The present invention discloses a product detection method and a product detection system, and more particularly, a product detection method and a product detection system capable of detecting an event of a product for determining a sales status of the product.
With the rapid developments of technologies, purchasing various products and logistic services has become more and more convenient for consumers. Many convenience stores, shopping malls, or grocery stores have a plurality of shelves. Each shelf contains at least one laminate for placing various products. In order to display names and selling prices of products for the consumers, traditional shelves use a manual method for placing at least one notepaper near corresponding products. The notepapers can list sales information, product information, special information, and discount periods. When a user wants to buy a product, the user has to look for the notepapers having sales messages before the user decides if he/she really needs to purchase this product.
In order to reduce a cost of consumables and increase purchasing convenience, some advanced shelves can include display devices for displaying sales information and/or promotional information of the products placed on the shelves. However, although the sales information and/or the promotional information can be intuitively understood by consumers, a sales status of each product placed on the shelf still needs to be checked or manually managed by the service staff. For example, statistical data of popularity, sales, attention of the products disposed on the shelves are determined by the service staff or manually recorded by the service staff when a patrolling process is executed by the service staff. Therefore, currently, the service staff has to spend a lot of manpower and recording time for managing the sales status of the products disposed on the shelves.
In an embodiment of the present invention, a product detection method is disclosed. The product detection method comprises acquiring an image comprising a shelf laminate and a plurality of products placed on the shelf laminate, acquiring position information of a product of the plurality of products according to the image, detecting an event of the product by using a plurality of sensors adjacent to the shelf laminate for generating a plurality of detection results, and determining a sales status of the product according to the position information of the product disposed on the shelf laminate and the plurality of detection results.
In another embodiment of the present invention, a product detection system is disclosed. The product detection system comprises a shelf laminate, a plurality of sensors, a transmitter, and a processor. The shelf laminate is configured to place a plurality of products. The transmitter is configured to transmit and receive data. The processor is coupled to the plurality of sensors and the transmitter and configured to control the plurality of sensors and the transmitter. After the processor acquires an image comprising the shelf laminate and the plurality of products placed on the shelf laminate, the processor acquires position information of a product of the plurality of products according to the image. The processor controls the plurality of sensors for detecting an event of the product for generating a plurality of detection results. The processor determines a sales status of the product according to the position information of the product disposed on the shelf laminate and the plurality of detection results.
These and other objectives of the present invention will no doubt become obvious to those of ordinary skill in the art after reading the following detailed description of the preferred embodiment that is illustrated in the various figures and drawings.
Further, the product detection system 100 can include a backend system 14. The backend system 14 is linked to the transceiver 12 and/or an image capturing device 16 for receiving the image transmitted from the transceiver 12 and/or receiving the image transmitted from the image capturing device 16. The backend system 14 can acquire range information, coordinates information, and/or volume information of the product of the plurality of products according to the image. Further, the backend system 14 can include a memory 14a, a processor 14b, and a transceiver 15. The transceiver 15 is used for communicating data with the transceiver 12 of the smart shelf 20. The memory 14a can buffer data and can store product model data, product size data, and product appearance data of the smart shelf 20. The processor 14b is capable of processing the image and is coupled to the transceiver 15 and the memory 14a. In the product detection system 100, the image capturing device 16 (i.e., such as a camera) can take at least one picture of the entire smart shelf 20 or one shelf laminate 10 of the smart shelf 20 for placing the products 10a and 10b. The image capturing device 16 can transmit the image to the transceiver 15 of the backend system 14 through a wired or a wireless link. After the transceiver 15 receives the image, the transceiver 15 can transmit the image to the processor 14b for processing an image recognition function. Since the memory 14a has the product model data, the product size data, and the product appearance data, the processor 14b can acquire range information, coordinates information, and/or volume information of the product placed on the shelf laminate 10 according to the image. Then, the backend system 14 transmits the range information, the coordinates information, and/or the volume information to the processor 13 of the smart shelf 20 through the transceiver 15. Therefore, the processor 13 of the smart shelf 20 can acquire the position information of each product placed on the shelf laminate 10. Briefly, the image capturing device 16 can transmit the image to the backend system 14. The backend system 14 can process the image for generating the position information of the products 10a and 10b placed on the shelf laminate 10. Then, the backend system 14 can transmit the position information of the products 10a and 10b placed on the shelf laminate 10 to the processor 13 of the shelf laminate 10. By doing so, the processor 13 can acquire the position information of the products 10a and 10b placed on the shelf laminate 10. However, if the processor 13 pre-stores the image of the products of the smart shelf 20, the image can be directly transmitted to the backend system 14 through the transceiver 12 and the transceiver 15 for processing the image. Any reasonable technology modification falls into the scope of the present invention. Details of the plurality of sensors 11 of the shelf laminate 10 and a method for detecting an event of the product by using the plurality of sensors 11 are illustrated later.
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Further, as previously mentioned, if the user takes a lot of time to pick up the product 10b placed on the shelf laminate 10 by hand, it implies that the product 10b is hard to be reached. It also implies that the product 10b is placed at a deep position of the shelf laminate 10. Since the product 10b is placed at the deep position of the shelf laminate 10, it implies that a remaining amount of the products 10b is small. If the user takes a short time to pick up the product 10b placed on the shelf laminate 10 by hand, it implies that the product 10b is easily reachable. It also implies that the product 10b is placed at an edge position of the shelf laminate 10. Since the product 10b is placed at the edge position of the shelf laminate 10, it implies that a remaining amount of the products 10b is large. In other words, the first time interval corresponds to a first remaining amount of products 10b placed on the shelf laminate 10. The second time interval corresponds to a second remaining amount of products 10b placed on the shelf laminate 10. When the length of the first time interval is greater than the length of the second time interval, the first remaining amount is less than the second remaining amount. Therefore, the detection system 100 is capable of determining the remaining amount of the specific products.
Further, the detection system 100 is capable of determining a popularity of a specific product. For example, the processor 13 can control the plurality of sensors 11 for detecting the event to determine the popularity of the product according to a blocking range of the plurality of sensors 11. When a first blocking range is detected by the plurality of sensors 11, the product is determined as being touched by the processor 13. The product has a first popularity. When a second blocking range is detected by the plurality of sensors 11, the product is determined as being untouched by the processor 13. The product has a second popularity. Here, the first blocking range is greater than the second blocking range. The first popularity is higher than the second popularity. In other words, when the product is determined as being touched, it implies that the user pays more attention to the product. Therefore, the product can be regarded as a popular product. Conversely, when the product is determined as being untouched, it implies that the user pays less attention to the product. Therefore, the product can be regarded as an unpopular product.
Further, the detection system 100 is capable of detecting a pickup count of the product by using the plurality of sensors 11 adjacent to the shelf laminate 10. For example, according to statistical data, when the product is touched, a chance of picking up the product is 80%. Therefore, the processor 13 can estimate the pickup count of the product according to a touched count of the product. The detection system 100 can record the pickup count of the product. Further, after the sales status of the product is generated by the processor 13, the sales status can be transmitted to the backend system 14 through the transceiver 12 and the transceiver 15. After the backend system 14 receives the sales status of the product, a manager can control the backend system 14 for generating a marketing strategy according to the sales status. For example, when a remaining amount of products is too small and inventories are insufficient, the backend system 14 can generate a “replenishment” marketing strategy. When there are too many remaining and unsalable products placed on the shelf laminate 10, the backend system 14 can generate a “limited-time specials” marketing strategy. Further, the products can also be reallocated on conspicuous places for stimulating consumption.
Details of step S401 to step S404 are previously illustrated. Thus, they are omitted here. The product detection system 100 can detect the event (i.e., a touched event or an untouched event) of the product for determining the sales status of the product according to step S401 to step S404. Since no manpower is required for performing step S401 to step S404, the product detection system 100 can automatically generate the sales status to the backend system. By doing so, the manager of the backend system can easily determine the marketing strategy of the product.
To sum up, the present invention discloses a product detection method and a product detection system. The product detection system is capable of determining an event, a remaining amount, and a popularity of specific products. The product detection system can use a linear sensor array for detecting a blocked range and a length of a blocked interval when a user wants to pick up the product by hand. Instead of executing a patrolling process by the service staff for acquiring a sales status, the product detection system can automatically generate the sales status to a backend system. Therefore, the product detection system of the present invention can reduce manpower consumption and can increase an efficiency of product sales management.
Those skilled in the art will readily observe that numerous modifications and alterations of the device and method may be made while retaining the teachings of the invention. Accordingly, the above disclosure should be construed as limited only by the metes and bounds of the appended claims.
Number | Date | Country | Kind |
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201910768408.6 | Aug 2019 | CN | national |