DETAILED ACTION
This is a Non-Final Office Action. This communication replaces the Non-Final Rejection mailed 05/06/2026.
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 .
Status of Claims
Claims 1-6, 8-12, 14-24 are currently pending in the application and have been examined.
Response to Amendment
The amendment filed 12/09/2025 has been entered.
Response to Arguments
Claim Rejections 35 U.S.C. § 101:
Applicant submits on page 13 of the remarks that the amended claims recite a concrete technological system and this is not a mental process. Examiner respectfully disagrees and notes that under the analysis of claims under step 2A of the Alice framework, if a claim limitation, under its broadest reasonable interpretation covers an observation or evaluation, then it falls under the “mental process" grouping of abstract ideas.
Applicant submits on page 13 of the remarks that the claims solve the technological problem of inefficient industrial work systems by providing real-time, automated optimization through wearable sensor networks. Examiner notes that the additional elements recited in the claims only provide a computer generic function of sending/receiving and storing information, do not provide improvement to the computer technology and do not provide a meaningful link of the abstract idea to a practical application.
Applicant submits on page 14 of the remarks that the claims integrate the claims are integrated into a practical application of industrial work system optimization. Examiner respectfully disagrees and notes that the present claims do not integrate the judicial exception into a practical application in a matter that imposes meaningful limit to the judicial exception.
Applicant submits on page 14 of the remarks that the claims contain significantly more than the alleged abstract idea. Examiner notes that when determining whether a claim recites significantly more in Step 2B the analysis takes into consideration whether the claim effects a transformation or reduction of a particular article to a different state or thing. Transformation 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." Bilski v. Kappos, 561 U.S. 593, 658, 95 USPQ2d 1001, 1007 (2010) (quoting Gottschalk v. Benson, 409 U.S. 63, 70, 175 USPQ 673, 676 (1972)). See MPEP 2106.05(c). Furthermore, the additional elements recited in the claims merely recite the use of a generic computer to perform generic computer functions of storing and transmitting data. These generic computer functions do not integrate the abstract idea into a practical application and do not recite significantly more than the judicial exception.
Claim Rejections 35 U.S.C. § 103:
Applicant’s arguments have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 22 and 24 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Claim 22 recites the limitations "wherein the analysis module determines that either (i) a congestion condition exists in a zone based on context records including at least the number of users who are currently executing a process or process step and expected utilization over time, or (ii) a potential collision involving a worker exists based on sensor data including acceleration exceeding a predefined threshold, and wherein, in response, a change order is transmitted that causes the worker's sensor means to output a visual alert on its display." Claim 24 recites the limitations "wherein the analysis module determines that either (i) a congestion condition exists at a location of the work system based on context records including at least the number of users currently executing a process or process step there and utilization information, including expected utilization, over time, or (ii) a potential unsafe event involving a worker exists based on sensor data including acceleration exceeding a predefined threshold, and wherein, in response, a change order is transmitted that causes the worker's sensor means to output a visual alert on its display".
The originally filed disclosure does not provide support for the limitations of new claims 22 and 24. Specifically, the analysis module 54 is described as having the ability to create a report on the state of the work system and/or on the deviations from the previous operating procedure of the work system (see at least pg. 33, line 18-20 of the specification, as filed). In addition, the specification describes that the analysis module can determine the setup of a work system using context records (see pg. 35, line 1-3). However, the disclosure does not specifically describe, or otherwise, demonstrate the features recited in new claims 22 and 24.
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.
Claim(s) 1-6, 8-12, 14-24 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-patentable subject matter. The claims are directed to an abstract idea without significantly more.
With respect to claims 1-6, 8-12, 14-24, the independent claims (claims 1 and 20) are directed, in part, to a method and a system for monitoring a work system. Step 1 – First pursuant to step 1, claims 1-6, 8-12, 14-19, 21-24 are directed to a method comprising a series of steps which falls under the statutory category of a process and claim 20 is directed to a system which falls under the statutory category of a machine. However, these claim elements are considered to be abstract ideas because they are directed to a mental process which includes observations or evaluations.
As per Step 2A - Prong 1 of the subject matter eligibility analysis, the claims are directed, in part, to monitoring a work system comprising a plurality of sensor means with at least a sensor and a control system, wherein the method comprises steps of: creating sensor data as well as event data packets by means of the plurality of sensor means worn on a hand workwear unit of a user during operation by the user, wherein the event data packets comprise current sensor data of at least one sensor of the sensor means as well as at least one situation information of the sensor means, wherein the sensor data comprises at least one of: an image of a camera being the sensor, a value or the image of a captured barcode, a measured value of one or more acceleration sensors, a movement recognized by means of one or more acceleration sensors, a number of steps carried out between two event points, a type of activity between two event points, a movement travelled between two event points, a length of time between two end points, or a measured value of a sensor of the sensor means, wherein the at least one situation information comprises at least one of information regarding the sensor means, information on a connection device by means of which the sensor means communicates with the control system or a monitoring system, an identifier of the user, or a time stamp of the time at which at least one of the event data packet or the sensor data have been generated, transmitting the event data packets to a correlation module of the monitoring system, receiving context information by means of the correlation module, wherein the context information contains information from sources that are not a sensor means or a connection device, correlating the event data packets with the context information by means of the correlation module and creating context records by means of the correlation module, said context records being based on the event data packets correlated with the context information, transmitting the context records to an analysis module, and determining a system improvement by the analysis module based on the context records; creating at least one change order based on the system improvement for at least one of the sensor means; wherein the change order contains at least one of an instruction to change process steps assigned to the sensor means, an amended configuration, an instruction to change an arrangement of the work system, or an instruction to change physical assets within the work system, transmitting the at least one change order to at least one of the respective sensor means, a connection device corresponding to the respective sensor means, or the control system; and changing, by at least one of the control system or the corresponding connection device, a process of the work system assigned to the corresponding sensor means in accordance with the at least one change order based on the system improvement, wherein the change order is then implemented by at least one of the sensor means or the connection device, so that the work system is changed as at least one of the user is redeployed to another location, a mode of operation of the sensor means changes or a mode of operation of the connection means changes. If a claim limitation, under its broadest reasonable interpretation covers an observation or evaluation, then it falls under the “mental process” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
As per Step 2A - Prong 2 of the subject matter eligibility analysis, this judicial exception is not integrated into a practical application. In particular, independent claim 1 recites additional elements: a work system, sensor, control system, data packets, correlation module, analysis module; independent claim 20 recites a system and monitoring system. These additional element in both steps are recited at a high-level of generality (i.e., as a generic device performing a generic computer function of receiving and storing data) such that these elements amount no more than mere instructions to apply the exception using a generic computer component. Examiner looks to Applicant’s specification and at least figures 2 and 3 to understand that the invention may be implemented in a generic environment that “The connection devices 22 are devices that typically have larger computing power as the sensor means 24, in particular the sensor devices 26. For example, the connection devices 22 are designed as smart devices, such as a smartphone, a tablet, a smart watch or smart glasses, or a wristband equipped with corresponding processors and communication modules. In this case, the connection devices 22 are also mobile and are worn by the user W. The combination of the sensor device 26 and the connection device 22 corresponds to the example of the sensor and information system comprising a secondary device (sensor device 26) and main device (connection device 22). It is however conceivable that stationary devices, such as base stations for wireless communication are used, e.g. WLAN access points or mobile base stations as connection devices 22, but also stationary devices that operate as WLAN clients. Connection devices 22 can also be connected per USB to a computer or the control system 20 and per wireless communication to the sensor means 24. It is however conceivable that sensor means 24 is built into a device with the connection device 22. Furthermore, as described, the machine learning is just being applied as a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they are mere instructions to implement the abstract idea on a computer.
As per Step 2B of the subject matter eligibility analysis, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements are mere instructions to apply the abstract idea on a computer. When considered individually, these claim elements only contribute generic recitations of technical elements to the claims. It is readily apparent, for example, that the claim is not directed to any specific improvements of these elements and the invention is not directed to a technical improvement. When the claims are considered individually and as a whole, the additional elements noted above, appear to merely apply the abstract concept to a technical environment in a very general sense – i.e. a generic computer receives information from another generic computer, processes the information and then sends information back. In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. Their collective functions merely provide generic computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that amount to significantly more than the abstract idea itself. Although not considered general purpose computer elements, the examiner notes the well-understood, routine and conventional nature of these additional element(s) and therefore these elements fail to add significantly more to the abstract idea recited in the claims. The most significant elements of the claims, that is the elements that really outline the inventive elements of the claims, are set forth in the elements identified as an abstract idea. The fact that the generic computing devices are facilitating the abstract concept is not enough to confer statutory subject matter eligibility. Next, when the “machine learning” is evaluated as an additional element, this feature is recited at a high level of generality and encompasses well-understood, routine, and conventional prior art activity. See, e.g., Balsiger et al., US 2012/0054642, noting in paragraph [0077] that “Machine learning is well known to those skilled in the art.” See also, Djordjevic et al. US 2013/0018651, noting in paragraph [0019] that “As known in the art, a generative model can be used in machine learning to model observed data directly.” See also, Bauer et al., US 2017/0147941, noting at paragraph [0002] that “Problems of understanding the behavior or decisions made by machine learning models have been recognized in the conventional art and various techniques have been developed to provide solutions.” Accordingly, the use of machine learning does not add significantly more to the claims. Examiner notes that although, the use of sensors does not fall within the scope of generic computer components it is considered well-understood, routine, and conventional activity and therefore fail to add significantly more to the claims.
The dependent claims, including the use of machine learning further refine the abstract idea. These claims do not provide a meaningful linking to the judicial exception. Rather, these claims offer further descriptive limitations of elements found in the independent claims and addressed above – such as by describing the nature and content of the data that is received/sent. While these descriptive elements may provide further helpful context for the claimed invention these elements do not serve to confer subject matter eligibility to the invention since their individual and combined significance is still not significantly more than the abstract concepts at the core of the claimed invention.
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 (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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)(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.
Claim(s) 1-6, 8-12, 14-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US Pub. No. 2018/0005161 (hereinafter; Cong).
Regarding claims 1/20, Cong discloses:
A method; A system for monitoring a work system comprising a plurality of sensor means with at least a sensor, comprising at least one of an optical sensor or an acceleration sensor, (Cong [0037] discloses optical sensors and accelerometers.) and a control system, wherein the method comprises steps of: creating sensor data as well as event data packets by means of the plurality of sensor means worn on a hand workwear unit of a user during operation by the user, (Cong [0037] discloses Examples of the user device can include …a watch, wearable device[…]) wherein the event data packets comprise current sensor data of at least one sensor of the sensor means as well as at least one situation information of the sensor means, (Cong [0050] discloses sensor data queries events.) wherein the sensor data comprises at least one of: an image of a camera being the sensor, a value or the image of a captured barcode, a measured value of one or more acceleration sensors, a movement recognized by means of one or more acceleration sensors, a number of steps carried out between two event points, a type of activity between two event points, a movement travelled between two event points, a length of time between two end points, or a measured value of a sensor of the sensor means, (Cong [0038] discloses images; [0037] discloses cameras; [0037] discloses accelerometer data.) wherein the at least one situation information comprises at least one of information regarding the sensor means, information on a connection device by means of which the sensor means communicates with the control system or a monitoring system, an identifier of the user, or a time stamp of the time at which at least one of the event data packet or the sensor data have been generated, (Cong [0026] discloses the method 100 and/or system 200 can provide ongoing information (e.g., insights, determined from the collected information; metrics; suggestions; etc.) to the user.) transmitting the event data packets to a correlation module of the monitoring system, receiving context information by means of the correlation module, wherein the context information contains information from sources that are not a sensor means or a connection device, correlating the event data packets with the context information by means of the correlation module and creating context records by means of the correlation module, said context records being based on the event data packets correlated with the context information, transmitting the context records to an analysis module, and determining a system improvement by the analysis module based on the context records; (Cong [0024] discloses The method 100 and/or system 200 can function to collect user data, organize the data (e.g., quantify the data; extract factor values correlated with user metrics; etc.), analyze the data (e.g., interpret the data; determine user metrics; etc.), and/or present the data to users (e.g., employees, managers, leadership such as the corporate suite, people operations such as human resources, etc.)… The method 100 can additionally or alternatively function to automatically recommend workplace actions (e.g., user actions to improve their skills, to correct undesired trends in user metrics; operations actions to mitigate negative effects of employee actions on other employees, to mitigate the occurrence of undesirable employee actions; managerial or leadership actions such as employee project or task assignment, employee team assignment; etc.) and/or generate any other suitable set of recommendations. However, the method 100 and/or system 200 can perform any suitable functionality.)
creating at least one change order based on the system improvement for at least one of the sensor means; wherein the change order contains at least one of an instruction to change process steps assigned to the sensor means, an amended configuration, an instruction to change an arrangement of the work system, or an instruction to change physical assets within the work system, transmitting the at least one change order to at least one of the respective sensor means, a connection device corresponding to the respective sensor means, or the control system; (Cong [0024] discloses The method 100 can additionally or alternatively function to predict user changes associated with the workplace, such as changes in performance, alignment, engagement, and/or any other suitable change. The method 100 can additionally or alternatively function to automatically recommend workplace actions (e.g., user actions to improve their skills, to correct undesired trends in user metrics; operations actions to mitigate negative effects of employee actions on other employees, to mitigate the occurrence of undesirable employee actions; managerial or leadership actions such as employee project or task assignment, employee team assignment; etc.) and/or generate any other suitable set of recommendations.) and changing, by at least one of the control system or the corresponding connection device, a process of the work system assigned to the corresponding sensor means in accordance with the at least one change order based on the system improvement, wherein the change order is then implemented by at least one of the sensor means or the connection device, so that the work system is changed as at least one of the user is redeployed to another location, a mode of operation of the sensor means changes or a mode of operation of the connection means changes. (Cong [0024] discloses The method 100 can additionally or alternatively function to predict user changes associated with the workplace, such as changes in performance, alignment, engagement, and/or any other suitable change. The method 100 can additionally or alternatively function to automatically recommend workplace actions (e.g., user actions to improve their skills, to correct undesired trends in user metrics; operations actions to mitigate negative effects of employee actions on other employees, to mitigate the occurrence of undesirable employee actions; managerial or leadership actions such as employee project or task assignment, employee team assignment; etc.) and/or generate any other suitable set of recommendations.)
Regarding claim 2, Cong discloses:
The method according to claim 1, wherein the control system controls the plurality of sensor means at least in part for a purpose of executing a process assigned to a corresponding sensor means. (Cong [0036] discloses sensor data and control logins as part of control data communication.)
Regarding claim 3, Cong discloses:
The method according to claim 1, wherein at least one of said at least one sensor of the plurality of sensor means is a barcode reader, or the sensor means comprises at least one actuating element, or the sensor means comprises at least one output means. (Cong [0037] discloses sensors with outputs.)
Regarding claim 4, Cong discloses:
The method according to claim 1, wherein the work system comprises a plurality of connection devices, wherein each connection device is connected to one or more of the sensor means via a wireless communication link and is connected to the control system via a wired or wireless communication link or is configured on a same sensor means. (Cong [0031] discloses wireless communication.)
Regarding claim 5, Cong discloses:
The method according to claim 4, wherein the connection devices create the event data packets and transmit the event data packets to the correlation module. (Cong [0061] discloses correlating data from queries.)
Regarding claim 6, Cong discloses:
The method according to claim 1, wherein an event data packet is at least one of created at regular intervals by the sensor means or is then created if there is a trigger event and includes information on the trigger event. (Cong [0050] discloses trigger events.)
Regarding claim 8, Cong discloses:
The method according to claim 1, further comprising creating a report comprising the system improvement determined by the analysis module based on the context records, wherein at least one of the report further contains at least one of information on a setup of the work system as a state of the work system; a utilisation of the work system; the state of at least one of sensor means, gateways or connection devices; at least one process executed with the work system; a discharge rate of a storage battery or a primary battery of the sensor means; a storage battery life or primary battery life; a type of barcode read; a duration of a reading process; a success of the reading process; a number of steps between two reading processes; a change in a location between two reading processes; a software version of the sensor means; the software version of the connection devices; or information regarding a charging behavoir of the sensor means; or the report further contains deviations from a previous operating sequence including at least one of information of the sensor means comprising more or less executed process steps as the previous operating sequence; changes to the setup of the work system; changes to the utilisation of the work system; changes to the state of the work system; changes to said at least one process executed with the work system; differences between same processes at at least one of different locations or different workstations; or differences regarding industry reference values. (Cong [0053] discloses reports.)
Regarding claim 9, Cong discloses:
The method according to claim 1, wherein at least one of the context records or the event data packets are stored in a storage device to be used at a later date as past context records or past event data packets, respectively. (See historic users data and metrics stored in at least [0038-0040]; [0049]; [00066].)
Regarding claim 10, Cong discloses:
The method according to claim 1, wherein at least one of the correlation module contains at least one of the context information from the control system, an inventory management system, an enterprise resource planning system, a machine controller for a machine of the work system, a mobile device management system, data from external data providers, or publicly accessible data sources; or wherein the context information comprises at least one of information regarding a working environment, processes of the work system, users of the work system or regarding a utilisation of the work system. (Cong [0060] discloses correlation metrics from auxiliary sources.)
Regarding claim 11, Cong discloses:
The method according to claim 1, wherein a report comprising the system improvement determined by the analysis module based on the context records is transmitted to at least one of the control system, an inventory management system, an enterprise resource planning system, a mobile end device, a workplace computer or an output means. (Cong [0075] discloses User metrics and/or other suitable user data can optionally be presented through a means of ‘virality’. User interactions with the user data can cause the system to republish that user data to the user's peers (organizational, project based, etc.), the user's manager, to the user themselves (e.g., in the form of a report if the a user is a manager), and/or any other suitable grouping, such as based on the degree of interactions with the user data.)
Regarding claim 12, Cong discloses:
The method according to claim 1, wherein the analysis module receives the event data packets as well as creates the context information for the event data packets based on at least one of the event data packets or past event data packets and transmits this to the correlation module. (See historic users data and metrics stored in at least [0038-0040]; [0049]; [00066].)
Regarding claim 14, Cong discloses:
The method according to claim 1, further comprising creating a report by: determining at least one of a state of the work system, a previous operating sequence, or deviations from the previous operating sequence on a basis of the context records, and creating the report using at least one of the state of the work system, the previous operating sequence or deviations from the previous operating sequence. (Cong [0075] discloses User metrics and/or other suitable user data can optionally be presented through a means of ‘virality’. User interactions with the user data can cause the system to republish that user data to the user's peers (organizational, project based, etc.), the user's manager, to the user themselves (e.g., in the form of a report if the a user is a manager), and/or any other suitable grouping, such as based on the degree of interactions with the user data.)
Regarding claim 15, Cong discloses:
The method according to claim 14, wherein a first machine learning module of the analysis module is used to determine at least one of the state of the work system, the previous operating sequence or deviations from the previous operating sequence. (Cong [0042] discloses the use of machine learning.)
Regarding claim 16, Cong discloses:
The method according to claim 1, wherein the system improvement determined by the analysis module is transmitted to a distribution module, wherein the distribution module creates the at least one change order. (Cong [0024] discloses The method 100 can additionally or alternatively function to predict user changes associated with the workplace, such as changes in performance, alignment, engagement, and/or any other suitable change. The method 100 can additionally or alternatively function to automatically recommend workplace actions (e.g., user actions to improve their skills, to correct undesired trends in user metrics; operations actions to mitigate negative effects of employee actions on other employees, to mitigate the occurrence of undesirable employee actions; managerial or leadership actions such as employee project or task assignment, employee team assignment; etc.) and/or generate any other suitable set of recommendations.)
Regarding claim 17, Cong discloses:
The method according to claim 16, wherein the sensor means outputs an action order to the user on a basis of the change order. (Cong [0024] discloses The method 100 can additionally or alternatively function to automatically recommend workplace actions (e.g., user actions to improve their skills, to correct undesired trends in user metrics; operations actions to mitigate negative effects of employee actions on other employees, to mitigate the occurrence of undesirable employee actions; managerial or leadership actions such as employee project or task assignment, employee team assignment; etc.) and/or generate any other suitable set of recommendations.)
Regarding claim 18, Cong discloses:
The method according to claim 16, wherein at least one of the control system or the corresponding connection device further instructs the sensor means to output an action order. (Cong [0024] discloses The method 100 can additionally or alternatively function to automatically recommend workplace actions (e.g., user actions to improve their skills, to correct undesired trends in user metrics; operations actions to mitigate negative effects of employee actions on other employees, to mitigate the occurrence of undesirable employee actions; managerial or leadership actions such as employee project or task assignment, employee team assignment; etc.) and/or generate any other suitable set of recommendations.)
Regarding claim 19, Cong discloses:
The method according to claim 1, wherein at least one of a machine learning module of the correlation module, a first machine learning module of the analysis module, a second machine learning module of the analysis module, a third machine learning module of the analysis module, a fourth machine learning module of the analysis module, a context machine learning module of the analysis module, or a machine learning module of a distribution module is or comprises at least one of an artificial neural network, a decision tree, a statistical algorithm, a cluster algorithm, a module for generating text, or a principal component analysis. (Cong [0042] discloses the use of machine learning.)
Regarding claim 21, Cong discloses:
The method according to claim 1, wherein the context information is received, via the correlation module, from at least one of the control system, an inventory management system, an enterprise resource planning system, a machine controller of a machine, a mobile device management system (MDM), data from external data providers, and publicly accessible data sources. (Cong [0060] discloses correlation metrics from auxiliary sources.)
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 22-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cong in view of US Pub. No. 2019/0122036 (hereinafter; Ward).
Regarding claim 22, although Cong discloses monitoring a work system using sensors, Cong does not specifically disclose deviations in worker procedures or safety data. However, Ward discloses the following limitations.
The method of claim 1, wherein the analysis module determines that either (i) a congestion condition exists in a zone based on context records including at least the number of users who are currently executing a process or process step and expected utilization over time, or (ii) a potential collision involving a worker exists based on sensor data including acceleration exceeding a predefined threshold, and wherein, in response, a change order is transmitted that causes the worker's sensor means to output a visual alert on its display. (Ward [0013] discloses different devices, including a wearable device on the worker and/or a mobile or handheld device, such as for a manager, both having sensors, are used in some examples to monitor safety metrics to identify potentially unsafe conditions.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the system for user metrics of Cong with the worker task performance safety of Ward in order to generate worker specific data (Ward abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Regarding claim 23, although Cong discloses monitoring a work system using sensors, Cong does not specifically disclose deviations in worker procedures or safety data. However, Ward discloses the following limitations.
The method of claim 1, wherein the analysis module detects a deviation in a worker's operating procedure based on movement recognized from acceleration sensor data and, in response, the sensor means outputs an action order to the user. (Ward [0013] discloses different devices, including a wearable device on the worker and/or a mobile or handheld device, such as for a manager, both having sensors, are used in some examples to monitor safety metrics to identify potentially unsafe conditions.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the system for user metrics of Cong with the worker task performance safety of Ward in order to generate worker specific data (Ward abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Regarding claim 24, although Cong discloses monitoring a work system using sensors, Cong does not specifically disclose deviations in worker procedures or safety data. However, Ward discloses the following limitations.
The method of claim 1, wherein the analysis module determines that either (i) a congestion condition exists at a location of the work system based on context records including at least the number of users currently executing a process or process step there and utilization information, including expected utilization, over time, or (ii) a potential unsafe event involving a worker exists based on sensor data including acceleration exceeding a predefined threshold, and wherein, in response, a change order is transmitted that causes the worker's sensor means to output a visual alert on its display. (Ward [0013] discloses different devices, including a wearable device on the worker and/or a mobile or handheld device, such as for a manager, both having sensors, are used in some examples to monitor safety metrics to identify potentially unsafe conditions.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the system for user metrics of Cong with the worker task performance safety of Ward in order to generate worker specific data (Ward abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FRANCIS Z SANTIAGO-MERCED whose telephone number is (571)270-5562. The examiner can normally be reached M-F 7am-4:30pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, BRIAN EPSTEIN can be reached at 571-270-5389. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/FRANCIS Z. SANTIAGO MERCED/Examiner, Art Unit 3625
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