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 .
Status of Claims
This is a first action on the merits in response to the application filed on 03/10/2025.
Claims 1 – 8 are currently pending and have been examined in this application.
Claim Rejections – 35 U.S.C. § 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 – 8, are rejected under 35 U.S.C. § 101 because the claimed invention is directed towards an abstract idea without significantly more
Claim 1 recites:
A method of determining a performance index (PI) for monitoring a key performance indicator (KPI) comprising:
a. identify a plurality of animals;
d. to collect and analyze the data;
e. grouping the data into one or more sets for analysis;
and f. calculating one or more PIs for the KPIs where the PIs represent an average performance normalized to a percentage to show the performance of one or more of the data sets against the other data sets.
The limitations of claim 1, under its broadest reasonable interpretation, recites mental processes related to observation and evaluation of data and uses a computer as a tool to perform mental processes. For example, in claim 1, the steps of observe a plurality of animals, observes and evaluate the data; grouping the data into one or more sets for evaluation; and evaluating one or more PIs for the KPIs where the PIs represent an average performance normalized to a percentage to show the performance of one or more of the data sets against the other data sets; however these limitations all involve observation and evaluation of data to calculate a performance index. Accordingly, claim 1 recites an abstract idea of mental processes.
The dependent claims encompass the same abstract ideas as well. For instance, claim 2, is directed towards observing the KPI is a factor related to the health of the animals; claim 3 is directed towards observing the KPI is a factor related to the environment of the animals; claim 5 us directed towards observing the PI is a composite PI comprised of multiple KPIs; claim 6 is directed towards observing individual PIs in the composite PI are weighted to create the composite PI; claim 7 is directed towards observing the animals are cattle; and claim 8 is directed towards observing KPIs are factors associated with the cattle operations; where all these dependent claims involve observation of data. Accordingly, the dependent claims further limit the abstract idea.
These judicial exceptions are not integrated into a practical application. Claim 1 recites the additional elements of a plurality of sensors, a plurality of data collection devices associated with devices, a data transmission system for transmitting the data for storing and processing, and a data collection and analysis system using computer controlled operations. However, the additional elements of a plurality of sensors, a plurality of data collection devices associated with devices, a data transmission system for transmitting the data for storing and processing, and a data collection and analysis system using computer controlled operations are considered generic computer components performing generic computer functions as per Applicant’s Specifications shown below:
“[0013] Third, data transmission systems such as wireless technologies like Wi-Fi, Bluetooth, or similar systems enable smooth data transfer between the above sensors and systems and downstream systems that read, store, and analyze the data. Fourth, data collection and analysis systems such as livestock management software systems running on remote computing devices such as through SaaS or cloud based software systems, or similar software deployed on servers located near the livestock operations, store, arrange, and display the above referenced data for users such as livestock managers.”
and thus, are not practically integrated nor significantly more.
The claims do not include additional elements that are sufficient to amount significantly more than the judicial exception. Each of the additional limitations are no more than mere instructions to apply the exception using generic computer components (e.g., processor). The combination of these additional elements are no more than mere instructions to apply the exception using generic computer components (e.g., processor). the additional elements do not impose meaningful limits on practicing the idea. Thus, the claims are directed to an abstract idea. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
Dependent claims 2 – 8, when analyzed both individually and in combination are also held to be ineligible for the same reason above and the additional recited limitations fail to establish that the claims are not directed to an abstract idea. The additional limitations of the dependent claims when considered individually and as an ordered combination do not amount to significantly more than the abstract idea.
Looking at these limitations as ordered combination and individually add nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use generic computer components, to “apply” the recited abstract idea. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amount to significantly more than the abstract idea itself. Therefore, claims 1 – 8 are not patent eligible under 35 U.S.C. § 101.
Claim Rejections – 35 U.S.C. § 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
4. Claims 1 – 8, are rejected under 35 U.S.C. § 103 as being unpatentable over Biffert, Kevin N. et al. (U.S. Publication No. 2022/0192151) hereinafter “Biffert” in view of Rapaport-Rom, Yuval et al. (U.S. Publication No. 2025/0005677) hereinafter “Rapaport-Rom”.
Claim 1:
Biffert teaches the following:
a. providing a plurality of sensors to identify a plurality of animals; Biffert teaches in ¶ 0107, if included, the RFID transceiver 92 is operative to transmit and receive data wirelessly with other nearby RFID transceivers that are within signal range. The RFID transceiver 92 may comprise a commercially available RFID transceiver. In addition to each of the tags 20, RFID transceivers 92 may also be embedded in sensor(s) 32 implanted in and/or attached to the livestock 12 to which the tags 20 are attached and in local sensors and transceivers 34 that are located in various areas or locations of a property under management where livestock 12 may be present. Such sensor(s) 32 and local sensors and transceivers 34 are described further below. Each tag 20 is thus adapted and configured to communicate wirelessly and directly with the sensor(s) 32 implanted in and/or attached to the livestock 12 to which the tag 20 is attached, and with every other nearby tag 20 and every local sensor and transceiver 34 within RFID signal range via their respective RFID transceivers 92. Biffert teaches in ¶ 0108, it will be appreciated that some or all of the communication functions performed by the RFID transceiver 92 embedded in the tag 20 may also be performed by the Bluetooth transceiver 84 and/or the LPWAN transceiver 88. Accordingly, an RFID transceiver 92 may not be necessary and may not be included in all embodiments. Biffert teaches in ¶ 0109, If an RFID transceiver 92 is included, in lieu of embedding it in the tag 20, it may be embedded in a chip that is implantable in an ear or other body part of the livestock 12 separate from the tag 20. In that case, the chip and the RFID transceiver 92 may be powered externally by sunlight, a laser light, or by energy from an external RFID reader or scanner. Upon being powered up, the chip and RFID transceiver 92 would be adapted and configured to communicate directly with the tag 20 and to transfer its information directly to the tag 20. The chip can also be read by a scanner/reader, for example to identify an animal with which a tag 20 is associated when the tag 20 has become detached and fallen off the animal. Such data could include, but is not limited to, information identifying the livestock 12 and associated tag 20, e.g., unique identification number and tag ID. The chip and RFID transceiver 92 could thus operate as a redundant backup of the tag data should the tag 20 become detached, damaged, or otherwise unavailable or unusable.
b. providing a plurality of data collection devices associated with devices that the animals interact with; Biffert teaches in ¶ 0092, the communications (COMMS) interface 62 provides interfaces to a number of different communication channels over which the tag 20 can communicate. These include channels for communicating with one or more sensors 32 implanted in and/or attached to the livestock 12 to which the tag 20 is attached, with other nearby tags 20, with nearby local sensors and transceivers 34, with the management system platform 140, with the remote computer system 220, and with global positioning satellites 83; Biffert teaches in ¶ 0093, the LED 64, microphone (MIC) 66, tone generator 68 with speaker, stimulator 70, and camera 72 components are adapted and configured to collect various forms of data from the external environment and to communicate and interact with the livestock 12 to which the tag 20 is attached.
c. providing a data transmission system for transmitting the data for storing and processing; Biffert teaches in ¶ 0047, each tag 20 in a dynamic local mesh network at any given time can be adapted and configured to receive all or a subset of the data of each other tag 20 in the network and to transmit all or a subset of its own data to every other tag 20 in the network. Biffert teaches in ¶ 0082, the data collection, processing, storage, communications, and control components and elements of each tag 20 may include a processor and memory element 50, a three-axis accelerometer 52, a three-axis gyroscope 54, a compass 56, an altimeter 58, a barometer 59, non-volatile memory (NVM) 60, a communications (COMMS) interface 62, one or more LED's 64, a microphone (MIC) 66, a tone generator 68 and speaker, a stimulator 70, a camera 72, an air temperature sensor 74, and a humidity sensor 76. The three-axis accelerometer 52 and the three-axis gyroscope 54, collectively, may comprise or be referred to as an Inertial Measurement Unit 55. When the accelerometer 52 is being used, the gyroscope may also be used in unison to detect motion of the livestock.
d. providing a data collection and analysis system using computer controlled operations to collect and analyze the data; Biffert teaches in ¶ 0172, The tag 20 can detect the presence of a loud noise, such as a gunshot or vehicle motor, from audio data acquired or received from the microphone 66. In the same manner, the tag 20 can detect the presence of noise associated with another potentially dangerous condition, e.g., flowing water. The tag 20 can acquire, record, e.g., store, and analyze audio data from the microphone 66 periodically or on demand. The microphone 66 can also include circuitry that automatically responds to a loud sound and automatically provides a sample of the audio. The tag 20 can store the audio data without analysis for subsequent communication to the management system platform 140. Alternatively, the tag 20 and/or the management system platform 140 can analyze the audio by comparing it to stored samples or by executing an AI model or other algorithm to attempt to identify the nature of the noise. The tag 20 preferably stores or records audio data with the time and date it was acquired or received to assist a rancher or herd manager with any subsequent investigation or evaluation of the noise.
e. grouping the data into one or more sets for analysis; Biffert teaches in ¶ 0274, the management system platform 140 can monitor, track, update, and maintain data about a selected group of livestock 12 or the entire herd under management. Such herd data can include for example, but is not limited to, location(s), head count, demographics, etc. The management system platform 140 is adapted and configured to aggregate and process the data and information regarding individual livestock 12 received as input data from one or more input devices 146, from one or more external sources, from the tags 20 attached to individual livestock 12, and from the local sensors and transceivers 34 as described herein to produce the herd data.
Biffert teaches a livestock management system, tags on livestock that includes cattle, collecting data with sensors, aggregating livestock data, and receives and/or acquires physical parameters of the livestock and conditions external to livestock from one or more sensors and Biffert and Rapaport-Rom are related where Biffert and Rapaport-Rom teach collecting and analyzing data on livestock and Rapaport-Rom further teaches the following:
A method of determining a performance index (PI) for monitoring a key performance indicator (KPI) associated with an animal, comprising: Rapaport-Rom teaches in ¶ 0056, the method further comprises calculating, based on the subset of the records, for each given member of the first group of given members, at least one of: (a) an animal health score indicative of a health state of the respective member, (b) an animal natural living score, indicative of compliance of a behavior pattern of the respective member with a desired natural behavior pattern, or (c) an animal affectivity/happiness score, indicative of compliance of an affectivity/happiness measure of the respective member with a desired affectivity/happiness measure, the affectivity/happiness measure being determined based on one or more of the following monitored parameters, being affectivity/happiness parameters: (1) respiration level of the given member, (2) percentage of rumination time within a fourth time period of the given member, or (3) percentage of feeding time within a fifth time period of the given member; and wherein: the health score is calculated based on the animal health scores calculated for the first group of given members; and the welfare score is calculated based on the at least one of: (a) the health score, (b) the animal natural living scores calculated for the first group of given members, or (c) the animal affectivity/happiness scores calculated for the first group of given members.
and f. calculating one or more PIs for the KPIs where the PIs represent an average performance normalized to a percentage to show the performance of one or more of the data sets against the other data sets; Rapaport-Rom, teaches in ¶ 0159, turning to animal welfare, it can be determined for a specific animal or for a group of animals using one or more animal welfare Key Performance Indicators (KPIs). The animal welfare KPIs can include a health score (that can be determined as detailed herein), an affectivity/happiness score and/or a natural living score. Rapaport-Rom teaches in ¶ 0222, The health score 120 of the members of the animal population can be used for calculating a health index indicative of the overall health level of the members of the animal population. In some cases, the health index can be used for identifying morbidity levels in the animal population. For example, a health index showing that more than a threshold (e.g., around 5%) of the animals in the animal population are having health scores 120 below a threshold can be an indication of a developing health problem within the animal population. A health index showing that more than a second threshold (e.g., around 10%) of the animal population are having health scores below a threshold can be an indication of a prevailing health problem. A health index showing that more than a third threshold (e.g., around 20%) of the animal population are having health scores below a threshold can be indicative of a pandemic.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine a livestock management system for detecting, tracking, and responding to livestock location and physical parameters, and for determining livestock behavior and physical conditions correlated of Biffert with a system for determining insurance parameters, the system comprising: one or more monitoring devices configured to monitor parameters of members of an animal population of Rapaport-Rom to assist businesses with implementing systems the determine performance indicators for livestock (Rapaport-Rom, Spec. ¶ 0159).
Claim 2:
Biffert and Rapaport-Rom teach claim 1. Biffert teaches a livestock management system, tags on livestock that includes cattle, collecting data with sensors, aggregating livestock data, and receives and/or acquires physical parameters of the livestock and conditions external to livestock from one or more sensors and Biffert and Rapaport-Rom are related where Biffert and Rapaport-Rom teach collecting and analyzing data on livestock and Rapaport-Rom further teaches the following:
where the KPI is a factor related to the health of the animals; Rapaport-Rom teaches in ¶ 0157, It is to be noted that analysis of the health scores can enable identification of given animals of the group of animals that have a certain health issue (e.g., illness, lameness, estrus, etc.). In some cases, analysis of the health index (generated based on the health scores of the animals in the group) can enable, at the population level, identifying whether the overall health level of the animal in the group is above an acceptable predetermined health threshold.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine a livestock management system for detecting, tracking, and responding to livestock location and physical parameters, and for determining livestock behavior and physical conditions correlated of Biffert with a system for determining insurance parameters, the system comprising: one or more monitoring devices configured to monitor parameters of members of an animal population of Rapaport-Rom to assist businesses with implementing systems the determine performance indicators for livestock (Rapaport-Rom, Spec. ¶ 0159).
Claim 3:
Biffert and Rapaport-Rom teach claim 1. Biffert teaches a livestock management system, tags on livestock that includes cattle, collecting data with sensors, aggregating livestock data, and receives and/or acquires physical parameters of the livestock and conditions external to livestock from one or more sensors and Biffert and Rapaport-Rom are related where Biffert and Rapaport-Rom teach collecting and analyzing data on livestock and Rapaport-Rom further teaches the following:
where the KPI is a factor related to the environment of the animals; Rapaport-Rom teaches in ¶ 0065, 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 animal natural living score of the respective member or (b) of the animal affectivity/happiness score of the respective member, is also based on the environmental parameters.
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine a livestock management system for detecting, tracking, and responding to livestock location and physical parameters, and for determining livestock behavior and physical conditions correlated of Biffert with a system for determining insurance parameters, the system comprising: one or more monitoring devices configured to monitor parameters of members of an animal population of Rapaport-Rom to assist businesses with implementing systems the determine performance indicators for livestock (Rapaport-Rom, Spec. ¶ 0159).
Claim 4:
Biffert and Rapaport-Rom teach claim 1. Biffert further teaches the following:
where the sensors are attached to the animals; Biffert teaches in ¶ 0004, tags fitted with sensors and electronics have been attached externally to various body parts of cattle and other livestock as components of livestock management systems to record and communicate data regarding the location, certain physical parameters, and the health and welfare of the livestock. For example, such tags have been attached to the ears, dewlap, and brisket regions of cattle. Any discussion of the related art throughout the specification should in no way be considered as an admission that such related art is widely known or forms part of common general knowledge in the field.
Claim 5:
Biffert and Rapaport-Rom teach claim 1. Biffert further teaches the following:
where the PI is a composite PI comprised of multiple KPIs; Biffert teaches in ¶ 0317, indicators of medical and health-related data can include vaccinations, medicines, etc. Indicators of physical conditions can include illness, injury, estrus, pregnancy, abortion, calving.
Claim 6:
Biffert and Rapaport-Rom teach claim 1. Biffert further teaches the following:
where the individual PIs in the composite PI are weighted to create the composite PI; Biffert teaches in ¶ 0187, The data from the other tags 20 comprises the data acquired and received by the other tags 20 in the dynamic local mesh network during operation and that is to be aggregated and communicated to the management system platform 140 and/or the remote computer system 220 by the tag 20 that is determined to be in the optimal condition to transmit the data. The data and updates from the management system platform 140 and/or the remote computer system 220 can include data and information to be stored in the local memory of the tag 20 and/or updates to data and information stored in the local memory. The data and updates can also include new or updated programs, algorithms, or applications to be stored and executed in the tag 20. The data and updates can also include new or updated AI models, model parameters, weights or other values, etc. to be executed in the tag 20. For example, as the tags 20 continue to communicate data to the management system platform 140 and/or the remote computer system 220, the AI models that were created can be refined, updated, and trained to make more accurate determinations and predictions.
Claim 7:
Biffert and Rapaport-Rom teach claim 1. Biffert further teaches the following:
where the animals are cattle; Biffert teaches in ¶ 0060, While it is contemplated that the example livestock management system as described herein will be particularly useful for managing livestock, in particular cattle, it is contemplated and will be appreciated that it can also be used more generally to manage other domesticated animals and even wild animals.
Claim 8:
Biffert and Rapaport-Rom teach claim 1. Biffert further teaches the following:
where the KPIs are factors associated with the cattle operations; Biffert teaches in ¶ 0126, the tag 20 autonomously and automatically processes some or all of the acquired and stored data locally and autonomously and automatically performs various livestock management functions and operations locally. Broadly, the tag 20 is adapted and configured to perform functions and operations that include and are based on detecting, monitoring and tracking the absolute location of the livestock 12, and the position and orientation of the livestock 12 relative to other nearby livestock 12. The tag 20 also is adapted and configured to perform functions and operations that include detecting, determining, and monitoring certain physical parameters, activities, and behaviors of the livestock 12, and determining health-related and other physical conditions of the livestock 12 that are correlated thereto. The tag 20 is also adapted and configured to perform functions and operations that include detecting the presence of external conditions that may indicate a threat or risk to the well-being of the livestock.
Conclusion
The prior art made of record and not relied upon is considered relevant but not applied:
Note: these are additional references found but not used.
- Reference Fichman; Alon et al. (U.S. Publication No. 2024/0090473 ) discloses An animal marking control system includes: at least one transceiver communicatively coupled to a remote base station (BS) and configured to exchange data with the BS, the transceiver having a plurality of operation modes (OMs), each of the OMs defining a respective frequency of communication (FoC) of the transceiver with the BS.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Frank Alston whose telephone number is 703-756-4510. The Examiner can normally be reached 9:00 AM – 5:00 PM Monday - Friday. Examiner can be reached via Fax at 571-483-7338. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s supervisor Beth Boswell can be reached at (571) 272-6737.
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/FRANK MAURICE ALSTON/
Examiner, Art Unit 3625
05/29/2026
/BETH V BOSWELL/Supervisory Patent Examiner, Art Unit 3625
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