DETAILED ACTION
Amendment received on April 27, 2026 has been acknowledged. Claims 3, 17 and 19 have been cancelled and amendments to claims 1 and 15 have been entered. Therefore, claims 1-2, 4-16, 18 and 20 are pending.
Response to Arguments
Applicant’s arguments, see Remarks, filed April 7, 2026, with respect to claims 1-20 have been fully considered and are persuasive. The 35 USC 101 rejection of claims 1-20 has been withdrawn.
Applicant's arguments filed April 7, 2026 have been fully considered but they are not persuasive.
Applicant argues: “Alkan, as Katsu handles static information entered in advance and would not be able to generate menus based on dynamic input data taken from Alkan.”
Examiner respectfully disagrees. The claim limitation requires generating a menu, using detection data and using a recommendation engine. Katsu teaches a system 10 that interacts with user terminals, much like the claimed invention. Katsu teaches a system and method capable of interacting with a user terminal. The system 10 of Katsu, much like the victual ordering device of the claimed invention is capable of receiving information from one or more user devices. See Applicant submitted Specifications pg.4, lines 1-10. Katsu is combined with Alkan to teach the portions of the claim in which the data is gathered and a menu is generated based on the gathered information. One of ordinary skill in the art would see the benefit in combining Katsu with Alkan, because of the ability to generate a recommended menu utilizing information derived from user devices.
Applicant argues: “Neither Alkan nor Katsu discloses optically monitoring the physical consumption state of a victual item such as quantity, portion, or state of consumption, as a detection input to a recommendation engine. Alkan's detection of facial expressions and satisfaction signals monitors diner reactions, not the physical state of the food itself. Neither reference discloses using a pose parameter indicative of a consumption status of subjects to autonomously control a victual ordering system.”
Examiner respectfully disagrees in part. Alkan ¶ [0072] and ¶ [0078] respectively, teaches:
The meal recommendation service 502 may gather and collect collaborative data from each of the one or more IoT devices, such as communication messages (assuming authorization and security protocols have been approved, allowed, or provided), audio, images or videos from cameras 560A, 560B and/or one or more computer devices, such as, for example, computer devices 506A-C, in a plurality of mixed types of IoT devices in an IoT network to derive a holistic view of member/user satisfaction.
…the meal or food source having the highest rated positive customer level may be determined according to the collaborative data of the customer 504 eating a meal at a selected food source (e.g., restaurant).
The cited portions of Alkan teaches a system and method capable of collecting image data from cameras of customers eating a meal and deriving a satisfaction. One of ordinary skill would recognized that the consumption status of eating a meal as having a portion of the meal consumed. However, both Alkan and Katsu are silent regarding outputting a recommendation to order more victual.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1 and 15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 and 15 recite: “outputting a recommendation to order more of the victual based on the pose parameter and the victual tracking parameter.” It is unclear as to what or where the recommendation is being output to. The independent claim and dependents fail to link the step to a functional device, i.e. display, alarm or electronic device. Furthermore, it is unclear who or what is provided with the recommendation to order more of the victual. Applicant submitted specification provides support for delivering more food to a consumer and reordering menu item. For examination purposes the Examiner is construing the recommendation is being output to the kitchen staff to refill drinks. Appropriate clarification is requested.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 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 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(s) 1-2, 4-11, 13-16, 18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Alkan et al., U.S. Patent Application Publication 2019/0073601 in view of Katsu Japanese Patent JP 2020107096 further in view of Cronin et al., U.S. Patent Application Publication 2018/0276770.
As per Claim 1, Alkan et al., discloses an electronic device
- memory circuitry
- processor circuitry
- interface circuitry
wherein the electronic device
- obtain, from an optical device, detection data indicative of an item (pg.7, ¶ [0072] discusses the meal recommendation service 502 may be in communication with one or more IoT devices, such as cameras 560A, 560B…the meal recommendation service 502 may gather and collect collaborative data from each of the one or more IoT devices such as communication messages, audio, images or videos from cameras 560A, 560B); and
- control, based on the detection data, a victual ordering system (pg.6, ¶ [0068] discusses the GUI 422 may display a recommended meal, meal courses, food sources, or a combination thereof to a user via an interactive graphical user interface);
wherein the electronic device comprises a recommendation engine (Figure 4, Meal Recommendation System 430).
Alkan is directed toward recommending meals for a group of members to maximize consumption satisfaction of each member of a group using one or more Internet of Things (IoT) devices in an IoT network.
However, Alkan fails to disclose wherein the controlling of the victual ordering system comprises to generate, based on the detection data and using the recommendation engine, menu data indicative of a victual menu.
Katsu teaches wherein the controlling of the victual ordering system comprises to generate, based on the detection data and using the recommendation engine, menu data indicative of a victual menu (pg.3, 4th paragraph discusses the proposed menu determination unit 113, the recommended intake of nutrients and the like of the constituent users, and the content of nutrients and the like, which is the amount of energy and/or nutrients included in each of the plurality of menus… the proposed menu determining unit 113 determines a menu having a content of nutrients or the like that satisfies the recommended intake of nutrients or the like of the constituent user as a proposed menu).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have utilized information detected from dining customers to recommend food items displayed on a menu as in the improvement discussed in Katsu in the system executing the method of Alkan. As in Katsu, it is within the capabilities of one of ordinary skill in the art display recommended items onto a menu to the monitoring and detection data of diners with the predicted result of displaying recommended items on a menu as needed in Alkan.
Both Alkan and Katsu discloses the claimed invention. However, the Alkan-Katsu combination fails to disclose and to determine, from the detection data, a pose parameter indicative of one or more subject persons' relationship to a victual in the victual menu (, and
to determine, from the detection data, a victual tracking parameter indicative of consumption of the victual, and
wherein the controlling the victual ordering system further comprises outputting a recommendation to order more of the victual based on the pose parameter and the victual tracking parameter.
Cronin et al. teaches wherein the controlling of the victual ordering system comprises to generate, based on the detection data and using the recommendation engine, menu data indicative of a victual menu (pg.3, ¶ [0026] discusses based on the patron's age, sex, the patron's activities within the theme park, both past and future schedule events/activities, all of which are stored in the theme park database for the given patron, the CPU 14 using known artificial intelligence/machine learning related programs, such as but not limited to, SVM, Deep Learning, Bayesian Networking, etc.) generates a model which predicts what the patron may wish to order);
determine, from the detection data, a pose parameter indicative of one or more subject persons' relationship to a victual in the victual menu (pg.4, ¶ [0035] discusses only two patrons are at the table, with one of the patron's plates being full and the other patron's plates being empty, and
to determine, from the detection data, a victual tracking parameter indicative of consumption of the victual (pg.4, ¶ [0035] discusses individual areas 1, 2 and 4 are considered empty (i.e., meal completed), and individual area 3 is considered full, i.e., meal not completed), and
wherein the controlling the victual ordering system further comprises outputting a recommendation to order more of the victual based on the pose parameter and the victual tracking parameter (pg.4, ¶ [0034] discusses monitoring can also be utilized to determine drink levels, and send an appropriate notice once a drink has been completed so as to signal the staff to inquire if the patron would like another drink).
The cited portions of Cronin et al. teaches a system and method capable of identifying a seating position of each member of a group, determine the consumption of a meal and recommending staff to refill a drink.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have the ability to monitor patrons within a restaurant, detect consumption status of a meal and output a recommendation to staff to request a refill as in the improvement discussed in Cronin et al., in the system executing the method of the Alkan Katsu combination. As in Cronin et al., it is within the capabilities of one of ordinary skill in the art to visually monitor patrons at a table determine the consumption state of a meal and provide recommendations to reorder completed portion of a meal to the Alkan Katsu with the predicted result of 1) improve the patron's dining experience; 2) improve supply chain and response; and 3) improve patron turnover. as needed in the Alkan Katsu combination.
As per Claim 2, Alkan discloses the electronic device according to claim 1, wherein the detection data comprises one or more of: a subject parameter, a group of subjects parameter, an object parameter, a face parameter, a victual parameter, a victual tracking parameter, and a radio sensing parameter (pg.7, ¶ [0073] discusses the satisfaction level component 510 may use the collaboration of data (e.g., historical and real-time data) gathered from one or more collaborative members in a group of members).
As per Claim 4, Alkan discloses the electronic device according to claim 1,510 may determine, from the collaborative data, that a customer 504 has a positive level or high level of customer satisfaction of a previously ordered or consumed meal(s) as compared to other previously determined levels of customer satisfaction relating to the member profile).
Examiner is construing using the positive satisfaction of a previously ordered or consumed meal as content based filtering because items similar to what a user liked before, by analyzing item features (like genre, director, keywords) and user preferences to build a profile, making it great for personalized niche suggestions but requiring good item metadata).
As per Claim 5, Alkan discloses the electronic device according to claim 1. However, Alkan fails to disclose wherein the electronic device is configured to control the victual ordering system based on the menu data (pg.4, 1st paragraph discusses the proposed menu may be determined based at least on the nutrient intake, and the nutrient content of each of the plurality of menus).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have utilized menu data to provide a proposed menu as in the improvement discussed in Katsu in the system executing the method of Alkan. As in Katsu, it is within the capabilities of one of ordinary skill in the art display recommended items onto a menu to the monitoring and detection data of diners with the predicted result of displaying recommended items on a menu as needed in Alkan.
As per Claim 6, Alkan discloses the electronic device according to claim 1,
Katsu teaches wherein the menu data comprises data indicative of a sharing menu for a group of subjects (pg.3, 7th paragraph discusses Since the proposed menu is determined based on the content of the nutrients, etc., it is possible to propose the menu to a group such as a family composed of a plurality of users…pg.4, 1st paragraph discusses Since such a configuration calculates the recommended nutrient intake of the proposed target unit and uses it for the determination of the proposed menu, for example, the same rule is applied when the proposed target unit is an individual or a group).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have utilized menu data to provide a proposed menu for a group of individuals as in the improvement discussed in Katsu in the system executing the method of Alkan. As in Katsu, it is within the capabilities of one of ordinary skill in the art display recommended items onto a menu to the monitoring and detection data of diners with the predicted result of displaying recommended items on a menu as needed in Alkan.
As per Claim 7, Alkan discloses the electronic device according to claim 2,
The cited portion of Alkan teaches a system and method capable of monitoring a customer eating a meal, thereby providing a victual tracking parameter.
However, Alkan fails to explicitly state menu data.
Katsu teaches menu data. (pg.2, 4th paragraph discusses a menu information DB 153 that stores menu information related to the menu proposed in the menu proposal service).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have utilized menu information regarding menu items as in the improvement discussed in Katsu in the system executing the method of Alkan. As in Katsu, it is within the capabilities of one of ordinary skill in the art to retrieve menu item information with the predicted result of displaying recommended items on a menu as needed in Alkan.
As per Claim 8, Alkan discloses the electronic device according to claim 1,410 may include data relating to a satisfaction level for a variety of meals, food types, food sources, or a combination thereof each of which may include a plurality of factors. The plurality of factors may include a plurality of eating preferences, eating preference locations, nutritional constraints, one or more health constraints, one or more meal types, one or more available meals, favorite food choices, dislikes, cooking skills of each member, preparation time, time constraints of each member ( e.g., calendars and appointments), recipe database, or a combination thereof).
As per Claim 9, Alkan discloses the electronic device according to claim 8, wherein the menu data is based on the first user input (pg.8, ¶ [0081] discusses the collaboration component 540 may also be used to receive one or more communications, messages, reviews, or input/output data from each member of the group of members).
However, Alkan fails to explicitly state menu data.
Katsu teaches menu data. (pg.2, 4th paragraph discusses a menu information DB 153 that stores menu information related to the menu proposed in the menu proposal service).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have utilized menu information regarding menu items as in the improvement discussed in Katsu in the system executing the method of Alkan. As in Katsu, it is within the capabilities of one of ordinary skill in the art to retrieve menu item information with the predicted result of displaying recommended items on a menu as needed in Alkan.
As per Claim 10, Alkan discloses the electronic device according to claim 1,
However, Alkan is silent regarding output the menu data to one or more subjects.
Katsu discloses output the menu data to one or more subjects (pg.9, 1st paragraph discusses a suggested menu display (family) screen 80B displayed on the user terminal 30 in response to reception of menu information or the like transmitted from the system 10).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have displayed the menu to family members on a user terminal as in the improvement discussed in Katsu in the system executing the method of Alkan. As in Katsu, it is within the capabilities of one of ordinary skill in the art to retrieve menu item information with the predicted result of displaying recommended items on a menu as needed in Alkan.
As per Claim 11, Alkan discloses the electronic device according to claim 10, wherein the electronic device is configured to obtain a second user input indicative of one or more of: an acceptance of the victual menu, a refusal of the victual menu, and a modification of the victual menu (pg.8, ¶ [0085] discusses the recommendation component 530 may communicate a recommendation of group member messages, voting results, or likes/dislikes to a graphical user interface (GUI) of each member's computing device or mobile device).
As per Claim 13, Alkan discloses the electronic device according to claim 1,
As per Claim 14, Alkan discloses the electronic device according to claim 1,506A-C (which may have a camera device embedded or associated with a computing device such as, for example, a personal computer, laptop, smart phone, tablet, watch, and the like).
As per Claim 15, Alkan discloses a method, performed by an electronic device, the method comprising:-
obtaining, from an optical device, detection data indicative of an item(pg.7, ¶ [0072] discusses the meal recommendation service 502 may be in communication with one or more IoT devices, such as cameras 560A, 560B…the meal recommendation service 502 may gather and collect collaborative data from each of the one or more IoT devices such as communication messages, audio, images or videos from cameras 560A, 560B); and
- controlling based on the detection data, a victual ordering system (pg.6, ¶ [0068] discusses the GUI 422 may display a recommended meal, meal courses, food sources, or a combination thereof to a user via an interactive graphical user interface);
wherein the electronic device comprises a recommendation engine (Figure 4, Meal Recommendation System 430).
Alkan is directed toward recommending meals for a group of members to maximize consumption satisfaction of each member of a group using one or more Internet of Things (IoT) devices in an IoT network.
However, Alkan fails to disclose wherein the controlling of the victual ordering system comprises to generating, based on the detection data and using the recommendation engine, menu data indicative of a victual menu.
Katsu teaches wherein the controlling of the victual ordering system comprises to generating, based on the detection data and using the recommendation engine, menu data indicative of a victual menu (pg.3, 4th paragraph discusses the proposed menu determination unit 113, the recommended intake of nutrients and the like of the constituent users, and the content of nutrients and the like, which is the amount of energy and/or nutrients included in each of the plurality of menus… the proposed menu determining unit 113 determines a menu having a content of nutrients or the like that satisfies the recommended intake of nutrients or the like of the constituent user as a proposed menu).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have utilized information detected from dining customers to recommend food items displayed on a menu as in the improvement discussed in Katsu in the system executing the method of Alkan. As in Katsu, it is within the capabilities of one of ordinary skill in the art display recommended items onto a menu to the monitoring and detection data of diners with the predicted result of displaying recommended items on a menu as needed in Alkan.
Both Alkan and Katsu discloses the claimed invention. However, the Alkan-Katsu combination fails to disclose and to determine, from the detection data, a pose parameter indicative of one or more subject persons' relationship to a victual in the victual menu (, and
to determine, from the detection data, a victual tracking parameter indicative of consumption of the victual, and
wherein the controlling the victual ordering system further comprises outputting a recommendation to order more of the victual based on the pose parameter and the victual tracking parameter.
Cronin et al. teaches wherein the controlling of the victual ordering system comprises to generate, based on the detection data and using the recommendation engine, menu data indicative of a victual menu (pg.3, ¶ [0026] discusses based on the patron's age, sex, the patron's activities within the theme park, both past and future schedule events/activities, all of which are stored in the theme park database for the given patron, the CPU 14 using known artificial intelligence/machine learning related programs, such as but not limited to, SVM, Deep Learning, Bayesian Networking, etc.) generates a model which predicts what the patron may wish to order);
determine, from the detection data, a pose parameter indicative of one or more subject persons' relationship to a victual in the victual menu (pg.4, ¶ [0035] discusses only two patrons are at the table, with one of the patron's plates being full and the other patron's plates being empty, and
to determine, from the detection data, a victual tracking parameter indicative of consumption of the victual (pg.4, ¶ [0035] discusses individual areas 1, 2 and 4 are considered empty (i.e., meal completed), and individual area 3 is considered full, i.e., meal not completed), and
wherein the controlling the victual ordering system further comprises outputting a recommendation to order more of the victual based on the pose parameter and the victual tracking parameter (pg.4, ¶ [0034] discusses monitoring can also be utilized to determine drink levels, and send an appropriate notice once a drink has been completed so as to signal the staff to inquire if the patron would like another drink).
The cited portions of Cronin et al. teaches a system and method capable of identifying a seating position of each member of a group, determine the consumption of a meal and recommending staff to refill a drink.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have the ability to monitor patrons within a restaurant, detect consumption status of a meal and output a recommendation to staff to request a refill as in the improvement discussed in Cronin et al., in the system executing the method of the Alkan Katsu combination. As in Cronin et al., it is within the capabilities of one of ordinary skill in the art to visually monitor patrons at a table determine the consumption state of a meal and provide recommendations to reorder completed portion of a meal to the Alkan Katsu with the predicted result of 1) improve the patron's dining experience; 2) improve supply chain and response; and 3) improve patron turnover. as needed in the Alkan Katsu combination.
As per Claim 16, Alkan discloses the method according to claim 15, wherein the detection data comprises one or more of: a subject parameter, a group of subjects parameter, an object parameter, a face parameter, a victual parameter, a victual tracking parameter, and a radio sensing parameter (pg.7, ¶ [0073] discusses the satisfaction level component 510 may use the collaboration of data (e.g., historical and real-time data) gathered from one or more collaborative members in a group of members).
As per Claim 18, Alkan discloses the method according to claim 15,510 may determine, from the collaborative data, that a customer 504 has a positive level or high level of customer satisfaction of a previously ordered or consumed meal(s) as compared to other previously determined levels of customer satisfaction relating to the member profile).
Examiner is construing using the positive satisfaction of a previously ordered or consumed meal as content based filtering because items similar to what a user liked before, by analyzing item features (like genre, director, keywords) and user preferences to build a profile, making it great for personalized niche suggestions but requiring good item metadata).
As per Claim 20, Alkan discloses the method according to claim 15. However, Alkan fails to disclose wherein the menu data comprises data indicative of a sharing menu for a group of subjects.
Katsu teaches wherein the menu data comprises data indicative of a sharing menu for a group of subjects (pg.3, 7th paragraph discusses Since the proposed menu is determined based on the content of the nutrients, etc., it is possible to propose the menu to a group such as a family composed of a plurality of users…pg.4, 1st paragraph discusses Since such a configuration calculates the recommended nutrient intake of the proposed target unit and uses it for the determination of the proposed menu, for example, the same rule is applied when the proposed target unit is an individual or a group).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have utilized menu data to provide a proposed menu for a group of individuals as in the improvement discussed in Katsu in the system executing the method of Alkan. As in Katsu, it is within the capabilities of one of ordinary skill in the art display recommended items onto a menu to the monitoring and detection data of diners with the predicted result of displaying recommended items on a menu as needed in Alkan.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Alkan et al., U.S. Patent Application Publication 2019/0073601 in view of Katsu Japanese Patent JP 2020107096 in view of Cronin et al., U.S. Patent Application Publication 2018/0276770 further in view of Dillion et al., U.S. Patent Application Publication 2014/0229498.
As per Claim 12, Alkan and Katsu discloses the electronic device according to claim 11.
As stated above, Alkan is directed toward recommending meals for a group of members to maximize consumption satisfaction of each member of a group using one or more Internet of Things (IoT) devices in an IoT network.
Katsu teaches a menu suggestion system that is communicably connected to a user terminal and provides a menu suggestion service for suggesting a menu composed of one or a plurality of dishes to a user who operates the user terminal… then enables menu suggestion to a group such as a family composed of a plurality of users.
However, the Alkan-Katsu combination fails to wherein the electronic device is configured to determine whether the menu data is to be updated and/or modified based on the second user input.
Dillon teaches wherein the electronic device is configured to determine whether the menu data is to be updated and/or modified based on the second user input (pg.18, ¶ [0152] discusses the request may be a specific request submitted by a user, such as a member of the group. Or it may be an automated command to provide a group recommendation whenever a member of the group performs a certain action, such as accesses the application. The request may include one or more criteria, such as a desired class of items, desired traits, a context, or other information that the system may consider to be a required criterion for a recommended item when making a group recommendation 1325 for one of the items in the database).
Therefore it would have been obvious to one of ordinary skill in the art of group ordering before the effective filing date of the claimed invention to modify the system of the Alkan-Katsu combination to include the ability to allow updates to a menu based on a member input as taught by Dillon et al.to provide a method and system for recommending items, such as beverages, that members of a group are likely to find appealing. Abstract
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ASHFORD S HAYLES whose telephone number is (571)270-5106. The examiner can normally be reached M-F 6AM-4PM with Flex.
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/ASHFORD S HAYLES/Primary Examiner, Art Unit 3627
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