DETAILED ACTION
A. This action is in response to the following communications: Transmittal of New Application filed 12/19/2023.
B. Claims 1-24 remains pending.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claims 1-24 are directed to a program per se as they are directed to safety device comprised of units, which as described in the specification can be mere software; a computer program per se is not included in one of the statutory categories of invention and is believed to be non-statutory, more information about this matter is covered in the Annex IV of the Interim Guidelines for Subject matter Eligibility.
http://www.uspto.gov/web/offices/pac/dapp/opla/preognotice/guidelines101_20051026.pdf
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) 1-24 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Sobol, Adam G. et al. (US Pub. 2023/0046739 A1), herein referred to as “Sobol”.
As for claim 1, Sobol teaches. A safety device for monitoring at least one machine, wherein the safety device has at least one sensor for generating sensor data on the machine and a processing unit for the sensor data that is connected at least indirectly to the sensor and to the machine (par. 94 FIG. 12 , the wearable electronic device 100 forms the basis for a scalable technology stack (also referred to herein as an IoT platform) that may be used as an enterprise platform, industrial control system or network, industrial analytics platform, data processing system, system for the performance management (including optimization) or related control of one or more IoT devices, process automation or the like to build systems with or manage the operation of various connected devices or assets (in either case, the so-called “smart devices” as previously discussed) and their applications within an industrial setting 3000; Examiner notes par. 46 states that it does not just have to be a wearable device such that sensors can be included inside or outside of the wearable devices such that they can be within other devices to monitor and the wearable device can interface with these devices; fig.12 provides detailed overview of this ideal scenario within an industrial environment),
that is configured as a performance environment having at least one computing node and if further configured to allow a plurality of logic units to run on the at least one computing node, wherein at least one logic unit is configured as a safety function unit for a safety directed evaluation of the sensor data (par. 37 a system 1 is shown in the form of a network-based or network-accessible computing platform configured to perform various data acquisition activities associated with the operation of a PAN P. In one form, system 1 may be referred to as a network-capable computing platform to perform software as a service (SaaS), cloud services, on-demand computing, platform computing, data center computing or the like. A wearable electronic device (also referred to herein as a source node) 100 is used as a central part of the PAN P and may be affixed to a wearer W so that data related to one or more of the wearer W location, environment, activity and physiological (LEAP) attributes may be collected by sensors S1, S2, S3 . . . Sn or other devices (collectively referred to as peripheral nodes or end nodes));
and at least one logic unit is configured as a diagnostic unit for monitoring the at least one safety function unit (par. 47 the sensors S1, S2, S3 . . . Sn form so-called “smart devices” in that they are made IoT-compatible through suitable RF connection such that data that they acquire may be conveyed based on certain triggering criteria. In one form, the acquired data may be conveyed based on triggering criteria established by logic contained within the sensors S1, S2, S3 . . . Sn or wearable electronic device 100, while in another form via logic contained within the gateway 300, servers 400 or cloud 500.),
wherein the at least one safety function unit is configured to transmit status reports and performance reports to the diagnostic unit (par. 35 a dashboard or other display-based approach may be used to provide various organization management functions. For example, when the organization is a place of employment, place of public accommodation, healthcare facility or other entity where groups of people can be expected to congregate, the dashboard may be made to provide notification functions, as well as the results of analytic-based assessments (such as those from one or more machine learning algorithms as is discussed in more detail herein), as a way to view organization-wide risks, create and track infection cases, send automatic messages (such as short message system (SMS), push or voice notifications), as well as—in the case of a healthcare facility—to manage staff, residents and visitors. In configurations where machine learning is being used to analyze data collected by the wearable electronic device and its associated PAN, one form involves using the machine learning model to evaluate a health condition of an individual being monitored) ; and
wherein the diagnostic unit is configured to recognize a safety related malfunction of the safety device in a status monitoring using a status from the status reports and in a performance monitoring using a performance routine from the performance reports (par. 44 bidirectional nature of the communication between the source and peripheral nodes 100, 200 may be used to conduct diagnostic tests, system information or related status updates for the various components that make up the PAN P, such as when such diagnostics, tests or status information is transmitted to the source node 100 from the one or more peripheral nodes 200. For example, an error code or an update (such as an update on the number of battery charge cycles or an indication that it is time for some predictive or preventative maintenance of a particular device) may be transmitted in order to allow machine code (such as that resident on the wearable electronic device 100) to conduct an analysis, prepare a report or the like.).
Also note in paragraph 108 Automatically collect data related to industrial or tactical assets and personnel that interact with such assets, as well as to automatically communicate the data over disparate wireless communication protocols and over different architectures of the communication network 4000. Another aspect is to analyze, report and—if necessary—act upon the collected data.
As for claim 2, Sobol teaches. The safety device in accordance with claim 1,
wherein the diagnostic unit is configured to determine in a situation related manner whether a malfunction is safety related (par. 97 examples of data collected including safety diagnostic data).
As for claim 3, Sobol teaches. The safety device in accordance with claim 1,
that has a shutdown unit that is configured to set the machine into a safe state at the instruction of the diagnostic unit in the case of a safety related malfunction or at the instruction of a safety function unit on recognition of a hazard situation with reference to the evaluated sensor data (par. 97 data that is acquired or generated by the field devices includes (but is not limited to) calibration data, control data, device identification data, diagnostic data, historical data, measurement data, parametric data, production data (such as quantities, qualities or throughput of manufactured goods), state data or the like.).
As for claim 4, Sobol teaches. The safety device in accordance with claim 1,
wherein the performance environment has a report system via which the at least one safety function unit transmits status reports and performance reports to the diagnostic unit (par. 108 Automatically collect data related to industrial or tactical assets and personnel that interact with such assets, as well as to automatically communicate the data over disparate wireless communication protocols and over different architectures of the communication network 4000. Another aspect is to analyze, report and—if necessary—act upon the collected data. ).
As for claim 5, Sobol teaches. The safety device in accordance with claim 4,
wherein the report system is formed with two report channels to transmit status reports and performance reports next to one another (par. 63 the hybrid wireless communication module 175).
As for claim 6, Sobol teaches. The safety device in accordance with claim 1,
wherein the at least one safety function unit is configured to regularly transmit a status report and/or to transmit a performance report on an event basis for a respective performance of its safety function (par. 97 data that is acquired or generated by the field devices includes (but is not limited to) calibration data, control data, device identification data, diagnostic data, historical data, measurement data, parametric data, production data (such as quantities, qualities or throughput of manufactured goods), state data or the like.).
As for claim 7, Sobol teaches. The safety device in accordance with claim 1,
wherein at least one of the status report and/or the performance report has a piece of transmitted information on the transmitting safety function unit (par. 44 the bidirectional nature of the communication between the source and peripheral nodes 100, 200 may be used to conduct diagnostic tests, system information or related status updates for the various components that make up the PAN P, such as when such diagnostics, tests or status information is transmitted to the source node 100 from the one or more peripheral nodes 200).
As for claim 8, Sobol teaches. The safety device in accordance with claim 7,
wherein the piece of transmitted information on the transmitting safety function unit comprises at least one of a time stamp, a sequence, and a checksum (par. 41 integrity of the data is required or otherwise important, data acquired by and contained by the peripheral node or nodes 200 may only be removed from its internal queue of data once the peripheral node has been assured from the source node 100 that the data has been correctly received and processed. Such assurance may use checksum or other suitable algorithms in responses from the source node 100 to the peripheral node 200 after data transmission.).
As for claim 9, Sobol teaches. The safety device in accordance with claim 1,
wherein the at least one safety function unit is configured for a self-diagnosis in which it checks its own data, programs, processing results, and/or the agreement with a system time (par. 41 integrity of the data is required or otherwise important, data acquired by and contained by the peripheral node or nodes 200 may only be removed from its internal queue of data once the peripheral node has been assured from the source node 100 that the data has been correctly received and processed. Such assurance may use checksum or other suitable algorithms in responses from the source node 100 to the peripheral node 200 after data transmission.).
As for claim 10, Sobol teaches. The safety device in accordance with claim 1,
wherein the diagnostic unit for the status monitoring is configured to invoke a specified status expectation for the statuses of the at least one safety function unit (par. 44 the bidirectional nature of the communication between the source and peripheral nodes 100, 200 may be used to conduct diagnostic tests, system information or related status updates for the various components that make up the PAN P, such as when such diagnostics, tests or status information is transmitted to the source node 100 from the one or more peripheral nodes 200. ).
As for claim 11, Sobol teaches. The safety device in accordance with claim 10,
wherein the diagnostic unit for the status monitoring is configured to invoke a specified status expectation for the statuses of the at least one safety function unit to modify the status expectation with reference to previous statuses, work routines, and/or work results of the logic units, and to compare the status expectation with a current overall status derived from the statuses of the status reports (par. 44 an error code or an update (such as an update on the number of battery charge cycles or an indication that it is time for some predictive or preventative maintenance of a particular device) may be transmitted in order to allow machine code (such as that resident on the wearable electronic device 100) to conduct an analysis, prepare a report or the like).
As for claim 12, Sobol teaches. The safety device in accordance with claim 1,
wherein the status report provides information on whether the safety function unit transmitting the status report exists, was able to initialize itself, all the required resources are available to it, and/or is operational (par. 44 self calibration tests of devices on IOT).
As for claim 13, Sobol teaches. The safety device in accordance with claim 1,
wherein the diagnostic unit for the performance monitoring is configured to invoke a specified performance expectation for the runtime routine of the at least one safety function unit (par. 44 an error code or an update (such as an update on the number of battery charge cycles or an indication that it is time for some predictive or preventative maintenance of a particular device) may be transmitted in order to allow machine code (such as that resident on the wearable electronic device 100) to conduct an analysis, prepare a report or the like.).
As for claim 14, Sobol teaches. The safety device in accordance with claim 13,
wherein the diagnostic unit for the performance monitoring is configured to invoke a specified performance expectation for the runtime routine of the at least one safety function unit to modify the performance expectation with reference to previous statuses, work routines, and/or work results of the logic units, and to compare the runtime expectation with the runtime routine derived from the performance reports (par. 109; fig. 12 industrial setting 3000 may be subjected to software that is performing a predictive maintenance solution in order to maintain or even improve the up-time of the various assets; par. 110 supplemented or supplanted by providing real-time, edge-based analytics and control over such equipment. Significantly, remote control or monitoring of connected assets may be implemented by using the LPWAN-based wireless communication capability of the wearable electronic device 100 (either in its mobile form or when some or all of its functionality, such as the wireless communication module 175) is physically affixed or otherwise associated with a particular connected piece of equipment, machinery or related asset… advantageous in industrial settings 3000 that may be inaccessible or otherwise present significant health or safety risks… freeing up PLCs from application-specific modes of operation, they become much simpler to modify in response to changes in equipment, process, manufacturing, production or other needs within the industrial setting 3000.).
As for claim 15, Sobol teaches. The safety device in accordance with claim 13,
wherein the diagnostic unit is configured to take at least one of the following criteria into account on an evaluation of the comparison of the runtime expectation with the runtime routine derived from the performance reports: a runtime order, the absence of a performance, an additional performance, a deviation of the runtimes from a time pattern, too short a performance duration, or too long a performance duration (par. 109-110 monitoring real-time data for predictive maintenance).
As for claim 16, Sobol teaches. The safety device in accordance with claim 1,
wherein the performance report has runtime information on the respective last performance of the safety function (par. 110 automating or otherwise performing an industrial process, the robotic equipment 3030 is responsive to control signals being provided by other equipment, such as the control equipment 3050 in general and one or more PLCs in particular. By way of example, this extends the connected device paradigm such that a mere on-premise mode of operation (such as a PLC providing direct control over one or more pieces of equipment such as a pump, valve, motor or—in the case of robotic equipment 3030—a robotic controller, robotic arms, servo driver and motor, imaging equipment or the like) is either supplemented or supplanted by providing real-time, edge-based analytics and control over such equipment. Significantly, remote control or monitoring of connected assets.).
As for claim 17, Sobol teaches. The safety device in accordance with claim 16,
wherein the performance report has runtime information on the respective last performance of the safety function, with a start time and/or performance duration (par. Par. 109-110 real-time information monitoring based upon preventative maintenance on historic data patterns and/or predictive maintenance).
As for claim 18, Sobol teaches. The safety device in accordance with claim 1,
wherein the performance environment has an aggregator that is logically arranged between the at least one safety function unit and the diagnostic unit and that is configured to receive the performance reports and to generate the runtime routine from them with an order and/or duration of the performances of the safety functions of the at least one safety function unit (par. 109 various connected devices within the industrial setting 3000 may be subjected to software that is performing a predictive maintenance solution in order to maintain or even improve the up-time of the various assets, equipment or the like; par. 112 Management and control of the various service layer functions, including data, event, resource and backup/security, may be used to permit application (or content) layer interfacing, analytics and decision-making… the communication network 4000 that is centered around the wearable electronic device 100 is configured (that is to say, designed or constructed to be used in a particular machine, component, piece of equipment or related asset within the industrial setting 3000 in a particular way) to provide the data required to allow timely decision-making about a particular asset, process and related operations by promoting edge, cloud (whether public or private, including architectures involving the use of multiple clouds) or facility-based networking and database management of such operations.).
As for claim 19, Sobol teaches. The safety device in accordance with claim 1,
wherein the performance environment has an aggregator that is logically arranged between the at least one safety function unit and the diagnostic unit and that is configured to receive the performance reports and to generate the runtime routine from them with an order and/or duration of the performances of the safety functions of the at least one safety function unit in real time (par. 109-112 environment for collecting industrial machine data from sensors for aggregation to decide on safety predictively for multiple industrial machines being monitored to change settings based upon analytics of collected data).
As for claim 20, Sobol teaches. The safety device in accordance with claim 1,
wherein the at least one sensor is configured as an optoelectronic sensor or as a process parameter sensor (par. 112 process settings from sensor readouts based upon data analytics from said retrieved data).
As for claim 21, Sobol teaches. The safety device in accordance with claim 20,
wherein the optoelectronic sensor is one of a light barrier, light sensor, light grid, laser scanner, FMCW LIDAR, or camera, as an ultrasound sensor, inertia sensor, capacitive sensor, magnetic sensor, inductive sensor, and an UWB sensor (par. 134 sensors S1, S2, S3 . . . Sn, as well as be in other common form factors such as meters, gauges or other such data-gathering means known to be used in industrial environments as a way to measure temperatures, pressures, flows and flow rates, positions, power, motion, acceleration, proximity, visual images—including those used for subsequent image processing and related process control—or the like)..
As for claim 22, Sobol teaches. The safety device in accordance with claim 20,
wherein the process parameter sensor is one of a temperature sensor, throughflow sensor, filling level sensor, and a pressure sensor (par. 134 sensors S1, S2, S3 . . . Sn, as well as be in other common form factors such as meters, gauges or other such data-gathering means known to be used in industrial environments as a way to measure temperatures, pressures, flows and flow rates, positions, power, motion, acceleration, proximity, visual images—including those used for subsequent image processing and related process control—or the like)..
As for claim 23, Sobol teaches. The safety device in accordance with claim 20,
wherein the safety device has a plurality of the same or different sensors (par. 134 sensors S1, S2, S3 . . . Sn, as well as be in other common form factors such as meters, gauges or other such data-gathering means known to be used in industrial environments as a way to measure temperatures, pressures, flows and flow rates, positions, power, motion, acceleration, proximity, visual images—including those used for subsequent image processing and related process control—or the like)..
As for claim 24, Sobol teaches. A computer implemented method of monitoring at least one machine in which at least one sensor generates sensor data on the machine and a processing unit for the sensor data that is connected at least indirectly to the sensor (par. 94 FIG. 12 , the wearable electronic device 100 forms the basis for a scalable technology stack (also referred to herein as an IoT platform) that may be used as an enterprise platform, industrial control system or network, industrial analytics platform, data processing system, system for the performance management (including optimization) or related control of one or more IoT devices, process automation or the like to build systems with or manage the operation of various connected devices or assets (in either case, the so-called “smart devices” as previously discussed) and their applications within an industrial setting 3000) and to the machine as a performance environment allows a plurality of logic units to run on at least one computing node (par. 47 the sensors S1, S2, S3 . . . Sn form so-called “smart devices” in that they are made IoT-compatible through suitable RF connection such that data that they acquire may be conveyed based on certain triggering criteria. In one form, the acquired data may be conveyed based on triggering criteria established by logic contained within the sensors S1, S2, S3 . . . Sn or wearable electronic device 100, while in another form via logic contained within the gateway 300, servers 400 or cloud 500.);
wherein at least one logic unit as a safety function unit evaluates the sensor data in a safety related manner and at least one logic unit as a diagnostic unit monitors the at least one safety function unit (par. 35 a dashboard or other display-based approach may be used to provide various organization management functions. For example, when the organization is a place of employment, place of public accommodation, healthcare facility or other entity where groups of people can be expected to congregate, the dashboard may be made to provide notification functions, as well as the results of analytic-based assessments (such as those from one or more machine learning algorithms as is discussed in more detail herein), as a way to view organization-wide risks, create and track infection cases, send automatic messages (such as short message system (SMS), push or voice notifications), as well as—in the case of a healthcare facility—to manage staff, residents and visitors. In configurations where machine learning is being used to analyze data collected by the wearable electronic device and its associated PAN, one form involves using the machine learning model to evaluate a health condition of an individual being monitored);
wherein the at least one safety function unit transmits status reports and performance reports to the diagnostic unit; and wherein the diagnostic unit recognizes a safety related malfunction in a status monitoring using statuses from the status reports and in a performance monitoring using the performance routine from the performance reports (par. 44 bidirectional nature of the communication between the source and peripheral nodes 100, 200 may be used to conduct diagnostic tests, system information or related status updates for the various components that make up the PAN P, such as when such diagnostics, tests or status information is transmitted to the source node 100 from the one or more peripheral nodes 200. For example, an error code or an update (such as an update on the number of battery charge cycles or an indication that it is time for some predictive or preventative maintenance of a particular device) may be transmitted in order to allow machine code (such as that resident on the wearable electronic device 100) to conduct an analysis, prepare a report or the like.).
(Note :) It is noted that any citation to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006,1009, 158 USPQ 275, 277 (CCPA 1968)).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
APPARATUS AND CONTROL METHOD FOR A HYBRID TANKLESS WATER HEATER
Document ID
US 20130312671 A1
Date Published
2013-11-28
Abstract
An on demand tankless water heater system that is capable of quickly delivering water within a desired temperature range. The tankless water heater provides a hybrid heating method that contains a primary heating system and a secondary heating system disposed in a buffer tank that cooperate to facilitate control of output water temperature during water usage. A pressure differential switch detects low flow demand and allows the secondary heating system to provide immediate heating to the water. This secondary heating system provides a faster temperature response and fine tuning of output water temperature.
NON-INTRUSIVE SENSOR SYSTEM
Document ID
US 20150094988 A1
Date Published
2015-04-02
Abstract
A non-intrusive sensor system includes an array of sensors disposed in a process to measure various input process phenomena and a logic unit that analyses the sensor measurements using an empirical model to produce an estimate of a further process phenomenon not measured directly by any of the array of sensors. The sensors within the array of sensors may be non-intrusive sensors that measure input process phenomena in an intrusive or non-intrusive manner but are non-intrusive with respect to the output process phenomenon as none of these sensors comes into direct contact with the process fluid or process element exhibiting the output process phenomenon. The sensors within the array of sensors can be any type of sensors that produce a measurement of a particular process phenomenon at the same or at different locations within a process.
Inquires
Any inquiry concerning this communication should be directed to NICHOLAS AUGUSTINE at telephone number (571)270-1056.
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.
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/NICHOLAS AUGUSTINE/Primary Examiner, Art Unit 2178 February 11, 2026