DETAILED ACTION
Claims 1-5,7-12,14-19 and 21-22 are presented for examination.
Claims 1, 8, 15, and 21-22 have been amended.
This office action is in response to the RCE submitted on 19-May-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 .
Response to Arguments – 35 USC 103
On pg. 9-10 the applicant argues the combination of the references doesn’t teach the newly amended limitation: (ii) an acoustic profile of the equipment based on the simulated vibration generated by the digital twin
However, as per the updated mapping below, Mirus teaches customizing the audible warning in accordance to the noise levels (acoustic profile) see [0042-0044].
Mirus teaches a known process causing an indication to be present to an operator of the equipment, the indication specifying a level of audible safety of using the equipment based on 1) the determined distance between the equipment and the user and ii) an acoustic profile of the equipment. It would be obvious to one of ordinary skill in the art to apply the known technique of Mirus in the environment and process of Dosluoglu, which teaches a simulated vibration generated by the digital twin, in order to achieve a safer work environment that allows machines and humans to operate side by side safely and provide sufficient warning alerts in the case of adverse events with expected results. Note MPEP 2143- (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Applicant’s arguments with respect to the 103 rejections have been considered, but are not persuasive.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION. —The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 8, and 15 recite the following limitation: based on calculating effectiveness by the digital twin. Additionally, the specification does not define effectiveness. [0022] “Embodiments of the present disclosure disclose deploying a robot to an optimized area determined by the digital twin model in order to attenuate the noise to all nearby personnel below the acceptable threshold. A robot can achieve this via multiple means which may be determined based on the effectiveness calculated via the digital twin modeling: deployable noise insulation panels placed in the sound path between a tool and nearby personnel, attenuation by dampening effect of vibration directly on material being worked on such as a robot rubber arm applying pressure on vibrating material, and active noise cancellation by intercepting the sound wave between the noise source and nearby personnel and generating a sound wave to cancel the sound wave.” Effectiveness is a relative term and the claims are rejected for lack of clarity.
Claims 2-5, 7 and 21-22, 9-12 and 14, and 16-19 are dependent on 1, 8, and 15 respectively and are rejected for inheriting the same deficiency of their parent claims.
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.
Claims 1-5,7-12,14-19 and 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Dosluoglu (US20240155313A1) in view of Hentunen et al. (US20190297412A1) and further in view of Mirus et al. (US20220113698A1).
Regarding Claim 1, Dosluoglu teaches a computer implemented method comprising:
generating, by one or more processors, a digital twin of an environment, wherein the digital twin simulates vibration within the environment based on equipment and activities within the environment that are simulated by the digital twin ([0015] “the first subset of sensors comprises an array of sound or vibration sensors configured to provide directional sensitivity,” and [0177-0180] " With reference to the sensing system 100 of the present disclosure, any change to be implemented in the sensing system 100 may be determined (modelled and simulated) in a digital twin copy of the sensing system 100 before being implemented in the sensing system 100").
determining, by one or more processors, how vibration is propagated within the environment based on the simulated vibration generated by the digital twin ([0180] “in embodiments where the sensing systems 100 comprise an integrated artificial intelligence component, this can be configured to track the deviation of the sensing system's response from the response of its digital twin counterpart,” and [0182] "with sensing systems according to the present disclosure only some significant data need to be transmitted in order to make real-time corrections in the system response (or in the system model of its digital twin counterpart)" Also see [0123 and 0131]).
generating, by one or more processors, a plan for mitigating the vibration for a user within the environment ([0040] "the one or more active noise cancellation modules being configured to receive in input the noise signals detected by the sensors; and control the one or more actuator devices in order to generate noise cancelling signals for the purpose of achieving localized noise cancellation at one or more locations" also see [0166]).
deploying, by one or more processors, 100 of the present disclosure, any change to be implemented in the sensing system 100 may be determined (modelled and simulated) in a digital twin copy of the sensing system 100 before being implemented in the sensing system 100.” And [0004] “WSNs are characterized by the ability to dynamically self-organize and self-configure after deployment. This allows to deploy sensors without careful pre-planning or engineering as well as to dynamically re-configure the network to respond to a change in the environment or the network itself. This capability is key to most WSN applications, since the sensors may have to be deployed in hostile or remote locations where it is hard or impossible to replace faulty sensors as well as to recharge or replace the sensors' batteries. Moreover, the sensors are generally deployed in environments with mutating conditions which can cause the sensors' relative positions to vary over time and require frequent re-configuration.”)
However, Dosluoglu is not relied on for:
determining, by one or more processors, a distance between the equipment and the user using a Euclidean metric on a bounding area identified in a video;
responsive determining the distance: causing, by one or more processors, an indication to be presented to an operator of the equipment, the indication specifying a level of audible safety of using the equipment based on: (i) the determined distance between the equipment and the user and (ii) an acoustic profile of the equipment based on the simulated vibration generated by the digital twin
deploying, by one or more processors, a robot to a sound path location between the equipment and the user, based on calculating effectiveness by the digital twin.
Hentunen teaches deploying, by one or more processors, a robot to a sound path location between the equipment and the user, based on calculating effectiveness by the digital twin ([0037-0040] “The target position 150 is on a line of sight between the position of the acoustic source 130 and the position of the acoustic receiver 140… the noise cancelling apparatus may further increase privacy by blocking an optical path from the acoustic source to the acoustic receiver. The acoustic source may be optically covered by the noise cancelling apparatus from the perspective of the acoustic receiver… According to some examples, the noise cancelling apparatus may be a robot or robotic device, or part of a robot or robotic device, and the propulsion component 110 comprises a movement device of a robot” Also see Fig. 2 and [0059]. EN: The DT is provided by Dosluoglu)
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Dosluoglu and Hentunen are analogous art because they are from the same field of endeavor in noise cancellation. Before the effective filing date of the invention, it would have been obvious to a person of ordinary skill in the art, to combine Dosluoglu and Hentunen to employ mobile robots to cancel the noise instead of Dosluoglu’s static noise cancellation devices. A POSITA would have been motivated to do so to achieve a more dynamic real-time mitigation of noise through robots that can update their location to automatically cancel noise in a dynamically changing environment. “The noise cancelling apparatus comprises a propulsion component configured to autonomously move the noise cancelling apparatus.” (Hentunen [0008]).
Mirus teaches determining, by one or more processors, a distance between the equipment and the user using a Euclidean metric on a bounding area identified in a video ([0050] “Similarly, the location of the human locationhuman, could be estimated from sensors in the infrastructure as well as sensors on smart devices carried or worn by the human. Finally, the gaze of the human gazehuman can be inferred from sensors on smart devices worn by the human (e.g., smart goggles or headphones) or by external sensors such as cameras in the infrastructure. Approaches based on the latter typically consist of several steps such as head detection, gaze estimation as well as tracking and data association. This results in a vector gazehuman in 3D space representing the human gaze as well as 3D poses locationrobot) and locationhuman,representing the locations of the AME and the human respectively. The vector v=lr−lh represents the direction of the AME from the location of the human. Using the distance d=|lr−lh| between the AME and the human as well as the angle alpha (or the cosine similarity) between the vectors gh and v enables the virtual placement of the warning signal at the real location of the AME (or, more generally, the source of the danger) “ and [0034] “In FIG. 4, humans 402-1 and 402-2 can share the physical workspace 400 with a mobile device, e.g., an AME 404. Humans 402-1 and 402-2 can utilize hearing protection (e.g., devices 406-1, 406-2) as part of a normal work procedure. The physical workspace 400 can include cameras 408-1, 408-2 as well as other sensors (not shown in FIG. 4). In some aspects, the AME 404 can include sensors, such as machine vision sensors (not shown in FIG. 4). The humans 402-1, 402-2, AME 404, cameras 408-1, 408-2 and any other computing devices can communicate to a centralized risk monitoring and mitigation apparatus 410 using any of the communication methods described herein with respect to FIGS. 1-3, 10A and 10B, such as through the cloud, within an edge computing environment and/or in an IoT environment.” EN: [0050] shows the formula for the distance calculation using Euclidean distance)
responsive determining the distance: causing, by one or more processors, an indication to be presented to an operator of the equipment, the indication specifying a level of audible safety of using the equipment based on: (i) the determined distance between the equipment and the user ([0042] “For various AME and human tasks (e.g., taskw and taskr), there exist algorithmic approaches for AME-centric perception and even first cloud-based approaches. Thus, the final risk of a worker w and a AME is a function of the current state of the digital environment model with all cues collected in the apparatus 410. Risk can be significantly higher if the AME moves outside the human's field of view or is approaching from behind, and therefore gazew can be important to determining risk in addition to the other factors listed above. The processing circuitry 414 can provide the notification by simple verbal commands (localized to different languages, for example) and by varying at least one of a volume level and a frequency level of the notification based on a level of severity of the risk condition or on a proximity of the risk condition to at least the first user device (e.g., device 406-1, 406-2). For example, the volume of the warning signal can be a function of the noise in the environment and the estimated risk, according to Equation (2):” See Also [0043-0046])
and (ii) an acoustic profile of the equipment based on the simulated vibration generated by the digital twin ([0043-0044] “For example, the volume of the warning signal can be a function of the noise in the environment and the estimated risk, according to Equation (2):
v=g(N)+p(R(w,r)) (2)
where g(N) denotes a function to account for level of noise N in the environment and p denotes a piece-wise function of the estimated risk level. In some examples, the processing circuitry 414 can ensure that the warning signal will be audible for the worker as it will be louder than the noise in the environment and that the volume will increase if the risk increases. For example, volume may increase with risk according to FIG. 5A. As can be seen in FIG. 5A, if the estimated risk surpasses a certain threshold r0, the volume 502 of the warning signal is linearly increased until a maximal volume value is reached for a fixed risk value r1.” EN: The noise in the environment is an acoustic profile. Dosluglu provides the simulated vibration provided by the digital twin as per [0123, 0131, and 0180-0182])
Dosluoglu, Hentunen and Mirus are analogous art because they are from the same field of endeavor in operation safety. Before the effective filing date of the invention, it would have been obvious to a person of ordinary skill in the art, to combine Dosluoglu, Hentunen and Mirus.
Mirus teaches a known process causing an indication to be present to an operator of the equipment, the indication specifying a level of audible safety of using the equipment based on 1) the determined distance between the equipment and the user and ii) an acoustic profile of the equipment. It would be obvious to one of ordinary skill in the art to apply the known technique of Mirus in the environment and process of Dosluoglu which teaches a simulated vibration generated by the digital twin in order to achieve a safer work environment that allows machines and humans to operate side by side safely and provide sufficient warning alerts in the case of adverse events with expected results.
Note MPEP 2143- (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results.
Regarding Claim 2, Dosluoglu in view of Hentunen and further in view of Mirus teaches the method of claim 1. Dosluglu further teaches the plan for mitigating the vibration includes determining by one or more processors, at least one location to deploy a noise cancellation module within the environment ([0040] "the one or more actuator devices in order to generate noise cancelling signals for the purpose of achieving localized noise cancellation at one or more locations inside the railway car").
Regarding Claim 3, Dosluoglu in view of Hentunen and further in view of Mirus teaches the method of claim 2. Dosluglu further teaches dynamically positioning, by one or more processors, the noise cancellation module in the environment ([0040] "the one or more active noise cancellation modules being configured to receive in input the noise signals detected by the sensors; and control the one or more actuator devices in order to generate noise cancelling signals for the purpose of achieving localized noise cancellation at one or more locations inside the railway car." The sound is dynamically being detected and cancelled. The actuators choose which noise cancellation modules at which location to activate and to what extent).
based on the simulation vibration generated by the digital twin ([0179] "change to be implemented in the sensing system 100 may be determined (modelled and simulated) in a digital twin copy of the sensing system 100 before being implemented in the sensing system 100").
Regarding Claim 4, Dosluoglu in view of Hentunen and further in view of Mirus teaches the method of claim 2. Dosluglu further teaches identifying, by one or more processors, one or more sources of the generated vibration and the properties of the vibration (Fig 7 shows the source location detection. [0043] "the noise signals comprise motion vibration signals; the one or more sensors located on the railway car comprise motion vibration sensors configured to detect said motion vibration signals," and [0083] "the neural network layers 238 i may be trained to ignore a specific signal noise or to extract specific features for dimensionality reduction prior to the data being fed to the gateway neural network layers 236").
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Regarding claim 5, Dosluoglu in view of Hentunen and further in view of Mirus teaches the method of claim 1. Hentunen further teaches the plan for mitigating the vibration includes deploying by one or more processors, a robot attenuating the vibration in a determined location ([0040] “According to some examples, the noise cancelling apparatus may be a robot or robotic device, or part of a robot or robotic device, and the propulsion component 110 comprises a movement device of a robot”).
Regarding Claim 7, Dosluoglu in view of Hentunen and further in view of Mirus teaches the method of claim 1. Dosluglu further teaches tracking, by one or more processors, the generated vibration with one or more piezoelectric sensors ([0052] "the noise signals are one of motion vibration signals or acoustic signals and the sensors comprise one or more of acoustic sensors and vibration sensors" piezo (squeeze) electric is a vibration to electricity sensor).
measuring, by one or more processors, combined vibration and noise generated by different activities ([0052] " the sensors comprise one or more of acoustic sensors and vibration sensors").
Regarding Claim 8, Dosluoglu teaches a computer program product comprising: one or more computer readable storage media; and program instructions stored on the one or more computer readable storage media, to perform operations comprising ([0085] “The gateway 220 may be coupled to a server 250 to which the data are uploaded for further analysis and/or storage and be configured to communicate with the server 250 for sending and receiving data and instructions”).
The remaining limitations are similar to claim 1 and are rejected under the same rationale.
Claims 9-12, and 14 are medium claims reciting limitations similar to claims 2-5, and 7 respectively and are rejected under the same rationale.
Regarding Claim 15, Dosluoglu teaches a computer system comprising: one or more computer processors, one or more computer readable storage media, and program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the program instructions comprising ([0085] “The gateway 220 may be coupled to a server 250 to which the data are uploaded for further analysis and/or storage and be configured to communicate with the server 250 for sending and receiving data and instructions”).
The remaining limitations are similar to claim 1 and are rejected under the same rationale.
Claims 16-19 are system claims reciting limitations similar to claims 2-5 respectively and are rejected under the same rationale.
Regarding Claim 21, Dosluoglu in view of Hentunen and further in view of Mirus teaches the method of claim 1. Mirus teaches further comprising: responsive to the determined distance between the equipment and the user being less than a threshold, preventing operation of the equipment by the operator ([0066] “Based on the above factors and conditions, the apparatus 410 can create a dynamic risk assessment and provide information and risk mitigation actions to take to any AME 702 or other systems within the workspace 700. For example, the apparatus 410 can transfer reaction policy parameters or notification to all AMEs 702 within a workspace 700, wherein such parameters can include speed limit thresholds, areas to avoid, wait times based on traffic, and other details. The parameters can also be used to program a safety field within any safety field devices (e.g., scanners and machine vision devices). A safety field is configured by a AME 702 based on AME speed. For example, if an AME is operating at a high speed, the safety field in front of the AME 702 will be larger than if the AME was operating at a lower speed, to account for the probability that the AME will encounter other devices or humans while traveling at that higher speed. The safety field size can also be set based on traffic density, lighting conditions, or the profiles of nearby workers (e.g., workers 704).” [0051] “In additional aspects, depending on local privacy issues or laws, specific warning signals can be more personally tailored human 402-1, 402-2 receiving the alarm or notification. Additional aspects can provide a learning system that explores different warning sounds and collects the reaction time of the human 402-1, 402-2. Still further aspects can create a map of locations where most of safety warnings were issued to identify areas where additional safety means such as physical barriers or warning signs could be helpful for improved risk mitigation. Smart phones or other devices for providing notifications can be used in place of or in addition to headphones. Warning lamps and speakers can be provided elsewhere in the physical workspace 400 to provide warning signals to a group of users or an area of the physical workspace 400. A user can subscribe to the type of alarms that he or she wants to receive. In these and other examples, depending on the persona (e.g., the type of job description responsibilities of the user, etc.), the alarm can be programmed. For example, a factory floor supervisor or security personnel may want to receive all the alarms. A factory floor worker may want to receive alarms for threats/risk within a certain area around him or her, etc. In still other examples, if a threat exceeds a defined severity level, then it should be broadcast to all.” Also [0055-0056 and 0070-0072])
Regarding Claim 22, Dosluoglu in view of Hentunen and further in view of Mirus teaches the method of claim 21. Mirus further teaches wherein the indication is presented as a color coded indication light on the equipment ([0033] “Systems, apparatuses, and methods according to aspects address these concerns by providing a centralized risk monitoring and mitigation system including individually customized warnings for smart factories with AMEs or other automated devices sharing a workspace with human staff. Data from sensors in the infrastructure or mounted on mobile AMEs can be collected in a centralized system over the cloud to estimate the individual risk of humans in the factory. Depending on the risk level, an individual warning may be sent to the respective user devices (e.g., ear protection headphones) to make the apparatus user aware of the source and location of the risk. In some examples, signals can be made to seem sourced at the location of the original risk.” [0037] “Visual warnings can include lights, text, etc. provided at a user's smart phone, smart glasses, AR components, etc. Tactile or haptic feedback can be provided to wearable devices, for example.” [0051] “Warning lamps and speakers can be provided elsewhere in the physical workspace 400 to provide warning signals to a group of users or an area of the physical workspace 400. A user can subscribe to the type of alarms that he or she wants to receive. In these and other examples, depending on the persona (e.g., the type of job description responsibilities of the user, etc.), the alarm can be programmed. For example, a factory floor supervisor or security personnel may want to receive all the alarms. A factory floor worker may want to receive alarms for threats/risk within a certain area around him or her, etc. In still other examples, if a threat exceeds a defined severity level, then it should be broadcast to all.” And [0053] “The notification can include an audio signal. The audio signal can vary in at least one of volume and frequency based on at least one of a proximity of the risk to the apparatus 600 and a severity level of the risk. In these or other aspects, the notification can include a visual signal indicating a direction of the risk relative to the apparatus 600.” And [0096] “In some optional examples, various input/output (I/O) devices may be present within or connected to, the edge computing node 1050. For example, a display or other output device 1084 may be included to show information, such as sensor readings or actuator position. An input device 1086, such as a touch screen or keypad may be included to accept input. An output device 1084 may include any number of forms of audio or visual display, including simple visual outputs such as binary status indicators (e.g., light-emitting diodes (LEDs)) and multi-character visual outputs, or more complex outputs such as display screens (e.g., liquid crystal display (LCD) screens), with the output of characters, graphics, multimedia objects, and the like being generated or produced from the operation of the edge computing node 1050. A display or console hardware, in the context of the present system, may be used to provide output and receive input of an edge computing system; to manage components or services of an edge computing system; identify a state of an edge computing component or service, or to conduct any other number of management or administration functions or service use cases.” EN: binary status indicator leds are color coded to indicated the binary status. )
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Gabriel et al. (Arduino Uno, Ultrasonic Sensor HC-SR04 Motion Detector with Display of Distance in the LCD): discloses using color coded light to indicate distance/proximity.
Boopathy (US-20210217398-A1): Discloses active noise control with autonomous noise cancellation robots.
Koofman et al. (US-20220074820-A1): Discloses digital twin acoustic modeling.
Brown et al. (US-20120237049-A1): Discloses noise cancellation techniques in a networked setting.
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/A.E.D./Examiner, Art Unit 2199
/LEWIS A BULLOCK JR/Supervisory Patent Examiner, Art Unit 2199
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