Age-Sensitive and Product-Classified Automated Bagging System and Method

Abstract

This invention relates to an age-sensitive and product-classified automated bagging system (1) and method (1000) designed for use in retail outlets, particularly supermarkets and large-scale stores. The invention offers customers hygiene and safety, comfort, speed and efficiency, balance and user experience, and learning capability.

Description

1 TARIFF Age-Sensitive and Product-Classified Automated Bagging System and Method Technical Area This invention is suitable for retail outlets, particularly supermarkets and large-scale businesses. A 5-page age-sensitive and product-classified system designed for use in stores. It relates to automatic bagging systems and methods. State of the Art Current automated bagging systems used in the retail sector are based on basic robotics. These include arms and simple classification algorithms. However, most of these systems Packaging without distinguishing between products or without customer-focused optimization 10 It is carrying out the process. The automated bagging systems currently in place are as follows:  Standard Automatic Bagging: Nowadays, some supermarkets use barcodes for product packaging. After being scanned, the passengers are transported to the designated bagging area using conveyor belts. They are transported and manually bagged. 15  Semi-Automatic Bagging: Some systems bag bags with the cashier's guidance. It helps to open and bag only specific products.  Fully Automatic Bagging: In advanced systems, robotic arms hold the bags. It automatically places products, but it doesn't separate product categories or customer preferences. It does not have the ability to perform weight optimization. 20 The shortcomings and technical problems of the current systems are as follows:  Inability to Categorize Products: Current systems categorize food and health products. They cannot distinguish between them. Health products and food products are placed in the same bag. Placing these products in these facilities poses a hygiene risk. Identification exists, but classification-based bagging is not. 25  Lack of weight management in the bagging process: Existing systems, This causes the bags to be unevenly filled. The customer's carrying capacity and... Weight optimization is not done according to age. Heavy bags, especially for the elderly. It makes transportation more difficult for customers. 2  Inefficient bag opening mechanisms: Current systems are manual. or mechanical opening mechanisms are used. This is the case, such as with an air blower. It can be accelerated with automated systems.  Insufficient image processing and sensor usage: The products only Barcode-based identification results in error 5 for broken or unreadable barcode products. It creates image processing-supported systems for barcode scanning in the market. It can reduce the problems caused by their mistakes. Patent application number TR2019 / 16673, which is included in the prior art. The document describes an automated packaging machine. The relevant application... The machine described in the document has a different hardware structure. 10 In conclusion, solutions that address the needs described above are relevant to the subject. Due to its shortcomings, it has become necessary to make improvements in the relevant technical field. Brief Description of the Invention The invention was created by drawing inspiration from existing situations and overcoming the aforementioned drawbacks. It aims to solve it. 15 The purpose of this invention is to improve retail outlets, particularly supermarkets and large retail spaces. Age-sensitive and product-classified designed for use in large-scale stores. The goal is to develop an automated bagging system and method. The invention allows products scanned by cashiers in supermarkets to be separated by category. It enables them to be placed in different bags. The invention allows for the packaging of health products and food products in 20 different bags. while placing items in separate bags, also balancing the bag weight according to the customer's age. It offers this feature. The invention is for grocery chains that operate integrated with supermarkets, hypermarkets, and pharmacies. It can be used in areas such as retail stores equipped with automated cash registers. The structural and characteristic features and all the advantages of the invention are given in the figures below and 25 This becomes clearer thanks to the detailed explanation written with references to these figures. This will be understood as such, and therefore the evaluation will also take these forms and detailed explanations into account. This should be done taking that into consideration. Figures that will help understand the invention. 3 Figure 1 shows the circuit diagram of the system that is the subject of the invention. Figure 2 shows the flowchart of the method described in the invention. Explanation of Part References 1. System 2. Image processing module 5 3. Barcode and RFID reader 4. Age detection module 5. Weight optimization module 6. Air gun 7. Robotic arm and product placer 10 8. Weight sensor 9. Learning module Method 1000 1001. The product is scanned by the cashier at the checkout and AI-powered learning. Definition of module 15 1002. The product defined in the learning module is placed in the temporary hopper and processed. start 1003. Image processing module and barcode and RFID reader for the product in the hopper. analyze and categorize through 1004. The product, categorized by image processing module and barcode and RFID reader, is 20 Determining whether it is a food or a health product through the learning module. 1005. Age detection module, facial recognition technology, customer loyalty card or determining the user's age via NFC payment information and bag optimizing the weight 4 1006. Detected by the age detection module via the weight optimization module. Based on customer age information, it is lighter for older individuals and more gentle for younger individuals. Preparation of bags with balanced weight distribution 1006. The air gun activates automatically, distinguishing between old and young people. 5 to open the designated bag 1007. Using a robotic arm and product placement device, products are opened with an air gun. transfer to bag 1008. Measuring the weight of each bag via weight sensors and if a If the bag is too heavy, some items can be transferred to a different bag to distribute the load evenly. distribution 10 1009. Through the learning module, heavy items can be placed in bags for ease of transport. lighter items should be placed at the bottom of the bag, and fragile items should be handled with care. using an algorithm and placing fragile items in the bag according to this algorithm. Through the 1010th learning module, the bagging process is completed and the bagged product is processed. 15 Detailed Description of the Invention In this detailed description, the system (1) and method (1000) that are the subject of the invention are preferred. Their structures are explained solely to facilitate a better understanding of the subject. This invention is suitable for retail outlets, particularly supermarkets and large-scale businesses. A 20-page age-sensitive and product-classified system designed for use in stores. It is related to the automatic bagging system (1) and method (1000). The invention allows products scanned by cashiers in supermarkets to be separated by category. It enables them to be placed in different bags. The invention applies to health products and food products. while placing items in separate bags, also balancing the bag weight according to the customer's age. It offers feature 25 The invention is for grocery chains that operate integrated with supermarkets, hypermarkets, and pharmacies. It can be used in areas such as retail stores equipped with automated cash registers. The system, schematically shown in Figure 1 (1);  By analyzing the product scanned at the checkout by the cashier, the product is checked to determine if it is food or healthy. AI-powered image processing module (2) which determines whether it is a product  Integrated with the image processing module (2), the identity of the products scanned at the cash register Barcode and RFID reader (3) that determines information and categories,  Equipped with facial recognition technology, and in addition to this technology, customer loyalty 5 By identifying the user's age via card or NFC payment information, the bag Age detection module that optimizes weight (4),  Customer age information detected via age detection module (4) Accordingly, lighter weight for older individuals and more balanced weight for younger individuals. Age-based weight 10 enabling the preparation of bags with distribution optimization module (5) and  The system automatically sorts bags by age (old or young) using air blowing. Automatic bag opener air gun (6),  activated after the bag is opened by means of an air gun (6), Robot arm and product placer (7) that carry the products into the designated bag, 15  Measuring the weight of each bag, and if a bag is too heavy, moving some of the products to a different one. By directing the load into the bag, it distributes the load evenly, thus preventing the bags from becoming unbalanced. weight sensors (8) which increase carrying comfort by preventing filling and  if the product is via the image processing module (2) and barcode and RFID reader (3) If it cannot be identified, it intervenes, analyzes the product, and determines the most appropriate classification. 20 This involves separating food and health products and putting them in separate bags. robotic arm and product placer (7) and weight sensors that enable placement (8) In order to facilitate carrying heavy items, they are placed under the bag, light items are placed under the bag. Ensure items are placed on top of the bag; handle fragile items with care. using an algorithm and according to this algorithm, fragile products are placed in bags 25 enables placement and automatically identifies newly added products. by using the correct bagging algorithm that has a continuously learning structure Artificial intelligence that enables better sorting over time for bagging. Supported learning module (9) It includes. 30 In the system (1) automatic classification of products by separating food and health products. is being implemented. Artificial intelligence-supported image processing module (2) and barcode and As a result of the analysis performed by means of the RFID reader (3), it can be determined whether the product is food or health product. It is determined if the product has an image processing module (2) and a barcode and RFID reader (3) 6 If it cannot be identified by means of, the AI-assisted learning module (9) The image recognition algorithm examines a database by looking at the physical characteristics of the product. For example, the system (1) compares a bottle of pain relief gel with a carton of milk. It can distinguish between them. The system (1) directs both product categories to different bags. While current systems put all products in a single bag, the system in question (1) 5 Separating health products from food provides a hygiene advantage. The system (1) then optimizes the bag weight according to age. Age Detection module (4), face recognition technology, customer loyalty card or NFC payment It estimates the customer's age group based on the information. Weight sensors (8) It dynamically calculates the weight of the bags. AI-powered learning module (9), 10 By using a bagging algorithm based on age group, for elderly customers Smaller and lighter bags, with the weight divided into fewer parts for younger customers. It creates bags in which the contents are distributed evenly. The bagging process involves the user's physical Customer comfort is enhanced by adapting to the carrying capacity. The bags formed are opened with the help of an air gun (6). Both bags (food and health) 15 They are opened separately. The air gun (6) widens the mouths of the bags, allowing the robotic arms to open the product. This makes placement easier. The bags are automatically secured with mechanical arms and It does not remain closed during filling. The bag opening width depends on the angle at which the product falls. Adjustable (e.g., opens wider if a large-volume item arrives). Available. While bag opening is usually done manually in conventional systems, in this invention, it is done entirely manually. an automatic system (1) is used. In the system (1) weight sensors (8) ensure balanced load distribution. Each bag weighs It is controlled by sensors (8). If unbalanced load is detected, the learning module (9) It optimizes the weight distribution. Equal weight distribution included in the learning module (9) The algorithm, if a heavy product is placed inside, moves the next product to a different bag. It can be directed. The equal weight distribution algorithm prioritizes lighter products over smaller ones. It adds to the full bags. This prevents unbalanced loading that is common in today's structures. This prevents the problem and ensures ease of transportation. Learning module (9) image processing-assisted classification and learning process It performs. Machine learning-assisted learning module (9), system (1) 30 It enables the recognition and classification of new products over time. Learning module (9), first It evaluates a product encountered only once using a machine learning algorithm and categorizes it. It makes a prediction. Learning module (9), in situations requiring human intervention (e.g., 7 (rare products), the system (1) improves itself by receiving data from operators. The system (1) barcode It offers a smarter solution to their problems than existing structures, and over time... He improves himself. As a result, the following gains are achieved thanks to the system (1); Hygiene and safety: Food and health products are bagged separately to maintain hygiene. 5 Comfort: Portability is enhanced through age-based weight optimization. Speed ​​and Efficiency: Automatic bag opening reduces processing time. Balance and User Experience: The bags are balanced during transport by adjusting the weights. Learning Ability: With machine learning, the system (1) improves itself over time and becomes more It works well. 10 The method presented in the flowchart in Figure 2 (1000);  The product is scanned by the cashier at the checkout and artificial intelligence-assisted learning Defining module (9) (1001),  The product defined in the learning module (9) descends into the temporary hopper and is processed start (1002), 15  Image processing module (2) and barcode and RFID reader (3) of the product in the container by means of analysis and categorization (1003),  Categorized by image processing module (2) and barcode and RFID reader (3) through the learning module (9) whether the product is food or health product determination (1004), 20  Through the age detection module (4), face recognition technology, customer loyalty Determining the user's age via card or NFC payment information and Optimizing bag weight (1004),  Detected by the weight optimization module (5) and the age detection module (4) Based on the customer age information provided, milder measures are recommended for elderly individuals, and 25 for younger individuals. Preparation of bags with more balanced weight distribution (1005),  The air gun (6) activates automatically, distinguishing between old and young. opening the designated bag (1006),  Using a robotic arm and product placer (7), the products are placed with an air gun (6). Transfer to the opened bag (1007), 30 8  By means of weight sensors (8), the weight of each bag is measured and if a If the bag is too heavy, some items can be transferred to a different bag to evenly distribute the load. distribution in this way (1008),  Through the learning module (9), heavy products in terms of ease of transport Place lighter items at the bottom of the bag and lighter items on top; for fragile items, use a size 5. A sensitive transportation algorithm is used, and fragile products are handled according to this algorithm. placing in a bag (1009) and  through the learning module (9), the bagging process is completed and (1010) The cashier presents the packaged products to the customer It includes the steps of the process. 10 In the method (1000), the product is first scanned by the cashier and placed in the temporary container. The product is directed to the temporary container, where the bagging process begins. The system uses (1) image processing module (2) and barcode and RFID reader (3) to process the product It analyzes. As a result of this analysis, the learning module (9) is activated and it determines whether the product is food or not. or determines whether it is a health product. 15 Age detection module (4), face recognition technology, customer, loyalty card and NFC payment It determines the customer's age based on the information. Weight optimization module (5), detection Based on the customer age information collected, milder options are available for older individuals, and more suitable options for younger individuals. It prepares bags with a balanced weight distribution. The prepared bags are opened by automatically inflating them using an air gun (6). 20 The robotic arm and product placer (7) place the product into the correct bag. Weight sensors (8) measure the weights and prevent the bag from being filled unevenly. Learning module (9) heavy products are placed under the bag for ease of carrying, light products It ensures that the products are placed on top of the bag. Learning module (9) also ensures that fragile products are placed on top of the bag. A sensitive transportation algorithm is used for the products, and according to this algorithm, fragile products are handled on the 25th. This allows it to be placed in a bag. Once the bagging process is complete, the products are presented to the customer by the cashier.

Claims

9 REQUESTS 1. At retail points of sale, especially supermarkets and large-scale age-sensitive and product-classified designed for use in stores It is an automatic bagging system (1), and its feature is;  By analyzing the product scanned at the checkout by the cashier, the product is determined to be food or healthy. 5 AI-powered image processing module (2) which determines whether it is a product  Integrated with the image processing module (2), the identity of the products scanned at the cash register Barcode and RFID reader (3) that determines information and categories,  Equipped with facial recognition technology, and in addition to this technology, customer loyalty By identifying the user's age via card or NFC payment information, the bag 10 Age detection module that optimizes weight (4),  Customer age information detected via age detection module (4) Accordingly, lighter weight for older individuals and more balanced weight for younger individuals. Age-based weighting that enables the preparation of bags with a distribution optimization module (5) and 15  The system automatically sorts bags by age (old or young) using air blowing. Automatic bag opener air gun (6),  activated after the bag is opened by means of an air gun (6), Robotic arm and product placer (7) that carry the products into the designated bag.  It measures the weight of each bag, and if a bag is too heavy, it sends some of the products to a different bag. By directing the load into the bag, it distributes the load evenly, thus preventing the bags from becoming unbalanced. weight sensors (8) which increase carrying comfort by preventing filling and  if the product is via the image processing module (2) and barcode and RFID reader (3) If it cannot be identified, it intervenes to analyze the product and determine the most appropriate classification. The process involves separating food and health products and placing them in separate bags. 25 robotic arm and product placer (7) and weight sensors that enable placement (8) In order to facilitate carrying heavy items, they are placed under the bag, light items are placed under the bag. Ensure items are placed on top of the bag; handle fragile items with care. using an algorithm and according to this algorithm, fragile products are placed in bags enabling placement, automatically identifying newly added products, 30 by using the correct bagging algorithm that has a continuously learning structure Artificial intelligence that enables better sorting over time for bagging. Supported learning module (9) It includes.

2. At retail points of sale, especially supermarkets and large-scale age-sensitive and product-classified designed for use in stores Automatic bagging method (1000), its feature is;  The product is scanned by the cashier at the checkout and AI-assisted learning 5 Defining module (9) (1001),  The product defined in the learning module (9) descends into the temporary hopper and is processed start (1002),  Image processing module (2) and barcode and RFID reader (3) of the product in the container by means of analysis and categorization (1003), 10  Categorized by image processing module (2) and barcode and RFID reader (3) through the learning module (9) whether the product is food or health product determination (1004),  Through the age detection module (4), face recognition technology, customer loyalty Determining the user's age via card or NFC payment information and 15 Optimizing bag weight (1004),  Detected by the weight optimization module (5) and the age detection module (4) Based on the customer age information collected, milder options are available for elderly individuals, and for younger individuals. Preparation of bags with more balanced weight distribution (1005),  The air gun (6) activates automatically and fires 20 rounds, according to the distinction between old and young. opening the designated bag (1006),  Using a robotic arm and product placer (7), the products are placed with an air gun (6). Transfer to the opened bag (1007),  By means of weight sensors (8), the weight of each bag is measured and if a If the bag is too heavy, some items can be transferred to a different bag to evenly distribute the load. distribution in this way (1008),  Through the learning module (9), heavy products in terms of ease of transport Lighter items should be placed at the bottom of the bag, and fragile items at the top. A sensitive transportation algorithm is used, and fragile products are handled according to this algorithm. placement in a bag (1009) and 30  through the learning module (9), the bagging process is completed and The cashier presents the packaged products to the customer (1010) It includes the steps involved in the process.

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