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 .
Claim Objections
Claim 1, 12, 13, 14, 17, 27, and 29 are objected to because of the following informalities:
“analysing” should be corrected to “analyzing”
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
Video module for capturing video data in claim 1, and 17
Sensing module for detecting one or more conditions in claim 1, and 17
Identifying module for identifying in claim 1, 11, 17
Identifying module is adapted to process a computer implemented algorithm in claim 10
Analysing module for analysing in claim 1, 13, and 17
Analysing module is adapted to processing a computer implemented algorithm in claim 12
Actuating module adapted to automatically adjust or modify the one or more conditions of the aquatic environment in claim 14
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
The video module has sufficient structure in at least pg. 7 paragraph 1, “the video module 110 may comprise one or more video cameras 30”. The sensing module has sufficient structure in at least pg.7 paragraph 2, “sensing module 120 may comprise one or more sensing devices comprising internet-of-things (IoT) devices such as, but are not limited to, one or more of a temperature sensor 6, a color sensor 7, a pH sensor 8, a chemical sensor 9 such as an ammonia sensor 9, a turbidity sensor 11, a conductivity sensor 12, a pressure sensor 13, a sensor for dissolved oxygen 14, a water level sensor 15, and a leak sensor 18, etc. The sensing module 120 is adapted to detect one or more conditions of the aquatic environment, which may include, but are not limited to, temperature, pH, ammonia level, color of water, turbidity of water, conductivity of water, pressure of water, oxygen level”. The identifying module has sufficient structure in at least pg. 8 paragraph 2, “The identification or extraction of visual characteristics of the life forms can be processed by using artificial intelligent-based software which may include…computer vision programs or algorithms”. The actuating module has sufficient structure in at least pg. 11 paragraph 2, “actuating module 160 may comprise one or more of a feeding device 19, a lighting device 3, a cooling device 17, a heating device 16, a water level controller 20, a water pump 5, a chemical dispenser 21, a filter 5 and/or a timer 22”.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-32 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim limitation, “analyzing module for analyzing the detected one or more conditions” in independent claim 1 and, “analyzing, by an analyzing module, the detected one or more conditions” in independent claim 17 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Pg. 8 describes, “the analyzing module which may comprise or be provided as a component at a processor”, and pg. 9 describes, “the analyzing module 150 analyzes the detected one or more conditions…by processing the AI-based algorithm”. It appears the analyzing module is attributed to a general-purpose computer executing a program. However, the specification provides no detail of the acts being executed to perform the function, nor would it be readily apparent to one of ordinary skill in the art. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
The terms “erratic swimming”, “lacking of energy”, “wobbly swimming”, and “slow to react to stimuli”, in claims 4 and 20 are relative terms which renders the claim indefinite. The terms are not defined by the claim, and the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Thereby the behavioral pattern being identified is indefinite.
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-32 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Regarding the, “analyzing module”, the specification appears to describe the analyzing module as a general-purpose computer executing a program. However, the specification provides no written description of the computer implemented structure performing the function. Particularly, the software is described as an AI based algorithm in at least pg. 9 lines 25-26, and further described that the AI-based software may include one or more machine learning and/or data analytic programs or algorithms on pg. 8 lines 10-12. There are no further descriptions provided than these general statements.
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 1-13, 16-28, and 31-32 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that Claims 1-13, 16-28, and 31-32 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories (i.e. process, a computer readable medium, i.e. a system)? YES. Claims 1-16 are directed to a system, and Claims 17-32 are directed to a method.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? YES, the claims are directed towards an abstract idea – mental process.
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
- Mathematical concepts — mathematical relationships, mathematical formulas or equations, mathematical calculations;
- Certain methods of organizing human activity — fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations
- Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgement, opinion).
The claim(s) recite(s):
Regarding Claim 1, representative of claims 17, 31, and 32, the claim recites an aquarium management system, comprising:
a video module for capturing video data comprising a series of frames showing an aquatic environment containing one or more life forms (see step 2A prong 2 – insignificant extra solution activity/ mere data gathering step);
a sensing module for detecting one or more conditions of the aquatic environment (see step 2A prong 2 – insignificant extra solution activity/ mere data gathering step);
an identifying module for identifying, from one or more frames of the video data, one or more visual characteristics of the life forms (mental process including observation and evaluation, and can be done practically in the human mind or by a human using pen and paper); and
an analysing module for analysing the detected one or more conditions of the aquatic environment and the identified one or more visual characteristics of the life forms thereby determining a quality of the aquatic environment (mental process including observation, evaluation, and judgement and can be done practically in the human mind).
Regarding Claim 2, representative of Claim 18, the claim recites the aquarium management system according to claim 1, wherein the one or more visual characteristics of the life forms comprise one or more of a size, a color, a shape, a texture, a position, an orientation and/or a location of the life forms as shown in the one or more frames of the video data (mental process including observation, evaluation, and judgement and can be done mentally in the human mind).
Regarding Claim 3, representative of Claim 19, the claim recites the aquarium management system according to claim 1, wherein the identifying module is adapted to derive one or more behavioral pattern of the life forms based on the one or more identified visual characteristics of the life forms (mental process including observation, evaluation, and judgement and can be done mentally in the human mind).
Regarding Claim 4, representative of Claim 20, the claim recites the aquarium management system according to claim 3, wherein the one or more behavioural patterns of the life forms comprise one or more of the following actions: air gulping, staying at water surface, staying at bottom of a tank of the aquarium, not eating, erratic swimming, swimming upside down, accelerating or decelerating, jumping out of water, lacking of energy, spasming, nipping at other life forms in the tank, wobbly swimming, slow to react to stimuli, rubbing against other items and/or other life forms in the tank (mental process including observation, evaluation, and judgement and can be done mentally in the human mind).
Regarding Claim 5, representative of Claim 21, the claim recites the aquarium management system according to claim 1, wherein the sensing module comprises one or more of a temperature sensor, a color sensor, a pH sensor, a chemical sensor, a turbidity sensor, a conductivity sensor, a pressure sensor, a sensor for dissolved oxygen, a water level sensor, and a leak sensor (see step 2A prong 2 – insignificant extra solution activity/ mere data gathering step).
Regarding Claim 6, representative of Claim 22, the claim recites the aquarium management system according to claim 1, wherein the one or more conditions of the aquatic environment comprise one or more of a temperature, a pH, ammonia level, a color of water, turbidity of water, conductivity of water, pressure of water, oxygen level (see step 2A prong 2 – insignificant extra solution activity/ mere data gathering step).
Regarding Claim 7, representative of Claim 23, the claim recites the aquarium management system according to claim 1, wherein the video module comprises one or more video cameras (see step 2A prong 2 – insignificant extra solution activity/ mere data gathering step. Examiner notes the claim only puts limitations on how the data should be gathered).
Regarding Claim 8, the claim recites the aquarium management system according to claim 7, wherein the one or more video cameras comprise two video cameras arranged to capture videos from different directions (see step 2A prong 2 – insignificant extra solution activity/ mere data gathering step. Examiner notes the claim only puts limitations on how the data should be gathered).
Regarding Claim 9, representative of Claim 24, the claim recites the aquarium management system according to claim 1, further comprising one or more databases for storing one or more of the following data: the captured video data, the identified one or more visual characteristics of the life forms, the detected one or more conditions of the aquatic environment, and/or the determined quality of the aquatic environment (see step 2A prong 2 – insignificant extra solution activity).
Regarding Claim 10, representative of Claim 25, the claim recites the aquarium management system according to claim 9, wherein the identifying module is adapted to process a computer implemented algorithm, the algorithm comprising one or more computer vision algorithms (see step 2A prong 2 – additional element merely includes instructions to implement an abstract idea on a generic computer recited at a high level of generality).
Regarding Claim 11, representative of Claim 26, the claim recites the aquarium management system according to claim 10, wherein the identifying module identifies the one or more visual characteristics of the life forms from the one or more frames of the video data based on the data (mental process including observation, evaluation, and judgement and can be done mentally in the human mind) stored in the one or more databases (see step 2A prong 2 – insignificant extra solution activity).
Regarding Claim 12, representative of Claim 27, the claim recites the aquarium management system according to claim 9, wherein the analysing module is adapted to processing a computer implemented algorithm, the algorithm comprising one or more of a machine learning algorithm and/or a data analytic algorithm (see step 2A prong 2 – additional element merely includes instructions to implement an abstract idea on a generic computer recited at a high level of generality).
Regarding Claim 13, representative of Claim 28, the claim recites the aquarium management system according to claim 12, wherein the analysing module analyses the detected one or more conditions of the aquatic environment and the identified one or more visual characteristics of the life forms based on the data (mental process including observation, evaluation, and judgement and can be done mentally in the human mind) stored in the one or more databases (see step 2A prong 2 – insignificant extra solution activity).
Regarding Claim 16, the claim recites the aquarium management system according to claim 1, wherein the one or more life forms comprise aquatic micro-organisms, animals and/or plants (mental process including observation, evaluation, and judgement and can be done mentally in the human mind. Examiner notes the claim only puts a limitation on what life forms for which visual characteristics are being identified/observed).
These limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same). The mere nominal recitation that the various steps are being executed by a device/in a device (e.g. processing unit) does not take the limitations out of the mental process grouping.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? NO, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claims 1-13, 16-28, and 31-32 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? NO, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Claims 1-13, 16-28, and 31-32 do not recite any additional elements that are not well-understood, routine or conventional.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-8, 14-23, and 29-32 are rejected under 35 U.S.C. 102(a)(2) as being unpatentable by Kozachenok (US 20210329891 A1).
Regarding Claim 1, representative of Claims 17, 31, and 32, Kozachenok teaches an aquarium management system, comprising:
a video module for capturing video data comprising a series of frames showing an aquatic environment containing one or more life forms ([0039]: the one or more cameras of the first image sensor system 202a are configured to capture image data corresponding to, for example, the presence (or absence), abundance, distribution, size, and behavior of underwater objects (e.g., a population of fish, [0043]: Such imaging sensors of the first image sensor system 202a may be configured to capture, single, static images and/or also video);
a sensing module for detecting one or more conditions of the aquatic environment ([0044]: second set of one or more sensors include one or more environmental sensors configured to monitor the environment 204 below the water surface and generate data indicative of one or more environmental conditions associated with the marine enclosure);
an identifying module for identifying, from one or more frames of the video data, one or more visual characteristics of the life forms ([0039]: image data corresponding to, for example, the presence (or absence), abundance, distribution, size, and behavior of underwater objects (e.g., a population of fish, [0058]: classifiers determines class labels for underwater objects in image data including, for example, a species of fish, a swimming pattern of a school of fish, a size of each fish, a location of each fish); and
an analysing module for analysing the detected one or more conditions of the aquatic environment and the identified one or more visual characteristics of the life forms ([0047]: the processing system 210 receives one or more data sets 212 (e.g., image data set 212a and environmental data set 212b)…the image data set…describes presence (or absence), abundance, distribution, size, and/or behavior of underwater objects, [0051]: image data captured by one or more cameras of the first image sensor system 202a) and environmental data (which in various embodiments includes at least a subset of environmental data captured by one or more environmental sensors of the second sensor system 202b) is provided as training data to generate trained models 214 using machine learning techniques and neural networks) thereby determining a quality of the aquatic environment ([0052]: the training data includes various images of underwater objects (e.g., fish 206) that are annotated or otherwise labeled with label instances (e.g., bounding boxes, polygons, semantic segmentations, instance segmentations, and the like) that identify, for example, individual fish, parasites in contact with the fish, [0063]: machine learning techniques may be used to … identify relationships (e.g., as embodied in the trained models 214) between sensor data (including image and/or environmental data) and laser operating parameters sufficient for administering lethal energy doses to parasites).
Regarding Claim 2, representative of Claim 18, Kozachenok teaches the aquarium management system according to claim 1. In addition, Kozachenok teaches wherein the one or more visual characteristics of the life forms comprise one or more of a size, a color, a shape, a texture, a position, an orientation and/or a location of the life forms as shown in the one or more frames of the video data ([0039]: capture image data corresponding to, for example, the presence (or absence), abundance, distribution, size, and behavior of underwater objects (e.g., a population of fish, [0043]: Such imaging sensors of the first image sensor system 202a may be configured to capture…video).
Regarding Claim 3, representative of Claim 19, Kozachenok teaches the aquarium management system according to claim 1. In addition, Kozachenok teaches wherein the identifying module is adapted to derive one or more behavioural pattern of the life forms based on the one or more identified visual characteristics of the life forms ([0081]: the image data set 212a includes image data representing any image-related value or other measurable factor/characteristic that is representative of at least a portion of a data set describing the presence (or absence), abundance, distribution, size, and/or behavior of underwater objects, [0047]: image data may be indicative of, for example, movement of one or more objects, orientation of one or more objects, swimming pattern or swimming behavior of one or more objects, jumping pattern or jumping behavior of one or more objects, any activity or behavior of one or more objects, [0058]: classifiers determines class labels for underwater objects in image data including… a swimming pattern of a school of fish).
Regarding Claim 4, representative of Claim 20, Kozachenok teaches the aquarium management system according to claim 3. In addition, Kozachenok teaches wherein the one or more behavioural patterns of the life forms comprise one or more of the following actions: air gulping, staying at water surface, staying at bottom of a tank of the aquarium, not eating, erratic swimming, swimming upside down, accelerating or decelerating, jumping out of water, lacking of energy, spasming, nipping at other life forms in the tank, wobbly swimming, slow to react to stimuli, rubbing against other items and/or other life forms in the tank ([0047]: image data may be indicative of, for example, movement of one or more objects, orientation of one or more objects, swimming pattern or swimming behavior of one or more objects, jumping pattern or jumping behavior of one or more objects, [0058]: classifiers determines class labels for underwater objects in image data including… a swimming pattern of a school of fish).
Regarding Claim 5, representative of Claim 21, Kozachenok teaches the aquarium management system according to claim 1. In addition, Kozachenok teaches wherein the sensing module comprises one or more of a temperature sensor, a color sensor, a pH sensor, a chemical sensor, a turbidity sensor, a conductivity sensor, a pressure sensor, a sensor for dissolved oxygen, a water level sensor, and a leak sensor ([0049]: environmental data set 212b includes environmental data indicating environmental conditions such as, for example, an ambient light level, an amount of dissolved oxygen in water, a direction of current, a strength of current, a salinity level, a water turbidity, a topology of a location, a weather forecast, and any other value or measurable factor/characteristic that is representative of environmental conditions proximate to the marine enclosure 208…for example.. ambient light sensor… turbidity sensor…).
Regarding Claim 6, representative of Claim 22, Kozachenok teaches the aquarium management system according to claim 1. In addition, Kozachenok teaches wherein the one or more conditions of the aquatic environment comprise one or more of a temperature, a pH, ammonia level, a color of water, turbidity of water, conductivity of water, pressure of water, oxygen level ([0049]: environmental data set 212b includes environmental data indicating environmental conditions such as, for example, an ambient light level, an amount of dissolved oxygen in water, a direction of current, a strength of current, a salinity level, a water turbidity, a topology of a location, a weather forecast, and any other value or measurable factor/characteristic that is representative of environmental conditions proximate to the marine enclosure 208).
Regarding Claim 7, representative of Claim 23, Kozachenok teaches the aquarium management system according to claim 1. In addition, Kozachenok teaches wherein the video module comprises one or more video cameras ([0043]: various operations are described here in the context of multi-camera configurations… such imaging sensors of the first image sensor system 202a may be configured to capture, single, static images and/or also video).
Regarding Claim 8, Kozachenok teaches the aquarium management system according to claim 7. In addition, Kozachenok teaches wherein the one or more video cameras comprise two video cameras arranged to capture videos from different directions ([0040] In various embodiments, each camera (or lens) of the one or more cameras of the first image sensor system 202a has a different viewpoint or pose (i.e., location and orientation) with respect to the environment, [0041]: the imaging sensors of the first image sensor system 202a includes at least a second camera having a different but overlapping field of view (not shown) relative to the first camera (or lens)).
Regarding Claim 14, representative of Claim 29, Kozachenok teaches the aquarium management system according to claim 1. In addition, Kozachenok teaches further comprising an actuating module adapted to automatically adjust or modify the one or more conditions of the aquatic environment in response to the quality of the aquatic environment determined by the analysing module ([0064]: the trained models 214 include an output function representing learned laser system operating parameters, [0076]: the dynamic sensor operating parameter reconfiguration of system 200 improves laser operations so that parasite control is effective across various conditions and species without requiring physical repositioning of sensors).
Regarding Claim 15, representative of Claim 30, Kozachenok teaches the aquarium management system according to claim 14. In addition, Kozachenok teaches wherein the actuating module comprises one or more of a feeding device, a lighting device ([0064]: the trained models 214 include an output function representing learned laser system operating parameters, [0076]: the dynamic sensor operating parameter reconfiguration of system 200 improves laser operations so that parasite control is effective across various conditions and species without requiring physical repositioning of sensors), a cooling device, a heating device, a water level controller, a water pump, a chemical dispenser a filter and/or a timer.
Regarding Claim 16, Kozachenok teaches the aquarium management system according to claim 1. In addition, Kozachenok teaches wherein the one or more life forms comprise aquatic micro-organisms, animals and/or plants ([0080]: monitor an individual fish, multiple fish, or an entire population of fish within the marine enclosure 208).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 9-13, and 24-28 are rejected under 35 U.S.C. 103 as being unpatentable over Kozachenok (US 20210329891 A1) in view of Wang (US 20220079125 A1).
Regarding Claim 9, representative of Claim 24, Kozachenok teaches the aquarium management system according to claim 1. In addition, Kozachenok teaches further comprising ([0093]: the processing system 110 receives one or more sensor data sets 112 (e.g., first sensor data set 112a and the environmental sensor data set 112b) and stores the sensor data sets 112 at the storage device 116 for processing).
Kozachenok does not explicitly teach one or more databases for storing.
Wang teaches one or more databases for storing ([abstract]: current invention discloses a holding tank monitoring system based on a wireless sensor network and a monitoring method, [0014]: computer receives the conditions from the sensor, stores received condition in a database).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present invention to have modified the teachings of Kozachenok by the teachings of Wang by substituting the data storage for a database. Doing so would provide the predictable result of data storage for sensor data.
Regarding Claim 10, representative of Claim 25, the Kozachenok and Wang combination teaches the aquarium management system according to claim 9. In addition, Kozachenok teaches wherein the identifying module is adapted to process a computer implemented algorithm, the algorithm comprising one or more computer vision algorithms ([0056]: in some embodiments, the image training data may utilize image-level labels, such as for weakly supervised segmentation, [0058] In some embodiments, machine learning classifiers are used to categorize observations in the training image data. For example, in various embodiments, such classifiers generate outputs including one or more labels corresponding to detected objects. In various embodiments, the classifiers determines class labels for underwater objects in image data including, for example, a species of fish, a swimming pattern of a school of fish, a size of each fish, a location of each fish, estimated illumination levels, a type of activity that objects are engaged).
Regarding Claim 11, representative of Claim 26, the Kozachenok and Wang combination teaches the aquarium management system according to claim 10. Kozachenok teaches wherein the identifying module identifies the one or more visual characteristics of the life forms from the one or more frames of the video data based on the data ([0052]: the training data includes various images of underwater objects (e.g., fish 206) that are annotated or otherwise labeled with label instances (e.g., bounding boxes, polygons, semantic segmentations, instance segmentations, and the like) that identify, for example, individual fish, parasites in contact with the fish, feed pellets in the water, and various other identifiable features within imagery)
In addition, Wang teaches data stored in the one or more databases ([abstract]: current invention discloses a holding tank monitoring system based on a wireless sensor network and a monitoring method, [0014]: computer receives the conditions from the sensor, stores received condition in a database).
Regarding Claim 12, representative of Claim 27, the Kozachenok and Wang combination teaches the aquarium management system according to claim 9. In addition, Kozachenok teaches wherein the analysing module is adapted to processing a computer implemented algorithm, the algorithm comprising one or more of a machine learning algorithm and/or a data analytic algorithm ([0063]: machine learning techniques may be used to determine various relationships between training images and the contextual image data to learn or identify relationships (e.g., as embodied in the trained models 214) between sensor data (including image and/or environmental data) and laser operating parameters sufficient for administering lethal energy doses to parasites).
Regarding Claim 13, representative of Claim 28, the Kozachenok and Wang combination teaches the aquarium management system according to claim 12. Kozachenok teaches wherein the analysing module analyses the detected one or more conditions of the aquatic environment and the identified one or more visual characteristics of the life forms based on the data ([0063]: machine learning techniques may be used to determine various relationships between training images and the contextual image data to learn or identify relationships (e.g., as embodied in the trained models 214) between sensor data (including image and/or environmental data) and laser operating parameters sufficient for administering lethal energy doses to parasites)
In addition, Wang teaches data stored in the one or more databases ([abstract]: current invention discloses a holding tank monitoring system based on a wireless sensor network and a monitoring method, [0014]: computer receives the conditions from the sensor, stores received condition in a database).
Conclusion
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/JANICE E. VAZ/Examiner, Art Unit 2667
/MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667
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