DETAILED ACTION
Claims 1-20 are pending in the present application and are under examination on the merits. This communication is the first action on the merits (FAOM).
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
Applicant has not yet filed an IDS for this Application. As such, no IDS has been considered.
Drawings
The drawings filed on 11/21/2024 and 5/7/2025 are acceptable as filed.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102(A)(1) that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(A)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1 and 8-15 are rejected under 35 U.S.C. 102(A)(1) as being anticipated by U.S. Patent Application Publication Number 2017/0221296 to Jain et al. (hereafter referred to as Jain).
As per claim 1, Jain teaches:
A management method for catering automation device, comprising: connecting one or more catering automation devices to a cloud platform (Paragraph Number [0046] teaches one or more networks 104, 106, 108, may represent a cluster of systems commonly referred to as a “cloud.” In cloud computing, shared resources, such as processing power, peripherals, software, data processing and/or storage, servers, etc., are provided to any system in the cloud, preferably in an on-demand relationship, thereby allowing access and distribution of services across many computing systems. Cloud computing typically involves an Internet or other high speed connection (e.g., 4G LTE, fiber optic, etc.) between the systems operating in the cloud, but other techniques of connecting the systems may also be used. Paragraph Number [0053] teaches to facilitate such services and functionalities, the network architecture 120 includes one or more, preferably multiple, food preparation kiosks, a cloud-based management component, and mobile application software. As shown in FIG. 1B, the architecture 120 includes two kiosks 122a and 122b, a cloud-based management component 124, and mobile application software 126 available via an online marketplace (an “app store” or the like). The architecture 120 facilitates communication between the management component 124, the kiosks 122a and 122b and mobile application software via one or more network(s), e.g. as described generally above with reference to FIG. 1A).
the cloud platform receiving orders and distributing relevant formula information, including raw material codes and quantities, to one or more catering automation devices based on information of the orders (Paragraph Number [0057] teaches the preparation protocols are preferably determined based on recipes, as well as variations thereto which may be reflected in, and communicated to the kiosks by, modules of the cloud component 124. For instance, a kiosk management module may communicate with a recipe management module in response to receiving an order from a consumer, which may be submitted using a mobile application obtained from a proper source (e.g. mobile application software store 126). The kiosk management module may query the recipe management module to determine, for example, if the consumer has specified any dietary restrictions, flavor preferences, allergies, nutritional goals etc. and modify the recipe instructions accordingly. Paragraph Number [0062] teaches a dispensing component may receive instructions to dispense certain ingredients to a particular container, e.g. a blender component, in particular amounts. The amounts may be measured in units of mass (e.g. for frozen fruit, powders, grains or other solid ingredients) and/or volume (e.g. for juices and other liquid or semi-solid ingredients such as yogurt)).
wherein, the cloud platform obtains raw material codes and raw material quantities from the order related recipe according to information of the order, and distributes them to order related devices (Paragraph Number [0057] teaches in response to determining the user preferences, overlapping aspects of other outstanding orders, etc. the cloud component 124 may communicate instructions to an appropriate kiosk to initiate preparation of a particular food item in accordance with the recipe and any appropriate modifications thereto. Paragraph Number [0062] teaches a dispensing component may receive instructions to dispense certain ingredients to a particular container, e.g. a blender component, in particular amounts. The amounts may be measured in units of mass (e.g. for frozen fruit, powders, grains or other solid ingredients) and/or volume (e.g. for juices and other liquid or semi-solid ingredients such as yogurt). Accordingly, the dispensing component may employ corresponding sensors to detect whether an amount of each ingredient dispensed to the particular container is within a predetermined threshold, e.g. ±10-20% of the expected volume or mass (depending on ingredient type) and thus ensure appropriate dispensation of each ingredient to the container. To ensure the proper ingredients are dispensed to the proper container, a vision system including cameras may observe the dispensation of the individual ingredients (e.g. determining whether a source location from which ingredients are obtained corresponds to a known location of the ingredient(s) needed to prepare a particular food item) to the particular container (similarly ensuring the ingredients are delivered to a destination location corresponding to a known location of the container to which the ingredients are needed). Preferred embodiments of an exemplary vision system will be described in further detail below).
and the devices each drives corresponding material bins to dispense required raw material quantities according to the raw material codes and the raw material quantities (Paragraph Number [0074] teaches boxing components such as included in kiosk 122b may, in accordance with various embodiments, include and/or be coupled to sensors configured to provide awareness with respect to the particular container and food item(s) being delivered thereto. In general terms, such sensors may include a vision system and mass/volume sensing devices such as described above with respect to dispensing components. Controls coupled to the boxing component may include the robotic arm, which is configured to place the various completed food item(s) in the appropriate container and/or within a particular location in a container (e.g. a sectioned container having different compartments for different portions of a dish). Paragraph Number [0075] teaches in addition to the exemplary components discussed above, other components that may be included in kiosks but not shown in FIG. 1B may include storage components (which should be understood to be inclusive of all various types of storage, e.g. wet/dry ingredients, refrigerated, frozen, humidity controlled, etc. and may store containers, food items, utensils, preparation supplies, dispensers, etc.), cleaning components such as sinks, dishwashers, sterilizing chambers, etc.; display components configured to display pertinent information to consumers (e.g. the recipe by which the food item ordered by the consumer is being prepared, nutritional information, business transaction information, etc. as would be understood by a person having ordinary skill in the art upon reading the present descriptions)).
As per claim 8, Jain teaches each of the limitations of claim 1.
In addition, Jain teaches:
wherein the cloud platform is connected to each catering automation device through the Internet of Things. (Paragraph Number [0034] teaches in order to maximize the availability and publicity of food and beverage products produced in an automated fashion as described herein, the foregoing ordering and publication features are preferably available over a network, e.g. the Internet, a dedicated network in a particular location or enterprise (e.g. airport, educational facility, cafeteria, restaurant, bar, coffee shop, etc.), or any other equivalent network architecture as would be understood by a person having ordinary skill in the art upon reading the present descriptions. Paragraph Number [0035] teaches using the Internet as a means of communicating among a plurality of computer systems. One skilled in the art will recognize that the present invention is not limited to the use of the Internet as a communication medium and that alternative methods of the invention may accommodate the use of a private intranet, a Local Area Network (LAN), a Metro Area Network (MAN), a Wide Area Network (WAN) or other means of communication. In addition, various combinations of wired, wireless (e.g., radio frequency) and optical communication links may be utilized).
As per claim 9, Jain teaches each of the limitations of claim 1.
In addition, Jain teaches:
wherein each catering automation device is authorized by the cloud platform to access the cloud platform (Paragraph Number [0046] teaches one or more networks 104, 106, 108, may represent a cluster of systems commonly referred to as a “cloud.” In cloud computing, shared resources, such as processing power, peripherals, software, data processing and/or storage, servers, etc., are provided to any system in the cloud, preferably in an on-demand relationship, thereby allowing access and distribution of services across many computing systems. Cloud computing typically involves an Internet or other high speed connection (e.g., 4G LTE, fiber optic, etc.) between the systems operating in the cloud, but other techniques of connecting the systems may also be used. Paragraph Number [0057] teaches in response to determining the user preferences, overlapping aspects of other outstanding orders, etc. the cloud component 124 may communicate instructions to an appropriate kiosk to initiate preparation of a particular food item in accordance with the recipe and any appropriate modifications thereto. [0058] In addition, the cloud component 124 may include vendor management module(s) to control the supply of ingredients to various kiosks, and business modules such as a catalog and accounts module, and a payments and promotions module, each configured to provide back-end business transaction functionality to the architecture 120).
As per claim 10, Jain teaches each of the limitations of claim 1.
In addition, Jain teaches:
wherein the device related basic information includes working status, operation status, initialization status, cleaning status, and component usage time of each of the device (Paragraph Number [0075] teaches other components that may be included in kiosks but not shown in FIG. 1B may include storage components (which should be understood to be inclusive of all various types of storage, e.g. wet/dry ingredients, refrigerated, frozen, humidity controlled, etc. and may store containers, food items, utensils, preparation supplies, dispensers, etc.), cleaning components such as sinks, dishwashers, sterilizing chambers, etc.; display components configured to display pertinent information to consumers (e.g. the recipe by which the food item ordered by the consumer is being prepared, nutritional information, business transaction information, etc. as would be understood by a person having ordinary skill in the art upon reading the present descriptions); a plumbing component configured to provide drainage for various liquids used in preparing foods and/or cleaning equipment within the kiosk, generation of daily, monthly, etc. maintenance lists based on the operational feedback for that specific kiosk; special purpose machines such as espresso machines, toasters, waffle/crepe makers, steamers, instant pots, etc.; and utensils such as spoons, ladles, knives, slicers, peelers, etc. as would be understood by a person having ordinary skill in the art upon reading the present descriptions. Paragraph Number [0180] teaches a command and control software system supports higher level applications for discovering, ordering, managing and retrieving orders/beverages, refining, publishing and sharing recipes, manages all core functions required by the foodOS™ such as Dispensing, Mixing, Stirring, Blending, Mixing, Layering, Heating, Cooling, Wrapping, Pouring, Serving, Cleaning etc., and preferably provides a consistent software/driver interface to the command and control hardware System and various hardware subsystems such as Dispensers, Blenders etc. More preferably, the command and control software system provides load balancing, scheduling, monitoring, error detection and correction and robustness to allow for a distributed robotic kitchen deployment. Paragraph Number [0183] teaches the software system may include a user interface that allows discovery of available kiosks in a given proximity, available food and beverage options in them, needed time to prepare, personalization for a given food or beverage item (less salt, skip celery, etc.), ordering & payment, status check, authentication for dispensing etc.).
As per claim 11, Jain teaches each of the limitations of claim 1.
In addition, Jain teaches:
wherein the order management system comprises a local order system and a network order system, and the cloud platform is compatible with the network order management system. (Paragraph Number [0164] teaches with continuing reference to FIG. 9, method 900 also includes operation 904, in which the translated instructions, i.e. the instructions executable by the robotic arm assembly and some or all of the plurality of components to the robotic arm assembly, are communicated to the robotic arm assembly. In various approaches, the instructions may be translated using a kiosk server such as shown in FIG. 1B, a recipe management module or kiosk management module of a cloud or other networked component such as also shown in FIG. 1B, or any other suitable device that would be appreciated by a skilled artisan upon reading the present disclosures. Such translation process may be performed using one or more processors of the device, and subsequently communicated to the robotic arm assembly using a network connection.).
As per claim 12, Jain teaches each of the limitations of claim 1.
In addition, Jain teaches:
wherein the raw material bins of the catering automation device are equipped with a material monitoring device for monitoring amount of material, recording status of the bin, and uploading it to the cloud platform (Paragraph Number [0061] teaches in accordance with one embodiment sensors which may be coupled to dispensers may include mass- or weight-measuring devices such as scales; volume-measuring devices such as flow meters, displacement monitors etc., other indicators such as level indicators, temperature sensors, odor indicators, humidity indicators, etc.; visual sensors such as cameras or other optical devices; etc. as would be understood by a person having ordinary skill in the art upon reading the present descriptions. Controls associated with dispensers may include pistons, vacuums and/or pumps, servos, stepper motors, agitators, etc. as would be understood by a person having ordinary skill in the art upon reading the present descriptions. In one embodiment, all of the foregoing sensors are utilized, with the possible exception of the odor indicator(s), which may be optionally included or excluded from the system. Paragraph Number [0058] teaches the cloud component 124 may include vendor management module(s) to control the supply of ingredients to various kiosks, and business modules such as a catalog and accounts module, and a payments and promotions module, each configured to provide back-end business transaction functionality to the architecture 120).
As per claim 13, Jain teaches each of the limitations of claims 1 and 12.
In addition, Jain teaches:
wherein when the amount of material is below a threshold, or after the raw materials existing in the bins for a period of time, the material monitoring device sends a material addition prompt or a material expiration prompt to the cloud platform and/or a beverage and/or dish automated catering device (Paragraph Number [0061] teaches in accordance with one embodiment sensors which may be coupled to dispensers may include mass- or weight-measuring devices such as scales; volume-measuring devices such as flow meters, displacement monitors etc., other indicators such as level indicators, temperature sensors, odor indicators, humidity indicators, etc.; visual sensors such as cameras or other optical devices; etc. as would be understood by a person having ordinary skill in the art upon reading the present descriptions. Controls associated with dispensers may include pistons, vacuums and/or pumps, servos, stepper motors, agitators, etc. as would be understood by a person having ordinary skill in the art upon reading the present descriptions. In one embodiment, all of the foregoing sensors are utilized, with the possible exception of the odor indicator(s), which may be optionally included or excluded from the system. Paragraph Number [0107] teaches on a periodic basis the system may be further cleansed (and/or ingredients restocked, components replaced, etc.) with the assistance of a human operator. Importantly, the human operator is preferably not involved in the process of preparing and dispensing food and/or beverage items, but rather exclusively interacts with the system to restock, replace, or cleanse the system or components thereof. Ore preferably, the human operator may perform the additional maintenance, resupply, cleansing, etc. outside normal business hours so as to minimize service interruptions to consumers. Paragraph Number [0202] teaches once the baseline is established as noted above, for subsequent object detection the same process may be repeated and the deviations from the baseline computed to detect object motion within the kiosk. This approach advantageously allows the system to detect displacement of objects and account for such movement in the course of food preparation and/or servicing the kiosk (e.g. replacement of exhausted ingredients, cleaning, mechanical service, etc.)).
As per claim 14, Jain teaches:
A management system for catering automation device, comprising: a recipe management database, capable of being configured and input raw material codes and quantities related to beverages and/or dishes and ingredients, to form recipes for beverages and/or dishes (Paragraph Number [0046] teaches one or more networks 104, 106, 108, may represent a cluster of systems commonly referred to as a “cloud.” In cloud computing, shared resources, such as processing power, peripherals, software, data processing and/or storage, servers, etc., are provided to any system in the cloud, preferably in an on-demand relationship, thereby allowing access and distribution of services across many computing systems. Cloud computing typically involves an Internet or other high speed connection (e.g., 4G LTE, fiber optic, etc.) between the systems operating in the cloud, but other techniques of connecting the systems may also be used. Paragraph Number [0053] teaches to facilitate such services and functionalities, the network architecture 120 includes one or more, preferably multiple, food preparation kiosks, a cloud-based management component, and mobile application software. As shown in FIG. 1B, the architecture 120 includes two kiosks 122a and 122b, a cloud-based management component 124, and mobile application software 126 available via an online marketplace (an “app store” or the like). The architecture 120 facilitates communication between the management component 124, the kiosks 122a and 122b and mobile application software via one or more network(s), e.g. as described generally above with reference to FIG. 1A. Paragraph Number [0057] teaches the preparation protocols are preferably determined based on recipes, as well as variations thereto which may be reflected in, and communicated to the kiosks by, modules of the cloud component 124. For instance, a kiosk management module may communicate with a recipe management module in response to receiving an order from a consumer, which may be submitted using a mobile application obtained from a proper source (e.g. mobile application software store 126). The kiosk management module may query the recipe management module to determine, for example, if the consumer has specified any dietary restrictions, flavor preferences, allergies, nutritional goals etc. and modify the recipe instructions accordingly. Paragraph Number [0062] teaches a dispensing component may receive instructions to dispense certain ingredients to a particular container, e.g. a blender component, in particular amounts. The amounts may be measured in units of mass (e.g. for frozen fruit, powders, grains or other solid ingredients) and/or volume (e.g. for juices and other liquid or semi-solid ingredients such as yogurt)).
a device management database, capable of being input device codes, bin codes of the device, and device related information, and being set corresponding bin codes and raw material codes of the device (Paragraph Number [0057] teaches in response to determining the user preferences, overlapping aspects of other outstanding orders, etc. the cloud component 124 may communicate instructions to an appropriate kiosk to initiate preparation of a particular food item in accordance with the recipe and any appropriate modifications thereto. Paragraph Number [0062] teaches a dispensing component may receive instructions to dispense certain ingredients to a particular container, e.g. a blender component, in particular amounts. The amounts may be measured in units of mass (e.g. for frozen fruit, powders, grains or other solid ingredients) and/or volume (e.g. for juices and other liquid or semi-solid ingredients such as yogurt). Accordingly, the dispensing component may employ corresponding sensors to detect whether an amount of each ingredient dispensed to the particular container is within a predetermined threshold, e.g. ±10-20% of the expected volume or mass (depending on ingredient type) and thus ensure appropriate dispensation of each ingredient to the container. To ensure the proper ingredients are dispensed to the proper container, a vision system including cameras may observe the dispensation of the individual ingredients (e.g. determining whether a source location from which ingredients are obtained corresponds to a known location of the ingredient(s) needed to prepare a particular food item) to the particular container (similarly ensuring the ingredients are delivered to a destination location corresponding to a known location of the container to which the ingredients are needed). Preferred embodiments of an exemplary vision system will be described in further detail below).
wherein, the management system for catering automation devices is capable of being connected to the order management system, which receives orders including device codes, beverage and/or dish and recipe information (Paragraph Number [0057] teaches the preparation protocols are preferably determined based on recipes, as well as variations thereto which may be reflected in, and communicated to the kiosks by, modules of the cloud component 124. For instance, a kiosk management module may communicate with a recipe management module in response to receiving an order from a consumer, which may be submitted using a mobile application obtained from a proper source (e.g. mobile application software store 126). The kiosk management module may query the recipe management module to determine, for example, if the consumer has specified any dietary restrictions, flavor preferences, allergies, nutritional goals etc. and modify the recipe instructions accordingly. Paragraph Number [0062] teaches a dispensing component may receive instructions to dispense certain ingredients to a particular container, e.g. a blender component, in particular amounts. The amounts may be measured in units of mass (e.g. for frozen fruit, powders, grains or other solid ingredients) and/or volume (e.g. for juices and other liquid or semi-solid ingredients such as yogurt)).
wherein, the management system for catering automation device is capable of being connected to one or more catering automation devices, and each device is set corresponding to its device code, including a bin set corresponding to the raw material codes, which contains the corresponding raw materials (Paragraph Number [0074] teaches boxing components such as included in kiosk 122b may, in accordance with various embodiments, include and/or be coupled to sensors configured to provide awareness with respect to the particular container and food item(s) being delivered thereto. In general terms, such sensors may include a vision system and mass/volume sensing devices such as described above with respect to dispensing components. Controls coupled to the boxing component may include the robotic arm, which is configured to place the various completed food item(s) in the appropriate container and/or within a particular location in a container (e.g. a sectioned container having different compartments for different portions of a dish). Paragraph Number [0075] teaches other components that may be included in kiosks but not shown in FIG. 1B may include storage components (which should be understood to be inclusive of all various types of storage, e.g. wet/dry ingredients, refrigerated, frozen, humidity controlled, etc. and may store containers, food items, utensils, preparation supplies, dispensers, etc.), cleaning components such as sinks, dishwashers, sterilizing chambers, etc.; display components configured to display pertinent information to consumers (e.g. the recipe by which the food item ordered by the consumer is being prepared, nutritional information, business transaction information, etc. as would be understood by a person having ordinary skill in the art upon reading the present descriptions)).
wherein, the cloud platform obtains the raw material codes and raw material quantities of the order related recipe according to the order information, and distributes them to the order related device, which drives the corresponding material bins to dispense the required raw material quantities according to the raw material codes and raw material quantities (Paragraph Number [0057] teaches in response to determining the user preferences, overlapping aspects of other outstanding orders, etc. the cloud component 124 may communicate instructions to an appropriate kiosk to initiate preparation of a particular food item in accordance with the recipe and any appropriate modifications thereto. Paragraph Number [0062] teaches a dispensing component may receive instructions to dispense certain ingredients to a particular container, e.g. a blender component, in particular amounts. The amounts may be measured in units of mass (e.g. for frozen fruit, powders, grains or other solid ingredients) and/or volume (e.g. for juices and other liquid or semi-solid ingredients such as yogurt). Accordingly, the dispensing component may employ corresponding sensors to detect whether an amount of each ingredient dispensed to the particular container is within a predetermined threshold, e.g. ±10-20% of the expected volume or mass (depending on ingredient type) and thus ensure appropriate dispensation of each ingredient to the container. To ensure the proper ingredients are dispensed to the proper container, a vision system including cameras may observe the dispensation of the individual ingredients (e.g. determining whether a source location from which ingredients are obtained corresponds to a known location of the ingredient(s) needed to prepare a particular food item) to the particular container (similarly ensuring the ingredients are delivered to a destination location corresponding to a known location of the container to which the ingredients are needed). Preferred embodiments of an exemplary vision system will be described in further detail below. Paragraph Number [0074] teaches boxing components such as included in kiosk 122b may, in accordance with various embodiments, include and/or be coupled to sensors configured to provide awareness with respect to the particular container and food item(s) being delivered thereto. In general terms, such sensors may include a vision system and mass/volume sensing devices such as described above with respect to dispensing components. Controls coupled to the boxing component may include the robotic arm, which is configured to place the various completed food item(s) in the appropriate container and/or within a particular location in a container (e.g. a sectioned container having different compartments for different portions of a dish). Paragraph Number [0075] teaches other components that may be included in kiosks but not shown in FIG. 1B may include storage components (which should be understood to be inclusive of all various types of storage, e.g. wet/dry ingredients, refrigerated, frozen, humidity controlled, etc. and may store containers, food items, utensils, preparation supplies, dispensers, etc.), cleaning components such as sinks, dishwashers, sterilizing chambers, etc.; display components configured to display pertinent information to consumers (e.g. the recipe by which the food item ordered by the consumer is being prepared, nutritional information, business transaction information, etc. as would be understood by a person having ordinary skill in the art upon reading the present descriptions)).
As per claim 15, Jain teaches each of the limitations of claim 14.
In addition, Jain teaches:
A catering automation device, comprising: storage bins, used to hold raw materials required for preparing beverages and/or dishes; wherein the catering automation device uses the management system for catering automation device according to claim 14. (Paragraph Number [0074] teaches boxing components such as included in kiosk 122b may, in accordance with various embodiments, include and/or be coupled to sensors configured to provide awareness with respect to the particular container and food item(s) being delivered thereto. In general terms, such sensors may include a vision system and mass/volume sensing devices such as described above with respect to dispensing components. Controls coupled to the boxing component may include the robotic arm, which is configured to place the various completed food item(s) in the appropriate container and/or within a particular location in a container (e.g. a sectioned container having different compartments for different portions of a dish). Paragraph Number [0075] teaches other components that may be included in kiosks but not shown in FIG. 1B may include storage components (which should be understood to be inclusive of all various types of storage, e.g. wet/dry ingredients, refrigerated, frozen, humidity controlled, etc. and may store containers, food items, utensils, preparation supplies, dispensers, etc.), cleaning components such as sinks, dishwashers, sterilizing chambers, etc.; display components configured to display pertinent information to consumers (e.g. the recipe by which the food item ordered by the consumer is being prepared, nutritional information, business transaction information, etc. as would be understood by a person having ordinary skill in the art upon reading the present descriptions)).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication Number 2017/0221296 to Jain et al. (hereafter referred to as Jain) in view of U.S. Patent Application Publication Number 2016/0034876 to Speiser et al. (hereafter referred to as Speiser).
As per claims 2, Jain teaches each of the limitations of claim 1.
In addition, Jain teaches:
wherein a first message middleware and a second message middleware connected to the device, and an order management database are provided on the cloud platform (Paragraph Number [0057] teaches the preparation protocols are preferably determined based on recipes, as well as variations thereto which may be reflected in, and communicated to the kiosks by, modules of the cloud component 124. For instance, a kiosk management module may communicate with a recipe management module in response to receiving an order from a consumer, which may be submitted using a mobile application obtained from a proper source (e.g. mobile application software store 126). Paragraph Number [0155] teaches as will be appreciated by skilled artisans reading the present disclosure, commercial parts/equipment that are easily available to consumers and commercial kitchen operators are generally not designed to be compatible with robotic assemblies as disclosed herein. Accordingly, it is advantageous to make tools standard in the culinary industry compatible with the robotic arm assembly and corresponding software by attaching mechanical and electrical interfaces. This facilitates building a flexible kitchen that can be reconfigured to make and dispense different recipes and types of food (with software control). Paragraph Number [0179] teaches in preferred approaches, a software system (e.g. foodOS™) may be employed to facilitate control of the system as a whole. For instance, an exemplary software system may include one or more of the following subsystems, functions, etc.)
and after receiving the orders, the order management database sends them to the second message middleware for ... queuing (Paragraph Number [0143] teaches at the front of the system and optionally overlapping (vertically, e.g. via being suspended above) another station such as the rinsing station and/or optional dispensing station, the display may be included to provide visual indication to nearby customers, potential customers, etc. about the available menu, ingredients, ongoing preparation process, completed orders, orders in queue, videos demonstrating the preparation process, etc. as would be understood by a person having ordinary skill in the art upon reading the present descriptions).
and sends a current order to the first message middleware for processing, obtaining the raw material codes and quantities of the order related formulas, and sending them downstream to the order related devices (Paragraph Number [0057] teaches in response to determining the user preferences, overlapping aspects of other outstanding orders, etc. the cloud component 124 may communicate instructions to an appropriate kiosk to initiate preparation of a particular food item in accordance with the recipe and any appropriate modifications thereto. [0062] For example, a dispensing component may receive instructions to dispense certain ingredients to a particular container, e.g. a blender component, in particular amounts. The amounts may be measured in units of mass (e.g. for frozen fruit, powders, grains or other solid ingredients) and/or volume (e.g. for juices and other liquid or semi-solid ingredients such as yogurt). Accordingly, the dispensing component may employ corresponding sensors to detect whether an amount of each ingredient dispensed to the particular container is within a predetermined threshold, e.g. ±10-20% of the expected volume or mass (depending on ingredient type) and thus ensure appropriate dispensation of each ingredient to the container. To ensure the proper ingredients are dispensed to the proper container, a vision system including cameras may observe the dispensation of the individual ingredients (e.g. determining whether a source location from which ingredients are obtained corresponds to a known location of the ingredient(s) needed to prepare a particular food item) to the particular container (similarly ensuring the ingredients are delivered to a destination location corresponding to a known location of the container to which the ingredients are needed). Preferred embodiments of an exemplary vision system will be described in further detail below).
Jain teaches determining materials for food orders and placing them into a queue for order fulfillment but does not explicitly teach where the queue is asynchronous as described by the following citations from Speiser:
asynchronous queuing (Paragraph Number [0037] teaches the platform developer kit 134 may include a client payments module 136, a client queue module 138, a hardware module 140, a client inventory module 142, a client orders module 144, a client customers module 146, or any combination thereof. The client payments module 136, the client inventory module 142, the client orders module 144, and the client customers module 146 may be configured to communicate with the payments module 122, the inventory module 126, the orders module 128, and the customers module 120 respectively. The client queue module 138 may be configured to manage the sales queue by the client terminal 104, such as a reliable asynchronous queue to record transactions as described herein. The hardware module 140 may be configured to modify the other modules for operation of the point-of-sale terminal based on the hardware specification of the client terminal 104. Paragraph Number [0099] teaches furthering the example, the business may be a restaurant. Multiple devices may be utilized by waitresses to take food orders from customers. Additionally, at least one device in communication with the devices utilized by the waitresses may be utilized by the kitchen to receive the food orders from the waitresses. The orders generated by the waitresses using the devices may then be transmitted over a network to a remote server, which then transmits the order to the device in the kitchen for fulfillment of the food order).
Both Jain and Speiser are directed to food management. Jain discloses determining materials for food orders and placing them into a queue for order fulfillment. Speiser improves upon Jain by disclosing where the queue is asynchronous. One of ordinary skill in the art would be motivated to further include where the queue is asynchronous, to efficiently increase reliability hen multiple input devices are used to place items in queue. Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of determining materials for food orders and placing them into a queue for order fulfillment in Jain to further utilize where the queue is asynchronous as disclosed in Speiser, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claims 3 and 4 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication Number 2017/0221296 to Jain et al. (hereafter referred to as Jain) in view of U.S. Patent Application Publication Number 2016/0034876 to Speiser et al. (hereafter referred to as Speiser) and in further view of U.S. Patent Application Publication Number 2021/0201427 to Mimassi (hereafter referred to as Mimassi).
As per claim 3, the combination of Jain and Speiser teaches each of the limitations of claims 1 and 2.
In addition, Jain teaches:
wherein a recipe management is provided on the cloud platform and set with (Paragraph Number [0030] teaches pertinent information (e.g. custom recipes, order history, optimal and/or secondary pickup location(s), allergies, dietary restrictions, nutritional goals etc.) may be stored in a customer profile and utilized in subsequent order processing. Paragraph Number [0031] teaches customers may also optionally store and/or publish custom recipes for review and/or selection by other customers, diversifying the type of food and/or beverage products available for consumption. In one approach, recipe creation may therefore be at least partially based on crowdsourcing to maximize the range of products that may be prepared in an automated manner. Paragraph Number [0052] teaches a network architecture 120 suitable for use in conjunction with food preparation kiosks described herein is shown in FIG. 1B. The architecture 120 is configured to facilitate provision of food preparation services and associated functionalities such as recipe management and publication, mobile application integration, supply logistics, business transaction management, etc. as described in further detail below).
and the first message middleware obtains the raw material codes and raw material quantities of order related recipes (Paragraph Number [0057] teaches in response to determining the user preferences, overlapping aspects of other outstanding orders, etc. the cloud component 124 may communicate instructions to an appropriate kiosk to initiate preparation of a particular food item in accordance with the recipe and any appropriate modifications thereto. Paragraph Number [0062] teaches a dispensing component may receive instructions to dispense certain ingredients to a particular container, e.g. a blender component, in particular amounts. The amounts may be measured in units of mass (e.g. for frozen fruit, powders, grains or other solid ingredients) and/or volume (e.g. for juices and other liquid or semi-solid ingredients such as yogurt). Accordingly, the dispensing component may employ corresponding sensors to detect whether an amount of each ingredient dispensed to the particular container is within a predetermined threshold, e.g. ±10-20% of the expected volume or mass (depending on ingredient type) and thus ensure appropriate dispensation of each ingredient to the container. To ensure the proper ingredients are dispensed to the proper container, a vision system including cameras may observe the dispensation of the individual ingredients (e.g. determining whether a source location from which ingredients are obtained corresponds to a known location of the ingredient(s) needed to prepare a particular food item) to the particular container (similarly ensuring the ingredients are delivered to a destination location corresponding to a known location of the container to which the ingredients are needed). Preferred embodiments of an exemplary vision system will be described in further detail below).
Jain teaches storing order information in databases but does not explicitly teach where the databases utilize multi-level caching as described by the following citations from Mimassi:
multi-level caching… through the multi-level caching (Paragraph Number [0071] teaches CPU 12 may include one or more processors 13 such as, for example, a processor from one of the Intel, ARM, Qualcomm, and AMD families of microprocessors. In some aspects, processors 13 may include specially designed hardware such as application-specific integrated circuits (ASICs), electrically erasable programmable read-only memories (EEPROMs), field-programmable gate arrays (FPGAs), and so forth, for controlling operations of computing device 10. In a particular aspect, a local memory 11 (such as non-volatile random access memory (RAM) and/or read-only memory (ROM), including for example one or more levels of cached memory) may also form part of CPU 12. However, there are many different ways in which memory may be coupled to system 10. Memory 11 may be used for a variety of purposes such as, for example, caching and/or storing data, programming instructions, and the like).
Both the combination of Jain and Speiser and Mimassi are directed to data management and order fulfillment. The combination of Jain and Speiser discloses storing order information in databases. Mimassi improves upon the combination of Jain and Speiser by disclosing utilize multi-level caching. One of ordinary skill in the art would be motivated to further include utilize multi-level caching, to efficiently increase data recall and processing efficiency. Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of storing order information in databases in the combination of Jain and Speiser to further utilize multi-level caching as disclosed in Mimassi, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 4, the combination of Jain, Speiser, and Mimassi teaches each of the limitations of claims 1-3.
In addition, Jain teaches:
wherein each catering automation device comprises an upper computer, a lower computer, bins, and a bin driving device (Paragraph Number [0035] teaches various embodiments of the invention discussed herein are implemented using the Internet as a means of communicating among a plurality of computer systems. One skilled in the art will recognize that the present invention is not limited to the use of the Internet as a communication medium and that alternative methods of the invention may accommodate the use of a private intranet, a Local Area Network (LAN), a Metro Area Network (MAN), a Wide Area Network (WAN) or other means of communication. In addition, various combinations of wired, wireless (e.g., radio frequency) and optical communication links may be utilized. Paragraph Number [0043] teaches further included is at least one data server 114 coupled to the proximate network 108, and which is accessible from the remote networks 102 via the gateway 101. It should be noted that the data server(s) 114 may include any type of computing device/groupware. Coupled to each data server 114 is a plurality of user devices 116. Such user devices 116 may include a desktop computer, laptop computer, hand-held computer, printer or any other type of logic. It should be noted that a user device 116 may also be directly coupled to any of the networks, in one embodiment. Paragraph Number [0044] teaches a peripheral 118 or series of peripherals 118, e.g. facsimile machines, printers, networked storage units, food preparation kiosks, etc., may be coupled to one or more of the networks 104, 106, 108. It should be noted that databases, servers, and/or additional components may be utilized with, or integrated into, any type of network element coupled to the networks 104, 106, 108. In the context of the present description, a network element may refer to any component of a network).
the raw material codes and quantities of the order related recipes are sent from the cloud platform to the upper computer, and the upper computer sends instructions to the lower computers according to the raw material codes and quantities of the order related recipes (Paragraph Number [0057] teaches in response to determining the user preferences, overlapping aspects of other outstanding orders, etc. the cloud component 124 may communicate instructions to an appropriate kiosk to initiate preparation of a particular food item in accordance with the recipe and any appropriate modifications thereto. Paragraph Number [0062] teaches a dispensing component may receive instructions to dispense certain ingredients to a particular container, e.g. a blender component, in particular amounts. The amounts may be measured in units of mass (e.g. for frozen fruit, powders, grains or other solid ingredients) and/or volume (e.g. for juices and other liquid or semi-solid ingredients such as yogurt). Accordingly, the dispensing component may employ corresponding sensors to detect whether an amount of each ingredient dispensed to the particular container is within a predetermined threshold, e.g. ±10-20% of the expected volume or mass (depending on ingredient type) and thus ensure appropriate dispensation of each ingredient to the container. To ensure the proper ingredients are dispensed to the proper container, a vision system including cameras may observe the dispensation of the individual ingredients (e.g. determining whether a source location from which ingredients are obtained corresponds to a known location of the ingredient(s) needed to prepare a particular food item) to the particular container (similarly ensuring the ingredients are delivered to a destination location corresponding to a known location of the container to which the ingredients are needed). Preferred embodiments of an exemplary vision system will be described in further detail below).
the lower computer receives the instructions and drives the bin driving devices of the catering automation device corresponding to the raw material codes of the recipe to dispense the corresponding raw material quantities to a predetermined container according to the instructions (Paragraph Number [0057] teaches in response to determining the user preferences, overlapping aspects of other outstanding orders, etc. the cloud component 124 may communicate instructions to an appropriate kiosk to initiate preparation of a particular food item in accordance with the recipe and any appropriate modifications thereto. Paragraph Number [0062] teaches a dispensing component may receive instructions to dispense certain ingredients to a particular container, e.g. a blender component, in particular amounts. The amounts may be measured in units of mass (e.g. for frozen fruit, powders, grains or other solid ingredients) and/or volume (e.g. for juices and other liquid or semi-solid ingredients such as yogurt). Accordingly, the dispensing component may employ corresponding sensors to detect whether an amount of each ingredient dispensed to the particular container is within a predetermined threshold, e.g. ±10-20% of the expected volume or mass (depending on ingredient type) and thus ensure appropriate dispensation of each ingredient to the container. To ensure the proper ingredients are dispensed to the proper container, a vision system including cameras may observe the dispensation of the individual ingredients (e.g. determining whether a source location from which ingredients are obtained corresponds to a known location of the ingredient(s) needed to prepare a particular food item) to the particular container (similarly ensuring the ingredients are delivered to a destination location corresponding to a known location of the container to which the ingredients are needed). Preferred embodiments of an exemplary vision system will be described in further detail below).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication Number 2017/0221296 to Jain et al. (hereafter referred to as Jain) in view of U.S. Patent Application Publication Number 2016/0034876 to Speiser et al. (hereafter referred to as Speiser) and in further view of U.S. Patent Application Publication Number 2020/0295968 to Mundt et al. (hereafter referred to as Mundt).
As per claim 5, the combination of Jain and Speiser teaches each of the limitations of claims 1 and 2.
Jain teaches utilizing software to communicate between portions of the system but does not explicitly teach using Rocketmq as described by the following citations from Mundt:
wherein the first message middleware is a broker and the second message middleware is a Rocketmq (Paragraph Number [0005] teaches receiving, via the network, the multiple subscription requests may include receiving first multiple message queuing telemetry transport (MQTT) messages, Apache ActiveMQ messages, Amazon SQS messages, IBM Websphere MQ messages, RabbitMQ messages, or RocketMQ messages, among others. In one or more embodiments, receiving, via the network, the multiple publication requests may include receiving second multiple MQTT messages, Apache ActiveMQ messages, Amazon SQS messages, IBM Websphere MQ messages, RabbitMQ messages, or RocketMQ messages, among others. In one or more embodiments, receiving, via the network, the multiple queries from the multiple baseboard management controllers respectively associated with the multiple subscription requests may include receiving third multiple MQTT messages, Apache ActiveMQ messages, Amazon SQS messages, IBM Websphere MQ messages, RabbitMQ messages, or RocketMQ messages, among others).
Both the combination of Jain and Speiser and Waitkus are directed to computer communication systems for processing requests. The combination of Jain and Speiser discloses utilizing software to communicate between portions of the system. Mundt improves upon the combination of Jain and Speiser by disclosing using Rocketmq. One of ordinary skill in the art would be motivated to further include using Rocketmq, to efficiently utilize prepackaged software that fits the needs of the user. Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of utilizing software to communicate between portions of the system in the combination of Jain and Speiser to further utilize using Rocketmq as disclosed in Mundt, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claims 6 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication Number 2017/0221296 to Jain et al. (hereafter referred to as Jain) in view of U.S. Patent Application Publication Number 2021/0201427 to Mimassi (hereafter referred to as Mimassi)
As per claim 6, Jain teaches each of the limitations of claim 1.
Jain teaches providing user information to fulfill customer orders but does not explicitly teach linking orders specifically to establishments that provide that product which is taught by the following citations from Mimassi:
wherein the cloud platform further comprises a store management database, so that the cloud platform allows adding or selecting stores in the store management database, and each catering automation device is classified according to the selected store (Paragraph Number [0058] teaches a flow diagram showing the steps of an exemplary method for personalized food item design, selection, restaurant selection, order fulfilment by selected restaurant. A patron portal is provided for the patron to pre-enter preferences such as food types, food attributes, diet restrictions, health goals, and other preferences 401 this information is subsequently stored in a historical database 403 for future use. During mealtime and/or when patron is mobile, the patron is presented with an interface on mobile app to make real-time preferences on meal interests or desires for food ingestion, the app may ask “for dining, what are you in the mood for?” 402. An analysis (as further exemplified in FIG. 5) is performed on patrons historical and real-time food item requirements and compared to menu options and culinary capabilities of restaurants in proximity of patron 404 from which a consumer specific food item is generated 405. The food item options 406 are displayed to the patron, along with a recommended restaurant, with details such as type of food, food cost, additional drive time 407. A choice is made from the patron 408 for one or more food item displayed with its recommended restaurant. The patron's food item information is sent to the restaurant, confirmation to patron and food item fulfilment 409. Display food item confirmation along with restaurant details including restaurant address, driving, estimated travel time and estimated food item availability 410. Notify and update patron on order status and restaurant fulfilment 411. Paragraph Number [0052] teaches when a patron is desiring food item assistance a recipe generator engine 214 receives the patron's current food item requirements from a patron real time update engine 211 along with a patron profile 213. A recipe generation engine 214 obtains restaurant ingredient data 215 and restaurant recipe data 216 for one or more restaurants either from a database 150 or from external resources 180. A recipe generation engine 214 then uses machine learning algorithms to create a personalized food item optimized to meet the patron preferences and outcomes).
Both Jain and Mimassi are directed to customer order fulfillment. Jain discloses providing user information to fulfill customer orders. Mimassi improves upon Jain by disclosing linking orders specifically to establishments that provide that product. One of ordinary skill in the art would be motivated to further include linking orders specifically to establishments that provide that product, to efficiently list and provide products based on user selection of a particular establishment. Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of providing user information to fulfill customer orders in Jain to further utilize linking orders specifically to establishments that provide that product as disclosed in Mimassi, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 6, the combination of Jain and Mimassi teaches each of the limitations of claims 1 and 6.
Jain teaches providing user information to fulfill customer orders but does not explicitly teach linking orders specifically to establishments that provide that product which is taught by the following citations from Mimassi:
wherein the cloud platform further comprises a merchant management database so that the cloud platform allows adding or selecting merchants in the merchant management database, and the selected stores are classified according to the selected merchants (Paragraph Number [0058] teaches a flow diagram showing the steps of an exemplary method for personalized food item design, selection, restaurant selection, order fulfilment by selected restaurant. A patron portal is provided for the patron to pre-enter preferences such as food types, food attributes, diet restrictions, health goals, and other preferences 401 this information is subsequently stored in a historical database 403 for future use. During mealtime and/or when patron is mobile, the patron is presented with an interface on mobile app to make real-time preferences on meal interests or desires for food ingestion, the app may ask “for dining, what are you in the mood for?” 402. An analysis (as further exemplified in FIG. 5) is performed on patrons historical and real-time food item requirements and compared to menu options and culinary capabilities of restaurants in proximity of patron 404 from which a consumer specific food item is generated 405. The food item options 406 are displayed to the patron, along with a recommended restaurant, with details such as type of food, food cost, additional drive time 407. A choice is made from the patron 408 for one or more food item displayed with its recommended restaurant. The patron's food item information is sent to the restaurant, confirmation to patron and food item fulfilment 409. Display food item confirmation along with restaurant details including restaurant address, driving, estimated travel time and estimated food item availability 410. Notify and update patron on order status and restaurant fulfilment 411. Paragraph Number [0052] teaches when a patron is desiring food item assistance a recipe generator engine 214 receives the patron's current food item requirements from a patron real time update engine 211 along with a patron profile 213. A recipe generation engine 214 obtains restaurant ingredient data 215 and restaurant recipe data 216 for one or more restaurants either from a database 150 or from external resources 180. A recipe generation engine 214 then uses machine learning algorithms to create a personalized food item optimized to meet the patron preferences and outcomes).
A person of ordinary skill would have been motivated to combine these references for the same reasons put forth in regard to claim 6.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW H. DIVELBISS whose telephone number is (571) 270-0166. The fax phone number is 571-483-7110. The examiner can normally be reached on M-Th, 7:00 - 5:00. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O'Connor can be reached on (571) 272-6787.
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/M.H.D/Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624