DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The following FINAL Office Action is in response to Applicant’s communication filed 10/03/2025 regarding Application 18/056,127.
Status of Claim(s)
Claim(s) 1-6, 8-16, 18-19, and 21-23 is/are currently pending and are rejected as follows.
Response to Arguments – 101 Rejection
Applicant’s arguments and amendments in regards to 101 have been fully considered and deemed persuasive.
Accordingly, Examiner withdraws the previously applied 101 rejection.
Response to Arguments – 103 Rejection
Applicant’s arguments in regards to the previously applied 103 rejection are rendered moot in view of the newly amended prior art rejection below.
Claim Rejections - 35 USC § 103
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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-6, 8-16, 18-19, and 21-22 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chong (US 2018/0033279 Al) in view of Smith (US 2020/0070838 A1)
Claim(s) 1, 11, and 19 –
Chong discloses the following limitations:
A memory (Chong: Paragraph 4, "In some implementations, a non-transitory computer-readable medium may store one or more instructions that, when executed by one or more processors, cause the one or more processors to receive one or more environmental measurements associated with a workplace. The one or more instructions may cause the one or more processors to receive one or more physiological measurements associated with a worker. The one or more physiological measurements may be different from the one or more environmental measurements. The one or more instructions may cause the one or more processors to generate a safety score for the worker based on the one or more environmental measurements and the one or more physiological measurements. The one or more instructions may cause the one or more processors to provide information regarding the worker based on the safety score.")
A processing device (Chong: Paragraph 4, "In some implementations, a nontransitory computer-readable medium may store one or more instructions that, when executed by one or more processors, cause the one or more processors to receive one or more environmental measurements associated with a workplace. The one or more instructions may cause the one or more processors to receive one or more physiological measurements associated with a worker. The one or more physiological measurements may be different from the one or more environmental measurements. The one or more instructions may cause the one or more processors to generate a safety score for the worker based on the one or more environmental measurements and the one or more physiological measurements. The one or more instructions may cause the one or more processors to provide information regarding the worker based on the safety score.")
A non-transitory computer readable medium (Chong: Paragraph 4, "In some implementations, a non-transitory computer-readable medium may store one or more instructions that, when executed by one or more processors, cause the one or more processors to receive one or more environmental measurements associated with a workplace. The one or more instructions may cause the one or more processors to receive one or more physiological measurements associated with a worker. The one or more physiological measurements may be different from the one or more environmental measurements. The one or more instructions may cause the one or more processors to generate a safety score for the worker based on the one or more environmental measurements and the one or more physiological measurements. The one or more instructions may cause the one or more processors to provide information regarding the worker based on the safety score.")
identifying, by a processing device, work data associated with a worker of an organization, wherein the work data comprises a number of hours worked by the worker during one or more intervals of a time period; (Chong: Paragraph 50, "As another example, work information may include worker schedule information, such as a work schedule, an amount of time the worker has been working on a current shift, a quantity and/or length of shifts over a time period (e.g., a day, a week, a month, or a year), a time of the shift (e.g., a time of day), a length of time between shifts, or the like. In some implementations, safety analysis platform 240 may automatically obtain the worker schedule information by interacting with a scheduling system to obtain and/or analyze the schedule information. Safety analysis platform 240 may use the worker schedule information to generate a safety score for a worker, as described in more detail below. For example, safety analysis platform 240 may assign different values to different worker schedule factors described above, and a value assigned to the worker schedule factor may impact the value of the safety score."; Paragraph 84, "As shown in FIG. 7, workplace device 270 may cause the worker safety dashboard to show a list (shown by reference number 710) of workers (shown as User 1 through User 9) with information regarding a worker status (under "Status") based on a safety score, a worker name (under "Name"), a worker safety score (under "Safety Value"), physiological information (under "Heart Rate" and "Steps"), work information (under "Hours at Shift"), and/or environmental information. Workplace device 270 may allow a user to select a worker, such as by clicking on a portion of the user interface that identifies the worker, such that the user interface displays details associated with the selected worker.")
determining, by the processing device, a fatigue score associated with the worker based on the calculated fatigue state associated with the worker, wherein the fatigue score indicates a level of fatigue associated with the worker during a current time period in view of the calculated fatigue state associated with the worker; and (Chong: Paragraph 64, "For example, safety analysis platform 240 may generate a safety score for a worker based on one or more factors described herein. For example, the safety score may be based on one or more work factors associated with work information described in connection with block 510, one or more environmental factors associated with one or more environmental measurements described in connection with block 520, and/or one or more physiological factors associated with the physiological measurements described in connection with block 530."; Paragraph 66, "As another example, safety analysis platform 240 may apply different weights to different individual factors. For example, regarding work factors, safety analysis platform 240 may apply a first (e.g., high) weight to an amount of time the worker has been on a shift, may apply a second (e.g., medium) weight to an amount of worker experience, and may apply a third (e.g., low) weight to a quantity of shifts over time. Similarly, regarding environmental factors, safety analysis platform 240 may apply a first (e.g., high) weight to a weather forecast, may apply a second (e.g., medium) weight to a workplace temperature, and may apply a third (e.g., low) weight to a worker location. Similarly, regarding physiological factors, safety analysis platform 240 may apply a first (e.g., high) weight to a heart rate, may apply a second (e.g., medium) weight to an amount of skin perspiration, and may apply a third (e.g., low) weight to a number of steps taken. These weight value assignments are provided as examples, and weight values may be assigned to different individual factors in a different manner, in some implementations."; Paragraph 68, "In some implementations, safety analysis platform 240 may generate the safety score based on applying a model, applying machine learning, applying artificial intelligence, or the like. For example, safety analysis platform 240 may receive a training set of data (e.g., known factors) that led to accidents, and may apply machine learning to the training set to identify factors and/or combinations of factors likely to cause an accident."; Paragraph 87, "In some implementations, information may be updated in real time as the information is received and/or processed. As an example, a status of User 1 may be changed from green to amber, indicating a medium risk safety score. The user of workplace device 270 (e.g., a supervisor) may then select User 1 to obtain more information about User 1, such as why the status of User 1 was changed from green to amber. As shown in FIG. 11, as a result of the user selecting User 1, the icon for User 1 is enlarged (shown by reference number 1110) and the icon for User 5 is shrunk (shown by reference number 1120) based on supervisor selection of User 1."; Paragraph 88, "As further shown in FIG. 12, User 1 has a fatigue factor score of 6, a dangerous work factor score of 5, and a dangerous substance factor score of 7. In some implementations, the safety score may be calculated as the maximum of one or more of the factor scores.")
providing, by the processing device, the normalized fatigue score to a client device. (Chong: Paragraph 64, "For example, safety analysis platform 240 may generate a safety score for a worker based on one or more factors described herein. For example, the safety score may be based on one or more work factors associated with work information described in connection with block 510, one or more environmental factors associated with one or more environmental measurements described in connection with block 520, and/or one or more physiological factors associated with the physiological measurements described in connection with block 530."; Paragraph 66, "As another example, safety analysis platform 240 may apply different weights to different individual factors. For example, regarding work factors, safety analysis platform 240 may apply a first (e.g., high) weight to an amount of time the worker has been on a shift, may apply a second (e.g., medium) weight to an amount of worker experience, and may apply a third (e.g., low) weight to a quantity of shifts over time. Similarly, regarding environmental factors, safety analysis platform 240 may apply a first (e.g., high) weight to a weather forecast, may apply a second (e.g., medium) weight to a workplace temperature, and may apply a third (e.g., low) weight to a worker location. Similarly, regarding physiological factors, safety analysis platform 240 may apply a first (e.g., high) weight to a heart rate, may apply a second (e.g., medium) weight to an amount of skin perspiration, and may apply a third (e.g., low) weight to a number of steps taken. These weight value assignments are provided as examples, and weight values may be assigned to different individual factors in a different manner, in some implementations."; Paragraph 68, "In some implementations, safety analysis platform 240 may generate the safety score based on applying a model, applying machine learning, applying artificial intelligence, or the like. For example, safety analysis platform 240 may receive a training set of data (e.g., known factors) that led to accidents, and may apply machine learning to the training set to identify factors and/or combinations of factors likely to cause an accident."; Paragraph 87, "In some implementations, information may be updated in real time as the information is received and/or processed. As an example, a status of User 1 may be changed from green to amber, indicating a medium risk safety score. The user of workplace device 270 (e.g., a supervisor) may then select User 1 to obtain more information about User 1, such as why the status of User 1 was changed from green to amber. As shown in FIG. 11, as a result of the user selecting User 1, the icon for User 1 is enlarged (shown by reference number 1110) and the icon for User 5 is shrunk (shown by reference number 1120) based on supervisor selection of User 1. "; Paragraph 88, "As further shown in FIG. 12, User 1 has a fatigue factor score of 6, a dangerous work factor score of 5, and a dangerous substance factor score of 7. In some implementations, the safety score may be calculated as the maximum of one or more of the factor scores.")
Chong does not explicitly disclose the fatigue state calculation of a prior time period and including of rest hours, however, in analogous art of risk management Smith discloses the following:
calculating, by the processing device and based on the identified work data, a fatigue state associated with the worker for the prior time period, wherein the fatigue state represents a number of fatigue hours accumulated by the worker over each of one or more intervals of the prior time period relative to a number of work hours associated with the worker and a number of rest hours associated with the worker and based on a target work calendar associated with the worker (Smith: Paragraph 82, “An alertness score is calculated using the fatigue events. The alertness score is calculated using a non-linear function. The non-linear function may be a sigmoid function, a logistic function, a polynomial function, an asymptotic function, or other non-linear function. The alertness score represents how alert the operator 102 is over a period of time. The alertness score may be measured over an operator's shift (e.g., 8 hours), a 24-hour period, a week, or other interval.”; Paragraph 21, “Example 18 is a method of monitoring alertness, the method comprising: determining a number of fatigue events of that an operator experienced while operating equipment over a time period; determining a weighted alertness score based on the number of fatigue events, the weighted alertness score determined using a non-linear function, and initiating a remedial response based on the weighted alertness score.”; Paragraph 72, “A centralized computer system collects information about fatigue events for a single operator or a group of operators (e.g., a work crew or enterprise-wide), and calculates an alertness score. The alertness score is based on an inverse logistic function (or S-shaped sigmoid function), such that having two or more fatigue events in a given timeframe (e.g., a work shift) result in a significantly lower alertness score than only have one fatigue event. An aggregate alertness score may be calculated over a time period of days or weeks to determine trends for a particular operator. Additionally, multiple operators may be combined to determine other statistical alertness calculations. A jobsite foreman or other monitoring agent may use the alertness calculations to determine who is posing a risk or derive other insights into operating conditions at a workplace, jobsite, or the like.”; Paragraph 83, “A client system 110 may access the cloud service 108 and obtain reports, execute real-time reports, review alertness scores of one or more operators over one or more periods, issue notices or alerts to the operators, control equipment 106 remotely, or the like. The client system 110 may be used by a shift supervisor, administrative user, or other person overseeing operations. Multiple client systems 110 may be used to access data from the cloud service 108 so that people from multiple departments within an organization may review alertness scores and trends, for example. The client system 110 may be of any type of compute platform including, but not limited to a desktop, laptop, cellular phone, tablet, or wearable device.”; Paragraph 93, “Using Eq. 1, scores are normalized to avoid biases over shift schedules or days worked. It is important to eliminate bias from scheduling differences. Any number of works days may be aggregated using Eq. 1 so that weekly, monthly, yearly, or other intervals may be analyzed by a shift manager or other administrative user. A moving average may be used to analyze the last twenty-one days, or any moving window of days, shifts, or other periods.”; Paragraph 95, “In addition, individual weighted scores can then be averaged across a crew to create a crew alertness score, averaged across operators in a shift to create a shift alertness score, or averaged across a site a create a site alertness score. Also, weighted scores can be compared between day and night shifts or other variables. Other aggregations, averages or statistical analyses may be performed to provide insight to a manager, executive, or administrative user. Aggregations may include multiple operating sites, multiple business units, multiple work crews, or other data slices.”; Paragraph 96, “Other key performance indicators may be calculated from the individual weighted scores, such as to identify those people who are below a threshold and may be considered unsafe or in need of help; calculating a fatigue score for the week or day across a crew or job site; correlating fatigue scores or fatigue events with equipment losses, health insurance claims, or other expenses; or identifying inefficient equipment usage, for example by analyzing and correlating fatigue events with telematics from vehicles.”)
performing one or more normalization operations to obtain a normalized fatigue score associated with the worker based on the determined fatigue score associated with the worker and the fatigue state of other workers of the organization during the prior time period (Smith: Paragraph 81, “The fatigue detection system 106 may conduct data analytics on the fatigue events. Alternatively, the cloud service 108 may perform data analytics on the fatigue events. The data analytics may include operations such as data aggregation, normalization, statistical data mining, reporting, or the like.”; Paragraph 93, “Using Eq. 1, scores are normalized to avoid biases over shift schedules or days worked. It is important to eliminate bias from scheduling differences. Any number of works days may be aggregated using Eq. 1 so that weekly, monthly, yearly, or other intervals may be analyzed by a shift manager or other administrative user. A moving average may be used to analyze the last twenty-one days, or any moving window of days, shifts, or other period”; Paragraph 94, “For example, the fatigue events may be aggregated over time using Eq. 1, as described above. So, if an operator had a whole work week of days with two fatigue events each day, then the weighted and normalized score is still 13 (e.g., {(n.sub.2*w.sub.2)/[w.sub.0*(n.sub.2)]}*100={(5*13)/[100*(5)]}*100=13). As another example, if the operator had two days with no fatigue events, one day with one fatigue event, and two days with two fatigue events, the weighted and normalized score would be:”; Paragraph 104, “At 610, optionally, a combined alertness score is calculated over several time periods. For instance, the combined alertness score may represent an aggregate alertness score over a week's worth of work shifts. The combined alert score may be normalized over several time period's worth of data.”)
Chong discloses a method for calculating scores for employees as they relate to safety in view of factors such as fatigue. Smith discloses a method for monitoring fatigue for an employee and normalizing the scores. At the time of Applicant’s filed invention, one of ordinary skill in the art would have deemed it obvious to combine the methods of Chong with the teachings of Smith in order to improve safety and prevent accidents as disclosed by Smith (Smith: Paragraph 3, “By capturing environmental and physiological data that indicates operator fatigue, a supervisor or other response mechanism may be used to ensure continued safe operation.”)
Claim(s) 2 and 12 –
Chong in view of Smith discloses the limitations of claims 1 and 11
Chong does not explicitly disclose the following, however, in analogous art of risk management Smith teaches the following:
determining a level of fatigue associated with the worker during each time interval of the prior time period, wherein the level of fatigue for a respective time interval reflects the number of fatigue hours accumulated by the worker relative to the number of workhours associated with the worker during each prior time interval of the prior time period and the number of rest hours associated with the worker during each prior time interval of the prior time period; (Smith: Paragraph 82, “An alertness score is calculated using the fatigue events. The alertness score is calculated using a non-linear function. The non-linear function may be a sigmoid function, a logistic function, a polynomial function, an asymptotic function, or other non-linear function. The alertness score represents how alert the operator 102 is over a period of time. The alertness score may be measured over an operator's shift (e.g., 8 hours), a 24-hour period, a week, or other interval.”; Paragraph 84, “FIG. 2 is a flowchart illustrating a method to calculate an alertness score, according to an embodiment. A measurement period is determined (operation 200). The measurement period is the period during which an operator 102 is monitored. The measurement period may be a discrete amount of time, such as eight hours, or a labeled amount of time, such as a shift, where a length of the shift may be variable for each employee.”; Paragraph 91, “Using the values in Table 1, it can be observed that an operator that has two fatigue events in a given period (e.g., shift) will be assigned an alertness score of 13 for that period, which is significantly lower than another operator who only had one fatigue event in a shift. An example graph of the sigmoid function Eq. 2, is illustrated in FIG. 3.”; Paragraph 95, “In addition, individual weighted scores can then be averaged across a crew to create a crew alertness score, averaged across operators in a shift to create a shift alertness score, or averaged across a site a create a site alertness score. Also, weighted scores can be compared between day and night shifts or other variables. Other aggregations, averages or statistical analyses may be performed to provide insight to a manager, executive, or administrative user. Aggregations may include multiple operating sites, multiple business units, multiple work crews, or other data slices.”; Paragraph 98, “Based on the fatigue events of a single time period (e.g., a single shift), an aggregate of time periods (e.g., multiple days or multiple shifts), or across several people, a variety of remedial actions may be initiated. For instance, on the occurrence of the first fatigue event, an operator may be notified that the event was observed and logged. The notification may be a visual, audible, tactile, or other mode or combination of modes. The notification may include an electronic message to the operator (e.g., a text message or email message to a corporate messaging server), to the operator's manager or supervisor, to third-party regulators or agencies (e.g., to a governmental safety agency or the corporate insurance company), or the like.”; Paragraph 99, “Another remedial action may include partial or complete disabling of the equipment that the operator is controlling. For instance, on a first fatigue event, the equipment may be partially disabled so that the there is less chance of disaster if the operator experiences a second fatigue event. Examples include, but are not limited to, reduced maximum driving speed, reduced vehicle acceleration, or the like. On a second fatigue event, depending on the maximum allowable fatigue events, the equipment may be further disabled or may be completely disabled. The amount, type, severity, timing, or other aspects of equipment disabling may be controlled by policies enacted by the corporation or by administrative users.”; Paragraph 104, “At 610, optionally, a combined alertness score is calculated over several time periods. For instance, the combined alertness score may represent an aggregate alertness score over a week's worth of work shifts. The combined alert score may be normalized over several time period's worth of data.”; Paragraph 106, “At 614, alertness metrics are displayed in a user interface. The user interface may be configurable to display different data views of the alertness scores of one or more operators at one or more job sites, for example. FIGS. 7-8 are example user interfaces, according to embodiments. FIG. 7 illustrates a dashboard view with operators at a particular work site. The operators who have fatigue events are listed in descending order. Clicking or activating an icon representing an operator brings up a sub-presentation with specifics about the operator. FIG. 8 illustrates another dashboard view of historical fatigue events. The size of the historical period to display is controlled using a drop-down menu control. In the example illustrated, data for each particular piece of equipment is presented over a 24-hour period. Additional aggregate information about day and night shifts is displayed. The user may display enterprise-wide data and statistics or choose one or more sites to view. A supervisor may view the user interface to determine which operator are at risk, how a crew or group of operators are performing, execute reports for additional data analysis, or the like.”)
and aggregating the determined levels of fatigue to generate an aggregated level of fatigue over the time period, wherein the calculated fatigue state corresponds to the aggregated level of fatigue in view of the target work calendar associated with the worker (Smith: Paragraph 82, “An alertness score is calculated using the fatigue events. The alertness score is calculated using a non-linear function. The non-linear function may be a sigmoid function, a logistic function, a polynomial function, an asymptotic function, or other non-linear function. The alertness score represents how alert the operator 102 is over a period of time. The alertness score may be measured over an operator's shift (e.g., 8 hours), a 24-hour period, a week, or other interval.”; Paragraph 84, “FIG. 2 is a flowchart illustrating a method to calculate an alertness score, according to an embodiment. A measurement period is determined (operation 200). The measurement period is the period during which an operator 102 is monitored. The measurement period may be a discrete amount of time, such as eight hours, or a labeled amount of time, such as a shift, where a length of the shift may be variable for each employee.”; Paragraph 91, “Using the values in Table 1, it can be observed that an operator that has two fatigue events in a given period (e.g., shift) will be assigned an alertness score of 13 for that period, which is significantly lower than another operator who only had one fatigue event in a shift. An example graph of the sigmoid function Eq. 2, is illustrated in FIG. 3.”; Paragraph 95, “In addition, individual weighted scores can then be averaged across a crew to create a crew alertness score, averaged across operators in a shift to create a shift alertness score, or averaged across a site a create a site alertness score. Also, weighted scores can be compared between day and night shifts or other variables. Other aggregations, averages or statistical analyses may be performed to provide insight to a manager, executive, or administrative user. Aggregations may include multiple operating sites, multiple business units, multiple work crews, or other data slices.”; Paragraph 98, “Based on the fatigue events of a single time period (e.g., a single shift), an aggregate of time periods (e.g., multiple days or multiple shifts), or across several people, a variety of remedial actions may be initiated. For instance, on the occurrence of the first fatigue event, an operator may be notified that the event was observed and logged. The notification may be a visual, audible, tactile, or other mode or combination of modes. The notification may include an electronic message to the operator (e.g., a text message or email message to a corporate messaging server), to the operator's manager or supervisor, to third-party regulators or agencies (e.g., to a governmental safety agency or the corporate insurance company), or the like.”; Paragraph 99, “Another remedial action may include partial or complete disabling of the equipment that the operator is controlling. For instance, on a first fatigue event, the equipment may be partially disabled so that the there is less chance of disaster if the operator experiences a second fatigue event. Examples include, but are not limited to, reduced maximum driving speed, reduced vehicle acceleration, or the like. On a second fatigue event, depending on the maximum allowable fatigue events, the equipment may be further disabled or may be completely disabled. The amount, type, severity, timing, or other aspects of equipment disabling may be controlled by policies enacted by the corporation or by administrative users.”; Paragraph 104, “At 610, optionally, a combined alertness score is calculated over several time periods. For instance, the combined alertness score may represent an aggregate alertness score over a week's worth of work shifts. The combined alert score may be normalized over several time period's worth of data.”; Paragraph 106, “At 614, alertness metrics are displayed in a user interface. The user interface may be configurable to display different data views of the alertness scores of one or more operators at one or more job sites, for example. FIGS. 7-8 are example user interfaces, according to embodiments. FIG. 7 illustrates a dashboard view with operators at a particular work site. The operators who have fatigue events are listed in descending order. Clicking or activating an icon representing an operator brings up a sub-presentation with specifics about the operator. FIG. 8 illustrates another dashboard view of historical fatigue events. The size of the historical period to display is controlled using a drop-down menu control. In the example illustrated, data for each particular piece of equipment is presented over a 24-hour period. Additional aggregate information about day and night shifts is displayed. The user may display enterprise-wide data and statistics or choose one or more sites to view. A supervisor may view the user interface to determine which operator are at risk, how a crew or group of operators are performing, execute reports for additional data analysis, or the like.”)
Chong discloses a method for calculating scores for employees as they relate to safety in view of factors such as fatigue. Smith discloses a method for monitoring fatigue for an employee and normalizing the scores. At the time of Applicant’s filed invention, one of ordinary skill in the art would have deemed it obvious to combine the methods of Chong with the teachings of Smith in order to improve safety and prevent accidents as disclosed by Smith (Smith: Paragraph 3, “By capturing environmental and physiological data that indicates operator fatigue, a supervisor or other response mechanism may be used to ensure continued safe operation.”)
Claim(s) 3 and 13 –
Chong in view of Smith discloses the limitations of claims 1-2 and 11-12
Chong does not explicitly disclose the following, however, in analogous art of risk management Smith teaches the following:
applying a work fatigue function to the number of work hours during each interval of the time period and the number of rest hours during each interval of the time period (Smith: Paragraph 82, “An alertness score is calculated using the fatigue events. The alertness score is calculated using a non-linear function. The non-linear function may be a sigmoid function, a logistic function, a polynomial function, an asymptotic function, or other non-linear function. The alertness score represents how alert the operator 102 is over a period of time. The alertness score may be measured over an operator's shift (e.g., 8 hours), a 24-hour period, a week, or other interval.”; Paragraph 84, “FIG. 2 is a flowchart illustrating a method to calculate an alertness score, according to an embodiment. A measurement period is determined (operation 200). The measurement period is the period during which an operator 102 is monitored. The measurement period may be a discrete amount of time, such as eight hours, or a labeled amount of time, such as a shift, where a length of the shift may be variable for each employee.”; Paragraph 91, “Using the values in Table 1, it can be observed that an operator that has two fatigue events in a given period (e.g., shift) will be assigned an alertness score of 13 for that period, which is significantly lower than another operator who only had one fatigue event in a shift. An example graph of the sigmoid function Eq. 2, is illustrated in FIG. 3.”; Paragraph 95, “In addition, individual weighted scores can then be averaged across a crew to create a crew alertness score, averaged across operators in a shift to create a shift alertness score, or averaged across a site a create a site alertness score. Also, weighted scores can be compared between day and night shifts or other variables. Other aggregations, averages or statistical analyses may be performed to provide insight to a manager, executive, or administrative user. Aggregations may include multiple operating sites, multiple business units, multiple work crews, or other data slices.”; Paragraph 98, “Based on the fatigue events of a single time period (e.g., a single shift), an aggregate of time periods (e.g., multiple days or multiple shifts), or across several people, a variety of remedial actions may be initiated. For instance, on the occurrence of the first fatigue event, an operator may be notified that the event was observed and logged. The notification may be a visual, audible, tactile, or other mode or combination of modes. The notification may include an electronic message to the operator (e.g., a text message or email message to a corporate messaging server), to the operator's manager or supervisor, to third-party regulators or agencies (e.g., to a governmental safety agency or the corporate insurance company), or the like.”; Paragraph 99, “Another remedial action may include partial or complete disabling of the equipment that the operator is controlling. For instance, on a first fatigue event, the equipment may be partially disabled so that the there is less chance of disaster if the operator experiences a second fatigue event. Examples include, but are not limited to, reduced maximum driving speed, reduced vehicle acceleration, or the like. On a second fatigue event, depending on the maximum allowable fatigue events, the equipment may be further disabled or may be completely disabled. The amount, type, severity, timing, or other aspects of equipment disabling may be controlled by policies enacted by the corporation or by administrative users.”; Paragraph 104, “At 610, optionally, a combined alertness score is calculated over several time periods. For instance, the combined alertness score may represent an aggregate alertness score over a week's worth of work shifts. The combined alert score may be normalized over several time period's worth of data.”; Paragraph 106, “At 614, alertness metrics are displayed in a user interface. The user interface may be configurable to display different data views of the alertness scores of one or more operators at one or more job sites, for example. FIGS. 7-8 are example user interfaces, according to embodiments. FIG. 7 illustrates a dashboard view with operators at a particular work site. The operators who have fatigue events are listed in descending order. Clicking or activating an icon representing an operator brings up a sub-presentation with specifics about the operator. FIG. 8 illustrates another dashboard view of historical fatigue events. The size of the historical period to display is controlled using a drop-down menu control. In the example illustrated, data for each particular piece of equipment is presented over a 24-hour period. Additional aggregate information about day and night shifts is displayed. The user may display enterprise-wide data and statistics or choose one or more sites to view. A supervisor may view the user interface to determine which operator are at risk, how a crew or group of operators are performing, execute reports for additional data analysis, or the like.”)
Chong discloses a method for calculating scores for employees as they relate to safety in view of factors such as fatigue. Smith discloses a method for monitoring fatigue for an employee and normalizing the scores. At the time of Applicant’s filed invention, one of ordinary skill in the art would have deemed it obvious to combine the methods of Chong with the teachings of Smith in order to improve safety and prevent accidents as disclosed by Smith (Smith: Paragraph 3, “By capturing environmental and physiological data that indicates operator fatigue, a supervisor or other response mechanism may be used to ensure continued safe operation.”)
Claim(s) 4 and 14 –
Chong in view of Smith disclose the limitations of claims 1-3 and 11-13
Chong further discloses the following:
wherein an equation of the work fatigue function comprises one or more elements and wherein a fatigue weight coefficient is applied to at least one of the one or more elements, wherein the fatigue weight coefficient corresponds to an amount of fatigue accumulated during one or more hours of a respective time interval, and wherein the fatigue weight coefficient is optimized based on a target work schedule associated with the worker. (Chong: Paragraph 50, "As another example, work information may include worker schedule information, such as a work schedule, an amount of time the worker has been working on a current shift, a quantity and/or length of shifts over a time period (e.g., a day, a week, a month, or a year), a time of the shift (e.g., a time of day), a length of time between shifts, or the like. In some implementations, safety analysis platform 240 may automatically obtain the worker schedule information by interacting with a scheduling system to obtain and/or analyze the schedule information. Safety analysis platform 240 may use the worker schedule information to generate a safety score for a worker, as described in more detail below. For example, safety analysis platform 240 may assign different values to different worker schedule factors described above, and a value assigned to the worker schedule factor may impact the value of the safety score."; Paragraph 66, "As another example, safety analysis platform 240 may apply different weights to different individual factors. For example, regarding work factors, safety analysis platform 240 may apply a first (e.g., high) weight to an amount of time the worker has been on a shift, may apply a second (e.g., medium) weight to an amount of worker experience, and may apply a third (e.g., low) weight to a quantity of shifts over time. Similarly, regarding environmental factors, safety analysis platform 240 may apply a first (e.g., high) weight to a weather forecast, may apply a second (e.g., medium) weight to a workplace temperature, and may apply a third (e.g., low) weight to a worker location. Similarly, regarding physiological factors, safety analysis platform 240 may apply a first (e.g., high) weight to a heart rate, may apply a second (e.g., medium) weight to an amount of skin perspiration, and may apply a third (e.g., low) weight to a number of steps taken. These weight value assignments are provided as examples, and weight values may be assigned to different individual factors in a different manner, in some implementations.")
Claim(s) 5 and 15 –
Chong in view of Smith disclose the limitations of claims 1-2 and 11-12
Chong further discloses the following:
calculating a summation of each determined level of fatigue associated with the worker during each interval of the time period. (Chong: Paragraph 92, "As shown in FIGS. 19-20, workplace device 270 may display a historical data section upon selection by a user. The historical data section may include statistics for workers or teams of workers. As shown in FIG. 19, workplace device 270 may display the historical data section to show one or more graphs of various factors. The graphs may be plotted over a day, a week, a month, and/or a time range selected by the user. For example, workplace device 270 may display a graph of an aggregate or average safety score for a selected team of workers. As another example, workplace device 270 may display a graph of an aggregate or average factor score over time for one or more factors. In this case, workplace device 270 may display multiple graphs on a same field, with the graph for each different factor shown in a different color."; Paragraph 93, "As shown in FIG. 20, workplace device 270 may display the historical data section to show information such as rules violations, alerts, notifications, or the like for a selected worker, a selected team of workers, or all workers. For example, workplace device 270 may display all rules violations for a selected worker. In some implementations, workplace device 270 may display the information for a particular time period, such as a day, a week, a month, and/or a time period selected by the user.")
Claim(s) 6 and 16 –
Chong in view of Smith disclose the limitations of claims 1-2, 5, 11-12, and 15
Chong further discloses the following:
applying a time weight coefficient to each determined level of fatigue associated with the worker, wherein the time weight coefficient corresponds to an amount of time that has passed from a respective time interval associated with a determined level of fatigue and a current time interval of the time period. (Chong: Paragraph 50, "As another example, work information may include worker schedule information, such as a work schedule, an amount of time the worker has been working on a current shift, a quantity and/or length of shifts over a time period (e.g., a day, a week, a month, or a year), a time of the shift (e.g., a time of day), a length of time between shifts, or the like. In some implementations, safety analysis platform 240 may automatically obtain the worker schedule information by interacting with a scheduling system to obtain and/or analyze the schedule information. Safety analysis platform 240 may use the worker schedule information to generate a safety score for a worker, as described in more detail below. For example, safety analysis platform 240 may assign different values to different worker schedule factors described above, and a value assigned to the worker schedule factor may impact the value of the safety score."; Paragraph 66, "As another example, safety analysis platform 240 may apply different weights to different individual factors. For example, regarding work factors, safety analysis platform 240 may apply a first (e.g., high) weight to an amount of time the worker has been on a shift, may apply a second (e.g., medium) weight to an amount of worker experience, and may apply a third (e.g., low) weight to a quantity of shifts over time. Similarly, regarding environmental factors, safety analysis platform 240 may apply a first (e.g., high) weight to a weather forecast, may apply a second (e.g., medium) weight to a workplace temperature, and may apply a third (e.g., low) weight to a worker location. Similarly, regarding physiological factors, safety analysis platform 240 may apply a first (e.g., high) weight to a heart rate, may apply a second (e.g., medium) weight to an amount of skin perspiration, and may apply a third (e.g., low) weight to a number of steps taken. These weight value assignments are provided as examples, and weight values may be assigned to different individual factors in a different manner, in some implementations.")
Claim(s) 8 and 18 –
Chong in view of Smith disclose the limitations of claims 1 and 11
Chong further discloses the following:
determining whether the calculated fatigue state exceeds a fatigue state threshold value of a plurality of fatigue state threshold values, wherein each of the plurality of fatigue state threshold values corresponds to a respective fatigue score; and (Chong: Paragraph 62, "In some implementations, a physiological measurement may include a current or real time measurement of the physiological indicator. Additionally, or alternatively, a physiological measurement may include a projection of a future physiological indicator, such as a heart rate that is increasing towards a threshold that could indicate danger to the worker."; Paragraph 74, "In some implementations, safety analysis platform 240 may provide an alert when the safety score satisfies a threshold. The alert may cause an output component 360 to output a signal. For example, output component 360 may output a visual signal (e.g., to cause an LED light to turn red) that may be seen by the user of workplace safety device 250, an audible signal (e.g., a beeping alarm or an automated verbal instruction) that may be heard by the user of workplace safety device 250, or the like."; Paragraph 98, "Some implementations are described herein in connection with thresholds. As used herein, satisfying a threshold may refer to a value being greater than the threshold, more than the threshold, higher than the threshold, greater than or equal to the threshold, less than the threshold, fewer than the threshold, lower than the threshold, less than or equal to the threshold, equal to the threshold, etc."; Paragraph 86, "As shown in FIG. 9, workplace device 270 may display an icon for a selected worker in a different manner than icons for other workers (shown by reference number 910), such as an icon that is larger than the icons for the other workers. Additionally, or alternatively, when a safety score for a worker satisfies a threshold, workplace device 270 may receive an alert and may provide an icon for that worker in a different manner than other icons for workers not associated with an alert, such as showing the icon in a different color (shown by reference number 920). For example, a green icon may indicate a low risk safety score, an amber icon may indicate a medium risk safety score, and a red icon may indicate a high risk safety score. Additionally, or alternatively, workplace device 270 may provide alerts and/or notifications regarding the workers (shown by reference number 930). ")
responsive to determining that the calculated fatigue state exceeds the fatigue state threshold value, identifying the fatigue score corresponding to the fatigue state threshold value. (Chong: Paragraph 74, "In some implementations, safety analysis platform 240 may provide an alert when the safety score satisfies a threshold. The alert may cause an output component 360 to output a signal. For example, output component 360 may output a visual signal (e.g., to cause an LED light to tum red) that may be seen by the user of workplace safety device 250, an audible signal (e.g., a beeping alarm or an automated verbal instruction) that may be heard by the user of workplace safety device 250, or the like."; Paragraph 98, "Some implementations are described herein in connection with thresholds. As used herein, satisfying a threshold may refer to a value being greater than the threshold, more than the threshold, higher than the threshold, greater than or equal to the threshold, less than the threshold, fewer than the threshold, lower than the threshold, less than or equal to the threshold, equal to the threshold, etc."; Paragraph 86, "As shown in FIG. 9, workplace device 270 may display an icon for a selected worker in a different manner than icons for other workers (shown by reference number 910), such as an icon that is larger than the icons for the other workers. Additionally, or alternatively, when a safety score for a worker satisfies a threshold, workplace device 270 may receive an alert and may provide an icon for that worker in a different manner than other icons for workers not associated with an alert, such as showing the icon in a different color (shown by reference number 920). For example, a green icon may indicate a low risk safety score, an amber icon may indicate a medium risk safety score, and a red icon may indicate a high risk safety score. Additionally, or alternatively, workplace device 270 may provide alerts and/or notifications regarding the workers (shown by reference number 930)."; Paragraph 87, "As an example, a status of User 1 may be changed from green to amber, indicating a medium risk safety score. The user of workplace device 270 (e.g., a supervisor) may then select User 1 to obtain more information about User 1, such as why the status of User 1 was changed from green to amber. As shown in FIG. 11, as a result of the user selecting User 1, the icon for User 1 is enlarged (shown by reference number 1110) and the icon for User 5 is shrunk (shown by reference number 1120) based on supervisor selection of User l.")
Claim(s) 9 –
Chong in view of Smith disclose the limitations of claim 1
Chong further discloses the following:
providing, to the client device, one or more recommended measures to reduce at least one of the fatigue score or the normalized fatigue score. (Chong: Paragraph 73, "In other words, the safety score may indicate a current risk level associated with the worker and/or a predicted future risk level associated with the worker. In some implementations, safety analysis platform may provide a recommendation to mitigate the current risk level and/or the predicted future risk level, as described below in connection with providing an alert."; Paragraph 85, "Workplace device 270 may also indicate a prediction of future safety scores, shown as a dotted line on the graph (shown by reference number 860), based on historical safety scores and model analysis. In some implementations, a current safety score may be calculated based on an expected future safety score (e.g., a prediction of a likelihood of a future accident). Workplace device 270 may further provide a recommendation for the selected worker based on historical and/or predicted safety scores (e.g., take a day off, switch to a safer task for a day, etc.). Workplace device 270 may indicate the most recent safety scores that satisfied a threshold, and when those safety scores occurred (shown by reference number 870). ")
Chong does not explicitly disclose the following, however, in analogous art of risk management Smith teaches the following:
performing one or more operations corresponding to at least one of the one or more recommended measures based on a user selection of at least one of the one or more recommended measures via a user interface of the client device (Smith: Paragraph 99, “Another remedial action may include partial or complete disabling of the equipment that the operator is controlling. For instance, on a first fatigue event, the equipment may be partially disabled so that the there is less chance of disaster if the operator experiences a second fatigue event. Examples include, but are not limited to, reduced maximum driving speed, reduced vehicle acceleration, or the like. On a second fatigue event, depending on the maximum allowable fatigue events, the equipment may be further disabled or may be completely disabled. The amount, type, severity, timing, or other aspects of equipment disabling may be controlled by policies enacted by the corporation or by administrative users.”; Paragraph 100, “The equipment may be a vehicle and the remedial action may be initiated by way of an advanced driver assistance system (ADAS) or an autonomous vehicle control system. In other machinery, interfaces to a control system, power system, steering system, or the like, may be used to reduce or disable functionality after a threshold number of fatigue events has been detected.”; Paragraph 105, “At 612, a remedial action is initiated based on the alertness score or the combined alertness score. The remedial action may include alerting the operator, modifying the operation of equipment being used by the operator, alerting a supervisor, or the like.”)
Chong discloses a method for calculating scores for employees as they relate to safety in view of factors such as fatigue. Smith discloses a method for monitoring fatigue for an employee and normalizing the scores. At the time of Applicant’s filed invention, one of ordinary skill in the art would have deemed it obvious to combine the methods of Chong with the teachings of Smith in order to improve safety and prevent accidents as disclosed by Smith (Smith: Paragraph 3, “By capturing environmental and physiological data that indicates operator fatigue, a supervisor or other response mechanism may be used to ensure continued safe operation.”)
Claim(s) 10 –
Chong in view of Smith discloses the limitations of claims 1 and 9
Chong further discloses the following:
wherein the one or more recommended measures to reduce the fatigue score comprise an indication of a number of rest hours to mitigate the amount of fatigue accumulated by the worker. (Chong: Paragraph 73, "In other words, the safety score may indicate a current risk level associated with the worker and/or a predicted future risk level associated with the worker. In some implementations, safety analysis platform may provide a recommendation to mitigate the current risk level and/or the predicted future risk level, as described below in connection with providing an alert."; Paragraph 85, "Workplace device 270 may also indicate a prediction of future safety scores, shown as a dotted line on the graph (shown by reference number 860), based on historical safety scores and model analysis. In some implementations, a current safety score may be calculated based on an expected future safety score (e.g., a prediction of a likelihood of a future accident). Workplace device 270 may further provide a recommendation for the selected worker based on historical and/or predicted safety scores (e.g., take a day off, switch to a safer task for a day, etc.). Workplace device 270 may indicate the most recent safety scores that satisfied a threshold, and when those safety scores occurred (shown by reference number 870). ")
identifying schedule data associated with the worker (Chong: Paragraph 50, "As another example, work information may include worker schedule information, such as a work schedule, an amount of time the worker has been working on a current shift, a quantity and/or length of shifts over a time period (e.g., a day, a week, a month, or a year), a time of the shift (e.g., a time of day), a length of time between shifts, or the like. In some implementations, safety analysis platform 240 may automatically obtain the worker schedule information by interacting with a scheduling system to obtain and/or analyze the schedule information. Safety analysis platform 240 may use the worker schedule information to generate a safety score for a worker, as described in more detail below. For example, safety analysis platform 240 may assign different values to different worker schedule factors described above, and a value assigned to the worker schedule factor may impact the value of the safety score."; Paragraph 51, "As yet another example, work information may include work history information relating to a worker's work history, such as an experience level of the worker, a historical record of the worker's performance, a historical record of rules violations and/or when rules violations occurred, performance review information, or the like. In some implementations, safety analysis platform 240 may automatically obtain the work history information by interacting with a workplace record system to obtain and/or analyze the work history information. Safety analysis platform 240 may use the work history information to generate a safety score for a worker, as described in more detail below. For example, safety analysis platform 240 may assign different values to different work history factors described above, and a value assigned to the work history factor may impact the value of the safety score.")
determining based on the identified schedule data, an updated schedule for the worker based on the indicated number of rest hours (Chong: Paragraph 75, "In some implementations, safety analysis platform 240 may provide an alert to worker device 260 (e.g., a mobile phone). For example, safety analysis platform 240 may provide the alert to cause worker device 260 to prompt the user (e.g., by displaying a message on a display screen of worker device 260) to be careful, to stop work immediately, to take a rest, or the like. Further to the example, worker device 260 may provide an audible signal, a vibration, or the like, to notify the user of worker device 260 of the message. In some implementations, safety analysis platform 240 may concurrently provide multiple alerts to multiple workplace safety devices 250, worker devices 260, and/or other devices."; Paragraph 85, "For example, workplace device 270 may indicate a maximum safety score for different days. Workplace device 270 may also indicate a prediction of future safety scores, shown as a dotted line on the graph (shown by reference number 860), based on historical safety scores and model analysis. In some implementations, a current safety score may be calculated based on an expected future safety score (e.g., a prediction of a likelihood of a future accident). Workplace device 270 may further provide a recommendation for the selected worker based on historical and/or predicted safety scores (e.g., take a day off, switch to a safer task for a day, etc.). Workplace device 270 may indicate the most recent safety scores that satisfied a threshold, and when those safety scores occurred (shown by reference number 870). ")
updating the identified schedule data correspond to the updated schedule (Chong: Paragraph 81, "FIGS. 6-20 are diagrams of example implementations relating to the example process shown in FIG. 5. As shown in FIGS. 6-20, workplace device 270 may display one or more user interfaces in various states representing different safety-related circumstances associated with the workplace and/or workers. Workplace device 270 may display, update, and/or alter the user interfaces based on information obtained from safety analysis platform 240 and/or one or more other devices of environment 200, such as information and/or changes to information associated with work factors, environmental factors,
and/or physiological factors. In some implementations, collection, processing, and display of data described herein may occur in real-time."; Paragraph 85, "As shown in FIG. 8, if a user selects "User 5" on the worker safety dashboard (shown by reference number 810), workplace device 270 may display a safety score for User 5 (shown by reference number 820). Workplace device 270 may display an area showing different factors (shown by reference number 830), a value of a factor that indicates a likelihood of an accident due to that factor (for one or more displayed factors), and/or an impact of the factor on the safety score. Workplace device 270 may also indicate rules violations associated with the selected worker (shown by reference number 840). Workplace device 270 may further indicate a maximum, a minimum, and/or an average safety score, such as plotted on a graph over a time period (shown by reference number 850). For example, workplace device 270 may indicate a maximum safety score for different days. Workplace device 270 may also indicate a prediction of future safety scores, shown as a dotted line on the graph (shown by reference number 860), based on historical safety scores and model analysis. In some implementations, a current safety score may be calculated based on an expected future safety score (e.g., a prediction of a likelihood of a future accident). Workplace device 270 may further provide a recommendation for the selected worker based on historical and/or predicted safety scores (e.g., take a day off, switch to a safer task for a day, etc.). Workplace device 270 may indicate the most recent safety scores that satisfied a threshold, and when those safety scores occurred (shown by reference number 870)."; Paragraph 87, "As shown in FIG. 10, workplace device 270 may update information in the list of workers based on receiving the alert (shown by reference number 1010). In some implementations, information may be updated in real time as the information is received and/or processed. As an example, a status of User 1 may be changed from green to amber, indicating a medium risk safety score. The user of workplace device 270 (e.g., a supervisor) may then select User 1 to obtain more information about User 1, such as why the status of User 1 was changed from green to amber. As shown in FIG. 11, as a result of the user selecting User 1, the icon for User 1 is enlarged (shown by reference number 1110) and the icon for User 5 is shrunk (shown by reference number 1120) based on supervisor selection of User 1.")
Claim(s) 21 –
Chong in view of Smith disclose the limitations of claims 1-4
Chong does not specifically disclose the following, however, in analogous art of risk management Smith discloses the following:
wherein a first element of the one or more elements reflects a total number of working hours in a day, a second element of the one or more elements reflects a number of night working hours in a work day, a third element of the one or more elements reflects a number of daytime rest hours in the work day, a fourth element of the one or more elements reflects a number of weekend day work hours during the prior time period, a fifth element of the one or more elements reflects a number of over normal hours per work day, and a sixth element of the one or more elements reflects a number of weekday rest hours, and wherein the fatigue weight coefficient is applied to one or more of the second element, the third element, the fourth element, the fifth element, or the sixth element. (Smith: Paragraph 82, “An alertness score is calculated using the fatigue events. The alertness score is calculated using a non-linear function. The non-linear function may be a sigmoid function, a logistic function, a polynomial function, an asymptotic function, or other non-linear function. The alertness score represents how alert the operator 102 is over a period of time. The alertness score may be measured over an operator's shift (e.g., 8 hours), a 24-hour period, a week, or other interval.”; Paragraph 87, “Weights w.sub.0, w.sub.0, w.sub.1, w.sub.2, w.sub.3, and w.sub.3+ are calculated using a non-linear function. In an embodiment, the weights are calculated using an inverse sigmoid function. It is understood that more or fewer weights may be used depending on the design of the system.”; Paragraph 93, “Using Eq. 1, scores are normalized to avoid biases over shift schedules or days worked. It is important to eliminate bias from scheduling differences. Any number of works days may be aggregated using Eq. 1 so that weekly, monthly, yearly, or other intervals may be analyzed by a shift manager or other administrative user. A moving average may be used to analyze the last twenty-one days, or any moving window of days, shifts, or other periods.”; Paragraph 95, “In addition, individual weighted scores can then be averaged across a crew to create a crew alertness score, averaged across operators in a shift to create a shift alertness score, or averaged across a site a create a site alertness score. Also, weighted scores can be compared between day and night shifts or other variables. Other aggregations, averages or statistical analyses may be performed to provide insight to a manager, executive, or administrative user. Aggregations may include multiple operating sites, multiple business units, multiple work crews, or other data slices.”; Paragraph 96, “Other key performance indicators may be calculated from the individual weighted scores, such as to identify those people who are below a threshold and may be considered unsafe or in need of help; calculating a fatigue score for the week or day across a crew or job site; correlating fatigue scores or fatigue events with equipment losses, health insurance claims, or other expenses; or identifying inefficient equipment usage, for example by analyzing and correlating fatigue events with telematics from vehicles.”)
Chong discloses a method for calculating scores for employees as they relate to safety in view of factors such as fatigue. Smith discloses a method for monitoring fatigue for an employee and normalizing the scores. At the time of Applicant’s filed invention, one of ordinary skill in the art would have deemed it obvious to combine the methods of Chong with the teachings of Smith in order to improve safety and prevent accidents as disclosed by Smith (Smith: Paragraph 3, “By capturing environmental and physiological data that indicates operator fatigue, a supervisor or other response mechanism may be used to ensure continued safe operation.”)
Claim(s) 22 –
Chong in view of Smith disclose the limitations of claims 1
Chong does not specifically disclose the following, however, in analogous art of risk management Smith discloses the following:
providing, as an input to the one or more normalization operations, the determined fatigue score associated with the worker and fatigue trend data associated with one or more of the other workers of the organization, wherein the fatigue trend data indicates the fatigue state of the one or more of the other workers during the time period; and (Smith: Paragraph 82, “An alertness score is calculated using the fatigue events. The alertness score is calculated using a non-linear function. The non-linear function may be a sigmoid function, a logistic function, a polynomial function, an asymptotic function, or other non-linear function. The alertness score represents how alert the operator 102 is over a period of time. The alertness score may be measured over an operator's shift (e.g., 8 hours), a 24-hour period, a week, or other interval.”; Paragraph 84, “FIG. 2 is a flowchart illustrating a method to calculate an alertness score, according to an embodiment. A measurement period is determined (operation 200). The measurement period is the period during which an operator 102 is monitored. The measurement period may be a discrete amount of time, such as eight hours, or a labeled amount of time, such as a shift, where a length of the shift may be variable for each employee.”; Paragraph 91, “Using the values in Table 1, it can be observed that an operator that has two fatigue events in a given period (e.g., shift) will be assigned an alertness score of 13 for that period, which is significantly lower than another operator who only had one fatigue event in a shift. An example graph of the sigmoid function Eq. 2, is illustrated in FIG. 3.”; Paragraph 95, “In addition, individual weighted scores can then be averaged across a crew to create a crew alertness score, averaged across operators in a shift to create a shift alertness score, or averaged across a site a create a site alertness score. Also, weighted scores can be compared between day and night shifts or other variables. Other aggregations, averages or statistical analyses may be performed to provide insight to a manager, executive, or administrative user. Aggregations may include multiple operating sites, multiple business units, multiple work crews, or other data slices.”; Paragraph 98, “Based on the fatigue events of a single time period (e.g., a single shift), an aggregate of time periods (e.g., multiple days or multiple shifts), or across several people, a variety of remedial actions may be initiated. For instance, on the occurrence of the first fatigue event, an operator may be notified that the event was observed and logged. The notification may be a visual, audible, tactile, or other mode or combination of modes. The notification may include an electronic message to the operator (e.g., a text message or email message to a corporate messaging server), to the operator's manager or supervisor, to third-party regulators or agencies (e.g., to a governmental safety agency or the corporate insurance company), or the like.”; Paragraph 99, “Another remedial action may include partial or complete disabling of the equipment that the operator is controlling. For instance, on a first fatigue event, the equipment may be partially disabled so that the there is less chance of disaster if the operator experiences a second fatigue event. Examples include, but are not limited to, reduced maximum driving speed, reduced vehicle acceleration, or the like. On a second fatigue event, depending on the maximum allowable fatigue events, the equipment may be further disabled or may be completely disabled. The amount, type, severity, timing, or other aspects of equipment disabling may be controlled by policies enacted by the corporation or by administrative users.”; Paragraph 104, “At 610, optionally, a combined alertness score is calculated over several time periods. For instance, the combined alertness score may represent an aggregate alertness score over a week's worth of work shifts. The combined alert score may be normalized over several time period's worth of data.”; Paragraph 106, “At 614, alertness metrics are displayed in a user interface. The user interface may be configurable to display different data views of the alertness scores of one or more operators at one or more job sites, for example. FIGS. 7-8 are example user interfaces, according to embodiments. FIG. 7 illustrates a dashboard view with operators at a particular work site. The operators who have fatigue events are listed in descending order. Clicking or activating an icon representing an operator brings up a sub-presentation with specifics about the operator. FIG. 8 illustrates another dashboard view of historical fatigue events. The size of the historical period to display is controlled using a drop-down menu control. In the example illustrated, data for each particular piece of equipment is presented over a 24-hour period. Additional aggregate information about day and night shifts is displayed. The user may display enterprise-wide data and statistics or choose one or more sites to view. A supervisor may view the user interface to determine which operator are at risk, how a crew or group of operators are performing, execute reports for additional data analysis, or the like.”)
obtaining an output of the one or more normalization operations. (Smith: Paragraph 82, “An alertness score is calculated using the fatigue events. The alertness score is calculated using a non-linear function. The non-linear function may be a sigmoid function, a logistic function, a polynomial function, an asymptotic function, or other non-linear function. The alertness score represents how alert the operator 102 is over a period of time. The alertness score may be measured over an operator's shift (e.g., 8 hours), a 24-hour period, a week, or other interval.”; Paragraph 84, “FIG. 2 is a flowchart illustrating a method to calculate an alertness score, according to an embodiment. A measurement period is determined (operation 200). The measurement period is the period during which an operator 102 is monitored. The measurement period may be a discrete amount of time, such as eight hours, or a labeled amount of time, such as a shift, where a length of the shift may be variable for each employee.”; Paragraph 91, “Using the values in Table 1, it can be observed that an operator that has two fatigue events in a given period (e.g., shift) will be assigned an alertness score of 13 for that period, which is significantly lower than another operator who only had one fatigue event in a shift. An example graph of the sigmoid function Eq. 2, is illustrated in FIG. 3.”; Paragraph 95, “In addition, individual weighted scores can then be averaged across a crew to create a crew alertness score, averaged across operators in a shift to create a shift alertness score, or averaged across a site a create a site alertness score. Also, weighted scores can be compared between day and night shifts or other variables. Other aggregations, averages or statistical analyses may be performed to provide insight to a manager, executive, or administrative user. Aggregations may include multiple operating sites, multiple business units, multiple work crews, or other data slices.”; Paragraph 98, “Based on the fatigue events of a single time period (e.g., a single shift), an aggregate of time periods (e.g., multiple days or multiple shifts), or across several people, a variety of remedial actions may be initiated. For instance, on the occurrence of the first fatigue event, an operator may be notified that the event was observed and logged. The notification may be a visual, audible, tactile, or other mode or combination of modes. The notification may include an electronic message to the operator (e.g., a text message or email message to a corporate messaging server), to the operator's manager or supervisor, to third-party regulators or agencies (e.g., to a governmental safety agency or the corporate insurance company), or the like.”; Paragraph 99, “Another remedial action may include partial or complete disabling of the equipment that the operator is controlling. For instance, on a first fatigue event, the equipment may be partially disabled so that the there is less chance of disaster if the operator experiences a second fatigue event. Examples include, but are not limited to, reduced maximum driving speed, reduced vehicle acceleration, or the like. On a second fatigue event, depending on the maximum allowable fatigue events, the equipment may be further disabled or may be completely disabled. The amount, type, severity, timing, or other aspects of equipment disabling may be controlled by policies enacted by the corporation or by administrative users.”; Paragraph 104, “At 610, optionally, a combined alertness score is calculated over several time periods. For instance, the combined alertness score may represent an aggregate alertness score over a week's worth of work shifts. The combined alert score may be normalized over several time period's worth of data.”; Paragraph 106, “At 614, alertness metrics are displayed in a user interface. The user interface may be configurable to display different data views of the alertness scores of one or more operators at one or more job sites, for example. FIGS. 7-8 are example user interfaces, according to embodiments. FIG. 7 illustrates a dashboard view with operators at a particular work site. The operators who have fatigue events are listed in descending order. Clicking or activating an icon representing an operator brings up a sub-presentation with specifics about the operator. FIG. 8 illustrates another dashboard view of historical fatigue events. The size of the historical period to display is controlled using a drop-down menu control. In the example illustrated, data for each particular piece of equipment is presented over a 24-hour period. Additional aggregate information about day and night shifts is displayed. The user may display enterprise-wide data and statistics or choose one or more sites to view. A supervisor may view the user interface to determine which operator are at risk, how a crew or group of operators are performing, execute reports for additional data analysis, or the like.”)
Chong discloses a method for calculating scores for employees as they relate to safety in view of factors such as fatigue. Smith discloses a method for monitoring fatigue for an employee and normalizing the scores. At the time of Applicant’s filed invention, one of ordinary skill in the art would have deemed it obvious to combine the methods of Chong with the teachings of Smith in order to improve safety and prevent accidents as disclosed by Smith (Smith: Paragraph 3, “By capturing environmental and physiological data that indicates operator fatigue, a supervisor or other response mechanism may be used to ensure continued safe operation.”)
Claim(s) 23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chong (US 2018/0033279 Al) in view of Smith (US 2020/0070838 A1) and Lu (US 2024/0268769 A1)
Claim(s) 23 –
Chong in view of Smith disclose the limitations of claims 1
Chong in view of Smith does not specifically disclose the following, however, in analogous art of risk management Lu discloses the following:
wherein the one or more normalization operations comprise a linear scaling operation. (Lu: Paragraph 33, “The fatigue estimation model storage unit 42 stores information concerning a fatigue estimation model which is a model for calculating the fatigue level based on features of the biological data of the test subject. For instance, when the fatigue estimation model is a linear model, the fatigue estimation model storage unit 42 stores information of parameters (weights) of the linear model. The fatigue estimation model is not limited to the linear model, and may be a regression model (statistical model) or a machine learning model other than the linear model. In these cases, the fatigue estimation model storage unit 42 stores information of parameters necessary for configuring the fatigue estimation model. For instance, when the fatigue estimation model is a model based on a neural network such as a convolution neural network, the fatigue estimation model storage unit 42 stores information of various parameters such as the layer structure, a neuron structure of each layer, a number of filters and a filter size in each layer, and the weight of each element of each filter.”)
Chong discloses a method for calculating scores for employees as they relate to safety in view of factors such as fatigue. Smith discloses a method for monitoring fatigue for an employee and normalizing the scores. Lu discloses a method for estimating and detecting fatigue in a subject. At the time of Applicant’s filed invention, one of ordinary skill in the art would have deemed it obvious to combine the methods of Chong in view of Smith with the teachings of Lu in order to increase the accuracy of detecting fatigue in a subject as disclosed by Lu (Lu: Paragraph 15, “According to the present disclosure, it becomes possible to accurately estimate a fatigue level of a test subject.”)
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/Philip N Warner/Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624