DETAILED CORRESPONDANCE
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of claims
This final office action on merits is in response to the communication received on 12/08/2025. Claims 4-5, 8-9, 11-12, 14-17, 19-25, 29-30, 33-34, 36-37, 39-42, and 44-49 are cancelled. Amendments to claims 1, 26, and 50 are acknowledged and have been carefully considered. Claims 1-3, 6-7, 10, 13, 18, 26-28, 31-32, 35, 38, 43, and 50 are pending and considered below.
Claim Objections
Claims 1, 26, and 50 are objected to under 37 CFR § 1.121 because the changes are not clearly identifiable. In particular, the tracked changes presented in the PDF are not readily readable, making it unclear what text has been added or deleted. As a result, the amendment is not in a form suitable for entry into the record.
Applicant is required to resubmit the amendment in a format that clearly identifies all additions and deletions of text in compliance with 37 CFR § 1.121.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-3, 6-7, 10, 13, 18, 26-28, 31-32, 35, 38, 43, and 50 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Under step 1, the analysis is based on MPEP 2106.03, and claims 1-3, 6-7, 10, 13, and 18 are drawn to a system, claims 26-28, 31-32, 35, 38, and 43 are drawn to a method, and claim 50 is drawn to a non-transitory computer readable storage medium. Thus, each claim, on its face, is directed to one of the statutory categories (i.e., useful process, machine, manufacture, or composition of matter) of 35 U.S.C. §101.
Step 2A Prong One
Claim 1 recites the limitations of calculate, in near real time: (A) based on the subset of records, for each given member of the first group of members, at least two of: (a) a health score indicative of a health state of the respective member, (b) a natural living score, indicative of compliance of a behavior pattern of the respective member with a desired natural behavior pattern, or (c) an affectivity/happiness score, indicative of compliance of an affectivity/happiness measure of the respective member with a desired affectivity/happiness measure; and (B) a welfare score of the members of the animal population based on the at least two of: (a) the health scores calculated for the first group of members, (b) the natural living scores calculated for a second group of members, or (c) the affectivity/happiness scores calculated for a third group of members; analyze historical and/or statistical data of one or more animal populations to determine at least one welfare threshold; compare the calculated welfare score against the determined welfare threshold . These limitations, as drafted, are processes that, under their broadest reasonable interpretations, cover performance of the limitations in the mind or by using a pen and paper. But for the “a processing circuitry configured to” language, the claim encompasses a user collecting information about animals, evaluating observed parameters, assigning condition scores, comparing those scores to a threshold in their mind or by using a pen and paper. The mere nominal recitation of a processing circuitry configured to does not take the claim limitation out of the mental processes grouping. Thus, the claim recites a mental process which is an abstract idea.
Claim 1 also recites as a whole a method of organizing human activity (i.e., managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions)) because the claim recites a method that allows users to based on the comparison, identify whether said members are exposed to declining welfare conditions, and upon identifying declining welfare conditions, determine an action directed at improving said welfare conditions. This is a method of managing and directing behavior or decision making of animal caregivers in response to evaluative results. The mere nominal recitation of a generic processing circuitry does not take the claim out of certain methods of organizing human activity grouping. Thus, the claim recites an abstract idea.
The types of identified abstract ideas are considered together as a single abstract idea for analysis purposes.
Independent claims 26 and 50 recite identical or nearly identical steps with respect to claim 1 (and therefore also recite limitations that fall within this subject matter grouping of abstract ideas), and these claims are therefore determined to recite an abstract idea under the same analysis.
Under Step 2A Prong Two
The claimed limitations, as per method claim 1, include:
one or more monitoring devices configured to monitor parameters of one or more members of the animal population;
a data repository comprising one or more records, each of the records (i) being associated with a respective member of the members, and (ii) including one or more parameters of the respective member as monitored by at least one of the monitoring devices over time; and
a processing circuitry configured to:
obtain at least a subset of the records, the subset being associated with a first group of members of the animal population; calculate, in near real time:
(A) based on the subset of records, for each given member of the first group of members, at least two of: (a) a health score indicative of a health state of the respective member, (b) a natural living score, indicative of compliance of a behavior pattern of the respective member with a desired natural behavior pattern, or (c) an affectivity/happiness score, indicative of compliance of an affectivity/happiness measure of the respective member with a desired affectivity/happiness measure; and
(B) a welfare score of the members of the animal population based on the at least two of: (a) the health scores calculated for the first group of members, (b) the natural living scores calculated for a second group of members, or (c) the affectivity/happiness scores calculated for a third group of members;
analyze historical and/or statistical data of one or more animal populations to determine at least one welfare threshold;
compare the calculated welfare score against the determined welfare threshold; and
based on the comparison, identify whether said members are exposed to declining welfare conditions, and upon identifying declining welfare conditions, determine an action directed at improving said welfare conditions.
Examiner Note: underlined elements indicate additional elements of the claimed invention identified as performing the steps of the claimed invention.
The judicial exception expressed in claim 1 is not integrated into a practical application. The claim as a whole merely describes how to generally “apply” the concept of evaluating information to identify declining welfare conditions and suggesting responsive actions in a computer environment. The claimed computer components (i.e., a data repository comprising one or more records, each of the records (i) being associated with a respective member of the members, and (ii) including one or more parameters of the respective member as monitored by at least one of the monitoring devices over time; and a processing circuitry configured to) are recited at a high level of generality and are merely invoked as tools to perform an existing process of collecting, analyzing, and interpreting information to guide behavior and decision making. Simply implementing the abstract idea on a generic computer is not a practical application of the abstract idea. Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application.
The judicial exception expressed in claim 1 is not integrated into a practical application. The abstract idea is merely carried out in a technical environment or field (i.e., animal monitoring and welfare management systems), however fails to contain meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment (see MPEP 2106.05(h)). The additional elements that are carried out in a technical environment includes one or more monitoring devices configured to monitor parameters of one or more members of the animal population. Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application.
The judicial exception expressed in claim 1 is not integrated into a practical application. The claim recites the additional element of obtaining at least a subset of the records, the subset being associated with a first group of members of the animal population. This limitation is recited at a high level of generality (i.e., as a general means of collecting or retrieving data for subsequent analysis), and amounts to merely data gathering, which is a form of insignificant extra-solution activity. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
Therefore, under step 2A, the claims are directed to the abstract idea, and require further analysis under Step 2B.
Under step 2B
Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A, the claim as a whole merely describes how to generally “apply” the concept of evaluating information to identify declining welfare conditions and suggesting responsive actions in a computer environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A, the abstract idea is merely carried out in a technical environment or field, however fails to contain meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
Claim 1 does not include an additional element that are sufficient to amount to significantly more than the judicial exception. For the providing limitation that was considered extra-solution activity in Step 2A, this has been re-evaluated in Step 2B and determined to be well-understood, routine, conventional activity in the field. The specification does not provide any indication that the limitation of collecting or retrieving data for subsequent analysis is anything other than a conventional action that simply comes before analyzing the data to calculate welfare scores and suggest actions. Also noted in Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016), merely collecting information for analysis without a technological improvement does not add significantly more to an abstract idea. The use of the system is no more than collecting information before analyzing, comparing, and evaluating the information to support decision making and does not integrate the abstract idea into a practical application. For these reasons, there is no inventive concept. The claim is not patent eligible.
Claims 2-3, 6-7, 10, 13, 18, 27-28, 31-32, 35, 38, and 42-43 recite no further additional elements, and only further narrow the abstract idea. The previously identified additional elements, individually and as a combination, do not integrate the narrowed abstract idea into a practical application for reasons similar to those explained above, and do not amount to significantly more than the narrowed abstract idea for reasons similar to those explained above.
Claim 17 recite the additional element of the processing circuitry. However, this additional element amounts to implementing an abstract idea on a generic computing device. As such, this additional element, when considered individually or in combination with the prior devices, does not integrate the abstract idea into a practical application or amount to significantly more than the abstract idea.
Thus, as the dependent claims remain directed to a judicial exception, and as the additional elements of the claims do not amount to significantly more, the dependent claims are not patent eligible.
Therefore, the claims here fail to contain any additional element(s) or combination of additional elements that can be considered as significantly more and the claim is rejected under 35 U.S.C. 101 for lacking eligible subject matter.
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.
Claims 1-3, 6-7, 10, 13, 18, 26-28, 31-32, 35, 38, 43, and 49-50 are rejected under 35 U.S.C. 103 as being unpatentable over Moss et al. (U.S. Patent Publication 2020/0178504 A1), referred to hereinafter as Moss, in view of Donavon (U.S. Patent Publication 2016/0012748 A1), referred to hereinafter as Donavon.
Regarding claim 1, Moss teaches a system (Moss [0031] “The processor 220 may comprise any type of conventional processor or microprocessor that interprets and executes computer readable instructions. The processor 220 is configured to perform the operations disclosed herein based on instructions stored within the system 400.”), the system comprising:
one or more monitoring devices configured to monitor parameters of one or more members of the animal population (Moss [0051] “At least one sensor 407 is preferably attached to an animal 402 in a way such that it may measure lifetime data 440 of the animal 402.” and Moss [0052] “For instance, the at least one sensor 407 that was removed from one animal 402 and placed on another animal 402 may generate a new serial number that may allow the system 400 to differentiate between animals 402 that have used the same at least one sensor 407. In another preferred embodiment, the system 100 may be connected to third-party systems having lifetime data 440, wherein the system 400 may receive the lifetime data 440 from the third-party systems and populate animal profiles 432 with the third-party lifetime data 440.”);
a data repository comprising one or more records (Moss [0006] “One preferred embodiment of the system may comprise a plurality of databases operably connected to the processor. The plurality of databases may be configured to store lifetime data and QR data within animal profiles and QR profiles, respectively.”), each of the records (i) being associated with a respective member of the members, and (ii) including one or more parameters of the respective member as monitored by at least one of the monitoring devices over time (Moss [0022] “The term “wellness” and grammatical equivalents thereof are used herein to mean the fitness of an animal or group of animals based upon physiological parameters informing health and well-being.” and Moss [0009] “The system may couple lifetime data and QR data to a data block via an operation. Each time an operation occurs, the system may create a new data block containing the information of both the data block and the lifetime data or QR data. To facilitate the creation of a new data block, the system may provide the plurality of computing entities with lifetime data and/or data and a serial number associated with a particular animal.”); and
a processing circuitry configured to: obtain at least a subset of the records, the subset being associated with a first group of members of the animal population (Moss [0006] “One preferred embodiment of the system may comprise a plurality of databases operably connected to the processor. The plurality of databases may be configured to store lifetime data and QR data within animal profiles and QR profiles, respectively. The database may also be configured to store quality scores created via algorithms using the lifetime data and QR data of the animal.”);
calculate, in near real time: (A) based on the subset of records, for each given member of the first group of members, at least two of: (a) a health score indicative of a health state of the respective member (Moss [0006] “One preferred embodiment of the system may comprise a plurality of databases operably connected to the processor. The plurality of databases may be configured to store lifetime data and QR data within animal profiles and QR profiles, respectively. The database may also be configured to store quality scores created via algorithms using the lifetime data and QR data of the animal.” and Moss [0044] “Lifetime data 440 may be defined as data describing the health of an animal 402 over its lifetime, including, but not limited to, heart rate data 440A, respiration rate data, physical activity data 440B, temperature data, and blood oxygen saturation level (SPO.sub.2) data 440C, or any combination thereof.”), (b) a natural living score, indicative of compliance of a behavior pattern of the respective member with a desired natural behavior pattern (Moss [0051] “In yet another preferred embodiment, the at least one sensor 407 may be used to measure general behavior of the animal 402.”), or (c) an affectivity/happiness score, indicative of compliance of an affectivity/happiness measure of the respective member with a desired affectivity/happiness measure (Moss [0051] “For instance, the at least one sensor 407 may be used to determine how much time an animal 402 spends near a trough having a connecting sensor to estimate the amount of food and/or water the animal 402 is consuming.”); and
(B) a welfare score of the members of the animal population based on the at least two of: (a) the health scores calculated for the first group of members, (b) the natural living scores calculated for a second group of members, or (c) the affectivity/happiness scores calculated for a third group of members (Moss [0006] “One preferred embodiment of the system may comprise a plurality of databases operably connected to the processor. The plurality of databases may be configured to store lifetime data and QR data within animal profiles and QR profiles, respectively.” and Moss [0049] “The data block 530 preferably represents a historical data point representing the quality of a cut of meat 420 in the form of a substantially linear set of records outlining the wellness of the animal 402 prior to fabrication and the processing of that animal 402 from the fabrication floor to the store. When combined with a quality score 445, the new data block 530B represents the cut of meat 420 and the most up-to-date version of the wellness history of the live animal 402.” and Moss [0057] “To determine the quality score 445, lifetime data 440 and QR data 435 relating to all variables measured is gathered and compiled. Based on this data, the system 400 may generate a score… In a preferred embodiment, the quality score 445 is calculated by the system 400 using qualitative analysis methods. This may be performed by the system 400 by determining the stress level of an animal 402 over its lifetime using lifetime data 440. For instance, the system 400 may use heartrate data 440A, activity data 440B, and blood oxygen saturation data 440C to predict the stress an animal 402 experienced throughout its lifetime.”).
Moss fails to explicitly teach identifying declining animal conditions of a single animal or a group of animals of an animal population; analyze historical and/or statistical data of one or more animal population to determine at least one welfare threshold; compare the calculated welfare score against the determined welfare threshold; and identify whether said members are exposed to declining welfare conditions, and upon identifying declining welfare conditions, determine an action directed at improving said welfare conditions.
Donavon teaches identifying declining animal conditions of a single animal or a group of animals of an animal population (Donavon [0057] “By way of another example, and not by way of limitation, collected and analyzed data regarding the body weight of the animal can be indicative or otherwise informative of changes over time (e.g., over/under weight, over/under feeding; protein levels; by-breed comparisons; onset of illness; gastrointestinal issues; diseases, conditions, or other health issues (e.g., thyroid problems, tumors, etc.); energy balance; need to change foods based on life stage (e.g., when weight plateaus in puppies, begins declining in older dogs, etc.); effectiveness of weight loss/gain programs or diets; daily caloric needs; resting metabolism; water/food intake; combinations thereof; and the like. These collected data and analysis may, in turn, lead to outcomes and recommendations regarding one or more of changes in environment; initiating, limiting, or increasing exercise protocols; administration or cessation of vitamins, supplements, or medication; initiating or modifying training protocols; nutritional/feeding changes; veterinary visits; combinations thereof; and the like.”);
analyze historical and/or statistical data of one or more animal population to determine at least one welfare threshold (Donavon [0035] “The data is analyzed using various algorithms, formulas, and calculations which, in essence, codify fundamental expert knowledge and applied science and research regarding health, nutrition, and wellness characteristics of animals, as well as predictive analytics, to create a system that is capable of continuously screening the new data and comparing it to historically derived data. In this way, important and meaningful outcomes, insights, and predictions can be identified and communicated to the relevant individuals.” and Donavon [0063] “Expert review in real-time or over an extended period of time is used to determine the optimum therapeutic/nutritional index or recommendation for that particular animal or animal class. For example, if a threshold level or baseline of the collected data discussed above is breached, appropriate action can be recommended by the expert and taken by the animal owner or other individual.”):
compare the calculated welfare score against the determined welfare threshold (Donavon [0035] “The data is analyzed using various algorithms, formulas, and calculations which, in essence, codify fundamental expert knowledge and applied science and research regarding health, nutrition, and wellness characteristics of animals, as well as predictive analytics, to create a system that is capable of continuously screening the new data and comparing it to historically derived data. In this way, important and meaningful outcomes, insights, and predictions can be identified and communicated to the relevant individuals.” and Donavon [0063] “Expert review in real-time or over an extended period of time is used to determine the optimum therapeutic/nutritional index or recommendation for that particular animal or animal class. For example, if a threshold level or baseline of the collected data discussed above is breached, appropriate action can be recommended by the expert and taken by the animal owner or other individual.”);
identify whether said members are exposed to declining welfare conditions, and upon identifying declining welfare conditions, determine an action directed at improving said welfare conditions (Donavon [0057] “By way of another example, and not by way of limitation, collected and analyzed data regarding the body weight of the animal can be indicative or otherwise informative of changes over time (e.g., over/under weight, over/under feeding; protein levels; by-breed comparisons; onset of illness; gastrointestinal issues; diseases, conditions, or other health issues (e.g., thyroid problems, tumors, etc.); energy balance; need to change foods based on life stage (e.g., when weight plateaus in puppies, begins declining in older dogs, etc.); effectiveness of weight loss/gain programs or diets; daily caloric needs; resting metabolism; water/food intake; combinations thereof; and the like. These collected data and analysis may, in turn, lead to outcomes and recommendations regarding one or more of changes in environment; initiating, limiting, or increasing exercise protocols; administration or cessation of vitamins, supplements, or medication; initiating or modifying training protocols; nutritional/feeding changes; veterinary visits; combinations thereof; and the like.”, Donavon [0004] “Among the various aspects of the present disclosure is the provision of methods of preparing a nutrition, health, and/or wellness recommendation for an animal. The recommendation (which may be, for example, in the form of a diet, exercise, medication/supplement, treatment protocol, and/or changes in animal owner and/or animal behavior), is prepared based upon data collected from the animal.”, Donavon [0005] “Briefly, therefore, the present disclosure is directed to a method of preparing a nutrition, health, and/or wellness recommendation for an animal. The method comprises collecting the data from the animal, analyzing the data, and providing the nutrition, health, and/or wellness recommendation based upon the analyzed data. Preferably, the collected data is one or more of a health, diet, behavior, or environmental parameter of the animal.”).
Therefore, it would be obvious to a PHOSITA before the effective filing date of the invention to combine the animal monitoring and wellness scoring system of Moss with the health recommendation and action suggestion techniques of Donavon in order to improve automated animal management.
Moss teaches obtaining physiological and behavioral data from sensors attached to animals, storing lifetime data within databases linked to individual animal profiles, and generating quality or wellness scores that reflect the animal’s stress level, activity, and overall health. Donavon teaches analyzing animal specific health and behavioral data over time to detect changes in condition and to produce recommendations or actions, such as modifying feed, temperature, exercise, or treatment, when thresholds or abnormal trends are observed.
A PHOSITA would have been motivated to integrate Donavon’s rule based recommendation functions into Moss’s wellness scoring framework to provide automated, data driven feedback and actions when the calculated scores indicate declining welfare conditions, because both references address automated monitoring and decision making for improving animal health and welfare. This modification represents the predictable use of prior art elements according to their established functions to yield an expected improvement in the same field, specifically, enhancing Moss’s monitoring system with Donavon’s responsive recommendation capability to enable proactive animal welfare management.
Regarding claim 2, Moss and Donavon teach the invention in claim 1, as discussed above, and further teach wherein the parameters include one or more of the following behavioral parameters: (a) percentage of movement time within a first time period of the given member, (b) percentage of feeding time within a second time period of the given member or (c) percentage of social behavior time within a third time period of the given member; and wherein the natural living score for the given member is determined based on the behavioral parameters (Moss [0057] “In a preferred embodiment, the quality score 445 is calculated by the system 400 using qualitative analysis methods. This may be performed by the system 400 by determining the stress level of an animal 402 over its lifetime using lifetime data 440. For instance, the system 400 may use heartrate data 440A, activity data 440B, and blood oxygen saturation data 440C to predict the stress an animal 402 experienced throughout its lifetime. For instance, the system 400 may use geolocation data or activity data 440B to predict how much exercise an animal 402 received throughout a period of its lifetime or its entire lifetime. In another preferred embodiment, the system 400 may calculate the quality score 445 using a quantitative data analysis.” and Donavon [0050] “It will be understood that, for a multi-animal home or dwelling, it will in many respects be advantageous to have the ability to uniquely identify each animal and the parameters of the same that are collect and analyzed. In this way, the systems and methods have the ability to uniquely identify individual animals using the same system so that the data analysis is unique to each animal regardless of identity or even species (e.g., the possibility of having a single system in a home that captures data for both dogs and cats). For example, where multiple animals use a single waste container, each animal could be identified or distinguished based upon trends or observations (such as by weight, typical time of day of use, typical length of stay in the container, typical amount of waste deposited, etc.). By way of another example, where multiple animals use a single food and/or water container, each animal could be identified or distinguished based upon trends or observations (such as by weight, typical time of day of feeding/watering, typical length of stay at the food/water container, typical amount of food/water consumed, etc.). By way of further example, multiple measurement devices (e.g., including sensors) can be employed to accommodate multiple animals, such as distinct food/water containers, sleeping/resting locations, etc. In this way, the various systems and methods described herein can support any combination of single or multiple animals and single or multiple measurement/sensor devices.”).
Therefore, it would be obvious to a PHOSITA before the effective filing date of the invention to determine a “natural living score” based on behavioral parameters such as movement, feeding, or social activity, as recited in claim 2, because Moss teaches deriving wellness and stress related quality scores from animal activity and lifetime data, and Donavon teaches monitoring animal behavior patterns (feeding and social habits) for individualized analysis. A PHOSITA would have been motivated to incorporate Donavon’s detailed behavioral tracking techniques into Moss’s wellness scoring framework to improve the accuracy of animal behavior assessment, resulting in predictable performance benefits using known methods in the same field.
Regarding claim 3, Moss and Donavon teach the invention in claim 1, as discussed above, and further teach wherein the natural living score for the given member is determined based on consistency of values of at least some of the parameters over time (Moss [0057] “In a preferred embodiment, the quality score 445 is calculated by the system 400 using qualitative analysis methods. This may be performed by the system 400 by determining the stress level of an animal 402 over its lifetime using lifetime data 440. For instance, the system 400 may use heartrate data 440A, activity data 440B, and blood oxygen saturation data 440C to predict the stress an animal 402 experienced throughout its lifetime. For instance, the system 400 may use geolocation data or activity data 440B to predict how much exercise an animal 402 received throughout a period of its lifetime or its entire lifetime. In another preferred embodiment, the system 400 may calculate the quality score 445 using a quantitative data analysis.” and Donavon [0111] “This example highlights how the ability to acquire and view a animal's data over an extended period of time can identify insights into potential health and wellness concerns that might not be obvious to the pet owner. If Frasier's weight had been the only data tracked, it could have been possible to overlook the significance of the weight change by not seeing actual food/water consumption and activity data. The ability to see multiple, relevant data types on a single animal, longitudinally, provided surprising insight into our ability to analyze and assess changes in the data that might indicate changes in relative trends that can identify the potential of increased levels of risk to the pets health and wellness.”).
Therefore, it would be obvious to a PHOSITA before the effective filing date of the invention to determine a natural living score based on consistency of behavioral parameters over time, as recited in claim 3, because Moss teaches evaluating wellness trends from long term lifetime and activity data, and Donavon teaches the importance of longitudinal data analysis to detect deviations in animal behavior and health. A PHOSITA would have recognized that assessing parameter consistency over time is a known and predictable improvement to trend based welfare scoring systems to enhance the reliability of condition detection.
Regarding claim 6, Moss and Donavon teach the invention in claim 1, as discussed above, and further teach wherein the parameters include one or more of the following affectivity/happiness parameters: (a) respiration level of the given member, (b) percentage of rumination time within a fourth time period of the given member, or (c) percentage of feeding time within a fifth time period of the given member; and wherein the affectivity/happiness score for the given member is determined based on the affectivity/happiness parameters (Moss [0044] “Lifetime data 440 may be defined as data describing the health of an animal 402 over its lifetime, including, but not limited to, heart rate data 440A, respiration rate data, physical activity data 440B, temperature data, and blood oxygen saturation level (SPO.sub.2) data 440C, or any combination thereof.” and Moss [0057] “In a preferred embodiment, the quality score 445 is calculated by the system 400 using qualitative analysis methods.”).
Therefore, it would be obvious to a PHOSITA before the effective filing date of the invention to determine an affectivity/happiness score based on physiological parameters such as respiration level, rumination time, or feeding duration, as recited in claim 6, because Moss teaches using physiological measures, including respiration rate, activity level, and feeding behavior, to calculate an animal’s stress and quality score. Incorporating these parameters into a welfare or happiness score would have been a routine and predictable use of known physiological data to improve existing wellness scoring techniques.
Regarding claim 7, Moss and Donavon teach the invention in claim 1, as discussed above, and further teach wherein the affectivity/happiness score for the given member is determined based on consistency of values of at least some of the parameters over time (Moss [0057] “In a preferred embodiment, the quality score 445 is calculated by the system 400 using qualitative analysis methods. This may be performed by the system 400 by determining the stress level of an animal 402 over its lifetime using lifetime data 440. For instance, the system 400 may use heartrate data 440A, activity data 440B, and blood oxygen saturation data 440C to predict the stress an animal 402 experienced throughout its lifetime.” and Donavon [0111] “This example highlights how the ability to acquire and view a animal's data over an extended period of time can identify insights into potential health and wellness concerns that might not be obvious to the pet owner. If Frasier's weight had been the only data tracked, it could have been possible to overlook the significance of the weight change by not seeing actual food/water consumption and activity data. The ability to see multiple, relevant data types on a single animal, longitudinally, provided surprising insight into our ability to analyze and assess changes in the data that might indicate changes in relative trends that can identify the potential of increased levels of risk to the pets health and wellness.”).
Therefore, it would be obvious to a PHOSITA before the effective filing date of the invention to determine the affectivity/happiness score based on consistency of physiological and behavioral values over time, as recited in claim 7, because Moss teaches tracking health and stress indicators longitudinally and Donavon teaches that viewing animal data over extended periods reveals health and wellness trends. A PHOSITA would have been motivated to integrate timing consistency into Moss’s scoring framework to enhance stability of affectivity assessments, yielding a predictable improvement using established techniques.
Regarding claim 10, Moss and Donavon teach the invention in claim 1, as discussed above, and further teach wherein the welfare score is calculated based on a variation between the affectivity/happiness scores of the first group of the members (Moss [0057] “To determine the quality score 445, lifetime data 440 and QR data 435 relating to all variables measured is gathered and compiled. Based on this data, the system 400 may generate a score.” and Donavon [0119] “The data described FIGS. 19-23 was collected on a single cat using a single litter box over multiple days. While no software-based algorithms or analytics were designed into the prototype system that acquired this data, observation and manual analysis of the data clearly illustrate the ability to identify litter box engagement patterns such as event frequency, duration and time-of-day patterns and the level of variability that exists within and across these measures.”).
Therefore, it would be obvious to a PHOSITA before the effective filing date of the invention to calculate a welfare score based on variation between affectivity or happiness scores across members of the animal group, as recited in claim 10, because Moss teaches generating composite quality scores by aggregating lifetime and behavioral data across multiple animals, and Donavon teaches analyzing variability and patterns across time series data (event frequency, duration, and variability in behavior). A PHOSITA would have been motivated to incorporate variation analysis between individual scores to enhance the precision of group level welfare assessment, since measuring each animal’s variability is a known and predictable technique for identifying abnormal or declining conditions within a population.
Regarding claim 13, Moss and Donavon teach the invention in claim 1, as discussed above, and further teach wherein the records also include one or more environmental parameters, indicative of the state of the environment of the respective member and wherein the determination of (a) the natural living score of the respective member or (b) of the affectivity/happiness score of the respective member, is also based on the environmental parameters (Moss, [0057] “In a preferred embodiment, the quality score 445 is calculated by the system 400 using qualitative analysis methods. This may be performed by the system 400 by determining the stress level of an animal 402 over its lifetime using lifetime data 440. For instance, the system 400 may use heartrate data 440A, activity data 440B, and blood oxygen saturation data 440C to predict the stress an animal 402 experienced throughout its lifetime. For instance, the system 400 may use geolocation data or activity data 440B to predict how much exercise an animal 402 received throughout a period of its lifetime or its entire lifetime.” and Moss [0022] “The term “stress” and grammatical equivalents thereof are used herein to mean an environmental/social stimulus that evokes an unconscious physiological response that alters the behavior/metabolism of an animal or group of animals. The term “wellness” and grammatical equivalents thereof are used herein to mean the fitness of an animal or group of animals based upon physiological parameters informing health and well-being.”).
Therefore, it would be obvious to a PHOSITA before the effective filing date of the invention to include environmental parameters in determining the natural living or affectivity/happiness score, as recited in claim 13, because Moss teaches that stress and wellness are influenced by environmental and social stimuli and that environmental data such as geolocation and temperature may be used in evaluating animal wellness. A PHOSITA would have recognized that integrating environmental information (climate, housing, or habitat conditions) into welfare scoring would yield more accurate assessments, representing the predictable use of known techniques to improve similar systems in the same field.
Regarding claim 18, Moss and Donavon teach the invention in claim 1, as discussed above, and further teach wherein the action is one or more of: a treatment to be administered to the animal population, a change in temperature of an environment of the animal population, a change in feed of the animal population, or a change in a schedule of the animal population (Donavon [0057] “By way of another example, and not by way of limitation, collected and analyzed data regarding the body weight of the animal can be indicative or otherwise informative of changes over time (e.g., over/under weight, over/under feeding; protein levels; by-breed comparisons; onset of illness; gastrointestinal issues; diseases, conditions, or other health issues (e.g., thyroid problems, tumors, etc.); energy balance; need to change foods based on life stage (e.g., when weight plateaus in puppies, begins declining in older dogs, etc.); effectiveness of weight loss/gain programs or diets; daily caloric needs; resting metabolism; water/food intake; combinations thereof; and the like. These collected data and analysis may, in turn, lead to outcomes and recommendations regarding one or more of changes in environment; initiating, limiting, or increasing exercise protocols; administration or cessation of vitamins, supplements, or medication; initiating or modifying training protocols; nutritional/feeding changes; veterinary visits; combinations thereof; and the like.”, Donavon [0004] “Among the various aspects of the present disclosure is the provision of methods of preparing a nutrition, health, and/or wellness recommendation for an animal. The recommendation (which may be, for example, in the form of a diet, exercise, medication/supplement, treatment protocol, and/or changes in animal owner and/or animal behavior), is prepared based upon data collected from the animal.”, Donavon [0005] “Briefly, therefore, the present disclosure is directed to a method of preparing a nutrition, health, and/or wellness recommendation for an animal. The method comprises collecting the data from the animal, analyzing the data, and providing the nutrition, health, and/or wellness recommendation based upon the analyzed data. Preferably, the collected data is one or more of a health, diet, behavior, or environmental parameter of the animal.”).
Therefore, it would be obvious to a PHOSITA before the effective filing date of the invention to specify that the suggested action based on the welfare score includes one or more of treatment, environmental temperature adjustment, feed change, or schedule modification, as recited in claim 18. Donavon teaches providing actionable recommendations such as altering diet, exercise, temperature, or treatment protocols based on analyzed animal data to improve wellness outcomes. A PHOSITA would have been motivated to incorporate these well known types of interventions into Moss’s welfare scoring system to enable direct, automated guidance following detection of declining conditions, thereby enhancing the system and achieving predictable improvements in animal management.
Claim 26 is analogous to claim 1, thus claim 26 is similarly analyzed and rejected in a manner consistent with the rejection of claim 1.
Claims 27-28 are analogous to claims 2-3, thus claims 27-28 are similarly analyzed and rejected in a manner consistent with the rejection of claims 2-3.
Claims 31-32 are analogous to claims 6-7, thus claims 31-32 are similarly analyzed and rejected in a manner consistent with the rejection of claims 6-7.
Claim 35 is analogous to claim 10, thus claim 35 is similarly analyzed and rejected in a manner consistent with the rejection of claim 10.
Claim 38 is analogous to claim 13, thus claim 38 is similarly analyzed and rejected in a manner consistent with the rejection of claim 13.
Claim 43 is analogous to claim 18, thus claim 43 is similarly analyzed and rejected in a manner consistent with the rejection of claim 18.
Claim 50 is analogous to claim 1, thus claim 50 is similarly analyzed and rejected in a manner consistent with the rejection of claim 1.
Response to Arguments
Applicant’s arguments and amendments, see Remarks/Amendments submitted on 12/08/2025 with respect to the rejection of the claims have been carefully considered and is addressed below.
Claim Rejections - 35 USC § 101
Applicant’s arguments have been fully considered but are not persuasive. Although the claims have been amended to recite “near real time” calculations, analysis of historical or statistical data, and determination of an action, these additions do not remove the claims from the abstract idea category. The amended claims still recite, at a high level of generality, the collection of animal monitoring data, evaluation of that data to calculate condition scores, comparison of calculated values to thresholds, and determination of a responsive action. Under their broadest reasonable interpretation, these steps remain directed to mental processes and certain methods of human activity, even if automation of these processes makes the processes faster or more scalable.
The recitation of “near real-time” processing does not impose any specific technical constraint on the claimed processing circuitry and does not reflect an improvement to computer or sensor technology. Rather, it merely describes the timeliness with which a generic computer performs conventional data analysis. As stated in Electric Power Group, increased speed or automation does not render the claim patent eligible without a specific technological improvement.
Additionally, the limitation of “determining an action directed at improving said welfare conditions” does not integrate the abstract idea into a practical application. The claims do not require execution of a physical action, control of machinery, or modification of a technical system, but instead determine or suggest an action based on the evaluated information. This result oriented decision making is a form of managing or directing behavior and remains within the abstract idea of organizing information to guide decisions. The claimed data repository and processing circuitry are recited generically and function only as tools to perform the abstract data analysis steps.
Accordingly, even when the claims are considered as an ordered combination, the additional limitations amount to no more than implementing an abstract idea on generic computer components performing well understood, routine, and conventional activities. The claims therefore remain directed to an abstract idea and do not include significantly more. The rejection under 35 U.S.C. § 101 is therefore maintained.
Claim Rejections - 35 USC § 103
Applicant’s arguments have been considered but are not persuasive. Although is described by Applicant as being limited to post slaughter meat quality assessment, Moss discloses monitoring live animals using attached sensors, collecting lifetime physiological and behavioral data, storing that data in animal specific profiles, and generating algorithmic scores indicative of animal wellness, stress, and health prior to slaughter. Just because Moss applies these scores in a meat quality context does not discredit its disclosure of monitoring live animals and computing wellness related scores from physiological and behavioral parameters. The claims do not require a particular end use of the computed scores beyond identifying declining animal conditions and determining responsive actions, which are included in Moss’s teachings.
Applicant’s statements regarding the absence of express terms such as “affectivity/happiness” or “natural living” in Moss is not persuasive. The claims do not require any specific nomenclature for these scores, but broadly recite scores indicative of health state, behavior compliance, or affective condition based on monitored parameters. Moss discloses collecting and analyzing activity, stress, feeding, and physiological data to generate wellness or quality scores, which correspond to the broadly claimed score categories under the broadest reasonable interpretation. A reference does not disclose the same terminology as the claims to teach the claimed subject matter.
Regarding near real time processing, the claims or the specification do not require a specific update interval. Moss’s disclosure of periodically updated lifetime data and algorithmic scoring remains responsive to the claimed limitation of calculating scores “in near real time,” which is a relative description. Additionally, the optimization of update frequency represents a routine choice that would have been obvious to one of ordinary skill in the art seeking to adapt known animal monitoring systems for more timely assessment for animal conditions.
Donavon teaches analyzing animal data over time to detect changes in condition and generating recommendations or actions directed to improving animal health, environment, or behavior. Donavon therefore teaches the claimed limitations of identifying declining conditions and determining actions responsive to such conditions. Combining Donavon’s recommendation and action logic with Moss’s animal monitoring and wellness scoring system would have been obvious to a person of ordinary skill in the art to improve automated animal management by allowing responsive interventions when monitored data indicates declining welfare. This represents a predictable use of prior art elements according to their established functions.
Applicant’s arguments regarding multi group segmentation, historical threshold derivation, and cross dependent scoring relationships do not align with the scope of the claims. The claims broadly recite obtaining subsets of records, computing scores for groups of animals, determining thresholds from historical or statistical data, and comparing values to identify declining conditions. These steps are routine data analysis techniques that fall within the combined teachings of Moss and Donavon and do not require any particular data structure, algorithm, or nonconventional processing arrangement. The rejection does not rely on impermissible hindsight, but instead on the combination of references addressing the same problem, automated monitoring and improvement of animal health and welfare.
Accordingly, the Examiner maintains that claims would have been obvious to a person of ordinary skill in the art at the time of the invention over Moss view of Donavon. The rejection under 35 U.S.C. § 103 is therefore maintained.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure.
Elazari-Volcani et al. (International Patent Publication No. WO 2014118788A2) teaches a system and method for early prediction of conditions affecting livestock population that includes optically tracking behavior of identified or unidentified sentinel individuals within a sample or flock, re-identifying or marking sentinels as needed, and detecting population conditions, such as disease outbreak, breeding status, or treatment efficacy, based on patterns of behavioral change.
Stroman et al. (U.S. Patent Publication 2008/0059264A1) teaches integrated systems and methods that connect livestock industry participants thorough shared data and communication tools to track, manage, and enhance the value and efficiency of animal from conception to consumption.
Cook et al (U.S. Publication 2015/0359200 A1) teaches a system and method that uses real time, non-invasive infrared thermography to capture both thermal and behavioral data from a group of animals, enabling earlier and more accurate detection of disease onset, growth, or reproductive states by combining thermal biometric data and behavioral information.
Neethirajan et al. (Neethirajan, S.; Kemp, B. Social Network Analysis in Farm Animals: Sensor-Based Approaches. 2021, Animals, 11, 434. (Year: 2021)) teaches how social network analysis (SNA), combined with sensor-based data collection, can enhance the understanding of animal social behaviors in farm settings, improving welfare assessments and livestock management. By comparing sensor-collected data with traditional observation methods, the invention highlights the potential of automated technologies to provide real-time insights that inform farm practices and animal well-being.
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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/K.R.L./Examiner, Art Unit 3685
/KAMBIZ ABDI/Supervisory Patent Examiner, Art Unit 3685