DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 16 July 2026 has been entered.
Status of Claims
This action is in reply to the response, amendments, and request for continued examination filed on 16 July 2026. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1, 6, 8, and 13 have been amended.
Claims 2-5, and 9-12 are cancelled.
Claims 7 are original / previously presented.
Claims 1, 6-8, and 13 are currently pending and have been examined.
Response to Arguments
Regarding the previous objection of claims 8 and 13, the Applicant has successfully amended the claims and accordingly the objection is rescinded.
Regarding the previous 35 USC 112(b) rejection of claims 1, 3-8, 10-13, the Applicant has successfully amended and/or cancelled the claims, and accordingly the rejection is rescinded.
Regarding the previous 35 USC 101 rejection of claims 3-5, 10-12, the Applicant has successfully cancelled the claims, and accordingly the rejection is rescinded.
Regarding the Applicant’s arguments filed regarding the previous 35 USC 101 rejection of claims 1, 6-8, and 13, the arguments have been considered but they are not persuasive.
Applicant argues the claims are eligible because “The present invention utilizes a CNN learning model to obtain biometric information, generate feature vectors from the obtained biometric information, and match them with a large dataset of reservation holders. Feature vectors are data in a high-dimensional numerical space, and humans cannot generate feature vectors in their minds, nor can humans perform feature vector matching. To state otherwise is to ignore the basic premise of the underlying area of technology” (Remarks pg. 9). Examiner disagrees. First, the CNN learning model does not obtain the biometric information or match the visitor as claimed. Instead, biometric information is acquired from a camera (which at this high level of detail this data gathering feature is not a practical application or significantly more), and the identifying a visitor / matching processing is performed by a processor (claim 1) or server (claims 8 and 18). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). The learning model trained by CNN as claimed only obtains / generates a first feature vector representing the biometric information of the visitor based on the biometric information of the visitor. No technical details are claimed about the learning model or how the learning model is trained by CNN / convolutional neural network. The CNN learning model is merely ‘applying’ the judicial exception step of generating the feature vector based on the biometric information, and at this high level of detail without any claimed algorithm steps how this occurs or any details regarding how the model is trained this is no more than generally linking the use of the judicial exception to a technology / field of use (i.e. machine learning) by applying a standard machine learning approach. Second, there are no technical details provided about the feature vector in the claims or the specification. Applicant’s specification ¶[0071] only states that a feature vector consists of a plurality of feature values. A person can construct a plurality of feature values. In further support, according to the Cross Validated website feature vectors store particular observations in a specific order, such as a row in a relational table. See Cross Validated ‘Difference between feature, feature ser and feature vector’ <https://stats.stackexchange.com/questions/192873/difference-between-feature-feature-set-and-feature-vector> (<https://web.archive.org/web/20220323225024/https://stats.stackexchange.com/questions/192873/difference-between-feature-feature-set-and-feature-vector> captured on 23 March 2022 using the Wayback Machine). A row in a relational table (such as the feature vector on the Cross Validated website) in a particular order can also be constructed manually by a person. There are no claimed particular, technical details regarding feature vectors or limitations regarding scope that would otherwise preclude a person from generating a feature vector (e.g. an array [1, 0, 1] or [male, blonde hair, blue eyes]), or identifying a visitor from a plurality of reservation holders (i.e. as few as two) by comparing feature vectors for a match. Hence, these features do not provide technical details that are a practical application or significantly more to the judicial exception. This argument is not persuasive.
Applicant argues the claims are eligible because “these features of the Applicant’s claims cannot be reasonably said to ‘manage personal behavior or relationships or interactions between people’ as that term or art is interpreted under the MPEP. The subgrouping ‘certain methods of organizing human activity’ is ‘not to be expanded beyond these enumerated sub-groupings except in rare circumstances…’ MPEP 2106.05(a)(2)(II). The present invention is directed to the conversion of biometric data into feature vectors which are then used to operate certain aspects of a hotel’s infrastructure. There is no example in the MPEP, or otherwise, where such a conversion and operation are considered ‘certain methods of organizing human activity’, and there is certainly no example where a CNN learning model is used to obtain biometric information, generate feature vectors from the obtained biometric information, and match them with a large dataset of reservation holders” (Remarks pg. 9). Examiner disagrees. First, the activities of generating a first feature vector…, identifying the visitor among the reservation holders…, matching feature vectors representing biometric information…, determining whether or not the visitor is allowed to check in…, based on the identified visitor being allowed to check in setting the identifiers visitor as a hotel guest…, notifying the hotel guest of a room number…, determining that check in to the hotel of the identified visitor is impossible, transmitting a first message regarding a time period which the visitor can check in…, notifying the hotel guest of a key…, determining whether or not the visitor is allowed to check in…, based on the hotel guest checking out invalidating the key / perform a control related to invalidating the key each represent managing personal behavior or relationships or interactions between people. A person can otherwise generate a first feature vector representing the biometric information of the visitor (e.g. person / hotel employee creates an array [1, 0, 1] or [male, blonde hair, blue eyes] describing features obtained in a biometric source such as an image). Note that nothing in the claims limit the complexity of the feature vectors. A person can otherwise identify a visitor among reservation holders by matching vectors (e.g. a person / hotel employee compares arrays to find matches). Nothing limits the complexity or volume of the feature vectors. A person can otherwise determine whether the visitor is allowed to check in (e.g. a hotel desk clerk obtains reservation information and checks to see if a room is ready). A person can otherwise set the identified visitor as a hotel desk (e.g. a person / hotel employee changes a registration status of the visitor / guest). A person can otherwise notify another person of a room number, and/or room number and key (e.g. person / hotel employee tells a customer checking in of their room number and room code to unlock their door). A person can otherwise transmit a message about when the visitor can check in (e.g. a person / hotel employee tells a customer when they are allowed to check in). A person can otherwise invalidate a key (e.g. a person / hotel employee removes access abilities for a customer passcode or changes an access passcode). Hence, each of these activities align with the subgrouping of managing personal behavior or relationships or interactions between people. Second, classifying these limitations in at least one of the subgroupings of commercial or legal interactions, managing personal behavior or relationships or interactions between people, and following rules or instructions does not go outside of the subgroupings. Third, the CNN learning model which is cited to generate a first feature vector is recited without any technical details, and since there are no details claimed how the model is trained or the algorithm steps how it actually generates the first feature vector representing the biometric information of the visitor, then at this high level of detail this is no more than using computers as a tool (i.e. apply it) with a standard machine-learning approach (e.g. CNN) as a general linkage to a technology to implement a judicial exception, which does not preclude the claims from reciting a judicial exception, and does not provide a practical application or significantly more. Fourth, the CNN learning model is not performing the matching processing, or that there is a ‘large dataset’ as argued above. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). This argument is not persuasive.
Regarding the previous 35 USC 103 rejection of claims 1, 3-4, 7-8, 10-11, 13, the Applicant has successfully amended and/or cancelled the claims, and accordingly the rejection is rescinded.
Priority
The application 18/904,241 filed on 2 October 2024 claims priority from Japan application JP2023-182330 filed on 24 October 2023.
Information Disclosure Statement
The Information Disclosure Statement (IDS) filed on 2 October 2024 has been acknowledged by the Office.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 6-8, and 13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 6-8, and 13:
Step 1:
Claims 1, 6-7 recite a server; claim 8 recite a method; and claim 13 recites a non-transitory computer readable storage device. Since the claims recite either a process, machine, manufacture, or composition of matter, the claims satisfy Step 1 of the Subject Matter Eligibility Framework in MPEP 2106 and the 2019 Patent Examination Guidelines (PEG). Analysis proceeds to Step 2A Prong One.
Step 2A – Prong One:
Claims 1, 6-8, and 13 recite an abstract idea. Independent claim 1 recites generate a first feature vector representing the biometric information of the visitor based on the biometric information of the visitor; identify the visitor from among the plurality of reservation holders of a hotel stay by performing a matching processing using the first feature vector and a second feature vector representing the stored biometric information, and determine whether or not the identified visitor is allowed to check in to the hotel based on the reservation information of the identified visitor; based on the identified visitor being allowed to check in, set the identified visitor as a hotel guest; notify the hotel guest of a guest room number assigned to the hotel guest; and based on determining that check in to the hotel of the identified visitor is impossible, transmit a first message regarding a time period during which the visitor can check in to the hotel and a second message regarding an employee of the hotel, notify the hotel guest of a key of the guest room assigned to the hotel guest together with the guest room number, determine whether or not the identified visitor is allowed to check in based on a check-in of the identified visitor being incomplete, and based on the hotel guest checking out, perform a control related to invalidating the key. Independent claim 8 recites generating, a first feature vector representing the biometric information of the visitor based on the biometric information of the visitor; identifying the visitor from among the plurality of reservation holders of hotel stay by performing a matching processing using the first feature vector and a second feature vector representing the stored biometric information, and determining whether or not the identified visitor is allowed to check in to the hotel based on the reservation information of the identified visitor; based on the identified visitor being allowed to check in, setting the identified visitor as a hotel guest; notifying the hotel guest of a guest room number assigned to the hotel guest; and based on determining that check in to the hotel of the identified visitor is impossible, transmitting, a first message regarding a time period during which the visitor can check in to the hotel and a second message regarding an employee of the hotel, notifying the hotel guest of a key of the guest room assigned to the hotel guest together with the guest room number, determining, whether or not the identified visitor is allowed to check in based on a check-in of the identified visitor being incomplete, and invalidating, the key based on the hotel guest checking out. Independent claim 13 recites generating a first feature vector representing the biometric information based on the biometric information; identifying the visitor from among the plurality of reservation holders of hotel stay by performing a matching processing using the first feature vector and a second feature vector representing the stored biometric information, and determining whether or not the identified visitor is allowed to check in to the hotel based on the reservation information of the identified visitor; based on the identified visitor being allowed to check in, setting the identified visitor as a hotel guest; notifying the hotel guest of a guest room number assigned to the hotel guest; and based on determining that check in to the hotel of the identified visitor is impossible, transmitting, a first message regarding a time period during which the visitor can check in to the hotel and a second message regarding an employee of the hotel, notifying the hotel guest of a key of the guest room assigned to the hotel guest together with the guest room number, determining, whether or not the identified visitor is allowed to check in based on a check-in of the identified visitor being incomplete, and based on the hotel guest checking out, perform a control related to invalidating the key.
The claims as a whole recite certain methods of organizing human activities.
First, the limitations of generating, a first feature vector representing the biometric information of the visitor based on the biometric information of the visitor; identifying the visitor from among the plurality of reservation holders of hotel stay by performing a matching processing using the first feature vector and a second feature vector representing the stored biometric information, and determining whether or not the identified visitor is allowed to check in to the hotel based on the reservation information of the identified visitor; based on the identified visitor being allowed to check in, setting the identified visitor as a hotel guest; notifying the hotel guest of a guest room number assigned to the hotel guest; and based on determining that check in to the hotel of the identified visitor is impossible, transmitting, a first message regarding a time period during which the visitor can check in to the hotel and a second message regarding an employee of the hotel, notifying the hotel guest of a digital key of the guest room assigned to the hotel guest together with the guest room number, determining, whether or not the identified visitor is allowed to check in based on a check-in of the identified visitor being incomplete, and invalidating / perform a control related to invalidating, the key based on the hotel guest checking out are certain methods of organizing human activities. For instance, these limitations represent the sub-groupings of commercial or legal interactions, managing personal behavior or relationships or interactions between people, and following rules or instructions. For example, commercial or legal interactions includes determining whether or not the visitor is allowed to check in…, based on the identified visitor being allowed to check in setting the identifiers visitor as a hotel guest…, notifying the hotel guest of a room number…, determining that check in to the hotel of the identified visitor is impossible, transmitting a first message regarding a time period which the visitor can check in…, notifying the hotel guest of a key…, determining whether or not the visitor is allowed to check in…; managing personal behavior or relationships or interactions between people includes generating a first feature vector…, identifying the visitor among the reservation holders…, matching the biometric information…, determining whether or not the visitor is allowed to check in…, based on the identified visitor being allowed to check in setting the identifiers visitor as a hotel guest…, notifying the hotel guest of a room number…, determining that check in to the hotel of the identified visitor is impossible, transmitting a first message regarding a time period which the visitor can check in…, notifying the hotel guest of a key…, determining whether or not the visitor is allowed to check in…, based on the hotel guest checking out invalidating the key / perform a control related to invalidating the key…; and following rules or instructions includes generating a first feature vector…, identifying the visitor among the reservation holders…, matching the biometric information…, determining whether or not the visitor is allowed to check in…, based on the identified visitor being allowed to check in setting the identifiers visitor as a hotel guest…, notifying the hotel guest of a room number, determining that check in to the hotel of the identified visitor is impossible, transmitting a first message regarding a time period which the visitor can check in…, notifying the hotel guest of a key…, determining whether or not the visitor is allowed to check in…, based on the hotel guest checking out invalidating the key / perform a control related to invalidating the key. The presence of generic / general computer components such as a server / server apparatus, memory, processor, learning model (a program, per Applicant specification ¶[0143-145]), non-transitory computer-readable storage medium, program, computer, terminal possessed by a hotel guest, a digital key does not preclude the steps from reciting certain methods of organizing human activities, since the number of people involved in the activities is not dispositive as to whether a claim limitation falls within this grouping and instead it is based on whether an activity itself falls within one of the sub-groupings. If a claim limitation, under its broadest reasonable interpretation, covers certain methods of organizing human activity (e.g. commercial or legal interactions, managing personal behavior or relationships or interactions between people, following rules or instructions) regardless of the recitation of generic computer components or other machinery in its ordinary capacity, then it falls within the ‘Certain Methods of Organizing Human Activity’ grouping of abstract ideas.
Accordingly, the claims recite an abstract idea. Analysis proceeds to Step 2A Prong Two.
Step 2A – Prong Two:
This judicial exception is not integrated into a practical application. First, claims 1, 6-8, and 13 as a whole merely describes how to generally ‘apply’ the concept of certain methods of organizing human activities in a computer environment. The claimed computer components (i.e. server / server apparatus, memory, processor, learning model (learning model (a program, per Applicant specification ¶[0143-145]), non-transitory computer-readable storage medium, program, computer, terminal possessed by a hotel guest, a digital key are recited at a high-level of generality and are merely invoked as tools to perform manual processes. Simply implementing the abstract idea on a generic / general purpose computer is not a practical application of the abstract idea. See MPEP 2106.04(d) and 2016.05(f). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Next, the additional element of biometric information in the limitations does no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e. biometrics), and as such does not provide integration into a practical application. See MPEP 2106.04(d) and 2106.05(h). Hence, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Next, the additional element of storing and its step of storing biometric information and reservation information for each of a plurality of reservation holders of a hotel stay is recited at a high level of generality (i.e. as a general means of storing data for subsequent matching / determining), and amounts to mere storing data, which is a form of insignificant extra-solution activity and not a practical application. See MPEP 2106.04(d) and 2106.05(g). Furthermore, the processor / server (generic computer) is only being used as a tool in the storing, which is also not indicative of integration into a practical application. See MPEP 2106.04(d) and 2106.05(f). Note that there are no particular technical steps regarding storing more than using computers as a tool to perform in their ordinary capacity (i.e. to store data). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Next, the additional element of acquiring and its step of acquiring biometric information of a visitor who has visited a hotel from a camera installed in the hotel are recited at a high level of generality (i.e. as a general means of gathering data for subsequent matching / determining), and amounts to mere data gathering, which is a form of insignificant extra-solution activity and not a practical application. See MPEP 2106.04(d) and 2106.05(g). Furthermore, the processor / server, camera (generic computer, general computer component) is only being used as a tool in the acquiring, which is also not indicative of integration into a practical application. See MPEP 2106.04(d) and 2106.05(f). Note that there are no particular technical steps regarding acquiring more than using computers as a tool to perform in their ordinary capacity (i.e. to receive data, to gather image data). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Next, the additional element of the learning model trained by CNN in the limitations (e.g. generating, by the server apparatus, a first feature vector representing the biometric information of the visitor based on the biometric information of the visitor, wherein the first feature vector is obtained by using a learning model trained by CNN (Convolutional Neural Network)) does no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e. machine learning, CNN), and as such does not provide integration into a practical application. See MPEP 2106.04(d) and 2106.05(h). There are no particular technical details regarding the steps involved to train the machine learning algorithm, or in the steps of the machine learning algorithm itself more than using computers as a tool (i.e. apply it) with a standard machine-learning approach (e.g. CNN). Hence, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Next, the additional element of transmitting a signal / displaying and its step to transmit a signal… the signal being configured to cause the first and the second messages to be displayed on a display installed in the hotel are recited at a high level of generality (i.e. as a general means of transmitting / outputting data regarding results of the determining), and amounts to mere transmitting data / outputting data, which is a form of insignificant extra-solution activity and not a practical application. See MPEP 2106.04(d) and 2106.05(g). Furthermore, the processor / server, signal, display installed in the hotel (generic computers, general computer components) are only being used as a tool in the transmitting and displaying, which is also not indicative of integration into a practical application. See MPEP 2106.04(d) and 2106.05(f). Note that there are no particular technical steps regarding transmitting and displaying more than using computers as a tool to perform in their ordinary capacity (i.e. to transmit data, to output data). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Next, the additional element of a digital key (e.g. notifying by the server apparatus the terminal possessed by the hotel guest of a digital key of the guest room assigned to the hotel guest together with the guest room number; invalidating, by the server apparatus, the digital key based on the hotel guest checking out) in the limitations does no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e. computers, keyless entry), and as such does not provide integration into a practical application. See MPEP 2106.04(d) and 2106.05(h). Hence, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Also, while identified above as an organizing human activity in Step 2A Prong One, note that the step of setting (e.g. based on the identified visitor being allowed to check in, set the identified visitor as a hotel guest) is recited at a high level of generality (i.e. as a general means of recording data associated with the determining), and also amounts to mere electronic record keeping, which is a form of insignificant extra-solution activity and not a practical application. See MPEP 2106.04(d) and 2106.05(g). Furthermore, the server / processor (generic computer) is only being used as a tool in the setting, which is also not indicative of integration into a practical application. See MPEP 2106.04(d) and 2106.05(f). Note that there are no particular technical steps regarding setting more than using computers as a tool to perform an otherwise manual process (i.e. to record information). Accordingly, this element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Also, while identified above as an organizing human activity in Step 2A Prong One, note that the step of notifying (e.g. notifying a terminal possessed by the hotel guest of a guest room number assigned to the hotel guest; notifying by the server apparatus the terminal possessed by the hotel guest of a digital key of the guest room assigned to the hotel guest together with the guest room number) is recited at a high level of generality (i.e. as a general means of transmitting / outputting data associated with the determining), and also amounts to mere transmitting data, which is a form of insignificant extra-solution activity and not a practical application. See MPEP 2106.04(d) and 2106.05(g). The subject matter of a digital key is no more than generally linking the judicial exception to a technology / field of use (i.e. computers, keyless entry), which is not indicative of a practical application. See MPEP 2106.05(d) and 2106.05(h). Furthermore, the server / processor and terminal (generic computers) are only being used as a tool in the notifying, which is also not indicative of integration into a practical application. See MPEP 2106.04(d) and 2106.05(f). Note that there are no particular technical steps regarding notifying more than using computers as a tool in their ordinary capacity (i.e. to transmit data). Accordingly, this element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The combination of these additional elements is no more than mere instructions to apply the exception using generic computers / general computer components (server / server apparatus, memory, processor, learning model (learning model (a program, per Applicant specification ¶[0143-145]), non-transitory computer-readable storage medium, program, computer, terminal possessed by a hotel guest), digital key, generally linked to a technology / field of use (biometrics, machine learning / CNN, keyless entry); and adding high-level extra-solution and/or post-solution activities (data gathering, data storage / record keeping, transmitting data). Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limitations on practicing the abstract idea. Hence, the claim is directed to an abstract idea. Analysis proceeds to Step 2B.
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above in Step 2A Prong Two with respect to integration of the abstract idea into a practical application, the additional element of using a server, memory, processor, learning model (learning model (a program, per Applicant specification ¶[0143-145]), non-transitory computer-readable storage medium, program, computer, terminal possessed by a hotel guest, digital key to perform generating a first feature vector…, identifying the visitor among the reservation holders…, matching the biometric information…, determining whether or not the visitor is allowed to check in…, based on the identified visitor being allowed to check in setting the identifiers visitor as a hotel guest…, notifying the hotel guest of a room number…, determining that check in to the hotel of the identified visitor is impossible, transmitting a first message regarding a time period which the visitor can check in…, notifying the hotel guest of a key…, determining whether or not the visitor is allowed to check in…, based on the hotel guest checking out invalidating the key / perform a control related to invalidating the key… amounts to no more than mere instructions to ‘apply’ the exception using generic / general purpose computers. The same analysis applies here in Step 2B, i.e. mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. See MPEP 2106.05(f). Hence, these features do not provide an inventive concept / significantly more.
As discussed above in Step 2A Prong Two with respect to integration of the abstract idea into a practical application, the additional element regarding biometric information does no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e. biometrics). The same analysis applies here in Step 2B, i.e. generally linking the use of the judicial exception to a particular technological environment or field of use does not provide integration into a practical application in Step 2A or provide an inventive concept in Step 2B. See MPEP 2106.05(h). Furthermore, see the Applicant’s specification background ¶[0002-6] describing the additional element using biometrics in the hotel industry for checking-in as existing technology, and also ¶[0032] describing biometric information such a high level that indicates this additional element is sufficiently well-known that the specification does not need to describe the particulars to satisfy 35 USC 112(a). Hence, these features do not provide an inventive concept / significantly more.
As discussed above in Step 2A Prong Two with respect to integration of the abstract idea into a practical application, the additional elements regarding the storing are recited at a high level of generality (i.e. as a general means of storing data for subsequent matching / determining), and amount to mere storing data, which is a form of insignificant extra-solution activity. The same analysis applies here in Step 2B, i.e. adding insignificant extra-solution activity to the judicial exception does not provide integration into a practical application in Step 2A or provide an inventive concept in Step 2B. See MPEP 2106.05(g). The use of the computer (i.e. server / processor) in these steps merely represents using a generic / general purpose computer as a tool, and is not indicative of an inventive concept. See MPEP 2106.05(f). Furthermore, these storing steps are also claimed at a high level of generality, and/or as insignificant extra-solution activities (e.g. data storage) representing computer functions that the courts have recognized as well-understood, routine, and conventional functions that do not present an inventive concept. See MPEP 2106.05(d)(II) in particular electronic record keeping (Alice), storing and retrieving information in memory (Versata; OIP Techs). See the Applicant’s specification ¶[0014], ¶[0159] describing the additional element of a storing means for storing biometric information and reservation information at such a high level that indicates this additional element is sufficiently well-known that the specification does not need to describe the particulars to satisfy 35 USC 112(a). Hence, these features do not provide an inventive concept / significantly more.
As discussed above in Step 2A Prong Two with respect to integration of the abstract idea into a practical application, the additional elements regarding the acquiring are recited at a high level of generality (i.e. as a general means of gathering data for subsequent identifying / matching), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. The same analysis applies here in Step 2B, i.e. adding insignificant extra-solution activity to the judicial exception does not provide integration into a practical application in Step 2A or provide an inventive concept in Step 2B. See MPEP 2106.05(g). The use of the computers (i.e. server / processor, camera) in these steps merely represents using a generic / general purpose computer and computer component as a tool, and is not indicative of an inventive concept. See MPEP 2106.05(f). Furthermore, these acquiring steps are also claimed at a high level of generality, and/or as insignificant extra-solution activities (e.g. data gathering) representing computer functions that the courts have recognized as well-understood, routine, and conventional functions that do not present an inventive concept. See MPEP 2106.05(d)(II) in particular receiving or transmitting data over a network (Symantec), using a telephone for image transmission (TLI Communications), electronically scanning or extracting data from a physical document (Content Extraction). See the Applicant’s specification ¶[0014], ¶[0021], ¶[0032], ¶[0105], ¶[0159] describing the additional element of acquiring biometric information from a visitor from an acquiring means, and acquiring an image from a camera of a visitor at the entrance of a hotel at such a high level that indicates this additional element is sufficiently well-known that the specification does not need to describe the particulars to satisfy 35 USC 112(a). Hence, these features do not provide an inventive concept / significantly more.
As discussed above in Step 2A Prong Two with respect to integration of the abstract idea into a practical application, the additional element regarding the learning model trained by CNN does no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e. machine learning, CNN). The same analysis applies here in Step 2B, i.e. generally linking the use of the judicial exception to a particular technological environment or field of use does not provide integration into a practical application in Step 2A or provide an inventive concept in Step 2B. See MPEP 2106.05(h). There are no particular claimed details regarding the algorithm steps involved to train the learning model, or the steps in implementing the learning model algorithm more than using computers as a tool to perform an otherwise manual process (i.e. generating a first feature vector representing the biometric information) associated with a standard machine learning approach (e.g. CNN). Furthermore, see the Applicant’s specification ¶[0106] omitting details about using and training a learning model learned by CNN because it is an existing technology “Note that a detailed description will be omitted since existing technology can be used for the face image extraction processing by the biometric information acquisition unit 403. For example, the biometric information acquisition unit 403 may extract a face image (a face area) from the image data by using a learning model learned by a CNN (Convolutional Neural Network)” at such a high level that indicates this additional element is sufficiently well-known that the specification does not need to describe the particulars to satisfy 35 USC 112(a). Also note that Applicant specification ¶[0071] also states that details are omitted about generating feature values because this is an existing technology “Note that since an existing technology can be used to generate the feature values by the reservation management unit 302, a detailed description thereof will be omitted. For example, the reservation management unit 302 extracts eyes, nose, mouth, and so on as feature points from the face image”. Hence, these features do not provide an inventive concept / significantly more.
As discussed above in Step 2A Prong Two with respect to integration of the abstract idea into a practical application, the additional elements regarding the transmitting a signal / displaying are recited at a high level of generality (i.e. as a general means of transmitting / outputting data regarding results of the determining), and amounts to mere transmitting data / outputting data, which is a form of insignificant extra-solution activity. The same analysis applies here in Step 2B, i.e. adding insignificant extra-solution activity to the judicial exception does not provide integration into a practical application in Step 2A or provide an inventive concept in Step 2B. See MPEP 2106.05(g). The use of the computers (i.e. server / processor, signal, display installed in the hotel) in these steps merely represents using a generic / general purpose computer and computer component as a tool, and is not indicative of an inventive concept. See MPEP 2106.05(f). Furthermore, these transmitting and displaying steps are also claimed at a high level of generality, and/or as insignificant extra-solution activities (e.g. transmitting data) representing computer functions that the courts have recognized as well-understood, routine, and conventional functions that do not present an inventive concept. See MPEP 2106.05(d)(II) in particular receiving or transmitting data over a network (Symantec), sending messages over a network (OIP Techs), a computer receives and sends information over a network (buySAFE). See the Applicant’s specification Fig 18, ¶[0127-129] describing the additional element of transmitting a message to the signage when it is determined that a visitor is not allowed to check in, and displaying the message that indicates this additional element is sufficiently well-known that the specification does not need to describe the particulars to satisfy 35 USC 112(a). Hence, these features do not provide an inventive concept / significantly more.
As discussed above in Step 2A Prong Two with respect to integration of the abstract idea into a practical application, the additional element regarding a digital key does no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e. computers, keyless entry). The same analysis applies here in Step 2B, i.e. generally linking the use of the judicial exception to a particular technological environment or field of use does not provide integration into a practical application in Step 2A or provide an inventive concept in Step 2B. See MPEP 2106.05(h). Furthermore, see the Applicant’s specification ¶[0023-26] describing the additional element of each door may be unlocked with a digital key and unlocking a door with the digital key is ‘obvious to those skilled in the art and is different from the purpose of the present application’, and ¶[0118] regarding invalidating a digital key at such a high level that indicates this additional element is sufficiently well-known that the specification does not need to describe the particulars to satisfy 35 USC 112(a). Hence, these features do not provide an inventive concept / significantly more.
Also, as discussed above in Step 2A Prong Two with respect to integration of the abstract idea into a practical application, the Step 2A Prong One organizing human activity elements regarding the setting are recited at a high level of generality (i.e. as a general means of recording data associated with the determining), and also amounts to the extra-solution activity of electronic record keeping, which is not a practical application or an inventive concept. See MPEP 2106.05(g). The use of the computer (i.e. server / processor) in these steps merely represents using a generic / general purpose computer as a tool, and is not indicative of an inventive concept. See MPEP 2106.05(f). Furthermore, these setting steps are also claimed at a high level of generality, and/or as insignificant extra-solution activities (e.g. record keeping) representing computer functions that the courts have recognized as well-understood, routine, and conventional functions that do not present an inventive concept. See MPEP 2106.05(d)(II) in particular electronic record keeping (Alice). Hence, these features do not provide an inventive concept / significantly more.
Also, as discussed above in Step 2A Prong Two with respect to integration of the abstract idea into a practical application, the Step 2A Prong One organizing human activity elements regarding the notifying are recited at a high level of generality (i.e. as a general means of transmitting / outputting data associated with the determining), and also amounts to the extra-solution activity of transmitting data, which is not a practical application or an inventive concept. See MPEP 2106.05(g). The use of the computer (i.e. server / processor, terminal) in these steps merely represents using generic / general purpose computers as a tool, and is not indicative of an inventive concept. See MPEP 2106.05(f). The subject matter of a digital key is no more than generally linking the judicial exception to a technology / field of use (i.e. computers, keyless entry), which is not indicative of an inventive concept. See MPEP 2106.05(h). Furthermore, these notifying steps are also claimed at a high level of generality, and/or as insignificant extra-solution activities (e.g. transmitting data) representing computer functions that the courts have recognized as well-understood, routine, and conventional functions that do not present an inventive concept. See MPEP 2106.05(d)(II) in particular receiving or transmitting data over a network (Symantec), using a telephone for image transmission (TLI Communications), sending messages over a network (OIP Techs), a computer receives and sends information over a network (buySAFE). See the Applicant’s specification ¶[0023-26] describing the additional element of each door may be unlocked with a digital key and unlocking a door with the digital key is ‘obvious to those skilled in the art and is different from the purpose of the present application’ at such a high level that indicates this additional element is sufficiently well-known that the specification does not need to describe the particulars to satisfy 35 USC 112(a). Hence, these features do not provide an inventive concept / significantly more.
The claims do not improve another technology or technical field. Instead the claims represent a generic implementation of organizing human activities ‘applied’ by generic / general purpose computers, generally ‘applied’ to a field of use, and using general computer components in extra-solution capacities such as data gathering / data storage / transmitting data. The claims do not provide meaningful limitations beyond generally linking the user of an abstract idea to a particular technological environment. At best, the claims are more directed towards solving a business / economic / entrepreneurial problem (i.e. how to identify a guest for check in), that is tangentially associated with a technology element (e.g. biometrics, machine learning / CNN, keyless entry), rather than solving a technology based problem. See MPEP 2106.05(a). The claims do not improve the functioning of a computer itself. The claims do not improve biometrics technology. The claims are more directed towards improving a commercial / business / entrepreneurial process rather than improving a computer outside of a business use, i.e. using computers a tool. The claims do not apply the judicial exception with or by use of a particular machine. The claims do not effect a transformation or reduction to a particular article to a different state or thing. The claims do not add a specific limitation other than what is well understood, routine, and conventional in a way that confines the claim to a particular useful application.
Viewing the claim limitations as an ordered combination does not add anything further than looking at each of the claim limitations individually, both with respect to the independent claims 1, 8, 13, and further considering the addition of dependent claims 6-7. Note that the combination of limitations and claim elements add nothing that is not already present when the steps are considered separately, simply reciting implementation as performed by using generic computers / general computer components, see Alice (2014), and does not provide a non-conventional and non-generic arrangement of various computer components to achieve a technical improvement, see BASCOM Global Internet v. AT&T Mobility LLC (2016). Hence, the ordered combination of elements does not provide significantly more. With respect to the dependent claims:
Dependent claim 6: The limitation wherein the digital key is used to determine whether or not an elevator can be used is further directed to a method of organizing human activity (managing personal behavior or interactions between people, following rules or instructions) as described in the independent claim. The recitation of a digital key is recited at a high level of detail and no more than a general linkage to a field of use / technology (i.e. keyless entry). Furthermore, see the Applicant’s specification ¶[0023-26] describing the additional element of each door may be unlocked with a digital key and unlocking a door with the digital key is ‘obvious to those skilled in the art and is different from the purpose of the present application’, and ¶[0132] regarding using a digital key to board an elevator at such a high level that indicates this additional element is sufficiently well-known that the specification does not need to describe the particulars to satisfy 35 USC 112(a). Similar to the independent claims and the claims above, this recitation does not meaningfully integrate the abstract idea in a practical application, and is not significantly more than the abstract idea.
Dependent claim 7: The limitation wherein the camera is incorporated into a signage installed in the hotel or is a surveillance camera represents an additional element that is not indicative of a practical application or significantly more. Further limiting the device as a surveillance camera still represents a general computer component performing in its ordinary capacity (i.e. a camera capturing / receiving data), which does not provide a practical application or significantly more. Furthermore, see the Applicant’s specification ¶[0129-131] describing the additional element of the device including a surveillance camera at the entrance of a hotel at such a high level that indicates this additional element is sufficiently well-known that the specification does not need to describe the particulars to satisfy 35 USC 112(a). For the reasons described above with respect to the independent claims, this judicial exception is not meaningfully integrated into a practical application, and is not significantly more than the abstract idea.
Therefore claims 1, 8, 13, and the dependent claims 6-7, and all limitations taken both individually and as an ordered combination, do not integrate the judicial exception into a practical application, nor do they include additional elements that are sufficient to amount to significantly more than the judicial exception. Accordingly, claims 1, 6-8, and 13 are ineligible.
Novelty / Non-Obviousness
Claims 1, 6-8, 13 are not rejected under 35 USC 102 or 35 USC 103. The Examiner knows of no art which teaches or suggests the features collectively recited in claim 1 and similarly recited in claims 8 and 13. The following reference(s) teach the features in the limitations of claims 1, 8, 13, however the Examiner has determined it would not have been obvious to one of ordinary skill in the art before the effective date of the claimed invention to combine these references in combination to render the claims obvious.
Claim 1:
A server apparatus, comprising:
at least one memory storing a set of instructions; and
at least one processor configured to execute the set of instructions to:
store biometric information and reservation information for each of a plurality of reservation holders of a hotel stay;
acquire biometric information of a visitor who has visited a hotel from a camera installed in the hotel;
generate a first feature vector representing the biometric information of the visitor based on the biometric information of the visitor, wherein the first feature vector is obtained by using a learning model trained by CNN (Convolutional Neural Network);
identify the visitor from among the plurality of reservation holders of a hotel stay by performing a matching processing using the first feature vector and a second feature vector representing the stored biometric information, and
determine whether or not the identified visitor is allowed to check in to the hotel based on the reservation information of the identified visitor;
based on the identified visitor being allowed to check in, set the identified visitor as a hotel guest;
notify a terminal possessed by the hotel guest of a guest room number assigned to the hotel guest; and
based on determining that check in to the hotel of the identified visitor is impossible, transmit a signal including a first message regarding a time period during which the visitor can check in to the hotel and a second message regarding an employee of the hotel, the signal being configured to cause the first and the second messages to be displayed on a display installed in the hotel;
wherein the at least one processor is further configured to execute the set of instructions to notify the terminal possessed by the hotel guest of a digital key of the guest room assigned to the hotel guest together with the guest room number;
wherein the at least one processor is further configured to execute the set of instructions to determine whether or not the identified visitor is allowed to check in based on a check-in of the identified visitor being incomplete;
wherein the at least one processor is further configured to execute the set of instructions to:
notify the terminal possessed by the hotel guest of a digital key of a guest room assigned to the hotel guest together with the guest room number,
determine whether or not the identified visitor is allowed to check in based on a check-in of the identified visitor being incomplete, and
based on the hotel guest checking out, perform a control related to invalidating the digital key.
The closest prior art of Nakahira (US 2022/0172218 A1) details a computer readable medium, memory and a program, and CPU; storing face image data and the name for the users / guests as identity information with reservation information for a hotel arrival date / departure date / room reservation, and there are N number of stored face images for reservations in the guest database; a pre-authentication device constantly / periodically photographing (i.e. camera) the vicinity of the entrance of the hotel and determining the face of the passerby people in the captured image; if there is a match of the guest of the day from the information in the central DB with a reservation, and if there is a match then the pre-authentication device transmits the detection information of the person registered to the management server to change their status from null to OFF; upon receiving detection information of the person having a reservation from the pre-authentication device the management server updates the guest DB and central database and changes the entrance passing status flag in the guest DB from null to OFF (i.e. a guest allowed to check in), and send information to the front terminal regarding check-in; determining that as a result of the comparison that there is no matching for the user, and the front terminal notifies the staff that the identify verification of the user has failed (i.e. determining that check in to hotel the identified visitor is impossible), and the front terminal is installed at the front desk of the hotel (i.e. …messages to be displayed on a display installed in the hotel); but does not explicitly state based on determining that check in to the hotel of the identified visitor is impossible, transmit a signal including a first message regarding a time period during which the visitor can check in to the hotel and a second message regarding an employee of the hotel, the signal being configured to cause the first and the second messages to be displayed; extracting the guest records of the day (i.e. a time based criteria) from the central DB which are used to compare the detected passerby (identified visitors) and determine whether to change their status flag to OFF and send to check-in, i.e. determining whether the identified visitor is allowed to check in; and determining there is no matching in the comparison and notifying that the identity verification has failed (and follows a ‘notify’ procedure) (Nakahira Fig 27, Fig 29-30, ¶[0063-65], ¶[0205-206], ¶[0214-228], ¶[0269]).
The prior art of Yamaguchi et al. (WO 2022/070252 A1) details generating a feature amount (feature vector) from a face image of the user when the user visits a hotel, and the face image is extracted from the image data by using a learning model learned by CNN convolutional neural network; the authentication server executes a collation process using the feature amount included in the authentication request (i.e. first feature vector) and the feature amount registered in the authentication database (i.e. second feature vector) (Yamaguchi pg. 5 ¶2 beginning “The authentication server 10 that has acquired…”, pg. 5 ¶4-8 beginning “After completing the user registration using the user registration application…”, pg. 8 ¶1 beginning “Since the existing technology can be used for the face image detection process…”).
The prior art of Todasco et al. (US 2015/0348049 A1) details providing the room number to the user’s device without the user having to wait in line; upon arrival of the guest presenting messages when the guest’s room is not ready including an estimated time that the room will be ready (i.e. first message regarding a time period during which the visitor can check in) and a reason the room is not ready (e.g. currently being cleaned, not yet check-in time) (i.e. second message regarding an employee of the hotel), and staff members accessing laptop computers associated with housekeeping and information associated with guest rooms; informing the guest on their mobile phone that they can access the guest room and unlock the room with their mobile phone as a key, along with a room number and any other welcome information / arrival information when the user arrives (Todasco ¶[0020], ¶[0059], ¶[0076-77], ¶[0079] ¶[0081]).
The prior art of Aase (US 2016/0005248 A1) details determining whether or not the identified visitor is allowed to check in based on a check-in of the identified visitor being incomplete, by detecting a first entry of a guest; and verifying during user authentication that both a time based criteria (e.g. a time prior to check-in or at the guest’s anticipated check-in) and an event based criteria (e.g. connected to a network) must be satisfied in order to continue and deliver the key (for check in), and if one criteria is answered negatively (i.e. check-in criteria is incomplete) then the access control server will instead continue to monitor events / time / triggers until the query is answered affirmatively at which time the key can then be issued (Aase Fig 4, Fig 9, ¶[0063-65], claim 1).
The prior art of Shahidzadeh (11,096,059 B1) details the key is activated only for the length of the stay of the user, and at the end of their stay the key is removed from the user entity device (Shahidzadeh col 28 ln 4-14).
The prior art of Brondrup (US 7,315,823 B2) details responding to a check-out request by remotely invalidating / deactivating the corresponding electronic key for a door lock; and also invalidating the electronic key if the reservation period associated with the electronic key has expired (Brondrup Fig 4, col 6 ln 8-31, claim1, claim 5, claim 10).
Additional Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US patent application publication 2021/0125111 A1 to Simon details a hospitality services processing system, that captures biometrics and identification credential information to confirm an existing reservation from a hotel reservation database.
US patent application publication 2021/0125187 A1 to Trelin details biometric pre-identification for hotels.
Conclusion
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BRIAN TALLMAN
Examiner
Art Unit 3628
/BRIAN A TALLMAN/Examiner, Art Unit 3628
/MICHAEL P HARRINGTON/Primary Examiner, Art Unit 3628
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