Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED CORRESPONDENCE
Priority
Applicant’s claim for the benefit of a prior-filed applications is acknowledged.
Receipt is acknowledged of certified copies of papers.
Information Disclosure Statement
The information disclosure statement filed October 15, 2024 fails to comply with 37 CFR 1.98(a)(2), which requires a legible copy of each cited foreign patent document; each non-patent literature publication or that portion which caused it to be listed; and all other information or that portion which caused it to be listed. It has been placed in the application file, but the information referred to therein has not been considered. Foreign reference EP 352931 by Dreyer has not been provided.
Claim Objections
Claims 31, 44, 50 is objected to because of the following informalities: the spelling of “synchronisation” should be “synchronization” in order to conform with USPTO practices. Appropriate correction is required.
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 31 – 50 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite:
performing a calibration procedure for the door to obtain reference data for the door;
obtaining data indicating kinetic performance of the door;
defining a start time of the data based on a first event to enable synchronisation of the data;
dividing the data in a plurality of time periods;
evaluating the data in each one of the plurality of time periods by comparing to the reference data respectively associated with each one of the plurality of time periods; and
determining to perform maintenance based on the evaluation of the data.
The invention is directed towards the abstract idea of maintenance management, which is based on the collection and comparison of information and, based on a rule, identify options, which corresponds to “Mental Processes” as it is directed towards steps that can be performed by a human(s), in the human mind, and/or with the aid of pen and paper, e.g., having a user observe and write down information regarding how a door is performing over a period of time, comparing the observations against known performance information, and, based on rule(s)/comparison (are observations within acceptable defined parameters), determine whether maintenance should be performed on the door.
The limitations of:
performing a calibration procedure for the door to obtain reference data for the door;
obtaining data indicating kinetic performance of the door;
defining a start time of the data based on a first event to enable synchronisation of the data;
dividing the data in a plurality of time periods;
evaluating the data in each one of the plurality of time periods by comparing to the reference data respectively associated with each one of the plurality of time periods; and
determining to perform maintenance based on the evaluation of the data,
are processes that, under its broadest reasonable interpretation, covers performance of the limitation performed by a human(s), in the human mind, and/or with the aid of pen and paper, but for the recitation of a generic processor executing computer code stored on a computer medium and generic sensor. That is, other than reciting a generic processor executing computer code stored on a computer medium and generic sensor nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the generic processor executing computer code stored on a computer medium and generic sensor in the context of this claim encompasses a having a user observe and write down information regarding how a door is performing over a period of time, comparing the observations against known performance information, and, based on rule(s)/comparison (are observations within acceptable defined parameters), determine whether maintenance should be performed on the door. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of a generic processor executing computer code stored on a computer medium and generic sensor, then it falls within the “Mental Processes”” groupings of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements – a generic processor executing computer code stored on a computer medium to and generic sensor communicate information, as well as performing operations that a human can perform in their mind and/or pen and paper, i.e. comparing the communicated information against known information do determine if maintenance should be performed on an asset. The generic processor executing computer code stored on a computer medium and generic sensor in the steps are recited at a high-level of generality (i.e., as a generic processor executing computer code stored on a computer medium and generic sensor can perform the insignificant extra solution steps of communicating information (See MPEP 2106.05(g) while also reciting that the a generic processor executing computer code stored on a computer medium and generic sensor are merely being applied to perform the steps that can be performed by a human(s), in the human mind, and/or with the aid of pen and paper; "[use] of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” Therefore, according to the MPEP, this is not solely limited to computers but includes other technology that, recited in an equivalent to “apply it,” is a mere instruction to perform the abstract idea on that technology (See MPEP 2106.05(f)) such that it amounts no more than mere instructions to apply the exception using a generic processor executing computer code stored on a computer medium and generic sensor.
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. The claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a generic processor executing computer code stored on a computer medium and generic sensor to perform the steps of:
performing a calibration procedure for the door to obtain reference data for the door;
obtaining data indicating kinetic performance of the door;
defining a start time of the data based on a first event to enable synchronisation of the data;
dividing the data in a plurality of time periods;
evaluating the data in each one of the plurality of time periods by comparing to the reference data respectively associated with each one of the plurality of time periods; and
determining to perform maintenance based on the evaluation of the data,
amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Additionally:
Claim 32 is directed towards descriptive subject matter describing an event and a corresponding time frame for the event., wherein the event can be performed by a human, i.e. a human can open and close a door and observe how it is behaving.
Claim 33 is directed towards descriptive subject matter describing the information that will be used as the comparison against a human’s observation.
Claim 34 is directed towards descriptive subject matter describing an event and a corresponding time frame for the event, as well as reciting generic technology at a high level of generality and applying it to the abstract idea.
Claim 35 is directed towards descriptive subject matter describing an event and a corresponding time frame for the event., wherein the event can be performed by a human, i.e. a human can open and close a door and observe how it is behaving, as well as reciting generic technology at a high level of generality and applying it to the abstract idea.
Claim 36 is directed towards descriptive subject matter and a rule(s), in this case, describing time periods and establishing a rule that defines that a time period is defined as a plurality of time periods.
Claim 37 is directed towards descriptive subject matter and a rule(s), in this case, describing time periods and establishing a rule that defines that a time period is defined as a plurality of time periods.
Claim 38 is directed towards reciting generic technology at a high level of generality and applying it to the abstract idea to perform the extra-solution activity of data collection that the technology is designed to collect.
Claim 39 is directed towards reciting generic technology at a high level of generality and applying it to the abstract idea to perform the extra-solution activity of data collection that the technology is designed to collect and associating the collected information to a corresponding time frame.
Claim 40, 41, 42 is directed towards reciting generic technology at a high level of generality and applying it to the abstract idea to perform the extra-solution activity of data collection that the technology is designed to collect.
Claim 43 is directed towards reciting generic technology at a high level of generality and applying it to the abstract idea to perform the extra-solution activity of data collection that the technology is designed to collect.
Additionally, although the claim recites “a machine learning model”, the claims and specification fail to provide sufficient disclosure regarding an improvement to how a machine learning algorithm can be trained, but simply recites a high-level generic recitation that a machine learning algorithm is being trained. There is insufficient evidence from the specification to indicate that the use of the machine learning algorithm involves anything other than the generic application of a known technique or that the claimed invention purports to improve the functioning of the computer itself or the machine learning algorithm. None of the limitations reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field, applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, effects a transformation or reduction of a particular article to a different state or thing, or applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
The Examiner asserts that the scope of the disclosed invention, as presented in the originally filed specification, is not directed towards the improvement of machine learning, but directed towards collecting information regarding how an asset is performing, comparing the information against known/expected information, and, based on a rule(s), identify options with regards to determining whether maintenance should be performed on the asset. The specification’s disclosure on machine learning is nothing more than a high general explanation of generic technology and applying it to the abstract idea. Referring to MPEP § 2106.05(f), the machine learning model merely being used to facilitate the tasks of the abstract idea, which provides nothing more than a results-oriented solution that lacks detail of the mechanism for accomplishing the result and is equivalent to the words “apply it,” per MPEP § 2106.05(f). The Examiner asserts that in light of the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence, the claimed invention is analogous to Example 47, Claim 2.
Further, the combination of these elements is nothing more than a generic computing system with machine learning model. Because the additional elements are merely instructions to apply the abstract idea to a computer, as described in MPEP § 2106.05(f), they do not integrate the abstract idea into a practical application.
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. The claim is directed to an abstract idea.
The remaining claims recite subject matter that has already been discussed above.
In summary, the dependent claims are simply directed towards providing additional descriptive factors that are considered for determining whether maintenance should be performed on an asset based on how observed performance of the asset compares against expected performance. Accordingly, the claims are not patent eligible.
Claim Rejections - 35 USC § 102
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 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 31 – 37, 41, 44 - 50 are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Brown et al. (US PGPub 20210209924 A1).
In regards to claims 31, 44, 50, Brown discloses (Claim 31) a method for determining when to perform maintenance of a door, the method being performed by a maintenance determiner, the method comprising; (Claim 44) a maintenance determiner for determining when to perform maintenance of a door, the maintenance determiner comprising; (Claim 50) a non-transitory computer readable medium storing a computer program for determining when to perform maintenance of a door, the computer program comprising computer program code which, when executed on a maintenance determiner, causes the maintenance determiner to:
In regards to:
a processor; and
a memory storing instructions that, when executed by the processor, cause the maintenance determiner to
(¶ 50, 54):
performing a calibration procedure for the door to obtain reference data for the door (¶ 53 wherein the door, sensors, and calibration are activated to collect baseline operation data);
obtaining, from a first sensor, sensor data indicating kinetic performance of the door (¶ 50, 53, 54 where sensor data indicating opening/closing of the door is collected);
defining a start time of the sensor data based on a first event detected by a second sensor to enable synchronisation of the sensor data (¶ 53, 54, 55 wherein a plurality of sensors can be utilized to collect operation data for the door and where their readings are synchronized to indicate the operation of the door and its performance/condition;
¶ 53, 54, 57 wherein the sensor data from the plurality of sensors correspond with discrete defined periods of time or lifetime of the door, as well as open/close cycles, and synchronized with one another, as discussed above);
dividing the sensor data in a plurality of time periods (¶ 53, 54, 57 wherein the sensor data from the plurality of sensors correspond with discrete defined periods of time or lifetime of the door, as well as open/close cycles);
evaluating the sensor data in each one of the plurality of time periods by comparing to the reference data respectively associated with each one of the plurality of time periods (¶ 55, 59 wherein, after baseline data is collected and stored, sensor data from continued use of the door is collected and compared against the baseline data); and
determining to perform maintenance based on the evaluation of the sensor data (¶ 55, 59 wherein the results of the comparison are used to determine if the door is in need of maintenance).
In regards to claims 32, 45, Brown discloses the method of Claim 31 (the maintenance determiner of Claim 44), wherein the first event is a start of a door movement, wherein the door movement is a closing of the door or an opening the door (¶ 53, 54, 55 wherein a plurality of sensors can be utilized to collect operation data for the door and where their readings are synchronized to indicate the operation of the door and its performance/condition, i.e. opening/closing the door).
In regards to claims 33, 46, Brown discloses the method of Claim 32 (the maintenance determiner of Claim 45), wherein the reference data is selected based on whether the door movement is a closing of the door or an opening of the door (¶ 53, 54, 55, 57 wherein the sensor data from the plurality of sensors correspond with discrete defined periods of time or lifetime of the door, as well as open/close cycles).
In regards to claims 34, 47, Brown discloses the method of Claim 31 (the maintenance determiner of Claim 44), further comprising defining an end time of the sensor data based on a second event detected by the second sensor (¶ 53, 54, 57 wherein the sensor data from the plurality of sensors correspond with discrete defined periods of time or lifetime of the door, as well as open/close cycles, and synchronized with one another, as discussed above).
In regards to claims 35, 48, Brown discloses the method of Claim 32 (the maintenance determiner of Claim 45), further comprising defining an end time of the sensor data based on a second event detected by the second sensor, wherein the second event is an end of the door movement (¶ 53, 54, 57 wherein the sensor data from the plurality of sensors correspond with discrete defined periods of time or lifetime of the door, as well as open/close cycles, and synchronized with one another, as discussed above).
In regards to claims 36, 49, Brown discloses the method of Claim 34 (the maintenance determiner of Claim 47), wherein the plurality of time periods are defined as a preconfigured number of time periods of equal duration between the start time and the end time (¶ 53, 54, 57 wherein the sensor data from the plurality of sensors correspond with discrete defined periods of time or lifetime of the door, open/close cycles, and average number of events per time period (e.g., day or any other time interval), which are then synchronized with one another, as discussed above).
In regards to claim 37, Brown discloses the method of Claim 31 (the maintenance determiner of Claim 44), wherein the plurality of time periods are defined as a preconfigured number of time periods with a preconfigured duration from the start time (¶ 53, 54, 57 wherein the sensor data from the plurality of sensors correspond with discrete defined periods of time or lifetime of the door, open/close cycles, and average number of events per time period (e.g., day or any other time interval), which are then synchronized with one another, as discussed above).
In regards to claim 41, Brown discloses the method of Claim 31 (the maintenance determiner of Claim 44), wherein the first sensor comprises an accelerometer (¶ 50 wherein the first sensor comprises an accelerometer).
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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 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.
Claims 38, 39, 40, 42 are rejected under 35 U.S.C. 103 as being unpatentable over Brown et al. (US PGPub 20210209924 A1) in view of Cate et al. (CA 3090573)
In regards to claims 38, 39, 40, 42, Brown discloses a system and method to monitoring and tracking the performance and operations of a door utilizing sensors to determine if the door is operating outside expected parameters and, if so, determining that maintenance should be performed. Although Brown discloses a non-exhausted list of sensor types working together to determine the performance and operation of a door to determine if maintenance is needed, Brown fails to explicitly disclose all possible sensors that could be used.
To be more specific, Brown fails to explicitly disclose:
(Claim 38) the method of Claim 31 (the maintenance determiner of Claim 44), wherein the second sensor is a magnetometer, provided on one of the door or the door frame, configured to detect a magnetic field from a magnet provided on the other of the door or the door frame.
(Claim 39) the method of Claim 34, wherein:
the second sensor is a magnetometer, provided on one of the door or the door frame, configured to detect a magnetic field from a magnet provided on the other of the door or the door frame;
the first event is detected based on detecting a first magnetic polarity; and
the second event is based on detecting a second magnetic polarity being opposite the first magnetic polarity.
(Claim 40) the method of Claim 31, wherein the second sensor is a proximity sensor configured to detect when the door is in an open or closed position in relation to a door frame.
(Claim 42) the method of Claim 31, wherein the first sensor comprises a sound sensor.
However, Cate, which is also directed towards monitoring the performance and operations of a door using sensors for determining whether maintenance is needed, teaches that there is a plurality of sensors that can be utilized to monitor the performance and operation of a door, such as, but not limited to, proximity sensors. Cate teaches that such proximity sensors can include magnetometers, which detect changes in a magnetic field, e.g., strength and vector changes, and sound sensors. Brown teaches a non-exhausted list of sensors that can be utilized to monitor the performance and operation of a door to determine whether maintenance is needed and one of ordinary skill in the art looking upon the teachings of Cate would have found it obvious that in the field of door monitoring systems and methods that other sensors that can be utilized can be proximity sensors, such as, but not limited to, magnetometers and sounds sensors. Brown discloses that the plurality of sensors can collect and synchronize sensor data to accurately determine the performance and operation of a door and it would have been obvious to one of ordinary skill in the art to substitute the sensors of Cate with the second sensor types of Brown while still achieving the same predictable result of collecting sensor data regarding the performance and operation of a door to determine if maintenance is needed.
(For support see: ¶ 31, 44, 45, 83)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention that since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself-that is in the substitution of a magnetometer or sound sensor, as taught by Cate, for the plurality of second sensors disclosed by Brown.
Thus, the simply substitution of one known element for another producing a predictable result renders the claim obvious.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to try, by one of ordinary skill in the art, to pick a magnetometer or sound sensor, as taught by Cate, and incorporate it into the door performance and operation monitoring system and method of Brown since there are a finite number of identified, predictable potential solutions (available sensor types that can be used to collect information about the performance and operation of a door) to the recognized need (how to collect performance and operation data concerning a door) and one of ordinary skill in the art could have pursued the known potential solutions with a reasonable expectation of success (the advantages, benefits, and required resources are known).
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Claim 43 is rejected under 35 U.S.C. 103 as being unpatentable over Brown et al. (US PGPub 20210209924 A1) in view of Han et al. (KR 1020210054868).
In regards to claim 43, Brown discloses a system and method to monitoring and tracking the performance and operations of a door utilizing sensors to determine if the door is operating outside expected parameters and, if so, determining that maintenance should be performed. Although Brown discloses that the system learns to detect a baseline operation of the door to determine if future performance and operation of the door are outside expected parameters, Brown fails to explicitly disclose whether machine learning could be used to determine if collected sensor data is indicating that maintenance is required.
To be more specific, Brown fails to explicitly disclose:
the method of Claim 31, wherein evaluating the sensor data is based on a machine learning model wherein the sensor data in each one of the plurality of time periods is a separate input feature.
However, Han, which is also directed towards monitoring the performance and operations of a door using sensors for determining whether maintenance is needed, teaches that machine learning can be utilized to determine whether maintenance is needed. Han teaches that machine learning can be utilized to analyze collected data to predict if servicing will be needed because machine learning allows for analysis of data so that a specific object or condition can be understood or by finding and classifying patterns of data, which results in the system more effectively identifying and resolving potential issues that a door will have.
(For support see: Abstract; Background; Page 2, last ¶; Page 3 ¶ 4, 5; Page 4 ¶ 5; Page 5 ¶ 1; Page 7 ¶ 5
Therefore, it would have been obvious to one of ordinary skill in the art of door performance and monitoring to update the basic sensor learning process of Brown using modern data analysis technology, as taught in Han, to determine whether maintenance is needed in order to gain the commonly understood benefits of such adaptation, such as, reduced cost by pre-emptively identifying issues based on recognized patterns, efficiency by not requiring humans to inspect a door and potentially introduce human error, speed to pre-emptively address potential issues, and decreasing the difficulty to predict when a future failure will occur.
Accommodating the prior arts more manual and antiquated process with modern electronics, in this case, using machine learning to analyze collected sensor data regarding the performance and operation of door to identify patterns indicative of the door requiring servicing, would have been obvious. As stated in Leapfrog, “applying modern electronics to older mechanical devices has been commonplace in recent years.”
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention that since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself-that is in the substitution of machine learning to learn the performance and operation of a door to determine when it is malfunctioning, as taught by Han, for sensor learning process as disclosed by Brown.
Thus, the simply substitution of one known element for another producing a predictable result renders the claim obvious.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure can be found in the attached PTO-892 Notice of References Cited.
Zhu et al. (Study of remote monitoring system of working states of metro door system); Siewert (CA 3214662); Hass et al. (WO 2021/061727 A1); Hass et al. (US PGPub 2021/0090427 A1); Bachmann (DE 102018126347 A1); Yulkowski et al. (US PGPub 2017/0152696 A1); Misfatto (US PGPub 2016/0054148 A1); Fitzgibbon et al. (CA 2457935 C); Yulkowski et al. (WO 2011/011282 A2); Rodriguez et al. (CA 2267693 C); Kubo et al. (JP 2002309855); Kurumi (JP 2022065510 A); Leeser et al. (US PGPub 2021/0293631 A1); Quaiser (DE 102015107416 B4); Yulkowski et al. (US PGPub 2014/0182206 A1); Quaiser et al. (US PGPub 2018/0179800 A1); Quaiser et al. (US PGPub 2016/0245009 A1); Paulsson (WO 2020/260084 A1) – which are directed towards monitoring the performance of a door to determine if maintenance is needed
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GERARDO ARAQUE JR whose telephone number is (571)272-3747. The examiner can normally be reached Monday - Friday 8-4:30.
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GERARDO ARAQUE JR
Primary Examiner
Art Unit 3629
/GERARDO ARAQUE JR/Primary Examiner, Art Unit 3629 1/15/2026