysis of vegetable food consumption, users can not only better monitor capital expenditures, but also optimize procurement plans, improve supply chain efficiency, and adjust internal consumption patterns. Through these measures, users can achieve the goals of cost savings and rational resource allocation, thereby improving overall operational efficiency and economic benefits while ensuring food safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 This is a front view of the food safety intelligent scale of the present invention;

[0035] Figure 2 It is a schematic diagram of the structure of the food safety intelligent scale system of the present invention;

[0036] Figure 3 It is a side schematic diagram of the food safety intelligent scale of the present invention;

[0037] Figure 4 It is a schematic diagram of a food safety intelligent scale according to the present invention;

[0038] Figure 5 The invention is a flowchart of the operation mode of the food safety intelligent scale with infrared short wave and millimeter wave.

[0039] In the figure: 1. base; 2. weighing platform; 3. pressure sensor; 4. supporting structure; 5. display device; 6. image acquisition device; 61. first image acquisition unit; 62. second image acquisition unit; 7. infrared shortwave device; 8. millimeter wave device; 9. main control circuit board; 10. height-adjustable lifting rod; 11. roller; 12. wireless communication unit; 13. support; 14. barcode scanner; 15. power supply unit. DETAILED DESCRIPTION

[0040] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0041] See also Figures 1 to 4 As shown, the present embodiment provides a first aspect of providing a food safety smart scale with infrared shortwave and millimeter wave, which at least includes a base 1, a weighing platform 2, a pressure sensor 3, a supporting structure 4, a display device 5, an image acquisition device 6, an infrared shortwave device 7, a millimeter wave device 8 and a main control circuit board 9; wherein

[0042] The weighing platform 2 is located on the base 1; the pressure sensor 3 is fixed between the base 1 and the weighing platform 2, and the pressure sensor 3 is responsible for converting the weight on the weighing platform 2 into an electrical signal;

[0043] One end of the support structure 4 is connected to one side of the base 1; the display device 5 is directly or indirectly arranged on the support structure 4;

[0044] The main control circuit board 9 is placed inside the support structure 4; the pressure sensor 3, the display device 5, the image acquisition device 6, the external short wave device, and the millimeter wave device 8 are electrically connected to the active circuit board respectively;

[0045] The infrared shortwave device 7 and the millimeter wave device 8 are used to realize nondestructive detection of food ingredients, freshness and safety; the food safety intelligent scale provided by the present invention can be used in the food acceptance link. The scale can not only accurately record the weight, quantity and image information of the food, but also can detect the maturity of vegetables and fruits, whether the food is rotten inside and the pesticide residue on the surface.

[0046] As a preferred implementation scheme, the present embodiment further includes a height-adjustable lifting rod 10 , which is arranged above the supporting structure 4 and has an adjustable height. The display device 5 is fixed on the height-adjustable lifting rod 10 .

[0047] As a preferred implementation scheme, the image acquisition unit in this embodiment includes a first image acquisition unit 61 and a second image acquisition unit 62, wherein the first image acquisition unit 61 is arranged at the free end of the height-adjustable lifting rod 10, and is used to capture images of the surrounding environment, people and objects; the second image acquisition unit 62 is arranged on the supporting structure 4, and is used to photograph and weigh goods.

[0048] As a preferred implementation scheme, this embodiment further includes a wireless communication unit 12 , and the wireless communication unit 12 is electrically connected to the main control circuit board 9 .

[0049] As a preferred implementation scheme, the built-in Wi-Fi or Bluetooth module of the wireless communication unit 12 in this embodiment can transmit the weighing data and image information to a cloud server or a mobile device.

[0050] As a preferred embodiment, the present embodiment further includes a support member 13, the support member 13 is fixed to the side of the support structure 4, and the support member 13 has a hanging groove. The present embodiment further includes a barcode scanner 14, the barcode scanner 14 is communicatively connected to the main control circuit board 9, and the body of the barcode scanner 14 can be placed on the hanging groove of the support member 13.

[0051] As a preferred implementation scheme, the infrared short-wave device 7 and the millimeter wave device 8 in this embodiment are placed between the base 1 and the weighing platform 2 .

[0052] As a preferred implementation, this embodiment further includes a power supply unit 15, and the power supply unit 15 is used to supply power to the food safety smart scale.

[0053] As a preferred implementation scheme, the roller 11 in this embodiment is installed under the base 1.

[0054] It should be noted that the base is designed as a stable structure to ensure that the entire scale remains stable during use and avoid measurement errors caused by shaking. The scale platform uses a high-precision weighing sensor that can accurately measure the weight of food and ensure the reliability of the weighing results. The supporting structure is made of sturdy metal materials, which not only ensures the durability of the scale body, but also can adapt to various working environments. The display device uses a high-resolution touch screen, which is convenient for users to intuitively view the weighing data and operation interface. The image acquisition unit includes a high-definition camera that can capture the image information of food in real time. The main control circuit board is the core of the entire smart scale, responsible for processing data from various sensors and devices and performing comprehensive analysis. The main control circuit board has a built-in high-performance microprocessor and memory, which can quickly respond to user operation instructions and display the processing results on the touch screen in real time. In addition, the smart scale also has wireless communication function, through the built-in Wi-Fi or Bluetooth module, the weighing data and image information can be transmitted to the cloud server or mobile device. Users can remotely view and manage the weighing data of food through a dedicated mobile phone application or computer software to realize intelligent food quality monitoring.

[0055] On the other hand, it should be added that by utilizing the characteristics of infrared shortwave, rapid and non-destructive detection of food ingredients, freshness and safety can be achieved. First, infrared shortwave technology can detect the moisture content in food. Moisture is one of the important factors affecting food quality. By analyzing the absorption of infrared light of different wavelengths, the moisture content in food can be accurately measured. This is particularly important for the quality control of dry food, frozen food and baked food. Secondly, infrared shortwave technology can be used to detect the fat content in food. Fat not only affects the taste and nutritional value of food, but may also have adverse effects on health. Using infrared shortwave spectral analysis technology, the fat content in food can be quickly determined, thereby helping manufacturers optimize formulations and ensure product quality. In addition, infrared shortwave technology can also be used to detect the protein content in food. Protein is one of the important nutrients in food, and its content and quality directly affect the nutritional value of food. Through infrared shortwave spectral analysis, the protein content in food can be accurately determined, thus providing an important basis for food quality assessment. Finally, infrared shortwave technology also has significant advantages in detecting harmful substances in food. For example, through infrared short-wave spectrum analysis, harmful substances such as pesticide residues and heavy metal content in food can be detected. This is of great significance for ensuring food safety and maintaining consumer health.

[0056] Because millimeter waves have a higher frequency and a shorter wavelength, they can penetrate certain materials and detect small changes inside food. This feature gives millimeter wave technology a unique advantage in food safety and quality testing. First, millimeter waves can be used to detect the moisture content in food. Moisture is one of the important factors affecting food quality and shelf life. By measuring the dielectric properties of food in the millimeter wave frequency band, its moisture content can be accurately assessed. This is especially important for industries such as grain storage, food processing, and baking.

[0057] Secondly, millimeter wave technology can be used to detect impurities and foreign matter in food. For example, during grain processing, millimeter wave sensors can detect foreign matter such as stones and metal fragments mixed into grains. Since millimeter waves have different penetration and reflection characteristics for different substances, these impurities can be effectively identified and separated. In addition, millimeter wave technology can also be used to detect the internal structure and uniformity of food. For example, during meat processing, millimeter wave imaging technology can be used to detect the fat distribution in meat and the uniformity of muscle tissue. This is of great significance for ensuring the taste and nutritional value of food. Finally, millimeter wave technology also has broad application prospects in food safety testing. For example, millimeter wave sensors can be used to detect the content of bacteria and viruses in food. Since bacteria and viruses affect the propagation characteristics of millimeter waves, the hygiene of food can be evaluated by analyzing the changes in millimeter wave signals.

[0058] like Figure 5 As shown, the second aspect of the present invention provides an operation method of a food safety smart scale with infrared shortwave and millimeter wave functions, aiming to ensure the safety of food. The method at least involves using the above-mentioned food safety smart scale and includes the following steps:

[0059] Step S1: The user unit sends a purchase order to one or more suppliers through the order module of the smart logistics support system. This process ensures the accurate communication of procurement requirements and lays the foundation for the subsequent procurement process.

[0060] Step S2: The smart logistics support system pushes the purchase order information to the supplier. After the supplier accepts the order, the smart logistics support system generates an acceptance form for each purchasing unit;

[0061] The smart logistics support system pushes the purchase order information to the supplier. After the supplier accepts the order, the smart logistics support system will generate an acceptance form based on the needs of each purchasing unit. This step ensures that the supplier can clearly understand the specific needs of the purchasing unit, thus facilitating the subsequent delivery and acceptance work.

[0062] Step S3: The supplier brings the goods and the printed acceptance form to the purchasing unit. The user unit uses the above-mentioned food safety smart scale to accept the goods delivered by the supplier. This link is a key step to ensure food quality. Through the use of smart scales, the goods can be effectively inspected to ensure that they meet food safety standards.

[0063] As a preferred implementation, in step S3 of this embodiment, the staff will use the food safety smart scale to carry out the acceptance work in the following specific steps:

[0064] Step S31: The staff will use a barcode scanner to scan the QR code on the acceptance form, or manually enter the acceptance form number. At this time, the display screen of the smart scale will display the product information list of the order. This process simplifies the acceptance process and improves work efficiency.

[0065] Step S32: The staff clicks on the product name in turn, weighs the product, takes photos of the product and the surrounding environment, and uses the infrared shortwave device and millimeter wave device of the smart scale to inspect the product. Through these inspection methods, the maturity of the product, the pesticide residue on the surface, and whether there is rot inside the product can be detected. This link ensures the safety of food and provides protection for consumers.

[0066] In this embodiment, as a preferred implementation method, an efficient data processing method is adopted. Specifically, after the acceptance work is completed, all relevant data will be uploaded to an advanced intelligent logistics support system. This system has powerful data processing capabilities and can automatically generate a series of detailed data charts based on the uploaded data. These data charts not only include classification statistics, summaries and comparisons based on multiple dimensions such as product name, category, purchasing unit, supplier, date, etc., but also can perform more in-depth data analysis.

[0067] In terms of in-depth data analysis, the smart logistics support system uses a variety of advanced analysis methods. These methods include at least one or more of cluster analysis, factor analysis, correlation analysis, correspondence analysis, regression analysis and variance analysis. Through these analysis methods, the system can reveal the internal connections and rules between data and provide more accurate decision support for procurement managers.

[0068] When using the system, procurement managers can flexibly set different search conditions according to their specific needs. These search conditions can be single or combined, thus achieving multi-dimensional analysis and comparison of data. In this way, procurement managers can easily obtain the required information, conduct effective data mining and decision support, and greatly improve work efficiency and the depth of data utilization.

[0069] In this embodiment, the content of data analysis at least includes statistical analysis of the amount of vegetable food used, so as to more accurately grasp the needs of the user. Specifically, by making detailed statistics on the amount of various vegetables used, it can be found which vegetables are most popular and which vegetables are increasing or decreasing in usage. This analysis helps the user optimize the procurement plan, ensure sufficient inventory, avoid waste, and thus improve the overall operational efficiency.

[0070] As a preferred implementation, the data analysis in this embodiment also includes helping the user evaluate the performance of suppliers through data analysis. By making a detailed comparison of the quality, price and delivery time of vegetables provided by different suppliers, the user can optimize the supply chain management and select the supplier with the best cost performance. This analysis helps to reduce procurement costs and improve economic benefits while ensuring food quality.

[0071] As a preferred implementation, data analysis in this embodiment also includes revealing consumption patterns within the user unit. By analyzing the usage of vegetables in different departments or different time periods, it can be found that the usage of certain departments is abnormally high or low, so that corresponding measures can be taken. If the usage of a department is abnormally high, it is necessary to check whether there is waste; if the usage is abnormally low, it may be necessary to investigate whether it is because the employees are not satisfied with the types of vegetables provided, so as to adjust the menu to improve employee satisfaction. This analysis helps to improve employee satisfaction, optimize internal consumption patterns, and further improve employee work efficiency and the overall working atmosphere.

[0072] As a preferred embodiment, the present invention further comprises the following steps:

[0073] Step S4: After completing the inspection of the goods and uploading the data, the staff will classify the goods according to the inspection results of the smart scale. For those goods that meet the food safety standards, the staff will send them to the warehouse for storage to ensure that these goods can smoothly enter the supply chain of the user unit; for those goods that do not meet the standards, they will be isolated and the supplier will be notified in time for return and exchange. This link ensures that only qualified food can enter the supply chain of the user unit, further guarantees food safety, and provides consumers with a safer and more reliable source of food.

[0074] Step S5: The smart logistics support system will automatically adjust the subsequent procurement plan based on the acceptance results and inventory status. The system will intelligently predict the food demand in the future based on historical data and current inventory levels, thereby generating new purchase orders. This step helps to achieve dynamic inventory management, reduce inventory backlogs and out-of-stock risks, ensure the stability and timeliness of food supply, and thus improve the efficiency and responsiveness of the entire logistics support system.

[0075] Step S6: The canteen or catering department of the user unit formulates a daily menu and ingredient usage plan based on the purchase plan and inventory status. By using the smart scale, the freshness and safety of the ingredients can be ensured, thereby providing consumers with high-quality catering services. The precise measurement and data recording functions of the smart scale make the use of ingredients more scientific and reasonable, avoid waste, and also improve the efficiency and quality of catering services.

[0076] Step S7: The smart logistics support system will continuously monitor and analyze the entire procurement, acceptance, storage and use process. The system will regularly generate reports, including food safety test results, supplier performance evaluation, inventory status and consumption pattern analysis, etc. Procurement managers and user unit management can make decisions based on these reports, continuously optimize procurement and logistics support processes, improve the transparency and traceability of the entire system, and ensure food safety and efficient operation of the supply chain.

[0077] Through the operation methods of the above steps, the food safety intelligent scale of the present invention not only improves the efficiency and accuracy of food safety detection, but also realizes the whole process management from procurement to use through the support of the intelligent logistics support system, ensuring the safety of food and the efficient operation of the supply chain.

[0078] Although the embodiments of the present invention have been shown and described above, it will be appreciated that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, substitute and vary the above embodiments within the scope of the present invention.

Claims

1. A food safety smart scale with infrared shortwave and millimeter wave, characterized by: It at least includes a base, a weighing platform, a pressure sensor, a supporting structure, a display device, an image acquisition device, an infrared short-wave device, a millimeter wave device and a main control circuit board; in The weighing platform is located on the base; the pressure sensor is fixed between the base and the weighing platform, and the pressure sensor is responsible for converting the weight on the weighing platform into an electrical signal; One end of the support structure is connected to one side of the base; the display device is directly or indirectly arranged on the support structure; the infrared short-wave device and the millimeter wave device are used to realize non-destructive testing of food ingredients, freshness and safety; the main control circuit board is placed inside the support structure; The pressure sensor, the display device, the image acquisition device, the external short wave device, and the millimeter wave device are electrically connected to the active circuit board respectively.

2. The food safety intelligent scale according to claim 1, characterized in that: It also includes a height-adjustable lifting rod, which is arranged above the supporting structure and has an adjustable height; the display device is fixed on the height-adjustable lifting rod; The image acquisition unit includes a first image acquisition unit and a second image acquisition unit. The first image acquisition unit is arranged at the free end of the height-adjustable lifting rod and is used to capture images of the surrounding environment, people and objects; the second image acquisition unit is arranged on the supporting structure and is used to photograph the weighed goods.

3. The food safety intelligent scale according to claim 2, characterized in that: It also includes a wireless communication unit, which is electrically connected to the main control circuit board; the built-in Wi-Fi or Bluetooth module in the wireless communication unit can transmit weighing data and image information to a cloud server or a mobile device.

4. An operation mode of a food safety intelligent scale with infrared shortwave and millimeter wave, characterized in that: The method uses at least the food safety smart scale according to any one of claims 1 to 3, and comprises at least the following steps: Step S1: The user unit sends a purchase order to one or more suppliers through the ordering module of the smart logistics support system; Step S2: The smart logistics support system pushes the purchase order information to the supplier. After the supplier accepts the order, the smart logistics support system generates an acceptance form for each purchasing unit. Step S3: The supplier brings the goods and the printed acceptance form to the purchasing unit for delivery, and the user unit uses the food safety smart scale described in any one of claims 1 to 3 to inspect the goods delivered by the supplier.

5. The operating method according to claim 4, characterized in that: In step S3, the staff will use the food safety smart scale to conduct acceptance work as follows: Step S31: The staff will use a barcode scanner to scan the QR code on the acceptance form, or manually enter the acceptance form number. At this time, the display screen of the smart scale will display a list of product information for the order; Step S32: The staff clicks on the product name in turn to weigh the product, take photos of the product and the surrounding environment, and use the infrared shortwave device and millimeter wave device of the smart scale to inspect the product to detect the maturity of the product, the pesticide residue on the surface, and whether there is rot inside the product.

6. The operating method according to claim 5, characterized in that: After the acceptance work is completed, all data will be uploaded to the smart logistics support system; the system will automatically generate corresponding data charts based on these data. The data charts cover classification statistics, summarization and comparison based on multiple dimensions of product name, category, purchasing unit, supplier, date, and perform in-depth data analysis. The analysis methods include at least one or more of cluster analysis, factor analysis, correlation analysis, correspondence analysis, regression analysis and variance analysis; procurement management personnel can flexibly set different search conditions according to their specific needs, thereby realizing multi-dimensional analysis and comparison of data.

7. The operating method according to claim 6, characterized in that: The content of data analysis at least includes statistical analysis of the amount of vegetable food used, so as to more accurately grasp the needs of the user units, classify and count by vegetable type, analyze which vegetables are most popular, and which vegetables are increasing or decreasing in usage; It helps users optimize their purchasing plans and ensure sufficient inventory.

8. The operating method according to claim 6, characterized in that: The content of data analysis at least includes helping users evaluate the performance of suppliers through data analysis; by comparing the quality, price and delivery time of vegetables provided by different suppliers, users can optimize supply chain management and select the most cost-effective supplier, thereby reducing procurement costs while ensuring food quality.

9. The operating method according to claim 6, characterized in that: It also includes revealing consumption patterns within user units through data analysis; By analyzing the vegetable usage in different departments or at different time periods, it can be discovered that the usage in some departments is abnormally high or low, so that corresponding measures can be taken; if the usage in a department is abnormally high, it is necessary to check whether there is waste; if the usage is abnormally low, it may be necessary to investigate whether it is because employees are dissatisfied with the types of vegetables provided, so as to adjust the menu and improve employee satisfaction.

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