KR102179528B1 - System for providing non face-to-face grocery parking order service - Google Patents

Abstract

Provided is a system for providing a non-contact parking order service to provide a platform for automating customer services and increasing customer convenience. According to the present invention, the system comprises: an autonomous driving cart moving along a cart guide line and moving to a position corresponding to an input area code along the cart guide line when the area core corresponding to at least one area is input; an order and payment apparatus outputting at least one kinds of products on a screen, performing payment when at least one of the output products is selected and at least one kind of payment means is input, and outputting and transmitting a pickup request event when the payment is finished; and a parking order service providing server. The parking order service providing server comprises: a storage unit storing the position and area code of at least one area within a parking zone and an area code; a pickup request unit mapping the area code of an area, in which a vehicle having a vehicle license number is parked, with an order number when order and payment are completed in the order and payment apparatus and the vehicle license number is recognized, and outputting the pickup request event; and a delivery request unit, when receiving a pickup complete signal, recognizing the order number and requesting the autonomous driving cart to move to the area having the area code stored by being mapped with the recognized order number.

Description

Non-face-to-face parking order service provision system {SYSTEM FOR PROVIDING NON FACE-TO-FACE GROCERY PARKING ORDER SERVICE}

The present invention relates to a system for providing a non-face-to-face parking order service, and provides a system that enables non-face-to-face ordering and delivery to vehicles located in a parking lot using an autonomous cart and a cart guide line.

In recent years, the distribution industry continues to create efficient store operation and differentiated customer service through future stores. The intelligent customer service of these stores is being applied to each sector using IoT technology, and as a result, the focus is on the enhancement of customer service, such as improving business processes, efficient store operation, and providing convenience to customers' shopping. This change in services based on IoT technology in the distribution industry also means that the distribution industry has already undergone a development and is entering a maturity stage. Even in countries where the distribution industry has matured first, such as the United States and Europe, the recent trend is toward maximizing operational efficiency and customer service, and the main reason for such a direction is that numerous distributors have already reached a saturation state and are in competition. It is to survive.

At this time, an order method using a drive thru was researched and developed. In this regard, Korean Patent Registration No. 10-2098524 (announced on April 7, 2020) and Korean Patent Publication No. 2020-0011622, which are prior art (Released on February 4, 2020), drive-through stores request B/L and PSAM authentication according to the high pass payment request, B/L and PSAM authentication at the payment server, and high pass payment at the payment server. Process details and settle the high pass payment processing in the operation server, recognize the vehicle number of the vehicle, receive order information and member information corresponding to the vehicle number, and based on the vehicle number recognized by the service terminal Changes the order management unit from the order waiting state to the order start state, changes the order management unit from the order start state to the order completion state based on the order information, displays a message instructing to move the ordered product to the pickup location, and leaves the vehicle. Each of the configurations of recognizing the vehicle number of the vehicle when passing through the ward and transmitting the recognized vehicle number to a service terminal for automatic payment is disclosed.

However, the above-described configuration is a method of waiting in line for vehicles, and a one-to-one order is placed on a first-in-first-out basis (FIFO), and when the number of vehicles is large, the waiting time is exponentially increased compared to the method of ordering a many-to-one. Non-face-to-face orders are being activated due to the corona crisis, but drive-through is unavoidable during the pickup process, and the waiting time is also lengthened because vehicles must stand in a row to pick up. Customers who are very uncomfortable with shopping in the store, such as the disabled or the elderly, and customers who are unable to make additional shopping time such as busy office workers, or customers who purchase a single item rather than shopping, want the ordered product to be delivered on-site. Are doing. Moreover, in the case of fresh foods that are highly likely to deteriorate within a short period of time, the dispatch time for delivery is made every 3 hours on average, so it is very difficult to deliver all products in the best condition at the time the customer wants.

One embodiment of the present invention is a one-to-many platform that enables non-contact pickup because it is possible to deliver products ordered to the area where the customer's vehicle is parked using an autonomous driving cart, and does not require order payment pickup in a line. As order payment pickups can be distributed, it does not cause congestion, and it is possible to provide a platform for automation of order and receipt services of customers in distribution stores and increase customer convenience as it does not cause congestion, and it can save time for customers who are inconvenient to move or purchase purpose. In addition, it is possible to provide a method of providing a non-face-to-face parking order service that can help in building a future store by providing a higher level of customer service through the application of IoT technology in distribution stores. However, the technical problem to be achieved by the present embodiment is not limited to the technical problem as described above, and other technical problems may exist.

As a technical means for achieving the above-described technical problem, an embodiment of the present invention is a position corresponding to the input area code when moving along a cart guide line and an area code corresponding to at least one area is input. A self-driving cart that moves along the low-cart guide line, when at least one type of product is displayed on the screen, and when at least one of the output products is selected, payment is made when at least one type of payment method is input. , When payment is completed, an order payment device that outputs and transmits a pickup request event, and a storage unit that stores the location and area code of at least one area in the parking area, the order and payment is completed in the order payment device, and the vehicle number is recognized. If so, a pickup request unit that maps and stores the area code of the area where the vehicle with the vehicle number is parked to the order number and outputs a pickup request event.If a pickup completion signal is received, the order number is identified and mapped to the identified order number. And a parking order service providing server including a delivery request unit for requesting driving of an autonomous cart to an area having the stored area code.

According to any one of the above-described problem solving means of the present invention, a non-contact pickup is possible because an ordered product can be delivered to an area where the customer's vehicle is parked using an autonomous driving cart, and order payment pickup is not performed in a line. This is a one-to-many platform that does not require congestion because order payment pickups can be distributed, and it can save time for customers who are inconvenient to move or purchase purpose, thereby increasing automation and customer convenience of ordering and receiving services from customers in distribution stores. It can provide a platform for retail stores and help build future stores by providing higher-level customer service through the application of IoT technology in distribution stores.

1 is a view for explaining a system for providing a non-face-to-face parking order service according to an embodiment of the present invention.
FIG. 2 is a block diagram illustrating a parking order service providing server included in the system of FIG. 1.
3 and 4 are diagrams for explaining an embodiment in which a non-face-to-face parking order service is implemented according to an embodiment of the present invention.
5 is a flowchart illustrating a method of providing a non-face-to-face parking order service according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art can easily implement the present invention. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and similar reference numerals are assigned to similar parts throughout the specification.

Throughout the specification, when a part is said to be "connected" to another part, this includes not only "directly connected" but also "electrically connected" with another element interposed therebetween. . In addition, when a part "includes" a certain component, it means that other components may be further included, and one or more other features, not excluding other components, unless specifically stated to the contrary. It is to be understood that it does not preclude the presence or addition of any number, step, action, component, part, or combination thereof.

The terms "about", "substantially" and the like, as used throughout the specification, are used in or close to the numerical value when manufacturing and material tolerances specific to the stated meaning are presented, and are used in the sense of the present invention. To assist, accurate or absolute figures are used to prevent unfair use of the stated disclosure by unscrupulous infringers. As used throughout the specification of the present invention, the term "step (to)" or "step of" does not mean "step for".

In the present specification, the term "unit" includes a unit realized by hardware, a unit realized by software, and a unit realized using both. Further, one unit may be realized using two or more hardware, or two or more units may be realized using one hardware. Meanwhile,'~ unit' is not meant to be limited to software or hardware, and'~ unit' may be configured to be in an addressable storage medium or configured to reproduce one or more processors. Thus, as an example,'~ unit' refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, and procedures. , Subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays and variables. The components and functions provided in the'~ units' may be combined into a smaller number of elements and'~ units', or may be further divided into additional elements and'~ units'. In addition, components and'~ units' may be implemented to play one or more CPUs in a device or a security multimedia card.

In this specification, some of the operations or functions described as being performed by the terminal, device, or device may be performed instead in a server connected to the terminal, device, or device. Likewise, some of the operations or functions described as being performed by the server may also be performed by a terminal, device, or device connected to the server.

In this specification, some of the operations or functions described as mapping or matching with the terminal means mapping or matching the unique number of the terminal or the identification information of the individual, which is the identification information of the terminal. Can be interpreted as.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram illustrating a system for providing a non-face-to-face parking order service according to an embodiment of the present invention. 1, a non-face-to-face parking order service providing system 1 includes at least one order payment device 100, a parking order service providing server 300, at least one POS terminal 400, and at least one autonomous It may include a driving cart 500. However, since the non-face-to-face parking order service providing system 1 of FIG. 1 is only an embodiment of the present invention, the present invention is not limitedly interpreted through FIG. 1.

In this case, each component of FIG. 1 is generally connected through a network 200. For example, as shown in FIG. 1, at least one order payment device 100 includes a parking order service providing server 300, at least one POS terminal 400, and at least one autonomous device through the network 200. It may be connected to the driving cart 500. In addition, the parking order service providing server 300 may be connected to at least one order payment device 100, at least one POS terminal 400, and at least one autonomous cart 500 through the network 200. . In addition, at least one POS terminal 400 may be connected to the parking order service providing server 300 through the network 200. In addition, at least one autonomous cart 500 may be connected to at least one order payment device 100, a parking order service providing server 300, and at least one POS terminal 400 through the network 200. .

Here, the network refers to a connection structure in which information exchange is possible between respective nodes such as a plurality of terminals and servers, and examples of such networks include a local area network (LAN) and a wide area communication network (WAN: Wide Area Network), Internet (WWW: World Wide Web), wired/wireless data communication network, telephone network, wired/wireless television communication network, etc. Examples of wireless data networks include 3G, 4G, 5G, 3GPP (3rd Generation Partnership Project), 5GPP (5th Generation Partnership Project), LTE (Long Term Evolution), WIMAX (World Interoperability for Microwave Access), and Wi-Fi. , Internet, LAN(Local Area Network), Wireless LAN(Wireless Local Area Network), WAN(Wide Area Network), PAN(Personal Area Network), RF(Radio Frequency), Bluetooth(Bluetooth) network, NFC( Near-Field Communication) network, satellite broadcasting network, analog broadcasting network, DMB (Digital Multimedia Broadcasting) network, etc. are included, but are not limited thereto.

In the following, the term “at least one” is defined as a term including the singular number and the plural number, and even if the term “at least one” does not exist, each component may exist in the singular or plural, and may mean the singular or plural. It will be self-evident. In addition, it will be possible to change according to the embodiment that each component is provided in a singular or plural.

The at least one order payment device 100 may be a device that outputs an orderable product using a non-face-to-face parking order service related web page, app page, program, or application, and performs a payment process when a product is selected. . In this case, the at least one order payment device 100 may be a device that manually receives or automatically recognizes the vehicle number of a vehicle of a user who places an order. At this time, the order payment device 100 may be a device that receives the number of the vehicle through a camera, and the parking position of the vehicle is input through at least one camera (not shown) installed in the parking lot or input by the user's input. It may be a receiving device. And, at least one order payment device 100 is a device to be output from the remote POS terminal 400 by transmitting the vehicle number, parking location and order product to the parking order service providing server 300 when payment is completed. Can be

Here, at least one order payment apparatus 100 may be implemented as a computer that can access a remote server or terminal through a network. Here, the computer may include, for example, a navigation system, a notebook equipped with a web browser, a desktop, a laptop, and the like. In this case, the at least one order payment device 100 may be implemented as a terminal capable of accessing a remote server or terminal through a network. At least one order payment device 100, for example, as a wireless communication device that is guaranteed portability and mobility, navigation, PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular) , PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband) Internet) terminal, smart phone (Smartphone), smart pad (Smartpad), tablet PC (Tablet PC), such as all kinds of handheld (Handheld) based wireless communication devices may be included.

The parking order service providing server 300 may be a server that provides a non-face-to-face parking order service web page, an app page, a program, or an application. In addition, the parking order service providing server 300 is registered and managed by assigning a unique identification code to at least one order payment device 100, at least one POS terminal 400, and at least one autonomous driving cart 500. It can be a server that does. At this time, the parking order service providing server 300, when the order and payment is completed in the order payment device 100, transmits it to the POS terminal 400 to store the products ordered by the employees remotely in the autonomous driving cart 500. It may be a server that displays on the screen. And, the parking order service providing server 300, when all of the products ordered from the POS terminal 400 are contained in the autonomous driving cart 500 and the delivery menu is selected from the POS terminal 400, the autonomous driving cart 500 It may be a server that transmits a control signal so that the vehicle moves to the parked position. In addition, the parking order service providing server 300 confirms that the cart is emptied because the value input from the weight or pressure sensor of the autonomous driving cart 500 is less than a preset value, or pickup is completed at a user terminal (not shown). When an event is input, it may be a server that transmits a control signal to return the autonomous cart 500 to its original position. In addition, the parking order service providing server 300 may be a server that identifies a vehicle number through at least one camera and identifies a parking area in which the identified vehicle number is located. To this end, each parking area may be classified as an IoT node, or a code that can be identified for each parking area may be displayed on a panel, etc., and may be configured to be classified by a camera or the like. In addition, the parking order service providing server 300 may be a server that enables the order payment device 100 to identify a vehicle number through a camera.

Here, the parking order service providing server 300 may be implemented as a computer that can access a server or terminal in a remote location through a network. Here, the computer may include, for example, a navigation system, a notebook equipped with a web browser, a desktop, a laptop, and the like.

The at least one POS terminal 400 may be an employee's terminal using a web page, an app page, a program, or an application related to a non-face-to-face parking order service. The POS terminal 400 may be a terminal that prints or displays an order paper on a screen so that the product that has been paid for by the order payment device 100 is placed in the autonomous driving cart 500. And, at least one POS terminal 400 may be located in a place where the employee can put the product in the cart, and if the order payment device 100 is installed outside, the POS terminal 400 will be installed inside the building. I can. In addition, the at least one POS terminal 400 may be a terminal that maps an ordered product and a cart by scanning a barcode or the like of the autonomous driving cart 500 and then scanning a barcode or the like corresponding to an order number. That is, the autonomous driving cart 500 needs to move to a vehicle parked in the parking lot, because it is necessary to identify which vehicle the cart containing the product should go to. If the order number (vehicle number + parking area)-cart number is mapped, the cart can go to the location of the vehicle that ordered the product, but if the POS terminal 400 does not specify this, the product is This is because there is no information on where the self-driving cart 500 should go to.

Here, at least one POS terminal 400 may be implemented as a computer that can access a server or terminal in a remote location through a network. Here, the computer may include, for example, a navigation system, a notebook equipped with a web browser, a desktop, a laptop, and the like. At this time, at least one POS terminal 400 may be implemented as a terminal that can access a remote server or terminal through a network. At least one POS terminal 400, for example, as a wireless communication device that is guaranteed portability and mobility, navigation, PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS(Personal Handyphone System), PDA(Personal Digital Assistant), IMT(International Mobile Telecommunication)-2000, CDMA(Code Division Multiple Access)-2000, W-CDMA(W-Code Division Multiple Access), Wibro(Wireless Broadband Internet) ) It may include all kinds of handheld-based wireless communication devices such as terminals, smart phones, smart pads, and tablet PCs.

The at least one autonomous cart 500 may be a device that moves to each location of a parking area along a cart guide line and returns to its original position using a web page, app page, program or application related to a non-face-to-face parking order service. . At this time, the at least one autonomous cart 500 may be a cart managed by the parking order service providing server 300 by giving a unique identification code. And, the autonomous driving cart 500 may be a device that moves along a cart guide line laid on the parking lot floor, and when a unique identification code assigned to each parking zone is input, it is previously mapped to the unique identification code and moved to a stored location. It may be a device that returns to its original place after doing so. Here, the autonomous driving cart 500 may be a device including an algorithm and a control device for autonomous driving.

Here, the at least one autonomous cart 500 may be implemented as a computer that can access a remote server or terminal through a network. Here, the computer may include, for example, a navigation system, a notebook equipped with a web browser, a desktop, a laptop, and the like. At this time, the at least one autonomous cart 500 may be implemented as a terminal capable of accessing a remote server or terminal through a network. At least one autonomous driving cart 500 is, for example, a wireless communication device that guarantees portability and mobility, and includes navigation, personal communication system (PCS), global system for mobile communications (GSM), personal digital cellular (PDC) , PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband) Internet) terminal, smart phone (Smartphone), smart pad (Smartpad), tablet PC (Tablet PC), such as all kinds of handheld (Handheld) based wireless communication devices may be included.

2 is a block diagram illustrating a parking order service providing server included in the system of FIG. 1, and FIGS. 3 and 4 illustrate an embodiment in which a non-face-to-face parking order service is implemented according to an embodiment of the present invention. It is a drawing for explanation.

Referring to FIG. 2, the parking order service providing server 300 may include a storage unit 310, a pickup request unit 320, and a delivery request unit 330.

At least one order payment device 100, at least one POS terminal 400, and at least one of the parking order service providing server 300 or another server (not shown) interlocked with each other according to an embodiment of the present invention In the case of transmitting a non-face-to-face parking order service application, program, app page, web page, etc. to the autonomous driving cart 500 of, at least one order payment device 100, at least one POS terminal 400, and at least one The self-driving cart 500 may install or open a non-face-to-face parking order service application, program, app page, web page, and the like. In addition, a service program may be driven in at least one order payment device 100, at least one POS terminal 400, and at least one autonomous cart 500 by using a script executed in a web browser. Here, the web browser is a program that allows you to use the Web (WWW: World Wide Web) service, which means a program that receives and displays hypertext described in HTML (Hyper Text Mark-up Language). For example, Netscape , Explorer, Chrome, etc. In addition, the application refers to an application program on the terminal, and includes, for example, an app running on a mobile terminal (smartphone).

Referring to FIG. 2, the storage unit 310 may store a location and an area code of at least one area in a parking area. At this time, the location of at least one area may be XY coordinates or GPS coordinates. The area code is an IoT-based mesh type, which is stored in an IoT device such as RFID or beacon arranged at regular intervals in a grid pattern to distinguish each area, or separate each area code through a camera. In this case, the code may be assigned to each parking area and written on the sign. For example, in the A parking area, characters such as A-1 and A-2 may be provided as a printed sign.

In summary, the parking area is divided into at least one area where the vehicle and the autonomous driving cart 500 will be located in the parking area, and an area code identifying at least one divided area is given, and the ordered and paid products are A cart guide line may be installed from a starting point, which is contained in the autonomous driving cart 500 and departing, to an arrival point, which is at least one area. At this time, the cart guide line may correspond to a guide loop cable built into the floor. In addition to these cart guide lines, it can also be designed so that the cart cannot be taken outside. For example, if Zone A is a parking zone and a cart can move, if a cart stop line is installed along the outer periphery of Zone A, outside of Zone A, the wheels of the autonomous cart 500 are no longer locked. ) Is caught and does not move. Such devices may be further provided to prevent cart theft or theft.

Most of the cart guide lines are constructed by laying guide loop cables along the line where the cart moves, then applying a backup material on it, and placing urethane seallant on it. For example, an asphalt cutting work is carried out along the cart guide line, followed by water cleaning with a high-pressure sprayer, then the guide roof line is buried, a backup material is inserted, urethane seallant is injected, and the surface finish is performed. It is completed by installing an inspection box and embedding a steel plate for induction blocking of communication lines. The asphalt cutting work is, for example, 10mm wide and 30-40mm deep, but is not limited thereto.

In a wired guidance method such as a cart guide line, an object (magnetic, guide line, optical tape, spot) to be detected by a sensor is installed on the floor, and the autonomous cart 500 moves along the driving line (cart guide line) by detecting this. It is a technique that induces you to do. Compared to the sensor used in the high-precision wireless induction method, this technology shows high precision results in discriminating objects even when a low-cost sensor is used. However, as described above, since the asphalt interior construction is essential, there is a disadvantage in that a work such as buried/attached to the floor of the work environment is required, and it is difficult to change and maintain the induction line. As the wired induction method, a magnetic, optical, inductive, and magnetic-gyro induction method may be further used. Magnetic, optical tape, electromagnetic guidance wire, etc. can be used as guidance lines buried/attached to the work environment, and infrared rays, Hall sensors, and cameras can be used as sensors to detect.

The above-described method is a wire guidance type, and in addition to this, a wireless guidance type may be further used. The wireless guidance method does not create a path on the floor, but creates a virtual path in advance, and guides it to a target point using the current position of the autonomous driving cart 500 obtained through position measurement sensors. In the wireless induction method, a receiver or transmitter is installed on a wall, pillar, or ceiling, and a corresponding transmitter or receiver is installed on the autonomous driving cart 500 to induce the autonomous driving cart 500 through measured coordinates. The wireless guidance method enables complete autonomous driving because there is no guidance line, and it is flexible to change and maintain the driving line. However, since induction is performed wirelessly, the position measurement may not be accurate due to obstacles as well as distortion of signals such as disturbance of radio waves and refraction of light. Also, the difference in precision can be large depending on the work environment and the characteristics of the transmitter/receiver installed in the unmanned transport vehicle. As a wireless induction method, laser navigation, RFID, etc. can be used.In the method of using laser navigation, a reflector is attached to the wall and the laser from the laser navigation is reflected to measure the position of the autonomous driving cart 500, and RFID is a number / By installing the transmitter in the work environment, it is possible to measure the position of the autonomous driving cart 500 using data transmitted from the receiver.

In addition, an omni-directional driving method may be used. Representative methods of the omni-directional driving method include Swerve, Holonomic, and Mecanum driving methods. The omni-directional driving method is a driving method for effectively driving a narrow space in an industrial site, and refers to a method in which a posture can be changed without changing direction by using a special driving wheel mechanically in the driving unit. Among them, the swab driving method is a method that can move in all directions through a mechanical movement method by installing a driving unit capable of rotating 360° at a right angle to the driving driving unit. This is easy to control when using only one swarb driving unit, but the larger the body, the more difficult it is to control because it is necessary to use several driving units, and since it is a method of driving after rotating the wheel, the driving may proceed very slowly. The second holonomic driving method is a driving method that uses an omni wheel, a special wheel in which several rollers are attached parallel to the rotation axis on the circumferential surface of the main wheel. This is a simple system configuration and control, but the torque is weak and there is no brake of the rollers, which causes frequent slip, which can greatly reduce the driving precision. Lastly, the mecanum drive method uses a special wheel similar to the holonomic drive method, but unlike the omni wheel with rollers attached parallel to the rotation axis, a special wheel called the Mecanum wheel attached at an angle of 45° to the rotation axis is used. This is the driving method used. This has all the advantages of the holonomic driving method, but has a relatively large torque and less slipping. In addition to the above-described methods, various methods may be used, and different methods may be combined or combined according to each embodiment or installation location. In addition, it is not limited to the methods listed and is not excluded for reasons not listed.

When the order and payment is completed by the order payment device 100 and the vehicle number is recognized, the pickup request unit 320 maps the area code of the area where the vehicle having the vehicle number is parked to the order number and stores the pickup request event. Can be printed. To this end, the order payment apparatus 100, when at least one type of product is output on the screen, and when at least one of the output products is selected, proceeds with payment when at least one type of payment method is input, When payment is completed, a pickup request event may be output and transmitted to the pickup request unit 320. In addition, the order payment device 100 may receive the vehicle number of the customer's vehicle ordered before proceeding with the payment and the area code of the area where the vehicle is parked.

The pickup request unit 320 may transmit the order details received from the order payment device 100 to the POS terminal 400. The POS terminal 400 may output a pickup request event output from the order payment device 100, and may receive a driving start of the autonomous driving cart 500 when the pickup of the product is completed. That is, order and payment data is transmitted to the order payment device 100->pickup request unit 320->POS terminal 400->autonomous driving cart 500, and the autonomous driving cart 500 is When moving along the guide line and an area code corresponding to at least one area is input, the cart guide line may be moved to a position corresponding to the input area code. At this time, the autonomous driving cart 500 may use an Automatic Guided Vehicle (AGV). AGV refers to a vehicle that autonomously travels on a preset route. In the service according to an embodiment of the present invention, since each parking area is already partitioned and coordinates are stored, and the structure or arrangement of each parking area is the same, considering this situation, on the line attached using an infrared sensor. It is guided through the path of and can deliver the goods to the vehicle located in the parking lot, that is, to the customer non-face-to-face.

When a pickup completion signal is received, the delivery requesting unit 330 may request the driving of the autonomous cart 500 to an area having an area code that identifies the order number and is mapped to the identified order number and stored. At this time, in the case of the autonomous driving cart 500 that can obtain information about the surrounding environment, it is possible to detect obstacles using an ultrasonic sensor and adjust the direction of the vehicle through serial wireless communication. The driving cart 500 may be controlled. When delivering within a limited parking area using AGV, the AGV receives input from the POS terminal 400, uses Wi-Fi and ultrasonic sensors to identify the location in the limited parking area by the AGV and automatically sets the route. Goods can be transported to the vehicle that ordered them. If the user who ordered the product, that is, receives an input from the customer's terminal (not shown), through communication with the user terminal, an infrared sensor, Wi-Fi, and a method of setting a route using the location of the current AGV are added. The accuracy can be further improved. At this time, the AGV equipped with an infrared camera may be attached to the ground in advance, and the AGV may determine the landmark through the infrared camera, recognize it, and follow the path.

For example, a user terminal (a customer who ordered a product) places an order through the order payment device 100, and a parking order service providing server 300 requests the loading of goods to the POS terminal 400 and assigns a task. In this case, the POS terminal 400 may input the corresponding parking area to the AGV, and the user terminal may input the area code of the parking area in which the vehicle is parked in the parking lot. The AGV may set a destination based on data input from the POS terminal 400 and the user terminal, calculate a route accordingly, and adjust a delay time while following the route. It can communicate with the user terminal through a Bluetooth sensor, but Wi-Fi can also be used. In addition, it is possible to move along a line through an infrared sensor, but it does not exclude moving while drawing a map in real time by detecting surrounding objects with a lidar or radar sensor. The infrared sensor is a sensor used to detect an object or send a signal using infrared, which is a wavelength of 780nm~1mm that humans cannot see. In this case, when an infrared sensor including an infrared LED and an ADC (Analog to Digital Converter) is used, it does not spoil the aesthetics or interfere with the person because humans cannot see it, but AGV can find a path through it. In addition, if the infrared rays emitted from the LED are reflected on the ground and lines, the sensor detects the intensity of the infrared rays, and the ADC calculates the intensity of the infrared rays to simplify it to dark (0) and bright (1). AGV can use this to detect the line.

AGV can prepare for a new input by emptying the input buffer when Bluetooth communication is connected to an arbitrary application through a UART (Universal Asynchronous Serial Receiver and Transmitter) PORT. When an input is received from the affiliated store terminal 400, a corresponding input value is processed as the number of recipients corresponding to each destination, and a route may be selected so that only the purpose for which the customer exists is passed based on this. When the route selection is complete, the infrared sensor in the lower half of the front of the AGV can be initialized for route tracking. The infrared sensor detects the line attached to the ground by classifying the contrast, and the AGV can track the path by changing the direction so that the detected line is always recognized by the center sensor. When reaching a forked road, you can go straight/turn right/turn left/backward according to the selected route. When it reaches the destination, it waits for a certain delay, and when the user terminal receives the acknowledgment code, the reception factor of the destination can be reduced. When passing through all the selected routes through all destinations, the total number of recipients at each destination at the present time is summed up, and if it is greater than 0, it waits for an additional delay time in proportion to it and returns to the starting point. If it is 0, it is possible to immediately return to the starting point without waiting and wait for a new input from the affiliated store terminal 400. Of course, in the case of going to only one destination, it waits for a certain delay time upon reaching the destination, and when the user terminal receives the acknowledgment code, it can return to the origin immediately.

Meanwhile, at least one payment method may include a high pass payment. When the order payment device 100 is provided in the form of a kiosk, payment is made by inserting a card, sliding, or contacting. In the case of high-pass payment, the card inserted into the high-pass terminal and the order payment device 100 Since the payment is made through communication between the antennas of the device, you can literally proceed with the contactless payment. At this time, the order payment device 100 receives the card payment result when the high-pass payment is made, recognizes the high-pass terminal of the vehicle, requests payment information, and transmits the result after performing the card payment in the high-pass terminal. It may include an antenna. In addition, the antenna and the high-pass terminal of the vehicle may communicate with each other through DSRC (Dedicated Short-Range Communications), but the present invention is not limited thereto.

In addition, the non-face-to-face parking order service providing system 1, when a vehicle is parked in at least one area by photographing at least one area in the parking area, the vehicle number of the parked vehicle and the area assigned to the at least one area After identifying the code, it may further include at least one edge camera (not shown) that is transmitted to the order payment device 100. Unlike normal cameras, edge cameras are cameras that combine AI to analyze images from the camera end and send the results. In this case, the edge camera may be provided to identify the area code, or may include an algorithm for reading the license plate to identify the vehicle number.

The parking order service providing server 300 of the non-face-to-face parking order service providing system 1 acquires camera images, event analysis information, camera profile and setting information from edge cameras, classifies them, and stores and manages them in the system. In order to analyze the image, the parking order service providing server 300 acquires image and metadata information, enters and exits the vehicle, whether there is a vehicle parked in the parking area, and if so, the area of the parking area where the vehicle is located. Video analysis to check what the code and vehicle number are. The parking order service providing server 300 may acquire various types of situation information and classify data according to a collaborative analysis method. The situation information obtained from the parking order service providing server 300 includes status information such as event information, profile information, PTZ setting value, etc. analyzed by the edge camera, event information analyzed by the parking order service providing server 300, and object information. , Environment (weather) information, etc. Thereafter, through the analysis engine of the parking order service providing server 300, control information for collaboration with the edge camera may be adaptively generated in various situations.

Data can be transmitted and received using a REST (REpresentational State Transfer) API for system linkage between the parking order service providing server 300 and edge cameras, and context information can be transmitted using a JSON (JavaScript Object Notation) lightweight data exchange format. I can deliver. The collaboration analysis engine may generate collaboration control information through event-based analysis, rule-based analysis, and learning-based analysis method of the situation information received from the parking order service providing server 300. The collaboration analysis engine includes an I/F module for receiving situation information from the parking order service providing server 300, a situation information data classification module, a collaboration analysis module, a collaboration decision making module, a collaboration control metadata builder, and feedback. It can consist of information processing I/F.

The edge camera information acquisition I/F (InterFace) module of the parking order service providing server 300 acquires edge camera event analysis information, camera PTZ setting information and function setting information such as defog, thermal image, and image analysis information I /F is the image analysis information, event information, object information, environment (weather) information, etc., and manager control information acquisition I/F is an interface for the administrator to obtain direct camera control information, and context information data classification module Is a module for classifying context information data for collaborative analysis based on the analysis module, and the event-based analysis module may generate appropriate collaboration control rules for each event through analysis of anomaly event. For example, if a vehicle "enters" a parking lot, places an order and payment in the order payment device 100, and then "parks" in the A-13 (area code) area (stops for a preset minute (min)) )), Analyze as a "waiting" event waiting for delivery of the goods.

At this time, since one edge camera cannot shoot all areas including the parking area and the order area, for example, the “entry” of the vehicle (object) with the vehicle number “1234” in the edge camera 1 located at the entrance of the parking lot. When an event occurs and the object moves thereafter, camera #2 that can collaborate, that is, camera #2 that shoots up to the "order area", is selected based on the direction in which the object moves. Thereafter, when an object is moved from the ordering area to the parking area, the object tracking starts by selecting camera 3, which is an event-generating camera covering it, and the vehicle number "1234" on camera 4 among the plurality of cameras that photograph the parking area. When an in-vehicle is detected, camera 4 is selected and object monitoring is performed. At this time, when the autonomous driving cart 500 appears on camera 4, and a "leaving out" event occurs in which a human subject comes out, puts things, and leaves, the 4th camera sends a "leaving out" event to the parking order service providing server ( 300) so that the timing of the return signal of the autonomous driving cart 500 can be determined.

Rule-based analysis module is a module that generates a specific rule by analyzing frequently occurring abnormal situations in advance, and is executed when two or more conditions are satisfied. For example, when an "entry" event occurs and the object size is small, a rule of expanding the object size through zooming in edge camera 1 may be applied. However, it is not limited thereto. The learning-based analysis module is a module that creates a cooperative control rule by learning object and PTZ control information based on a Random Decision Tree in case an exceptional situation that cannot be accurately analyzed based on an event analysis method and rule-based analysis occurs. . For example, as input information, object XY coordinate information, object size information, and object speed information may be used, and camera PTZ control information (CC, Camera Control) may be output as a result value.

The collaboration decision-making module is a module that determines collaboration decisions such as camera control or video analysis reanalysis based on the information analyzed through the collaboration analysis module, and the collaboration control metadata builder delivers the determined collaboration control information to each system. It is a module that creates metadata for The feedback information processing I/F is a module that delivers the generated metadata to each system and receives feedback information from each system. The collaboration situation means a case in which an event occurs in the edge camera or the parking order service providing server 300. RTSP (Real-time Streaming Protocol) can be used to display camera images, and ONVIF (Open Network Video Interface Forum) protocol can be used for communication between the parking order service providing server 300 and the edge camera, but is not limited thereto. Does not.

When the parking order service providing server 300 operates the system based on collaboration, situation information collected from a plurality of edge cameras may be output in real time, and the collaboration situation may be recognized based on various collected situation information. As an example of an event-based analysis, when a “roaming” event of a vehicle occurs, users who do not understand the order and delivery system of the present invention can move the Pan and Tilt of the camera based on the object location information for continuous object tracking. It may be recognized as the POS terminal 400 may request the employee guidance.

In addition, the order payment device 100 is connected to the POS (Point of Sale) terminal 400 of the person in charge of picking up the product, and the microphone and speaker of the POS terminal 400, and the order payment device 100 It may be connected to the POS terminal 400 to transmit and receive voice data through a microphone and a speaker. In other words, the user, who is a customer, does not directly touch the screen, but speaks with a voice about which product to choose among the products displayed on the screen, so that it is output to the POS terminal 400 located remotely, and the POS terminal 400 is used. It can be arranged so that you can take orders in a way that you talk to an employee who does. For example, the elderly or people unfamiliar with kiosks may find it difficult to select from a kiosk and proceed to the payment step, and there are people who are reluctant to touch the touch panel when an infectious disease such as corona turns. Accordingly, when the person in charge speaks the identification number of the desired item or the item name by voice, and transmits the payment screen to the order payment device 100 so that the person in charge pays the summed amount through the POS terminal 400, the user who is a customer May proceed with payment by inserting a card into the order payment device 100. Alternatively, in the case of using O2O (Online to Offline) service, this step can also be skipped, and the parking zone area code and own vehicle number can be stated and payment can be made at the user terminal.In this case, order and payment through a kiosk Because you don't have to line up to do this, the movement of the vehicle can be much shorter and more concise.

The autonomous driving cart 500 may start driving to return to a previously stored starting point when the weight or pressure sensed by the weight sensor or pressure sensor included in the autonomous driving cart 500 is less than a preset threshold. The self-driving cart 500 contains products ordered and paid by the user, and the point of time to return them must be determined. When the loading and unloading of the ordered and paid products is finished, that is, the weight or pressure on the self-driving cart 500 It may be when there is no. Of course, as described above, when an outgoing event occurs from the edge camera through the collaboration platform, you can start, or you can start counting at a certain time to determine the return point, and apply it together with the values monitored by each sensor. Thus, various implementations may be performed according to embodiments.

In addition, when the vehicle number is manually input or automatically recognized through a camera, the order payment device 100 according to an embodiment of the present invention recommends food to be ordered through the past order history previously mapped to the vehicle number and stored. May be. In general, the reason for going to the mart is not only one-time purchase, but also recurring purchases that periodically purchase the same product repeatedly. For example, shopping for consumables such as A4 paper, cosmetics, tissue paper, daily necessities such as masks, alcohol disinfectants, detergents, food materials, etc. has a purchase pattern in which the same product is periodically and repeatedly purchased. The recommendation algorithm in such a periodic repetitive purchasing environment is different from the existing algorithm that determines the recommendation ranking based only on the evaluation score or purchase status according to the preference of the product, how often the product is repeatedly purchased or what products are purchased at the same time. It is possible to obtain a more suitable result by making it a criterion for recommendation.

It is possible to use a recommendation algorithm for periodic purchase products based on how often it is repeatedly purchased based on the case of shopping at a mart as a main criterion for recommendation. For this purpose, the first may include a module that updates the purchase cycle and the number of repeated purchases for each product offline, and the second automatically selects the products corresponding to the purchase cycle by analyzing the user's past purchase history. It may include an automatic selection platform to do so. Third, it is possible to use a collaborative filtering recommendation method that recommends products based on frequent purchases of other users with similar purchase patterns. By using the automatic selection platform, each user is notified of a list of products to purchase by time, thereby eliminating the case of forgetting and ordering, thereby increasing sales and securing fixed customers. The collaborative filtering recommendation method always keeps the list of frequently purchased products for each individual up-to-date, so that when selecting the top t products to be recommended, only the regularly purchased products of similar users are selected, so the execution speed is fast in online execution.

A method of recommending collaborative filtering according to an embodiment of the present invention proceeds through three steps of a data presentation step, a similar user selection step, and a recommendation step. First of all, in the data presentation stage, the input data is a collection of past purchase histories for m users and n products. It is usually expressed as an m × n user-product matrix R, and each element rij of the matrix is expressed as 1 when user i purchases product j, and 0 when user i does not. Alternatively, depending on the system, rij can be used to represent user i's evaluation score for product j.

Second, similar users are selected. In this step, user similarity can be measured. In the similar user selection step, k-nearest neighbors are selected for each user u in the order of the highest similarity between him and the user. Pearson Similarity, Cosine Similarity, and Jaccard Similarity can be used as measurement criteria for user similarity.

Pearson similarity is measured by the correlation coefficient for the rating of the product evaluated by both users a and b, and is calculated as in Equation 1 below.

Here, rai and rbi are respective ratings for product i evaluated by both users a and b, and q denotes the number of products evaluated by both users a and b among n products. The bar of ra and rb means the average of the ratings for all products evaluated by both users a and b, respectively.

The cosine similarity is measured as a cosine value representing an angle between the two vectors by displaying the ratings of products evaluated by both users a and b as a vector, and is calculated as in Equation 2 below.

Here, the product of the vector a and the vector b (Cdot) means the dot-product of the two vectors, which is calculated as sigma raixrbi from 1 to q. Each of the two vectors located in the denominator means the length of the vector, and the root i is calculated as the square of sigma rai from 1 to q and the square of rbi.

The jacquard similarity between the two sets A and B is defined as the ratio of the size of the intersection of the two sets and the union as shown in Equation 3 below.

Here, A and B refer to a set including only products evaluated (purchased) by users a and b.

Pearson similarity and cosine similarity are calculated according to the value of the rating, so that the similarity has a value between -1 and +1, and the jacquard similarity is the number of products jointly evaluated by two users a and b, regardless of the value of the rating. The larger is, the larger the value, and the similarity has a value between 0 and 1. On the other hand, since Pearson similarity and cosine similarity are calculated only for products that are jointly evaluated by two users, there is a weakness that inaccurate results may be produced when the number of jointly purchased products is very small. For example, if there is one joint purchase product and the rating for the product is the same by chance, the similarity is 1, which has the highest value.

As the final step of collaborative recommendation, the top-N items in the order of the highest recommendation prediction score among the products purchased or evaluated by k similar users of user u are recommended. As shown in Equation 4, the recommended prediction score for product i is calculated as a value obtained by weighting the ratings for product i of k similar users by the degree of similarity of each user. However, recommended products are recommended only for products that the user u has never purchased.

However, in the case of using the Pearson similarity, the recommended prediction score is obtained using the following Equation 5.

Based on the above-described concept, in the recommendation algorithm in a periodic purchase environment, the purchase frequency update that recalculates the purchase cycle of the product offline every time a purchase is confirmed, and the purchase frequency update, each time a user enters Whenever an order is placed, automatic selection that automatically selects the products corresponding to the cycle to be purchased and puts them in the recommended product shopping cart, and recommends the favorite products of other users with similar purchase patterns by collaborative filtering. May include a Collaborative Filtering Recommendation System.

First, the purchase cycle calculation and update is performed by analyzing the purchase history of each user for users who purchase daily necessities such as food ingredients, detergents, cosmetics, etc., and the number of repeated purchases per user for each product. Is calculated and stored to keep the latest information at all times. The purchase cycle according to the history of user u's purchase of product i is expressed as Freq(u, i), the number of repeated purchases in the meantime is Count(u, i), and the last purchase date is Last(u, As i), the visit period at the time of consideration for the latest purchase can be defined as Visit(u, i), and immediately before the current visit date, such as Visit(u,i)=(today-Last(u,i))/7 It is calculated by the date interval between the purchase date and the unit is mainly set.

At the initial application point of this recommendation, since the purchase history for a certain period of time must be stored as data, the Freq(u, i) value at the beginning of the operation is collectively assigned as shown in Equation 6 below. In addition, Count(u,i) at the beginning of the operation is the number of purchases after the reference point in time and is collectively assigned as shown in Equation 6.

Here, First(u, i) means the first purchase date after the reference point. For example, if you set the reference point as May 1, 2020, and you want to use the recommended platform from the current point, the purchase period of the last purchase minus the initial purchase date is extracted by extracting the record of the user u purchasing product i. After calculation, divide by the number of purchases so far, and the average purchase cycle is calculated. However, since the purchase cycle will be initialized to one week at the time of initial purchase, it is the addition of one week (= 7 days) to Last (u, i)-First (u, i) in Equation 6 when calculating the purchase cycle. Thereafter, each time the user u makes a purchase, the purchase cycle, the number of repetitive purchases, and the final purchase date must be updated for each purchased product i.This process takes place after the user decides to purchase. You can set and process the purchased products of the day collectively offline.

In the case of initial purchase, that is, when Last(u, i) = null, the purchase cycle is reset to "1 week", and when re-purchased, the visit period at the time of purchase (=Visit(u, i)) and the existing The "average" value with the purchase cycle (=Freq(u, i)) is designated as the new purchase cycle value. For each user u and purchased product i in the new purchase list, modify the Freq, Count, and Last values. In general, the number of actual purchased products per user is very small compared to the total number of products, so the user-product arrangement is used as above when storing in memory for online processing, but when storing in the database, it is stored in units of records (tuples) including fields. It is efficient to store it in a table. (userID, itemID, Freq, Count, Last) Here, you can update to keep the latest Freq, Count, Last values according to the above algorithm by using userID and itemID as keys of the table.

The second is the automatic selection process. In the case of a user who periodically purchases various daily necessities at a specific shopping mall, it would be convenient if the user does not directly select the corresponding products and automatically puts them in the shopping cart at the corresponding period. Automatic selection is a type of self-recommendation system for such a service, and when a user is placed in the order payment device 100 while boarding a vehicle, it corresponds to the time to purchase from among the products frequently purchased with the vehicle number. An algorithm may be configured to select s products to be placed on the screen of the order payment device 100. Whether each product corresponds to the purchase time can be compared with Freq(u, i) by calculating Visit(u, i) during the last visit.

Products frequently purchased for each user are defined as a "familiar product set", and since purchase cycles vary according to the characteristics of the product, regular products can be classified into a plurality of groups for each purchase cycle. For example, the j weekly regular product set can be defined as Favoritj(u,k), which means the set of regular products corresponding to the purchase cycle j group that user u frequently purchases, and user u It is a set of products including k items in the order of the shortest purchase cycle among products whose purchase cycle belongs to group j among the products that have been purchased. However, if the number of repeated purchases of a product is small, the purchase cycle is meaningless, so only products with a certain number of repeated purchases of c or more are included. The value of j, which means purchase cycle group, refers to each group by classifying the purchase cycle into groups such as 2 weeks, 4 weeks, 8 weeks (2 months), 16 weeks (4 months), 40 weeks (more). It is denoted as 2, 4, 8, 16, and 40, and products with a purchase cycle corresponding to the value between them should be included in the regular products of the corresponding group by raising the purchase cycle value. For example, a product with a purchase cycle of 2.5 weeks is put into the regular product set of week 4, and a product with a purchase cycle of 42 weeks is put in week 40.

When a new purchase occurs, the purchase cycle, the number of repeated purchases, and the final purchase date for each product in the purchase list are regularly updated at a certain time, and then the set of regular products is newly updated for all users as the next step. From a DB table that stores values of user u, product i-specific purchase cycle, repeat purchase count, and final purchase date values calculated from all purchase data from the base point to the present, in records (u, i, freq, count, last), It reads each record in turn and decides whether to put the product i into Favoritj(u,k). This process can be repeated as many times as the number of records in the DB table, and it is necessary to determine whether to include in Favoritj(u,k) for each record.To this end, items in Favoritj(u,k) are maintained in increasing order of frequency value. This is efficient, so when inserting item i, you can sort the insertion order and save them in order. In the automatic selection, if the user is located in the order payment device 100, it checks whether the time to purchase the products in the user's 5 regular product sets is correct, and then corrects the freq value if the user has not made a purchase for a very long time, Based on the corrected freq value, s items are selected and displayed on the screen, starting with products with small values.

Collaborative filtering is to recommend a certain number of products by referencing the regular products of other users with similar purchasing patterns.For similar users, after calculating the Jaccard coefficient for each parking regular product set of two random users. , The sum of these five values can be used as a user similarity between two users. The jacquard coefficient for the j-parking regular product set of users u1 and u2 is expressed as UserSimj(ui,u2), and can be calculated through Equation 7 below.

The similarity of users u1 and u2 UserSimj(ui,u2) is defined as the sum of 5 UserSimj(ui,u2) calculated for each j as in Equation 7.

The jacquard similarity considers only whether or not to evaluate or purchase regardless of the size of the rating. It can be seen that the magnitude of the rating is also reflected in the jacquard similarity obtained by Equation 7. In addition, it is much more efficient in terms of execution time because it has less computation compared to Pearson's similarity and cosine similarity. can do.

Since the rating for each product was not considered when calculating the jacquard similarity, a rating for each product should be given in order to recommend the preferred products of similar users by ranking as the next step. If an arbitrary user u1 frequently purchases product i, the evaluation score for each product (u1, i) is assigned to have a large value in inverse proportion to the purchase cycle, and if the product has never been purchased, it is assigned as 0. In addition, since a larger Count(u1, i) means that a product preference is higher, a related item may be added to the last term of Equation 9 below.

Since Freq(u1, i) has a maximum value of 40 weeks, the first two terms in Equation 9 have a value in the range [α,β].

The final step of collaborative filtering is to find the top-ℓ of similar users for the user u waiting for order, calculate the recommendation score Predict (u,i) for the product i they purchased or evaluated, and then this value is in the order of higher order. This is the step of selecting and recommending the top-t dogs. User u's recommendation score for product i is calculated as the average of the ratings for product i of similar user ℓ by weighting each user's similarity as shown in Equation 10.

However, rather than obtaining the recommendation score for all product i, it is limited to products belonging to the set of 5 regular products of similar users ℓ, but among these products, only products that u have not purchased before can be recommended. In Equation 10, the set L denotes a neighboring set composed of upper ℓ names with high similarity to the user u. Now, you can create an algorithm that recommends new products by referring to other users' regular products with similar purchasing patterns. In order to immediately recommend products in collaborative filtering recommendation for users who visit the mart by vehicle each time, as a pre-processing process, each time a purchase occurs and changes in the purchase history of the product, the purchase cycle, the set of regular products, and the evaluation score of the product , User similarity should be updated. Since this does not have to be done in real time, it is only necessary to process it offline in batch at a regularly designated time.

Hereinafter, the operation process according to the configuration of the parking order service providing server of FIG. 2 will be described in detail with reference to FIGS. 3 and 4 as examples. However, it will be apparent that the embodiment is only any one of various embodiments of the present invention, and is not limited thereto.

Referring to FIG. 3, (a) the parking order service providing server 300 may map and store an area code corresponding to at least one parking area and an XY coordinate corresponding thereto. And, (b) when the vehicle enters and the order payment device 100 says "please give me sausage, dumplings, ramen, dog food" by voice, the vehicle's vehicle number 1234 and the ordered product list are displayed at the POS terminal 400. When the payment screen is sent back to the order payment device 100 after calculation at the POS terminal 400, the user, who is a customer, inserts, slides or contacts a card, uses O2O simple payment, or pays with a high-pass terminal. Select and request payment. When payment is approved and payment is completed, a payment completion event is transmitted to the POS terminal 400, and if vehicle number 1234 is parked, the parking order service providing server 300 also includes the area code of A6 where the vehicle is located. It is transmitted to the POS terminal 400. At this time, the location of A6 where the vehicle is located may be automatically input through the above-described edge camera, or may be made manually by a user taking a seat and entering the area code, and an IoT device that divides the parking area. It may be automatically classified through, but is not limited thereto as described above.

When employees pick up the product and put it in the autonomous driving cart 500, the POS terminal 400 transmits the autonomous driving cart 500 and a start control signal to the autonomous driving cart 500, or directly, the autonomous driving cart 500 Enter the area code A6 to request departure. At this time, the self-driving cart 500 containing sausage, dumplings, ramen, and dog food moves to the parking area A6 along the cart guidance line, and waits in or outside the line A6. And, (d) Autonomous driving when the vehicle is confirmed after the user puts sausage, dumplings, ramen, or dog food into the trunk of a vehicle, or when the pressure or weight detected by the pressure sensor or weight sensor is less than the preset pressure or weight. The cart 500 returns to its original position along the cart guide line.

Referring to Figure 4 (a), a parking zone and a walking zone that can be moved on foot, and an order zone where the order payment device 100 is located so that orders can be placed. The traffic lines can be separated so that they do not overlap. This is because when a person moves on foot in the section where the vehicle and the self-driving cart 500 travel, it is difficult to control because there are many obstacles in the driving of the self-driving cart 500, and because the complexity increases, a delay may occur. . Accordingly, it is possible to separate the movement lines of a section in which a person moves on foot, a parking section, and a section ordered. (b) In addition, each parking area is equipped with a canopy to prevent overheating due to sunlight even when parking for a long time, and by dividing cart guide lines for each parking area, it is possible to prevent carts from colliding with each other. In addition, by using an ultrasonic sensor commonly used in the front and rear vehicle monitoring system, a collision can be prevented by transmitting ultrasonic waves according to the trigger pulse and measuring the distance by receiving the reflected ultrasonic waves. As a method of measuring the distance between objects using a beacon, it is possible to avoid obstacles or a situation in which carts collide with each other by dividing the region of interest according to the direction of the sensor and collecting data.

For example, because the autonomous cart 500 proceeds forward and backward, a region of interest is placed, and a collision prediction algorithm is performed when a new cart appears in the front, and a collision prediction algorithm is used when a new vehicle appears in the rear. Can be done. At this time, in order to recognize a new cart or object appearing in the rear, it is necessary to distinguish whether the cart is in a forward mode or a backward mode by interlocking OBD2 data. In order to determine the strength of the signal between terminals with a beacon signal, beacon signals can be transmitted and received for each minimum unit, avoiding each other, and the entire front or rear is scanned through the aforementioned infrared sensor or lidar. By doing so, you can also avoid collision.

Matters not described with respect to the method of providing the non-face-to-face parking order service of FIGS. 2 to 4 are the same as those described above or can be easily inferred from the description of the method of providing the non-face-to-face parking order service through FIG. Therefore, the description below will be omitted.

5 is a diagram illustrating a process of transmitting and receiving data between components included in the non-face-to-face parking order service providing system of FIG. 1 according to an embodiment of the present invention. Hereinafter, an example of a process in which data is transmitted/received between each component will be described with reference to FIG. 5, but the present application is not limitedly interpreted as such an embodiment, and is illustrated in FIG. 5 according to various embodiments described above. It is apparent to those skilled in the art that the process of transmitting and receiving data may be changed.

5, the parking order service providing server stores the location and area code of at least one area in the parking area (S5100), and when the order and payment is completed in the order payment device, and the vehicle number is recognized, the vehicle The area code of the area where the vehicle having the number is parked is mapped to the order number and stored, and a pickup request event is output (S5200).

In addition, when the pickup completion signal is received, the parking order service providing server identifies the order number and requests the autonomous driving cart to travel to an area having an area code that is mapped to the identified order number and stored (S5300).

The order between the above-described steps S5100 to S5300 is only an example and is not limited thereto. That is, the order of the above-described steps S5100 to S5300 may be mutually changed, and some of the steps may be executed or deleted at the same time.

Matters that are not described with respect to the method of providing the non-face-to-face parking order service of FIG. 5 are the same as those described for the method of providing the non-face-to-face parking order service through FIGS. 1 to 4 or can be easily inferred from the description. Therefore, the description below will be omitted.

The method of providing a non-face-to-face parking order service according to the exemplary embodiment described with reference to FIG. 5 may also be implemented in the form of a recording medium including instructions executable by a computer such as an application executed by a computer or a program module. . Computer-readable media can be any available media that can be accessed by a computer, and includes both volatile and nonvolatile media, removable and non-removable media. Further, the computer-readable medium may include all computer storage media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data.

The above-described method for providing a non-face-to-face parking order service according to an embodiment of the present invention may be executed by an application basically installed in a terminal (this may include a program included in a platform or an operating system basically installed in the terminal). In addition, it may be executed by an application (ie, a program) directly installed on the master terminal by a user through an application providing server such as an application store server, an application, or a web server related to the service. In this sense, the method for providing a non-face-to-face parking order service according to an embodiment of the present invention described above is implemented as an application (i.e., a program) installed basically in a terminal or directly installed by a user, and can be read by a computer such as a terminal. It can be recorded on an existing recording medium.

The above description of the present invention is for illustrative purposes only, and those of ordinary skill in the art to which the present invention pertains will be able to understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not limiting. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as being distributed may also be implemented in a combined form.

The scope of the present invention is indicated by the claims to be described later rather than the detailed description, and all changes or modified forms derived from the meaning and scope of the claims and their equivalent concepts should be interpreted as being included in the scope of the present invention. do.

Claims (10)

An autonomous driving cart that moves along the cart guide line and moves along the cart guide line to a position corresponding to the input area code when an area code corresponding to at least one area is input;
At least one type of product is displayed on the screen, when at least one of the output products is selected, payment is made when at least one type of payment method is input, and when the payment is completed, a pickup request event is output. An order payment device that transmits;
A storage unit that stores the location and area code of at least one area in the parking area, and when the order and payment is completed and the vehicle number is recognized, the area code of the area in which the vehicle having the vehicle number is parked is stored. A pickup request unit that maps and stores the order number and outputs a pickup request event, identifies the order number when a pickup completion signal is received, and drives the autonomous cart to an area with an area code mapped to the identified order number and stored. Parking order service providing server including a delivery request unit for requesting;
At least one point of sale (POS) terminal that outputs a pickup request event output from the order payment device and receives a driving start of the autonomous cart when the pickup of the product is completed; And
When a vehicle is parked in the at least one area by photographing at least one area in the parking area, the vehicle number of the parked vehicle and the area code assigned to the at least one area are identified and transmitted to the order payment device. It includes at least one edge camera (Edge Camera),
The parking area,
The parking area is divided into at least one area where the vehicle and the autonomous driving cart will be located, and an area code identifying the divided at least one area is given, and the ordered and paid product is put in the autonomous driving cart and departed. The cart guide line is installed from the starting point to the destination point, which is the at least one area,
The edge camera,
By monitoring the parked vehicle, the parking event is set to determine the timing of the return signal of the self-driving cart when a pre-set unloading event that starts after a human subject comes out of the vehicle and puts an object occurs. It is delivered to the order service providing server,
The parking order service providing server,
A ratio, characterized in that, when a preset roaming event occurs, by outputting context information collected from a plurality of edge cameras in real time, recognizing a collaboration situation based on the collected context information, and requesting employee guidance to the POS terminal Face-to-face parking order service delivery system.
The method of claim 1,
The at least one payment means is a non-face-to-face parking order service providing system, characterized in that it comprises a high pass payment.
The method of claim 2,
The order payment device,
An antenna for receiving the card payment result when the high-pass payment is made to recognize the high-pass terminal of the vehicle, request payment information, and transmit the result after performing the card payment in the high-pass terminal;
And,
A system for providing a non-face-to-face parking order service, characterized in that communication between the antenna and the high-pass terminal of the vehicle through DSRC (Dedicated Short-Range Communications).
delete delete The method of claim 1,
The order payment device,
A non-face-to-face parking order service providing system, characterized in that receiving the vehicle number of the customer's vehicle ordered before proceeding with the payment and the area code of the area where the vehicle is parked.
delete The method of claim 1,
The order payment device,
It is connected to the POS (Point of Sale) terminal of the person in charge of pickup of the product,
A non-face-to-face parking order service providing system, characterized in that connected to the POS terminal to transmit and receive voice data through the microphone and speaker of the POS terminal and the microphone and speaker of the order payment device.
The method of claim 1,
The autonomous driving cart,
When the weight or pressure sensed by the weight sensor or the pressure sensor included in the autonomous driving cart is less than a preset threshold, driving to return to a previously stored starting point is started.
The method of claim 1,
The cart guide line is a non-face-to-face parking order service providing system, characterized in that corresponding to a guide loop cable installed on the floor.

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