DETAILED ACTION
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 .
This Final Office Action is responsive to Applicant's amendment filed on 12 November 2025. Applicant’s amendment on 12 November 2025 amended Claims 1-5. The Examiner notes that the 112 rejection has been withdrawn and the Alice 101 rejection has been maintained.
Response to Arguments
Applicant's arguments filed 12 November 2025 have been fully considered but they are not persuasive.
The Applicant argues on page 8 that “The independent claims are directed to a technological system that physically integrates multiple sensors, synchronizes heterogeneous data streams, and dynamically constructs precise recognition models to identify human work actions in real time. Each independent claim recites a specific sensor-fusion and coordinate-frame estimation architecture, not a mental process, mathematical abstraction, or disembodied data operation.
Specifically, the independent claims do not recite any abstract idea (Step 2A, Prong 1). Rather, the claimed work-recognition system operates in conjunction with tangible components such a wearable sensor suite including motion and tactile/force sensors, a fixed overhead camera, and processors that temporally synchronize sensor streams and estimate 3-D positions within dynamically selected coordinate frames. The system, for example, acquires motion, force, and image data from multiple devices and integrates them on a common time base for action estimation (see, e.g., published 11 [0021]-[0028]). These complex operations act on real- world sensor inputs and require complex computing hardware, they cannot be reasonably performed mentally or with simple generic data manipulation”.
The Examiner respectfully disagrees.
In response to the arguments the Examiner notes that the Applicant's argument that the claims recite a "technological system" with physical sensors is acknowledged but not persuasive. The claims remain directed to an abstract idea under Step 2A, Prong 1 of the Alice/Mayo framework, specifically the mental process of observing, evaluating, and recognizing human work activities.
The claims are directed to the fundamental concept of recognizing and classifying human work actions through observation and evaluation - a process historically performed by human supervisors, trainers, and time-study analysts. The Federal Circuit has repeatedly held that claims directed to collecting information, analyzing it, and displaying results fall within the mental process category of abstract ideas. Electric Power Grp., LLC v. Alstom S.A; CyberSource Corp. v. Retail Decisions, Inc.
The claimed system performs steps that mirror human observation: watching a worker (via camera), noting their movements and touches (observation through sensors), determining what work is being performed (mental evaluation), identifying where the work occurs (spatial observation), and classifying the complete work action (judgment). A factory supervisor or industrial engineer could perform these same evaluative steps by observing workers, taking notes about their actions and positions, consulting work procedure manuals (analogous to the "work component recognition models"), determining which procedure matches the observed activity, and recording the recognized work. The fact that the claim uses electronic sensors rather than human eyes and ears does not change the character of the underlying abstract idea. See Elec. Power Grp., (data gathering step using generic sensors did not make claims non-abstract).
Applicant's emphasis on "tangible components such as wearable sensor suite including motion and tactile/force sensors, a fixed overhead camera" misapprehends the abstract idea inquiry. The Supreme Court in Alice Corp. v. CLS Bank Int'l, expressly rejected the notion that implementing an abstract idea on a generic computer or using generic equipment makes the claim non-abstract. Similarly, in Two-Way Media Ltd. v. Comcast Cable Commc'ns, LLC, the Federal Circuit held that claims directed to streaming copyrighted content were abstract despite requiring "bandwidth and processing limitations of prior art systems" and network architecture elements. The presence of generic sensors (motion sensors, cameras, force sensors) and generic computer processors performing routine data collection and processing does not transform the fundamental mental process of work recognition into something non-abstract.
Motion sensors, cameras, and processors are well-understood, routine, conventional technology widely used across countless applications for data gathering and processing. MPEP 2106.04(d)(2). The specification confirms these are standard components: wearable devices include "first-person viewpoint camera, microphone, vibration sensor, pressure sensor, IMU, strain sensor" (par. [0037])—all conventional sensors. External devices include "cameras, indoor GPS" and "equipment, jigs and tools, conveyance systems" (par. [0036])—again, conventional technology. The claim does not recite any specific, unconventional sensor configuration or processing technique that would indicate technological improvement; rather, it applies generic sensors in their ordinary capacity to gather data about observable human activities.
Applicant's reference to "temporally synchronize sensor streams" and "estimate 3-D positions" likewise does not overcome the abstract idea finding. Temporal synchronization of data streams is a fundamental, well-known computer function performed by operating systems and data acquisition systems as a matter of routine. MPEP 2106.05(d). Estimating 3-D positions from sensor data using coordinate frames is a conventional computer-vision and motion-tracking technique widely used in video games, animation, robotics, and surveillance systems. The claim does not recite any particular unconventional algorithm, sensor fusion technique, or coordinate transformation that would demonstrate technological innovation. The specification describes selecting between "fixed reference" and "moving object reference" coordinate frames (par. [0086]-[0090])—a straightforward mathematical choice that could be made mentally by an observer deciding whether to describe a worker's position relative to the floor or relative to a moving conveyor belt.
Applicant argues the operations "cannot be reasonably performed mentally or with simple generic data manipulation," but this misstates the legal standard. The mental process category includes not only processes that can be performed entirely in the human mind, but also "concepts performed in the human mind" even when aided by tools or instruments. MPEP 2106.04(a)(2). A human with a clipboard, stopwatch, and measuring tape could observe workers, note their movements and tool usage, measure positions, consult work procedure charts, and classify the observed work—this is precisely what industrial engineers have done for over a century. The fact that the claimed system automates this observation and classification using electronic sensors rather than human observation does not change the fundamental character of the process. See FairWarning IP, LLC v. Iatric Sys., Inc. (analyzing past behavior to identify current behavior was abstract even though performed by computer).
Moreover, the complexity of the data processing does not preclude abstraction. In SAP Am., Inc. v. InvestPic, LLC, the Federal Circuit held claims abstract despite requiring "a combined order of specific rules" and complex statistical analysis, noting that "a claim for a new abstract idea is still an abstract idea." The claimed system's use of multiple recognition models, filtering, and model combination represents increased complexity in implementing the abstract idea of work recognition, not a technological improvement that integrates the abstract idea into a practical application.
The claims remain directed to the abstract idea of recognizing and classifying human work activities through observation and evaluation—a mental process. The recitation of generic sensors, cameras, and processors performing conventional data collection, synchronization, and coordinate transformation functions does not change this fundamental character. Applicant is directed to MPEP 2106.04(a)(2) (mental processes) and the cases cited above, which explain that automating human observation and judgment using generic computer technology does not render claims non-abstract. Should Applicant wish to overcome this rejection, Applicant should consider amending the claims to recite specific unconventional technical implementations that provide a technological improvement, rather than merely automating conventional human observation with generic sensors and computers. The 101 rejection is therefore maintained.
The Applicant argues on page 8-9 that “The independent claims integrate those steps into a concrete industrial application (Step 2A, Prong 2)-the automated recognition of human assembly-line work. At least the recited features:
temporal synchronization of wearable- and camera-based data streams,
selection and fusion of relevant component recognition models, and
adaptive reference-frame switching depending on whether the work object moves implement a specific technical solution to the known problem of sensor occlusion and misrecognition when relying on a single modality (see, e.g., published 11 [0029]-[0036]). and the independent claims include non-generic, inventive technical features, such as:
Weighted model fusion and exclusion logic that dynamically selects relevant recognition models based on work progress;
Adaptive coordinate-frame switching between fixed and moving reference frames; and
Temporal synchronization of heterogeneous sensor streams to a common time base.
According to the specification, these mechanisms produce improve the technological field (Step 2A, Prong 2) by providing measurable gains in recognition accuracy and robustness (see, e.g., published 1 par. [0049]-[0054]). In other words, the independent claims go well beyond routine computer functions, representing a specific, unconventional combination that improves the functioning of multimodal perception systems themselves.
For at least these reasons the independent claims are patent eligible under both Step 2A, Prong 1 and Prong 2. Applicant respectfully requests withdrawal of the rejection”.
”.
The Examiner respectfully disagrees.
In response to the arguments the Examiner notes that the “Applicant's argument that the claims integrate the abstract idea into a practical application under Step 2A, Prong 2 is acknowledged but unpersuasive. The claims do not recite an integration into a practical application and do not provide a technological improvement to computer functionality; rather, they merely apply the abstract idea of work recognition to a particular field (assembly lines) using generic computer components.
Applicant's characterization of the claims as directed to "automated recognition of human assembly-line work" is precisely the type of field-of-use limitation that the Supreme Court and Federal Circuit have repeatedly held insufficient to confer patent eligibility. Alice, (applying abstract idea to particular technological environment does not render claim non-abstract); Elec. Power Grp., (applying abstract idea in power-grid monitoring context did not save claims). The abstract idea—observing and classifying human work actions—remains abstract whether applied to assembly-line workers, warehouse workers, construction workers, or any other field. Merely invoking "assembly-line work" or "industrial application" as the context does not integrate the abstract idea into a practical application. MPEP 2106.05(h).
Applicant identifies three purportedly "non-generic, inventive technical features," none of which represent unconventional technology or an inventive concept:
1. Temporal Synchronization: Synchronizing data streams from multiple sensors "to a common time base" is an entirely conventional function performed by data acquisition systems, operating systems, and multimodal processing systems as a matter of routine. See BASCOM Glob. Internet Servs., Inc. v. AT&T Mobility LLC, (generic computer components must be combined in unconventional manner). The specification confirms this conventional nature, stating only that the "time series synchronization unit 104 temporally synchronizes data of each of the external devices and equipment 101 and the wearable device 102" (par. [0040])—a generic description of standard timestamping and synchronization without any unconventional implementation detail. Applicant does not point to any specific, unconventional synchronization algorithm, hardware, or technique that would demonstrate technological innovation beyond well-understood, routine, conventional synchronization performed by generic computers.
2. Adaptive Coordinate-Frame Switching: Selecting between coordinate reference frames - fixed versus moving object reference - represents a straightforward mathematical choice routinely made in motion tracking, robotics, computer vision, and navigation systems. The specification describes this as simply "setting reference coordinates to a fixed reference" when objects don't move and to "an object reference" when they do (par. [0007], and par. [0086]-[0090]). This is analogous to choosing whether to describe a person's location relative to a stationary building or relative to a moving train—a conventional decision in any coordinate-based tracking system. The claims provide no detail about how this switching is implemented beyond the functional result, and the specification describes only generic operations: recognizing a worker's area and instructing a coordinate switch (FIG. 9, steps 901-904). This amounts to conventional computer logic (if-then switching) applied to a conventional computer-vision task, which courts have repeatedly found insufficient. TLI Commc'ns LLC v. AV Auto. LLC, (generic database storage and retrieval insufficient).
3. Model Fusion and Exclusion Logic: Applicant's reference to "weighted model fusion and exclusion logic that dynamically selects relevant recognition models based on work progress" fails for two reasons. First, the claims as written do not actually recite "weighted fusion" - Applicant introduced this language in the arguments without adequate claim support. The claims recite only "combining" models and "excluding" irrelevant models, which are generic database filtering and selection operations. See Content Extraction & Transmission LLC v. Wells Fargo Bank, (routine data recognition and storage is insufficient). Second, even accepting Applicant's characterization, combining multiple models and filtering based on relevance criteria represents conventional ensemble-learning and database-query techniques widely used in machine learning and data processing. The specification describes this filtering as simply excluding "models other than the corresponding product" and "completed models" based on production instructions and progress (FIG. 14, par. [0111]-[0115]) - standard database filtering operations. Nothing in the claims or specification indicates an unconventional combination or arrangement of these components that would rise above routine data manipulation.
Applicant's assertion that the claims "improve the technological field" and provide "measurable gains in recognition accuracy and robustness" (par. [0049]-[0054]) fundamentally misunderstands what constitutes a technological improvement under Step 2A, Prong 2. The improvement Applicant describes is to the abstract process of work recognition—making the recognition more accurate by using multiple sensors rather than one sensor - not an improvement to computer functionality or sensor technology itself. This is precisely the type of result-focused improvement that courts have found insufficient.
In Elec. Power Grp., the court rejected claims that allegedly improved the accuracy of power-grid monitoring through real-time data collection and analysis, holding that "the focus of the claims is not on such an improvement in computers as tools, but on certain independently abstract ideas that use computers as tools." Similarly, in SAP Am., the Federal Circuit held claims ineligible despite purported improvements to investment analysis accuracy, noting that improving the abstract process itself does not constitute technological improvement. Here, using multiple sensors to improve work-recognition accuracy improves the result of the observation process, not the functioning of the sensors, computers, or networks themselves. The computers and sensors perform their conventional functions—data collection, synchronization, database queries, coordinate transformations—exactly as they are designed to do.
The cited paragraphs (par. [0049]-[0054]) describe recognition models for "posture and action," "gestures and audio," and "physical feedback," stating these models work by "learning or setting" from sensor inputs. This describes conventional machine-learning or rule-based classification—applying training data to create models that classify future inputs—a well-known, generic computer function. See RecogniCorp, LLC v. Nintendo Co., (combining cameras with generic computer components to capture and match images was abstract). The specification does not describe any unconventional neural network architecture, sensor fusion algorithm, training technique, or hardware configuration that would demonstrate a technological improvement to computer or sensor systems.
Applicant's argument that the claims solve "the known problem of sensor occlusion and misrecognition when relying on a single modality" (par. [0029]-[0036]) is unavailing. Addressing a problem associated with an abstract idea by adding conventional technology does not transform the abstract idea into an eligible invention. The problem Applicant identifies—that one sensor type may have blind spots or limitations—is not a problem with sensor technology itself, but rather a limitation inherent in any observation-based recognition process, whether performed by humans or machines. A factory supervisor faces the same "problem"—if standing in one location, they may not see a worker behind equipment. The solution—moving to a different vantage point or using multiple observers—is the analog to using multiple sensors. Automating this obvious solution using generic, conventional multi-sensor systems does not provide an inventive concept. MPEP 2106.05(a)-(d).
Moreover, the cited paragraphs (par. [0029]-[0036]) describe routine, generic sensor components without any indication of unconventional use: "external devices and equipment 101 are, for example, cameras, indoor GPS... equipment, jigs and tools" (par. [0036]); "wearable device 102 is... first-person viewpoint camera, microphone, vibration sensor, pressure sensor, IMU" (par. [0037]). These are off-the-shelf sensors performing their ordinary functions. Using multiple conventional sensors to gather more complete data is itself a conventional approach to improving observation-based systems, analogous to posting multiple human observers at different positions. MPEP 2106.05(d)(II).
Even if Applicant's characterization of the technical features were accurate, the claims recite these elements at a high level of generality and functional abstraction that fails to provide the specificity required under MPEP 2106.05(c). For example, "temporally synchronize data streams... to a common time base" is purely functional language that does not specify how synchronization is achieved, what synchronization algorithm is used, what timestamp precision is required, or how clock drift is handled. Similarly, "estimate a 3D position... based on the set reference coordinates" is entirely result-oriented, claiming the result (position estimate) without limiting how it is achieved. Courts have held that claiming desired results through purely functional language, without limiting the claims to specific technical means, fails to provide an inventive concept. Electric Power Grp.; Interval Licensing LLC v. AOL, Inc.
In Ancora Techs., Inc. v. HTC Am., Inc., the Federal Circuit distinguished eligible claims that recited a "specific" improvement (particular boot sequence technique) from ineligible claims reciting only desired functional results. Here, the claims recite only desired functional results—synchronized data, recognized work, estimated position—without claiming the specific technical means by which these results are achieved, rendering them ineligible under Step 2A, Prong 2.
The claims do not integrate the abstract idea into a practical application. They merely apply the abstract idea of work recognition to a particular field (assembly lines) using well-understood, routine, conventional computer components (sensors, processors, databases) performing conventional functions (data collection, synchronization, filtering, coordinate transformation). The purported improvements relate to the accuracy of the abstract recognition process itself, not to an improvement in computer functionality or sensor technology. The claims amount to conventional automation of human observation and classification using generic technology, which is insufficient to confer patent eligibility. MPEP 2106.05(a)-(f).
Assuming arguendo that the claims were directed to a practical application under Step 2A (which they are not), they would still fail under Step 2B for lack of an inventive concept. The analysis above—demonstrating that the claimed elements are conventional sensors, conventional data synchronization, conventional database filtering, and conventional coordinate selection—applies equally to the Step 2B inquiry. Taking the elements individually and in combination, they amount to no more than well-understood, routine, conventional activity. Alice. The specification confirms the conventional nature of the components and lacks any description of unconventional implementation details that would demonstrate an inventive combination. BASCOM, (inventive concept requires unconventional arrangement of components, not merely conventional components performing conventional functions).
Applicant is advised that to overcome this rejection, amendments should recite specific, unconventional technical implementations with sufficient particularity to demonstrate technological improvement to computer or sensor functionality, rather than merely automating conventional human observation with generic technology and claiming improved results in the abstract process. Applicant is directed to MPEP 2106.05(a)-(f) for guidance on integrating abstract ideas into practical applications and MPEP 2106.05(d) regarding what constitutes well-understood, routine, conventional activity. The rejection is therefore maintained.
The remaining Applicant's arguments filed 12 November 2025 have been fully considered but they are moot in view of new grounds of rejection as necessitated by amendment.
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.
Additionally, claims 1-5 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter because the claim(s) 1-5 as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. The claim(s) is/are directed to the abstract idea of work recognition based on estimating and recognizing work utilizing a recognition model. The claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more than the judicial exception itself. Claim(s) (1-5) is/are directed to an abstract idea without significantly more.
Step 1
Regarding Step 1 of the Subject Matter Eligibility Test for Products and Processes (from the January 2019 §101 Examination Guidelines), claim(s) (1-3) is/are directed to a system, claim(s) (4) is/ are directed to a method, and claims(s) (5) is/are directed to a computer readable medium and therefore the claims recites a series of steps and, therefore the claims are viewed as falling in statutory categories.
Step 2A Prong 1
The claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) a mental process. Specifically, the independent claims 1, 4, and 5 recite a mental process: as drafted, the claim recites the limitation of generating work recognition model which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a processor and storage unit nothing in the claim precludes the determining step from practically being performed in the human mind. For example, but for a processor and storage unit language, the claim encompasses the user manually generating work recognition models. The mere nominal recitation of a generic processor and storage unit does not take the claim limitation out of the mental processes grouping. It has been established by ongoing guidance that claims that contain a generic processor are still viewed as mental process when they contain limitations that can practically be performed in the human mind, however this is different for instance when the human mind is not equipped to perform the claim limitations (network monitoring, data encryption for communication, and rendering images). Therefore, these limitations are viewed a mental process. Additionally, with regard to the instant application the Examiner has reviewed the disclosure and determined that the underlying claimed invention is described as a concept that is performed in the human mind and/or with the aid of a pen and paper, and thus it is viewed that the applicant is merely claiming that concept performed 1) on a generic computer, 2) in a computer environment or 3) is merely using a computer as a tool to perform the concept, and therefore is considered to recite a mental process.
Note to the Applicant per the 2019 October Guidance: The 2019 PEG sets forth a test that distills the relevant case law to aid in examination, and does not attempt to articulate each and every decision. As further explained in the 2019 PEG, the Office has shifted its approach from the case-comparison approach in determining whether a claim recites an abstract idea and instead uses enumerated groupings of abstract ideas. The enumerated groupings are firmly rooted in Supreme Court precedent as well as Federal Circuit decisions interpreting that precedent. By grouping the abstract ideas, the 2019 PEG shifts examiners’ focus from relying on individual cases to generally applying the wide body of case law spanning all technologies and claim types. In sum, the 2019 PEG synthesizes the holdings of various court decisions to facilitate examination.
Step 2A Prong 2
Specifically, the determined judicial exception is not integrated into a practical application because the generically recited computer elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer and additionally that data storing, synchronizing, selecting, combining, inputting, setting and outputting steps required to use the correlation do not add a meaningful limitation to the method as they are insignificant extra-solution activity (including post solution activity).
The claim recites the additional element(s): that a processor is used to perform the estimating and recognizing steps. The processor in the step is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing data (the generating work recognition model). This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. 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. The claim is directed to the abstract idea.
The claim recites the additional element(s): storing work components, synchronizing data streams, selecting, combining, inputting the data, setting a fixed reference, set a moving object and outputting a result performs the estimating and recognizing steps. The storing, synchronizing, selecting, combining, inputting, setting and outputting steps are recited at a high level of generality (i.e., as a general means of storing, synchronizing, selecting, combining, inputting, setting and outputting data for use in the estimating and recognizing steps), and amounts to mere data management, which is a form of insignificant extra-solution activity. The processor and storage unit that performs the estimating, and recognizing steps are also recited at a high level of generality, and merely automates the estimating, and recognizing step. Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer component (the processor and storage unit).
The Examiner has further determined that the claims as a whole does not integrate a judicial exception into a practical application in order to provide an improvement in the functioning of a computer or an improvement to other technology or technical field. It has been determined that based on the disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. It has not been provided clearly in the disclosure that the alleged improvement would be apparent to one of ordinary skill in the art, but is instead in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art, and therefore does not improve the technology. Second, in the instance, where it is not clear that the specification sets forth an improvement in technology, the claim must reflect the disclosed improvement (the claims must include components or steps of the invention that provide the improvement described in the specification).
Note to the Applicant from the October 2019 Guidance: Generally, examiners are not expected to make a qualitative judgment on the merits of the asserted improvement. If the examiner concludes the disclosed invention does not improve technology, the burden shifts to applicant to provide persuasive arguments supported by any necessary evidence to demonstrate that one of ordinary skill in the art would understand that the disclosed invention improves technology. Any such evidence submitted under 37 C.F.R. § 1.132 must establish what the specification would convey to one of ordinary skill in the art and cannot be used to supplement the specification. For example, in response to a rejection under 35 U.S.C. § 101, an applicant could submit a declaration under § 1.132 providing testimony on how one of ordinary skill in the art would interpret the disclosed invention as improving technology and the underlying factual basis for that conclusion.
For further clarification the Examiner points out that the claim(s) 1-5 recite(s) storing work components, synchronizing data streams, selecting, combining, inputting the data, setting a fixed reference, set a moving object, estimating a 3D position, recognize work, and outputting a result which are viewed as an abstract idea in the form of a mental process. This judicial exception is not integrated into a practical application because the use of a computer for storing, synchronizing, selecting, combining, inputting, setting, estimating, recognizing and outputting which is the abstract idea steps of valuing an idea (generating work recognition model) in the manner of “apply it”.
Thus, the claims recites an abstract idea directed to a mental process (i.e. to generating work recognition model). Using a computer to storing, synchronizing, selecting, combining, inputting, setting, estimating, recognizing and outputting the data resulting from this kind of mathematically-based, mental process merely implements the abstract idea in the manner of “apply it” and does not provide 'something more' to make the claimed invention patent eligible. The claimed limitations of a computing device is not constraining the abstract idea to a particular technological environment and do not provide significantly more.
The generating work recognition model would clearly be to a mental activity that a company would go through in order to determine the work recognition. The specification makes it clear that the claimed invention is directed to the mental activity data gathering and data analysis to determine how to manage work recognition:
The dependent claims recite elements that narrow the metes and bounds of the abstract idea but do not provide ‘something more’.
The dependent claims do not remedy these deficiencies.
No dependent claims recite limitations which further limit the claimed analysis of data.
Claims 3 recites limitations directed to claim language viewed insignificantly extra solution activity.
Using a computer to perform the data processing as claimed is merely implementing the abstract idea in the manner of “apply it” and does not provide significantly more. Additionally with respect to the Berkheimer the Examiner points out that the steps of the claim are viewed to be to nothing more than spell out what it means to apply it on a computer and cannot confer patent-eligibility as there are no additional limitations beyond applying an abstract idea, restricted to a computer. As the claims are merely implementing the abstract idea in the manner of “Apply It” the need for a Berkheimer analysis does not apply and is not required. With respect to the currently filed claims the implementing steps can be found in Takumi which discloses how the claims alone and in combination are viewed to be well understood, routine and conventional based on point 3 of the Berkheimer memo and subsequent evidence, complying with and providing evidence.
Claims 2 recites limitations directed to claim language viewed non-functional data labels.
Thus, the problem the claimed invention is directed to answering the question based on gathered and analyzed information about the work recognition generates a work recognition model. This is not a technical or technological problem but is rather in the realm of work recognition and therefore an abstract idea.
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed with respect to Step 2A Prong Two, the additional element in the claim amounts to no more than mere instructions to apply the exception using a generic computer component.
The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. This is the case because in order for the claims to be viewed as significantly more the claims must incorporate the integral use of a machine to achieve performance of a method, in contrast to where the machine is merely an object on which the method operates, which does not provide significantly more in order for a machine to add significantly more, it must play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly. Whether its involvement is extra-solution activity or a field-of-use, i.e., the extent to which (or how) the machine or apparatus imposes meaningful limits on the claim. Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more. Additionally, another consideration when determining whether a claim recites significantly more is whether the claim effects a transformation or reduction of a particular article to a different state or thing. "[T]ransformation and reduction of an article ‘to a different state or thing’ is the clue to patentability of a process claim that does not include particular machines. All together the above analysis shows there is not improvement in computer functionality, or improvement to any other technology or technical field. The claim is ineligible.
Additionally, with respect to the Berkheimer as noted above the same analysis applies to the 2B where the claims are viewed as applying it and as such no further analysis is required. However, with respect to the current claims storing, synchronizing, selecting, combining, inputting, setting, and outputting that are viewed as extra solution or post solution activity the Examiner notes that the claims are viewed as well-understood, routine, and conventional because a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s). An appropriate publication such as the currently cited prior art Takumi provides those extra solution activities and is viewed as a form of publication which also includes a book, manual, review article, or other source that describes the state of the art and discusses what is well-known and in common use in the relevant industry. The claim is ineligible.
The dependent claims recite elements that narrow the metes and bounds of the abstract idea but do not provide ‘something more’. Specifically, the dependent claims do not remedy these deficiencies of the independent claims.
With respect to the legal concept of prima facie case being a procedural tool of patent examination, which allocates the burdens going forward between the examiner and the applicant. MPEP § 2106.07 discusses the requirements of a prima facie case of ineligibility. In particular, the initial burden was on the Examiner and believed to be properly provided as to explain why the claim(s) are ineligible for patenting because of the above provided rejection which clearly and specifically points out in accordance with properly providing the requirement satisfying the initial burden of proof based on the Guidance from the United States Patent and Trademark Office and the burden now shifts to the applicant.
Therefore, based on the above analysis as conducted based on the Guidance from the United States Patent and Trademark Office the claims are viewed as a court recognized abstract idea, are viewed as a judicial exception, does not integrate the claims into a practical application, and does not provide an inventive concept, therefore the claims are ineligible.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent may not be obtained through the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 4, and 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Patel et al., Sept. 2022, Trends in Workplace Wearable Technologies ad Connected-Worker Solutions for Next Generation Occupational Safety, Adv. Intelligent Systems, pp 1-30 (hereafter Patel) in view of Varga et al. (U.S. Patent Publication 2013/0162632 A1) (hereafter Varga).
Referring to Claim 1, Takumi teaches a system for a work recognition, said system comprising:
A work recognition system comprising: an input interface operatively connected to: a wearable sensor suite including at least a motion sensor and a tactile or force sensor (see; pg. 10, Table 3 of Patel teaches an example of a wearable suit by Xsens that is a full body motion capture, pg. 14, Table 4 and the monitoring of force and flexibility of the user as well as provides, pg. 9, col. 1, par. 1 where a dashboard is provided to allow input).
a camera sensor mounted in a fixed overhead position in a workspace (see; pg. 7, col. 1, par. 2 of Patel teaches a camera mounted to a helmet (i.e. overhead) to monitor the work progress).
a memory configured to store a plurality of work component recognition models, each component recognition model mapping input features from the wearable sensor suite and camera sensor to component-level action hypotheses (see; pg. 13, col. 1, par. 2 of Patel teaches a combination of data including Xsens suit that generates 3D animation for easy visualization (i.e. mapping movement), pg. 7, col. 1, par. 2 as well as a camera mounted to a helmet (i.e. overhead) to monitor the work progress).
temporally synchronize data streams from the wearable sensor suite and the camera sensor in a common time base (see; pg. 13, col. 1, par. 2 of Patel teaches the Xsens body suit which has real time synchronized data for sampling for easy visualization in real time).
generate a general-purpose unit work recognition model by selecting and combining, via weighted fusion or model composition, a subset of the work component recognition models that are independent of individual product structures, while, based on a current production instruction and work progress, excluding any work recognition models that are irrelevant or already completed (see; pg. 13, col. 2, par. 4 of Patel teaches a combination of multiple devices used to compare progress over time and is used in models to understand work progress).
input the temporally synchronized data streams into the general-purpose unit work recognition model to recognize a unit work (see; pg. 13, col. 2, par. 4 of Patel teaches the input of recognition that identifies the current state (i.e. recognition of work)).
set a fixed reference coordinate frame when a work object remains stationary relative to floor (see; pg. 12, col. 2, par. 1 of Patel teaches the precise 3D position tracking of objects around the user).
recognize work based on the estimated 3D position of the worker's action (see; pg. 4, par. 2, col. 4 of Patel teaches based on the movement of a wearable sensing device recognizes the position and risk to the user).
output a result of the recognized work (see; pg. 23, col. 2, par. 1 – pg. 24, col. 1 of Patel teaches an example of a solution to identify risks and workflow (i.e. results of work)).
Patel does not explicitly disclose the following limitations, however,
Varga teaches one or more processors operatively connected to the input interface, the one or more processors being programmed to (see; par. [0067] of Varga teaches a computer system and controller used to interface external equipment, par. [0006] a haptic suit), and
set a moving object reference frame when the work object moves relative to the floor (see; par. [0006] of Varga teaches a haptic suit and par. [0121] as well as orientation sensors to set the frame of reference for the object to a fixed position (i.e. floor)).
estimate a 3D position of a worker's action by combining the recognized unit work from the general-purpose unit work recognition module and the set reference coordinate frame (see; par. [0121] of Varga teaches the orientation based on sensors to set the frame of reference for the object to a fixed position (i.e. floor), par. [0075] provides a 3D orientation using a haptic body suit)).
The Examiner notes that Patel teaches similar to the instant trends in workplace wearable technologies. Specifically, Patel discloses the instant trends in workplace wearable technologies and connected-worker solutions for next-generation occupational safety, health, and productivity and s it is therefore viewed as analogous art in the same field of endeavor. Additionally, Varga teaches computer aided 360o heads up display of safety mission critical data and as it is comparable in certain respects to Patel which a work recognition apparatus as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Patel discloses a work recognition device and work recognition method capable of detecting a work operation using camaras. However, Patel fails to disclose one or more processors operatively connected to the input interface, the one or more processors being programmed to, and set a moving object reference frame when the work object moves relative to the floor, and estimate a 3D position of a worker's action by combining the recognized unit work from the general-purpose unit work recognition module and the set reference coordinate frame.
Varga discloses one or more processors operatively connected to the input interface, the one or more processors being programmed to, and set a moving object reference frame when the work object moves relative to the floor, and estimate a 3D position of a worker's action by combining the recognized unit work from the general-purpose unit work recognition module and the set reference coordinate frame.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Patel the one or more processors operatively connected to the input interface, the one or more processors being programmed to, and set a moving object reference frame when the work object moves relative to the floor, and estimate a 3D position of a worker's action by combining the recognized unit work from the general-purpose unit work recognition module and the set reference coordinate frame as taught by Varga since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Patel and Varga teach the collecting and analysis of data in order to monitor a worker and their environment in order to detect pertinent events and they do not contradict or diminish the other alone or when combined.
Referring to Claim 4, Patel in view of Varga teaches a work recognition method. Claim 4 recites the same or similar limitations as those addressed above in claim 1, Claim 4 is therefore rejected for the same reasons as set forth above in claim 1.
Referring to Claim 5, Patel in view of Varga teaches a w non-transitory computer readable medium storing a program. Claim 5 recites the same or similar limitations as those addressed above in claim 1, Claim 5 is therefore rejected for the same reasons as set forth above in claim 1.
Claims 2 and 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Patel et al., Sept. 2022, Trends in Workplace Wearable Technologies ad Connected-Worker Solutions for Next Generation Occupational Safety, Adv. Intelligent Systems, pp 1-30 (hereafter Patel) in view of Varga et al. (U.S. Patent Publication 2013/0162632 A1) (hereafter Varga) in further view of Takumi (JP 2021-76888 A).
Referring to Claim 2, see discussion of claim 1 above, while Patel in view of Varga teaches the system above, Patel in view of Varga does not explicitly disclose a system having the limitations of, however,
Takumi teaches a reference setting unit configured to: set, when the object does not move with respect to a floor surface during the work performed by the worker, reference coordinates to a fixed reference (see; pg. 3, par. 2- par. 4 of Takumi teaches tracking the work product (i.e. object) compared to the work surface (i.e. floor surface) to be worked on and monitoring whether the work product moves or not in relation to the work surface), and
set, when the object moves with respect to the floor surface during the work performed by the worker, the reference coordinates to an object reference (see; pg. 3, par. 2- par. 4 of Takumi teaches tracking the work product (i.e. object) compared to the work surface (i.e. floor surface) to be worked on and monitoring the movement of the work product in relation to the work surface).
The Examiner notes that Patel teaches similar to the instant trends in workplace wearable technologies. Specifically, Patel discloses the instant trends in workplace wearable technologies and connected-worker solutions for next-generation occupational safety, health, and productivity and s it is therefore viewed as analogous art in the same field of endeavor. Additionally, Varga teaches computer aided 360o heads up display of safety mission critical data and as it is comparable in certain respects to Patel which a work recognition apparatus as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Takumi teaches work management equipment and work management methods and programs and as it is comparable in certain respects to Patel which a work recognition apparatus as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Patel and Varga discloses a work recognition device and work recognition method capable of detecting a work operation using camaras. However, Patel and Varga fails to disclose one or more processors operatively connected to the input interface, the one or more processors being programmed to, and set a moving object reference frame when the work object moves relative to the floor, and estimate a 3D position of a worker's action by combining the recognized unit work from the general-purpose unit work recognition module and the set reference coordinate frame.
Takumi discloses one or more processors operatively connected to the input interface, the one or more processors being programmed to, and set a moving object reference frame when the work object moves relative to the floor, and estimate a 3D position of a worker's action by combining the recognized unit work from the general-purpose unit work recognition module and the set reference coordinate frame.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Patel and Varga the one or more processors operatively connected to the input interface, the one or more processors being programmed to, and set a moving object reference frame when the work object moves relative to the floor, and estimate a 3D position of a worker's action by combining the recognized unit work from the general-purpose unit work recognition module and the set reference coordinate frame as taught by Takumi since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Patel, Varga, and Takumi teach the collecting and analysis of data in order to monitor a worker and their environment in order to detect pertinent events and they do not contradict or diminish the other alone or when combined.
Referring to Claim 3, see discussion of claim 1 above, while Patel in view of Varga teaches the system above, Patel in view of Varga does not explicitly disclose a system having the limitations of, however,
Takumi teaches receive the output result of the recognized work and reference coordinates of a work area, and estimate a work position (see; pg. 3, par. 3 of Takumi teaches estimating the position of the work product based on two different cameras that create a 3D work area in addition to monitored work performed (i.e. work recognition)).
take as input the output result of the recognized work and the estimated work position, and re-recognize the work (see; pg. 2, par. 3 of Takumi teaches taking a first estimate of relative position and adding a second relative position from a different camera and then combining that data and creating a 3D work area to estimate positions).
The Examiner notes that Patel teaches similar to the instant trends in workplace wearable technologies. Specifically, Patel discloses the instant trends in workplace wearable technologies and connected-worker solutions for next-generation occupational safety, health, and productivity and s it is therefore viewed as analogous art in the same field of endeavor. Additionally, Varga teaches computer aided 360o heads up display of safety mission critical data and as it is comparable in certain respects to Patel which a work recognition apparatus as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Takumi teaches work management equipment and work management methods and programs and as it is comparable in certain respects to Patel which a work recognition apparatus as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
Patel and Varga discloses a work recognition device and work recognition method capable of detecting a work operation using camaras. However, Patel and Varga fails to disclose receive the output result of the recognized work and reference coordinates of a work area, and estimate a work position and take as input the output result of the recognized work and the estimated work position, and re-recognize the work.
Takumi discloses receive the output result of the recognized work and reference coordinates of a work area, and estimate a work position and take as input the output result of the recognized work and the estimated work position, and re-recognize the work.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of Patel and Varga receive the output result of the recognized work and reference coordinates of a work area, and estimate a work position and take as input the output result of the recognized work and the estimated work position, and re-recognize the work as taught by Takumi since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, Patel, Varga, and Takumi teach the collecting and analysis of data in order to monitor a worker and their environment in order to detect pertinent events and they do not contradict or diminish the other alone or when combined.
Conclusion
The prior art made of record and not relied upon considered pertinent to Applicant’s disclosure.
Tomohiko (WO 2022/195749 A1) discloses work efficiency calculation system, method, and program.
Ito et al. (JP 7006682 B2) discloses work management equipment, work management methods and programs.
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.
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/SSS/
Patent Examiner, Art Unit 3623
/RUTAO WU/Supervisory Patent Examiner, Art Unit 3623