DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office action is responsive to the communication received on 08/26/2026. The claims 1, 5- 20, & 22-24 are pending, of which the claim(s) 1, 9, & 15 is/are in independent form.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Response to Arguments
I) Applicant’s arguments, see Remarks (page 15), filed 08/26/2026, with respect to amended claim 1 have been fully considered and are persuasive. The outstanding 103 rejection of claim 1 has been withdrawn.
II) Applicant’s arguments, see Remarks, filed 08/26/2026, with respect to the rejection(s) of amended claim 9 have been fully considered and are persuasive. Therefore, the outstanding rejection of this claim has been withdrawn.
Specifically, while Greenberg teaches of “receiving user data from a user device, the user data” and using the received user data to determine at least one parameter (like “temperature setting”) change to the greenhouses (see, paras. 035, 063, Figs. 1-2 allow/shows devices 150s to provide user inputs to the cloud/platform via double headed arrows using network 120), Greenberg still fails to clarify the user data including “plant consumption 1preferences”.
However, upon further consideration, a new ground(s) of rejection is made in view of discovery of new prior art and its combination with prior cited arts as discussed below that clearly teaches “receiving user data from a user device, the user data including plant consumption preferences” and using the user data to determine at least one parameter like temperature setting. See JP 2020053039 A to Higashide in pages 4, 7-8.
Page 7: “The target number of harvests in each week is displayed in the table of FIG. It is assumed that the target harvest number is input in advance by the operator via the input unit 95.”
“ Next, in step S20, the adjustment unit 40 adjusts the set temperature such that the maximum harvestable number in the greenhouse 18 approaches the target value (target harvest number), and the information output unit 38 outputs the adjustment result”.
III) Applicant's arguments (see pages 20 & 221) filed 08/26/2026 with respect to claim 15 and its dependent claims have been fully considered but they are not persuasive.
Arguments against Claim Rejections - 35 USC § 103
As to claim 15, applicant argues that “For at least the reasons presented above with respect to amended claim 9, the combination of Greenberg and Moeller fail to teach or suggest the above referenced features of amended claim 15. Accordingly, Applicant respectfully requests that the Office withdraw the § 103 rejection of claim 15.”
Response: Examiner respectfully disagrees. Please note that unlike the claim 9, the claim 15 does not require “user input data from a user device” for “including plant consumption preferences”. Hence, applicant’s comment that states the claim 15 overcomes Greenberg for the similar reasons as claim 9 is not commensurate with the actual scope of the claim 15.
As to the limitation of “user input data from a user device”, please note that Greenberg clearly states (see, para. 035, 063, Fig. 2 for items 230- 234 to interact with the platform 110/cloud 216) users including growers to provide feedback or other inputs to the platform 110 to generate adjustments to be made for the greenhouses. For example, the para. 035 states: “an agricultural machine learning or cognitive network model may be implemented with a feedback loop to update the recommendations based on currently available data. At least some of this data may be data shared by growers.”
Hence, the updated recommendations in Greenberg are based on inputs/feedback provided/shared/entered by users/growers. The outstanding 103 rejection of claim 15 is respectfully maintained.
Argument against Claim Rejections - 35 USC § 112 and 112(f) interpretation
Examiner notes in page 10 of the Remarks, applicant argues (in substance) that the amended claim 15 will render moot to the outstanding 112(b) rejections and 112(f) interpretations both. Applicant argues:
“Applicant herein amends claim 15 as shown above. Applicant respectfully submits that these amendments render the § 112(b) rejections moot… Applicant herein amends claims 15-20 as shown above. Applicant respectfully submits that these amendments render the § 112(f) rejections moot.”
Response: Examiner respectfully disagrees. In an attempt to cure the outstanding 112(b) rejection and 112(f) interpretations, applicant has merely amended claim 15’s preamble to add the word “management” before the word “system” and nothing more. Here, the claim element under 112(f) interpretation and subsequently under 112(b) rejection is “a system” of limitation of “a system to execute operations associated with decision engine instructions” in line 14, but not the element of the preamble. Since this element continues to meet 3-prong test set forth in MPEP 2181, this is still interpreted according to 112(f). Furthermore, specification fails to clearly describe the scope of this element for the reasons stated in last office action, the outstanding 112(b) rejection is also respectfully maintained.
Claim Objections
Claim 15- 20 objected to because of the following informalities:
In claim 15, lines 8- 9, claim elements of “a first growing appliance” and “a second growing appliance” should be changed to “[[a]] the first growing appliance” and “[[a]] the second growing appliance” respectively. This is to improve the clarity with recitation of these elements of lines 2 and 5 respectively.
Claims 16- 20 are also objected to because of their dependency with objected claim 15.
Appropriate correction is required.
Allowable Subject Matter
Claims 1, 5-8, & 22- 24 allowed.
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.
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:
In claim 15 line 14:
“a system to execute operations associated with decision engine
instructions”: Fig. 2 shown as item 216, Spec para. 044
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.
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
Claims 15- 20 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.
Regarding claim 15:
The claim limitation “a system to execute operations associated with decision engine instructions” (see claim 15, last limitation) invoke 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.
Specifically for the limitation of “a system to execute operations”, there is no disclosure of adequate structure to perform the claimed function. This limitation appears as being performed by the item 216 and also merely mentioned in para.044. The specification further states that-- “access a datastore housing configuration data 218” and “the decision system 216 may apply a multi-arm bandit technique to the received data”, and “The mirror copy and any proposed or suggested updates by the decision system 216 may be input into the machine learned models and/or networks and the configuration system 220”. Thus, specification links different algorithms (input outputs to access a datastore or an algorithm that applies multi-arm bandit technique, using of mirror copy input) to this limitation but still fails to clarify the full scope of this limitation to clarify what is included and what is not included in the scope of claimed “a system”. Furthermore, it is not clear how this element (“a system”, last limitation of claim 15) is similar or different from general purpose computer hardware and software system. Accordingly, the BRI of this claim element is indefinite.
Note: For the examination purpose, any generation purpose computer/processor performing the claimed function is mapped as claimed “a system to execute operations associated with decision engine instructions”.
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.
Regarding claims 16- 20, they are also rejected because of their dependency with the rejected claim 15.
Claim Rejections - 35 USC § 103
Claim(s) 9- 10 & 13- 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Greenberg et al. (US 20210304326 A1) in view of Moeller (US 20200315111 A1), and further in view of Higashide et al. (JP 2020053039 A, Publication Date: 2020-04-02, see attached machine translated FOR document).
Greenberg and Moeller were cited in earlier mailed Office action. The combination of Greenberg, Moeller, and Higashide referred to GMH hereinafter.
Regarding claim 9, Greenberg teaches a system [“implementation of a platform for collecting and analyzing high-fidelity data from greenhouses or other growing sites”, e.g., item 110 of fig. 1 or item 212 of fig. 2 or item 330 of fig. 3] for controlling a physical aspect of a first controlled physical environment of a first enclosure: one or more processors; and one or more non-transitory computer readable media storing instructions executable by the one or more processors, wherein the instructions, when executed, cause the system to perform operations comprising: ([016, 048], Figs. 1-3);
[a] receiving first sensor data [“platform for collecting and analyzing high-fidelity data from greenhouses or other growing sites”] from a first sensor of a first system [first greenhouse/growing sites out of many “greenhouses or other growing sites”, e.g., left greenhouse 202 of fig. 2], the first sensor data representing a first region associated with a first enclosure of the first system, the first enclosure configured to provide a first controlled physical environment ([016, 042-043], Fig. 2);
[b] receiving second sensor data from a second sensor of a second system [right side greenhouse of the “greenhouses or other growing sites”], the second sensor data [data from image capture device 208 and/or other data that are provided from the 2nd Greenhouse 202] representing a second region associated with a second enclosure of the second system, the second enclosure configured to provide a second controlled physical environment ([016, 042-043], Fig. 2);
[c] receiving user data [data provided to the cloud/platform from the users like growers as shown by double headed arrows between platform 110 and devices 150, e.g., “network model may be implemented with a feedback loop to update the recommendations…At least some of this data may be data shared by growers… model may be trained using the input data and, based on grower feedback, the model may be rewarded based on its output”] from a user device,
[d] determining, based [“collect information for every plant in a given operation… comparison to similar plants”] at least in part on the first sensor data and the second sensor data, and the user data [“model may be trained using the input data and, based on grower feedback, the model may be rewarded based on its output”], at least one parameter [“generate timely and accurate recommendations for designing new feedstock, mixtures/combinations of existing”] for the first system, wherein the at least one parameter [“transmitting data”] includes one or more of [“a light intensity or a light spectrum of existing… changing an amount of water or a frequency of a watering operation”] a lighting setting, a humidity setting, a temperature setting, or a water delivery setting ([016, 019, 035, 058, 0131-0140]); and
[e] causing the first system to apply [“transmitting data to a controller device associated with the plant growth operation”] the at least one parameter to alter a physical aspect of the first controlled physical environment ([058, 0136-0140]); and
[f]
Greenberg may or may not explicitly teach limitations shown with the strikethrough emphasis but are cured by Higashide and Moeller as shown below. That is, Greenberg may not teach:
(1) received user data from a user device to include “plant consumption preferences” in limitation [c]
(2) “causing the second system to apply the at least one parameter to alter a physical aspect of the second controlled physical environment” in limitation [f]. That is, Greenberg may not teach altering physical aspects of both controlled environments.
Moeller teaches system [“central irrigation controller/control system 204”, analogous to Greenberg’s platform/server] comprising a processor and computer readable media for controlling a physical aspect of a first controlled physical environment performing operations: receiving first sensor data [“the central irrigation controller 204 may preferably receive status updates from the individual valve assemblies 216, 220, 224 including state detection data”] from a first sensor of a first system [item 216+318 of “valve assemblies 216, 220, 224 and emitters 218, 222, 226.”] and receiving second sensor data from a second sensor of a second system [items 220+218, “valve assemblies 216, 220, 224 and emitters 218, 222, 226.”] ([026, 030]);
determining, based at least in part on the first sensor data and the second sensor
data, at least one parameter [“to determine complex changes to multiple controllers and transmit those instructions”] for the first system, wherein the at least one parameter includes one or more of a lighting setting, a humidity setting, a temperature setting, or a water delivery setting [changes to the valves in assembly 216 and 220 both] (Fig. 2, [027-028]).
causing the first system to apply the at least one parameter to alter [changes to the one of the controller 208 (of “multiple controllers”) of the valve assembly] a physical aspect of the first controlled physical environment; and causing the second system to apply the at least one parameter to alter [changes to another controller 208 of the valve assembly of “inputs to determine complex changes to multiple controllers and transmit those instructions to the control units for implementation by the various valve controllers 208”, wherein “he valve controller(s) 208 within each valve assembly 216, 220, 224 are in communication with the control system 204”] a physical aspect of the second controlled physical environment ([027-029], claim 19).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have (1) combined Moeller and Greenberg because they both related to a machine learning algorithm inputting monitored data from multiple crops growing systems to determine change parameters for the monitored systems and (2) modified the multiple Greenhouses of Greenberg to apply determined recommendations/one or more plant grower actions to multiple systems as in Moeller. Doing so would allow the determined optimum recommendations/plant “grower actions” from the machine learning model to be actually implemented in the pluralities of the greenhouses (growers/ “growing sites”) thereby realizing improvements across several plants monitored by the platform rather than only in only in one/first system (Greenberg, [019]).
Greenberg in view of Moeller does not teach the received user data also include “plant consumption preferences”.
Higashide relates to a computer system 10 (analogous to Greenberg’s platform 100/cloud 216) with prediction system 34 performing monitoring and controlling environment of enclosed physical environment (like greenhouse 18, analogous to Greenberg’s greenhouses 202s) with temperature adjustment device 16 and pluralities of sensors 14 (Figs. 1-3 & associated texts). Specifically, Higashide teaches A system for controlling a physical aspect of a first controlled physical environment of a first enclosure to perform:
receiving user data [“target value (target harvest number), wherein ‘It is assumed that the target harvest number is input in advance by the operator via the input unit 95.”] from a user device [“the input unit 95”], the user data including plant consumption preferences [“Next, in step S20, the adjustment unit 40 adjusts the set temperature such that the maximum harvestable number in the greenhouse 18 approaches the target value (target harvest number), and the information output unit 38 outputs the adjustment result.”]; and determining, based at least in part on the first sensor data [“temperature actually measured by the greenhouse sensor 14”], a second sensor data [e.g., “outdoor sensor 12 includes a temperature sensor for detecting an air temperature”], and the user data, at least one parameter for the first system, wherein the at least one parameter includes one or more of a lighting setting, a humidity setting, a temperature setting [“adjusts the set temperature”], or a water delivery setting (See, marked section of Pages 4, pages 7-8).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have (1) combined Higashide and Greenberg in view of Moeller because they both related to a system receiving multiple sensors data of the monitored greenhouses and controlling temperature and (2) modified the user data received from a user device of Greenberg in view of Moeller to include the user data including plant consumption preferences as in Higashide.
Doing so would allow adjusting the environment (e.g., temperature) inside the greenhouse of Greenberg in view of Moeller to obtain user desired consumption/harvest number so that systematic sales/contract shipment can be prepared or to appropriately allocate personnel for harvesting work (page 2). Therefore, the combination of Greenberg, Moeller, and Higashide (GMH) teaches each limitation of the claim and renders invention thereof obvious to PHOSITA.
Regarding claim 10, Greenberg teaches the system of claim 9, wherein
receiving first third party data from a first third party system [another plant out of many “other plants” growth operations of step 604 or one of the device 150 of figs. 1-2]; and wherein determining the at least one parameter for the first system is based at least in part on the user data and the first third party data (Figs. 2- 3, & 6, [046]).
Regarding claim 13, Greenberg further teaches the system of claim 9, wherein the operations further comprise: determining, based at least in part on the first sensor data, a first feature [“Operation 606 illustrates analyzing the sensor data and accumulated data to determine one or more conditions of the plants within the plant growth operation”] associated with a first plant inhabiting the first region; and wherein determining the least one parameter for the first system is based at least in part on the first feature (Figs. 6-7, [0107-0108, 0134-0135]).
Regarding claim 14, Greenberg further teaches the system of claim 13, wherein determining, based at least in part on the first sensor data [images taken], a first feature associated with a first plant [plant 206 of the greenhouse] inhabiting the first region further comprises: inputting the first sensor data into one or more machine learned models or networks; and receiving the first feature as an output from the one or more machine learned models or networks ([035-0041, 0119]).
Claim(s) 11- 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over GMH as in claim 9, and further in view of Bull et al. (US 20200077574 A1, reference of record).
Regarding claim 11, GMH teaches the system of claim 9 as set forth above but fails to teach remaining limitations.
As discussed above in claim 3, Bull teaches a system [“agricultural intelligence computer system 130] with a processor and memory for controlling crop growing system performing operations comprising:
receiving first cartridge data [information about a particular hybrid seed/seed bags provided to the computer 130 that causes to increase in yield for a first field/greenhouse] from a first third party system, the first cartridge data representing data and an identity of a first seed cartridge; determining, based at least in part on the first sensor data [yield data/production data from fields] and the first cartridge data, that the first seed cartridge is associated with the first third party system; determining, based at least in part on the first sensor data, a first metric associated with the first third party system; and adjusting [“increasing or decreasing a total number of seed bags that are delivered and planted”], based at least in part on the first metric, an order for additional seed cartridges with the first third party system ([097, 0231, 0241-0247, 0254, 0257]).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have (1) combined Bull and GMH because they both related to a server receiving various inputs from multiple data sources to generate upgrades/recommendations to improve productions and (2) modified the method/system of GMH to include missing limitations from Bull. Doing so would allow the generated recommendations or actions from the server of GHM to improve the planting strategies to the fields/greenhouses to increase agricultural productions or yields while reducing the loss in future planting (Bull [005]). Therefore, GMH in view of Bull teaches each limitation of the claim and renders invention thereof obvious to PHOSITA.
Regarding claim 12, GMH in view of Bull teaches/suggests wherein the operations further comprise: receiving second cartridge data from the first third party system, the second cartridge data representing data and an identity of a second seed cartridge; determining, based at least in part on the second sensor data and the second cartridge data, that the second seed cartridge is associated with the second region; determining, based at least in part on the second sensor data, a second metric associated with the first third party system; and adjusting, based at least in part on the second metric, the order for the additional seed cartridges with the first third party system (Greenberg, Figs. 2, 6 & Bull [0241-0247, 0257]).
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Greenberg et al. (US 20210304326 A1) in view of Moeller (US 20200315111 A1). Greenberg and Moeller are references of record.
Regarding claim 15, Greenberg teaches a management system comprising: (Figs. 1-2);
[a] a first growing appliance [one of the greenhouse 202 like left greenhouse 202 out of “Greenhouses 202”; the Greenhouses of Greenberg can be mapped to claimed appliance since it covers every possible type of the appliance(s)] to maintain a first controlled physical environment and to alter at least one physical aspect of the first controlled physical environment [providing controlled weather for plants 206] based at least in part on a configuration update [updated and transmitted “data to a controller device associated with the plant growth operation”] (Figs. 2- 3, [035, 043, 0136-0140]);
[b] a second growing appliance [another greenhouse 202 (like item 202 shown in right side of fig. 2) out of “greenhouses 202”] to maintain a second controlled physical environment
[c] a gateway [communication interface of the cloud with the monitored
greenhouses 202+ “platform”] for receiving at least first sensor data from a first growing appliance, second sensor data from a second growing appliance, and user input data [“a feedback loop to update… shared by growers… on grower feedback,
the model may be rewarded based on its output”. The growers are users and their feedback is user input data] from a user device and sending the configuration updates to the first growing appliance
a computer vision engine [classifying (item 444) and identifying (item
446) the sensor data] to segment or classify the first sensor data and the second sensor data ([083-084]), fig. 4); and
a system to execute operations [using of the "machine learning model" to generate actions/recommendations] associated with decision engine instructions, the operation to determine the configuration update [“the updating of the one or more plant grower actions”] based at least in part on an output of the computer vision engine and the user input data ([035-036, 0108, 0139, 0147]).
Greenberg may or may not teach:
its second growing appliance also to alter at least one physical aspect of the second controlled physical environment based at least in part on the configuration update and
the gateway to sending the configuration updates to the second growing appliance.
However, Moeller cures both of these deficiencies. Moller teaches a system comprising a central gateway [“central irrigation controller 204”] to receiving at least first sensor data from a first crop growing site and second sensor data from a second crop growing site and to process and determine one or more configuration updates to the both crops growing sites (Fig. 2). Specifically, Moeller teaches a system comprising: a first growing site to maintain a first controlled physical environment and to alter at least one physical aspect of the first controlled physical environment based at least in part on a configuration update [“machine learning techniques with the above inputs to determine complex changes to multiple controllers and transmit those instructions to the control units for implementation by the various valve controllers 208”]; a second growing site to maintain a second controlled physical environment and to alter at least one physical aspect of the second controlled physical environment based at least in part on the configuration update [determined and transmitted changes to the second controller from “complex changes to multiple controllers”] and a gateway system for receiving at least first sensor data from a first growing site, and sending [“inputs to determine complex changes to multiple controllers and transmit those instructions”] the configuration updates to the first growing site and the second growing site ([026-028]).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to have (1) combined Moeller and Greenberg because they both related to a machine learning algorithm processing data from multiple monitored crops growing systems to determine change parameter(s) for the monitored systems and (2) modified the a second growing appliance also to alter at least one physical aspect of the second controlled physical environment
based at least in part on the configuration update and the gateway to send configuration updates to the second growing appliance (greenhouse) as in Moeller. Doing so would allow the determined optimum recommendations/plant “grower actions” from the machine learning model to be actually implemented in the pluralities of the greenhouses (growers/ “growing sites”) thereby realizing improvements across several plants monitored by the platform rather than only in only in one/first system (Greenberg, [019]). Therefore, Greenberg in view of Moeller teaches each limitation of the claim and renders invention thereof obvious to PHOSITA.
Claim(s) 16- 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Greenberg in view of Moeller, and further in view of Bull et al. (US 20200077574 A1, reference of record). The combination of Greenberg, Moeller, and Bull is referred to as GMB hereinafter.
Regarding claim 16, Greenberg in view of Moeller teaches the system of claim 15, wherein the gateway is further configured to
receive [“supervised machine learning techniques by training on sensor data and user data as described herein”] external data external data
Greenberg in view of Moller further teaches that its system is capable of collecting data from various external sources but does not list the collected data to include information about “seed cartridge data”.
However, Greenberg in view of Moeller fails to teach its server’s gateway to receive seed cartridge data to use for determining the configuration update as claimed.
Bull teaches a system [“agricultural intelligence computer system 130] comprising: a gateway system to receive sensor data and fields data [data from sensors 112 or data of the agricultural apparatus 111 for a user 102 +data 106] from an agricultural fields and external information [data 110] other external systems [e.g., server 108] and generating one or more recommendations by analyzing the received sensor data (Fig. 1, [080, 097]). Specifically, Bull teaches a system comprising:
a gateway system for is further configured to receive seed cartridge data [information about “seed bags”/ “seed type” and “the server computer 108 accesses the grower yield data, seed type data, seed”] and the user data [“user input from user 102 specifying the data values”]; and the decision system is further configured to determine the configuration update [“apparatus 111 to adjust planting”] based at least in part on the seed cartridge data and the user data ([097, 0231, 0241-0247]).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to (1) combine Bull and Greenberg in view of Moeller because they both related to a server receiving various monitored inputs from multiple data sources to generate upgrades/recommendations to improve productions and (2) modify the system of Greenberg in view of Moeller to receive seed cartridge and use this data to determine the configuration update as in Bull. Doing so would allow the generated recommendations or actions from the server of Greenberg in view of Moeller to improve the planting strategies to the fields/greenhouses to increase agricultural productions/yields while reducing the loss (Bull [005]).
Regarding claim 17, GMB further teaches the system of claim 16, wherein the user data includes at least one criteria [“additional information pertaining to the plant growth operation” or various threshold values of Massey] for a plant associated with the first appliance or the second appliance (Greenberg [0128] & Massey [019]).
Regarding claim 18, GMB further teaches the system of claim 17, wherein the at least one criteria includes at least one of: a water preference, an environmental preference, a lighting preference, an algae preference, a harvesting preference, a tissue metric preference, a size preference, or a nutrition metric preference (Greenberg [0128] & Massey [019]).
Regarding claim 19, GMB further teaches the system of claim 16, wherein the computer vision engine is further configured to determine [“identifying hybrid seeds that will optimally perform on target fields”], based at least in part on the cartridge data [seed type used in the field] and the first sensor data [“agricultural data records for multiple different hybrid seeds”] or the second sensor data, a third party [supplier of the identified “hybrid seed” since seeds are linked to the suppliers] associated with producing a seed cartridge of a plant housed within the first appliance or the second appliance (Bull [0136, 0231, 0246]).
Regarding claim 20 GMB further teaches the system of claim 19, wherein the system adjusts [“automatically adjust a seed order to increase the number of bags”] an order associated with the third party in response to determining the third party is associated with producing the seed cartridge of the plant housed within the first appliance or the second appliance (Bull [0246]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SANTOSH R. POUDEL whose telephone number is (571)272-2347. The examiner can normally be reached Monday - Friday (8:30 am - 5:00 pm).
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/SANTOSH R POUDEL/ Primary Examiner, Art Unit 2115
1 See Spec, para. 037, 053 that describes “consumption preference” to cover, inter alia, “a rate of consumption or a rate of harvest of plants within the appliance 106” and “plant age or life cycle at consumption, and the like”
2 Greenberg, Moeller, and Bull et al., the combination fails to teach or suggest one or more features of independent claim 15.
Prosecution Insights