DETAILED ACTION
This Office action is in response to the original application filed on 10/27/2023.
Claims 1-4, 8-15, 17, and 31-37 are pending.
Claims 1-4, 8-15, 17, and 31-37 are rejected.
Notice of 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 .
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 10/27/2023 was filed prior to this Office action. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) is/are being considered by the examiner.
Claim Objections
Claim 15 recites “a wearable device” twice. The second recitation should likely recite “the wearable device.”
Appropriate correction is required.
Statutory Review under 35 USC § 101
Claims 1-4 and 8-10 are directed towards a method and have been reviewed.
Claims 1-4 and 8-10 appear to not be patent-eligible subject matter based on the evaluation of patent subject matter eligibility.
Claims 11-15 are directed towards a method and have been reviewed.
Claims 11-15 appear to not be patent-eligible subject matter based on the patent subject matter eligibility determination.
Claims 31-37 are directed toward a system and have been reviewed.
Claims 31-37 initially appear to be statutory, as the system includes hardware (at least one processor) as disclosed in ¶ 0058 of the applicant’s specification, “the processor may be a general purpose processor, such as a central processing unit (CPU) or a processor dedicated to a specific purpose, such as a digital signal processor (DSP).”
However, claims 31-37 appear to not be patent-eligible subject matter based on the evaluation of patent subject matter eligibility.
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.
(I)
Claims 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 recites assigning the second label to the second data point and determining that an event has occurred at a third time, which is a mental process (including an observation, evaluation, judgment, opinion).
Step 2A, Prong Two
This judicial exception of assigning the second label to the second data point and determining that an event has occurred at a third time is not integrated into a practical application despite the generically recited computer elements shown below:
a device
a first user interface
The generically recited computer elements amount to implementing the abstract idea on a computer, merely using a computer as a tool to perform an abstract idea, or generally linking the use of a judicial exception to a particular technological environment or field of use as seen below.
outputting a first user interface indicating that an event has occurred;
These additional elements are mere generic transmission and presentation of collected and analyzed data which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
receiving, by the device at a first time, first input corresponding to a first label;
receiving, by the device at a second time, second input;
receiving user input indicating a second label for the second time;
receiving, via the first user interface, a third label corresponding to the event;
These additional elements are mere data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception despite the additional elements shown below:
recording, by a device, data corresponding to an individual;
storing a first data point,
storing a second data point,
storing a third data point,
storing the dataset of labelled data points comprising the first data point, the second data point, and the third data point.
These elements store and retrieve information in memory, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d).
receiving, by the device at a first time, first input corresponding to a first label;
receiving, by the device at a second time, second input;
receiving user input indicating a second label for the second time;
receiving, via the first user interface, a third label corresponding to the event;
This performs receiving or transmitting data over a network, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d), specifically MPEP § 2106.05(d)(II)(i).
outputting a first user interface indicating that an event has occurred;
This additional element performs gathering and analyzing information using conventional techniques and displaying the result, which is considered to not be sufficient to show improvement to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)).
Claim 2 describes training a machine learning algorithm based on the dataset,
This additional element merely uses a computer as a tool to perform an abstract idea (see MPEP 2160.05(f)).
Claim 3 describes outputting a second user interface and receiving an indication that the individual has consented.
This additional element performs gathering and analyzing information using conventional techniques and displaying the result, which is considered to not be sufficient to show improvement to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)).
Claim 4 describes recording the data by a micro electro-mechanical system (MEMS), acoustic sensor, electrodermal activity sensor, and heart rate sensor in the device.
This claim stores and retrieves information in memory, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d).
Claim 8 describes encrypting and transmitting the encrypted dataset, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d), specifically MPEP § 2106.05(d)(II)(i).
Claim 9 describes recording second data corresponding to the individual.
This claim stores and retrieves information in memory, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d).
Claim 10 specifies that the device is a wearable device, which does no more than to generally link the use of a judicial exception to a particular technological environment or field of use (see MPEP 2160.05(h)).
(II)
Claims 11-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 11 recites assigning the second label to the second data point, which is a mental process (including an observation, evaluation, judgment, opinion).
Step 2A, Prong Two
This judicial exception of assigning the second label to the second data point is not integrated into a practical application despite the generically recited computer elements shown below:
a processor of a computer system,
The generically recited computer elements amount to implementing the abstract idea on a computer, merely using a computer as a tool to perform an abstract idea, or generally linking the use of a judicial exception to a particular technological environment or field of use as seen below.
the method being executable by a processor of a computer system,
generating, based on the responses, a third data point comprising a third label;
The generically recited computer element amounts to merely using a computer as a tool to perform an abstract idea (see MPEP 2160.05(f)).
receiving, at a first time, first input corresponding to a first label;
receiving, at a second time, second input indicating that an event is occurring;
receiving, after receiving the second input, third input
receiving responses to a questionnaire completed by an individual;
These additional elements are mere data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception despite the additional elements shown below:
storing a first data point,
storing a second data point
storing a dataset comprising the first data point, the second data point, and the third data point.
These elements store and retrieve information in memory, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d).
receiving, at a first time, first input corresponding to a first label;
receiving, at a second time, second input indicating that an event is occurring;
receiving, after receiving the second input, third input
receiving responses to a questionnaire completed by an individual;
This performs receiving or transmitting data over a network, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d), specifically MPEP § 2106.05(d)(II)(i).
generating, based on the responses, a third data point comprising a third label;
This additional element performs part of gathering and analyzing information using conventional techniques and displaying the result, which is considered to not be sufficient to show improvement to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)).
Claim 12 describes performing semi-supervised learning to generate a machine learning algorithm, which does no more than to generally link the use of a judicial exception to a particular technological environment or field of use (see MPEP 2160.05(h)).
Claim 13:
receiving physiological data corresponding to the individual;
This additional element is mere data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
determining, based on the physiological data, a third timestamp corresponding to an event;
This is a mental process (including an observation, evaluation, judgment, opinion).
generating, by the MLA, one or more predicted labels for the third timestamp;
generating a fourth data point comprising the third timestamp and the one or more predicted labels; and
The generically recited computer elements amount to merely using a computer as a tool to perform an abstract idea (see MPEP 2160.05(f)).
storing the fourth data point in the dataset.
These elements store and retrieve information in memory, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d).
Claim 14 describes outputting a user interface for labelling data and receiving input via the user interface.
These additional elements are gathering and analyzing information using conventional techniques and displaying the result, which is considered to not be sufficient to show improvement to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)).
Claim 15 specifies that the receipt of data is performed via wearable device, which does no more than to generally link the use of a judicial exception to a particular technological environment or field of use (see MPEP 2160.05(h)).
(II)
Claims 31-37 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 31 recites assigning the second label to the second data point and determining that an event has occurred at a third time, which is a mental process (including an observation, evaluation, judgment, opinion).
Step 2A, Prong Two
This judicial exception of assigning the second label to the second data point and determining that an event has occurred at a third time is not integrated into a practical application despite the generically recited computer elements shown below:
a wearable device
at least one processor
The generically recited computer elements amount to implementing the abstract idea on a computer, merely using a computer as a tool to perform an abstract idea, or generally linking the use of a judicial exception to a particular technological environment or field of use as seen below.
A wearable device … a plurality of executable instructions which, when executed by the at least one processor, cause the wearable device to:
The generically recited computer element amounts to merely using a computer as a tool to perform an abstract idea (see MPEP 2160.05(f)).
receive, at a first time, first input corresponding to a first label;
receive, at a second time, second input;
receive user input indicating a second label for the second time;
receive a third label corresponding to the event;
These additional elements are mere data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception despite the additional elements shown below:
memory storing a plurality of executable instructions
record data corresponding to an individual;
store a first data point,
store a second data point,
store a third data point,
store the dataset of labelled data points comprising the first data point, the second data point, and the third data point.
These elements store and retrieve information in memory, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d).
receive, at a first time, first input corresponding to a first label;
receive, at a second time, second input;
receive user input indicating a second label for the second time;
receive a third label corresponding to the event;
This performs receiving or transmitting data over a network, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d), specifically MPEP § 2106.05(d)(II)(i).
Claims 32-33 describe encrypting and transmitting the encrypted dataset, which are well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP § 2106.05(d), specifically MPEP § 2106.05(d)(II)(i).
Claims 34 and 36-37 provide further detail on the wearable device, which does no more than to generally link the use of a judicial exception to a particular technological environment or field of use (see MPEP 2160.05(h)).
Claims 35 describes collecting the data by a micro electro-mechanical system (MEMS), acoustic sensor, electrodermal activity sensor, and heart rate sensor in the device, mere data gathering which is considered to be insignificant extra solution activity (MPEP 2106.05(g)).
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 11 and 14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by McGranahan et al., U.S. Patent Application Publication No. 2019/0163848 (hereinafter McGranahan).
Regarding claim 11, McGranahan teaches:
A method for generating a dataset of labelled data points, the method being executable by a processor of a computer system, the method comprising: (McGranahan ¶ 0088: Users and end-customers use the mobile application labeling mechanism to tag events as they occur in real-time, and use the website to retroactively tag historical events; McGranahan ¶ 0111: The processes and logic flows described herein can be performed by one or more programmable processors executing one or more computer programs to perform actions by operating on input information/data and generating output)
receiving, at a first time, first input corresponding to a first label; (McGranahan ¶ 0067-0068: A real-time user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment in real-time (e.g., as data is collected). The user indicates the labeling by choosing the equipment or statistical model that is being labeled, and pressing a button on a PC-based, web-based, or mobile-based tool interface when the event begins, completes, or is active. The user also adds additional context information to the label)
storing a first data point, wherein the first data point comprises a first timestamp indicating the first time and the first label; (McGranahan ¶ 0123: collecting data corresponding to equipment performance of a monitored device from one or more data sources including an adaptive sensing coordinator, cataloging the data, and characterizing and tracking the operation of the monitored device based at least on the data and statistical models based on the data and historical data ... the data is stored in a repository; McGranahan ¶ 0124-0126, see ¶ 0124: cataloging the data comprises associating the data with the monitored device, equipment type, measurement type, time of collection and the operation of the equipment at the time of collection; see McGranahan ¶ 0126: an association, or label, is assigned between a real-world event and data related to a monitored device under monitoring by a labeling mechanism … the association or labeling occurs in real-time as data is collected)
receiving, at a second time, second input indicating that an event is occurring; (McGranahan ¶ 0067-0068: A real-time user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment in real-time (e.g., as data is collected). The user indicates the labeling by choosing the equipment or statistical model that is being labeled, and pressing a button on a PC-based, web-based, or mobile-based tool interface when the event begins, completes, or is active. The user also adds additional context information to the label; see also McGranahan addressing "second time" and "second input" as claimed in at least FIG. 8, ¶ 0077-0078: A mobile-based labeling mechanism 800 is used to label events occurring in real-time ... In real-time, the label start/stop button 803 [should say 903] is used to label events and states of the equipment ... When near the refrigerator, the ‘Refrigerator Door Open’ label is selected, and the ‘Start’ button is pressed at the same time the refrigerator door is opened. The ‘Stop’ button is then pressed at the same time the refrigerator door is closed. This can be repeated multiple times as needed to build a complete model)
storing a second data point comprising a second timestamp indicating the second time; (McGranahan shows a plurality of data points in at least FIG. 8, ¶ 0077: In real-time, the label start/stop button 803 is used to label events and states of the equipment; McGranahan describes storage in ¶ 0123: collecting data corresponding to equipment performance of a monitored device from one or more data sources including an adaptive sensing coordinator, cataloging the data, and characterizing and tracking the operation of the monitored device based at least on the data and statistical models based on the data and historical data ... the data is stored in a repository; McGranahan shows timestamps in at least ¶ 0124-0126, see ¶ 0124: cataloging the data comprises associating the data with the monitored device, equipment type, measurement type, time of collection and the operation of the equipment at the time of collection)
receiving, after receiving the second input, third input indicating a second label corresponding to the event; [and] assigning the second label to the second data point; (McGranahan ¶ 0067-0068: A real-time user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment in real-time (e.g., as data is collected). The user indicates the labeling by choosing the equipment or statistical model that is being labeled, and pressing a button on a PC-based, web-based, or mobile-based tool interface when the event begins, completes, or is active. The user also adds additional context information to the label; see also McGranahan ¶ 0126: an association, or label, is assigned between a real-world event and data related to a monitored device under monitoring by a labeling mechanism … the association or labeling occurs in real-time as data is collected ... assigning an association or labeling further comprises receiving additional context information from the user ... assigning an association or labeling occurs after data is collected in a historical user mode of the labeling mechanism ... the labeling mechanism prompts users to confirm, reject, or correct an automatically generated label suggestion)
receiving responses to a questionnaire completed by an individual; (McGranahan ¶ 0087-0091: Users and end-customers … use the website to retroactively tag historical events; see also McGranahan ¶ 0126: assigning an association or labeling includes prompting a user to choose the equipment or statistical model that is being labeled or assigned an association, receiving the user's equipment or statistical model selection, and receiving the user's indication of event begins, completes, or is active ... assigning an association or labeling occurs after data is collected in a historical user mode of the labeling mechanism; see also McGranahan ¶ 0068: A historical user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment that have occurred in the past (e.g., not in real-time). The user indicates this labeling by choosing the equipment or statistical model that is being labeled on a PC-based, web-based, or mobile-based tool interface)
generating, based on the responses, a third data point comprising a third label; and (McGranahan ¶ 0126: assigning an association or labeling includes prompting a user to choose the equipment or statistical model that is being labeled or assigned an association, receiving the user's equipment or statistical model selection, and receiving the user's indication of event begins, completes, or is active ... assigning an association or labeling occurs after data is collected in a historical user mode of the labeling mechanism; see also McGranahan ¶ 0068: A historical user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment that have occurred in the past (e.g., not in real-time). The user indicates this labeling by choosing the equipment or statistical model that is being labeled on a PC-based, web-based, or mobile-based tool interface; see also McGranahan FIG. 9, ¶ 0079: A web-based historical labeling mechanism 1000 is used to label events that have occurred in the past ... a piece of equipment is selected, and a data type is optionally selected 1001. A label is then selected or entered 1002. Labels are then added by aligning the appropriate start-stop times with the shown data 1003)
storing a dataset comprising the first data point, the second data point, and the third data point. (McGranahan shows storage in ¶ 0123: collecting data corresponding to equipment performance of a monitored device from one or more data sources including an adaptive sensing coordinator, cataloging the data, and characterizing and tracking the operation of the monitored device based at least on the data and statistical models based on the data and historical data ... the statistical models are built and altered via a training function ... the data is stored in a repository; see McGranahan addressing the first and second data points through ¶ 0124 and ¶ 0126: cataloging the data comprises associating the data with the monitored device, equipment type, measurement type, time of collection and the operation of the equipment at the time of collection ... the association or labeling occurs in real-time as data is collected; see then McGranahan addressing the third data point through ¶ 0126: assigning an association or labeling includes prompting a user to choose the equipment or statistical model that is being labeled or assigned an association, receiving the user's equipment or statistical model selection, and receiving the user's indication of event begins, completes, or is active ... assigning an association or labeling occurs after data is collected in a historical user mode of the labeling mechanism)
Regarding claim 14, McGranahan teaches:
outputting a user interface for labelling data, (McGranahan ¶ 0031: The input/output circuitry 203 may comprise a user interface and may include a display and may comprise a web user interface, a mobile application, a client device, a kiosk, or the like)
and wherein the first input, second input, and third input are received via the user interface. (McGranahan ¶ 0067-0068, see first ¶ 0067: A real-time user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment in real-time (e.g., as data is collected). The user indicates the labeling by choosing the equipment or statistical model that is being labeled, and pressing a button on a PC-based, web-based, or mobile-based tool interface when the event begins, completes, or is active; McGranahan ¶ 0068: A historical user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment that have occurred in the past (e.g., not in real-time). The user indicates this labeling by choosing the equipment or statistical model that is being labeled on a PC-based, web-based, or mobile-based tool interface)
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 1-2, 9-10; 31, and 33 are rejected under 35 U.S.C. 103 as being unpatentable over McGranahan in view of Hofshi, U.S. Patent Application Publication No. 2012/0194648 (hereinafter Hofshi).
Regarding claim 1, McGranahan teaches:
A method for generating a dataset of labelled data points, the method comprising: (McGranahan ¶ 0088: Users and end-customers use the mobile application labeling mechanism to tag events as they occur in real-time, and use the website to retroactively tag historical events)
recording, by a device, data… (McGranahan FIG. 2, ¶ 0038: The adaptive sensing coordinator 310 incorporates any number of raw sensor types. The sensors are either embedded in the coordinator 310 or connected to the coordinator 310 via a wired or wireless network. In the preferred embodiment, the coordinator 310 records the following measurements; see also McGranahan ¶ 0049: during a server operational function 324, data 305 is received by the server 106 and is stored by a database with a reference to the asset (i.e., piece of equipment under measure 101A-101N), asset type, measurement type(s), time of collection and any known information on the operation of the equipment at the given time. This allows the creation and generation of a database of collected sensor data 301 for the given coordinator 310)
receiving, by the device at a first time, first input corresponding to a first label; (McGranahan ¶ 0067-0068: A real-time user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment in real-time (e.g., as data is collected). The user indicates the labeling by choosing the equipment or statistical model that is being labeled, and pressing a button on a PC-based, web-based, or mobile-based tool interface when the event begins, completes, or is active. The user also adds additional context information to the label)
storing a first data point, wherein the first data point comprises: (McGranahan ¶ 0123: collecting data corresponding to equipment performance of a monitored device from one or more data sources including an adaptive sensing coordinator, cataloging the data, and characterizing and tracking the operation of the monitored device based at least on the data and statistical models based on the data and historical data ... the statistical models are built and altered via a training function ... the data is stored in a repository)
a first timestamp corresponding to the first time, the first label, and a first portion of the data corresponding to the first time; (McGranahan ¶ 0124-0126, see ¶ 0124: cataloging the data comprises associating the data with the monitored device, equipment type, measurement type, time of collection and the operation of the equipment at the time of collection; see McGranahan ¶ 0126: an association, or label, is assigned between a real-world event and data related to a monitored device under monitoring by a labeling mechanism … the association or labeling occurs in real-time as data is collected)
receiving, by the device at a second time, second input; (McGranahan ¶ 0067-0068: A real-time user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment in real-time (e.g., as data is collected). The user indicates the labeling by choosing the equipment or statistical model that is being labeled, and pressing a button on a PC-based, web-based, or mobile-based tool interface when the event begins, completes, or is active. The user also adds additional context information to the label; see also McGranahan addressing "second time" and "second input" as claimed in at least FIG. 8, ¶ 0077-0078: A mobile-based labeling mechanism 800 is used to label events occurring in real-time ... In real-time, the label start/stop button 803 is used to label events and states of the equipment ... When near the refrigerator, the ‘Refrigerator Door Open’ label is selected, and the ‘Start’ button is pressed at the same time the refrigerator door is opened. The ‘Stop’ button is then pressed at the same time the refrigerator door is closed. This can be repeated multiple times as needed to build a complete model)
storing a second data point, wherein the second data point comprises: (McGranahan shows a plurality of data points in at least FIG. 8, ¶ 0077: In real-time, the label start/stop button 803 is used to label events and states of the equipment; McGranahan describes storage in ¶ 0123: collecting data corresponding to equipment performance of a monitored device from one or more data sources including an adaptive sensing coordinator, cataloging the data, and characterizing and tracking the operation of the monitored device based at least on the data and statistical models based on the data and historical data ... the data is stored in a repository;)
a second timestamp corresponding to the second time, and a second portion of the data corresponding to the second time; (McGranahan shows timestamps in at least ¶ 0124-0126, see ¶ 0124: cataloging the data comprises associating the data with the monitored device, equipment type, measurement type, time of collection and the operation of the equipment at the time of collection; see McGranahan ¶ 0126: an association, or label, is assigned between a real-world event and data related to a monitored device under monitoring by a labeling mechanism … the association or labeling occurs in real-time as data is collected)
receiving user input indicating a second label for the second time; [and] assigning the second label to the second data point; (McGranahan ¶ 0067-0068: A real-time user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment in real-time (e.g., as data is collected). The user indicates the labeling by choosing the equipment or statistical model that is being labeled, and pressing a button on a PC-based, web-based, or mobile-based tool interface when the event begins, completes, or is active. The user also adds additional context information to the label; see also McGranahan ¶ 0126: an association, or label, is assigned between a real-world event and data related to a monitored device under monitoring by a labeling mechanism … the association or labeling occurs in real-time as data is collected ... assigning an association or labeling further comprises receiving additional context information from the user ... assigning an association or labeling occurs after data is collected in a historical user mode of the labeling mechanism ... the labeling mechanism prompts users to confirm, reject, or correct an automatically generated label suggestion)
determining, based on the data, that an event has occurred at a third time; (McGranahan FIG. 6, ¶ 0072: The anomaly is detected 710 and a label is generated for the anomaly 701; see also McGranahan ¶ 0124-0125: cataloging the data comprises associating the data with the monitored device, equipment type, measurement type, time of collection and the operation of the equipment at the time of collection ... the event is one or more of a detected anomaly, a set of readings that does not match an existing operational state, entering or exiting of a known state, and the application of a heuristic condition ... the heuristic conditions are configurable to detect specific events of interest including voltage or current specific limits which, when crossed, resulting in triggering a notification to a user)
outputting a first user interface indicating that an event has occurred; (McGranahan FIG. 6, ¶ 0072: The anomaly is detected 710 and a label is generated for the anomaly 701. A user is able to confirm or correct the anomaly 720 (see 702) with the labeling mechanism 740; see also McGranahan ¶ 0125: a user is notified of an equipment event ... the event is one or more of a detected anomaly, a set of readings that does not match an existing operational state, entering or exiting of a known state, and the application of a heuristic condition ... the heuristic conditions are configurable to detect specific events of interest including voltage or current specific limits which, when crossed, resulting in triggering a notification to a user)
receiving, via the first user interface, a third label corresponding to the event; (McGranahan ¶ 0087-0091: Users and end-customers … use the website to retroactively tag historical events; see also McGranahan ¶ 0126: assigning an association or labeling occurs after data is collected in a historical user mode of the labeling mechanism ... the labeling mechanism prompts users to confirm, reject, or correct an automatically generated label suggestion; see also McGranahan ¶ 0068: A historical user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment that have occurred in the past (e.g., not in real-time). The user indicates this labeling by choosing the equipment or statistical model that is being labeled on a PC-based, web-based, or mobile-based tool interface; see also McGranahan FIG. 9, ¶ 0079: A web-based historical labeling mechanism 1000 is used to label events that have occurred in the past ... a piece of equipment is selected, and a data type is optionally selected 1001. A label is then selected or entered 1002. Labels are then added by aligning the appropriate start-stop times with the shown data 1003)
storing a third data point, wherein the third data point comprises: (McGranahan FIG. 9, ¶ 0079-0081: A web-based historical labeling mechanism 1000 is used to label events that have occurred in the past ... This can be repeated multiple times as needed for various labels, time ranges, equipment types, etc. as needed to build a complete model ... This vastly increases the ease of labeling data and increases the amount of labeled data available to the statistical models; McGranahan describes storage in ¶ 0123: collecting data corresponding to equipment performance of a monitored device from one or more data sources including an adaptive sensing coordinator, cataloging the data, and characterizing and tracking the operation of the monitored device based at least on the data and statistical models based on the data and historical data ... the data is stored in a repository;)
a third timestamp corresponding to the third time, the third label, and a third portion of the data corresponding to the event; and (McGranahan shows timestamps in at least ¶ 0124-0126, see ¶ 0124: cataloging the data comprises associating the data with the monitored device, equipment type, measurement type, time of collection and the operation of the equipment at the time of collection; see McGranahan ¶ 0126: assigning an association or labeling occurs after data is collected in a historical user mode of the labeling mechanism ... the labeling mechanism prompts users to confirm, reject, or correct an automatically generated label suggestion)
storing the dataset of labelled data points comprising the first data point, the second data point, and the third data point. (McGranahan shows storage in ¶ 0123: collecting data corresponding to equipment performance of a monitored device from one or more data sources including an adaptive sensing coordinator, cataloging the data, and characterizing and tracking the operation of the monitored device based at least on the data and statistical models based on the data and historical data ... the statistical models are built and altered via a training function ... the data is stored in a repository; see McGranahan addressing the first and second data points through ¶ 0124 and ¶ 0126: cataloging the data comprises associating the data with the monitored device, equipment type, measurement type, time of collection and the operation of the equipment at the time of collection ... the association or labeling occurs in real-time as data is collected; see then McGranahan addressing the third data point through ¶ 0125-0126: the heuristic conditions are configurable to detect specific events of interest including voltage or current specific limits which, when crossed, resulting in triggering a notification to a user ... assigning an association or labeling occurs after data is collected in a historical user mode of the labeling mechanism ... the labeling mechanism prompts users to confirm, reject, or correct an automatically generated label suggestion)
McGranahan does not expressly disclose data corresponding to an individual.
However, Hofshi addresses this by teaching data corresponding to an individual. (Hofshi ¶ 0014: The EI apparatus receives indications of the emotional state of a user of the V/A device by measuring changes in his or her physiological characteristics, such as, heart rate, peripheral vasoconstriction (SCA), electro dermal activity (EDA), galvanic skin response (GSR), etc.)
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 sensor functionality of McGranahan with the sensor functionality of Hofshi.
In addition, both of the references (McGranahan and Hofshi) disclose features that are directed to analogous art, and they are directed to the same field of endeavor, such as operating over received sensor data.
Motivation to do so would be to improve the functioning of McGranahan performing operations over received sensor data with the ability in similar reference Hofshi to perform operations over received sensor data but with the improvement of manipulating the presentation of data in response to received sensor data associated with an individual.
Regarding claim 2, McGranahan in view of Hofshi teaches:
training a machine learning algorithm based on the dataset. (McGranahan FIG. 5, ¶ 0055: Statistical models 630 are created for a specific type of equipment (received and processed by sensor coordinator 620) and are used by the server 106 to interpret incoming and historical data for a specific piece of equipment (under measure, e.g., 101A-101N, not shown). The models 630 are created and improved using the server's 106 training function 622 and a labeling mechanism 640; see also relevant McGranahan ¶ 0058-0062: These heuristics can be selected and configured by users to tailor the statistical model to the user's understanding of normal and abnormal equipment operation and utilization ... With the supervised learning methods, a labeling mechanism 640 is used with the server training function 122 to build a statistical model 630 that includes identification of labeled states and events)
Regarding claim 9, McGranahan in view of Hofshi teaches all the features with respect to claim 1 above.
McGranahan teaches:
recording, by a second device, second data… wherein the first data point comprises a first portion of the second data corresponding to the first time, wherein the second data point comprises a second portion of the second data corresponding to the second time, (McGranahan ¶ 0049: during a server operational function 324, data 305 is received by the server 106 and is stored by a database with a reference to the asset (i.e., piece of equipment under measure 101A-101N), asset type, measurement type(s), time of collection and any known information on the operation of the equipment at the given time. This allows the creation and generation of a database of collected sensor data 301 for the given coordinator 310. The database is used to establish a baseline of operation for the equipment over time; McGranahan ¶ 0124-0126, see ¶ 0124: cataloging the data comprises associating the data with the monitored device, equipment type, measurement type, time of collection and the operation of the equipment at the time of collection)
and wherein the third data point comprises a third portion of the second data corresponding to the third time. (McGranahan ¶ 0091: Users and end-customers ... use the website to retroactively tag historical events; McGranahan ¶ 0124: cataloging the data comprises associating the data with the monitored device, equipment type, measurement type, time of collection and the operation of the equipment at the time of collection; see McGranahan ¶ 0126: assigning an association or labeling occurs after data is collected in a historical user mode of the labeling mechanism ... the labeling mechanism prompts users to confirm, reject, or correct an automatically generated label suggestion)
Hofshi teaches second data corresponding to the individual. (Hofshi ¶ 0014: The EI apparatus receives indications of the emotional state of a user of the V/A device by measuring changes in his or her physiological characteristics, such as, heart rate, peripheral vasoconstriction (SCA), electro dermal activity (EDA), galvanic skin response (GSR), etc.; Hofshi ¶ 0022-0023: As user 106 watches a movie or plays a game provided by computer 105, EI apparatus 102 may modify progress of the movie or the game in accordance with the determined emotional state of user 106 ... processing the physiological and/or image data may include calculating an average of physiological measurements taken over time, and/or by calculating a standard deviation, thereof)
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 sensor functionality of McGranahan with the sensor functionality of Hofshi.
Motivation to do so would be to improve the functioning of McGranahan performing operations over received sensor data with the ability in similar reference Hofshi to perform operations over received sensor data but with the improvement of manipulating the presentation of data in response to received sensor data associated with an individual.
Regarding claim 10, McGranahan in view of Hofshi teaches:
wherein the device is a wearable device. (Hofshi claim 16: Apparatus for interfacing a user with V/A material, the apparatus comprising: a wearable sensor that generates signals responsive to a physiological parameter of a user wearing the housing)
Regarding claim 31, McGranahan teaches:
A … device comprising at least one processor, and memory storing a plurality of executable instructions which, when executed by the at least one processor, cause the … device to: (McGranahan ¶ 0111: a processor will receive instructions and information/data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data)
record data… (McGranahan FIG. 2, ¶ 0038: The adaptive sensing coordinator 310 incorporates any number of raw sensor types. The sensors are either embedded in the coordinator 310 or connected to the coordinator 310 via a wired or wireless network. In the preferred embodiment, the coordinator 310 records the following measurements; see also McGranahan ¶ 0049: during a server operational function 324, data 305 is received by the server 106 and is stored by a database with a reference to the asset (i.e., piece of equipment under measure 101A-101N), asset type, measurement type(s), time of collection and any known information on the operation of the equipment at the given time. This allows the creation and generation of a database of collected sensor data 301 for the given coordinator 310)
receive, at a first time, first input corresponding to a first label; (McGranahan ¶ 0067-0068: A real-time user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment in real-time (e.g., as data is collected). The user indicates the labeling by choosing the equipment or statistical model that is being labeled, and pressing a button on a PC-based, web-based, or mobile-based tool interface when the event begins, completes, or is active. The user also adds additional context information to the label)
store a first data point, wherein the first data point comprises: (McGranahan ¶ 0123: collecting data corresponding to equipment performance of a monitored device from one or more data sources including an adaptive sensing coordinator, cataloging the data, and characterizing and tracking the operation of the monitored device based at least on the data and statistical models based on the data and historical data ... the statistical models are built and altered via a training function ... the data is stored in a repository)
a first timestamp corresponding to the first time, the first label, and a first portion of the data corresponding to the first time; (McGranahan ¶ 0124-0126, see ¶ 0124: cataloging the data comprises associating the data with the monitored device, equipment type, measurement type, time of collection and the operation of the equipment at the time of collection; see McGranahan ¶ 0126: an association, or label, is assigned between a real-world event and data related to a monitored device under monitoring by a labeling mechanism … the association or labeling occurs in real-time as data is collected)
receive at a second time, second input; (McGranahan ¶ 0067-0068: A real-time user mode of the labeling mechanism 640 enables a user to identify, label and describe events pertaining to a piece of equipment in real-time (e.g., as data is collected). The user indicates the labeling by choosing the equipment or statistical model that is being labeled, and pressing a button on a PC-based, web-based, or mobile-based tool interface when the event begins, completes, or is active. The user also adds additional context information to the label; see also McGranahan addressing "second time" and "second input" as claimed in at least FIG. 8, ¶ 0077-0078: A mobile-based labeling mechanism 800 is used to label events occurring in real-time ... In real-time, the label start/stop button 803 is used to label events and states of the equipment ... When near the refrigerator, the ‘Refrigerator Door Open’ label is selected, and the ‘Start’ button is pressed at the same time the refrigerator door is opened. The ‘Stop’ button is then pressed at the same time the refrigerator door is closed. This can be repeated multiple times as needed to build a complete model)
store a second data point, wherein the second data point comprises: (McGranahan shows a plurality of data points in at least FIG. 8, ¶ 0077: In real-time, the label start/stop button 803 is used to label events and states of the equipment; McGranahan describes storage in ¶ 0123: collecting data corresponding to equipment performance of a monitored device from one or more data sources including an adaptive sensing coordinator, cataloging the data, and characterizing and tracking the operation of the monitored device based at least on the data and statistical models based on the data and historical data ... the data is stored in a repository;)
a second timestamp correspond