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 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 12-21 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.
The term “ripened food” in claim 12 is a relative term which renders the claim indefinite. The term “ripened food” is not defined by the claim, 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. For example, those of ordinary skill in the art may disagree as to what specific degree (e.g. of color, softness, etc.) constitutes a “ripened” level of a given food (e.g. some may define a banana as being “ripened” when it is at least 90% yellow, while others may require that it is 100% yellow or have brown spots in order to be considered “ripened”).
The term “ripened food” is similarly recited in claims 17, 18, 20. Claims 13-16, 19, 21 are dependent on claim 12, 17, or 20 and thus similarly incorporate the term.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nakano (JP 2021165604 A) in view of Bohling (US 20210339956 A1).
Regarding claim 1, Nakano discloses a food management device supporting food state tracking based on a spectral image ([0158] refrigerator 2A may also function as a so-called server (maturity estimation device) connected to a network; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data), the device comprising:
at least one spectral camera for acquiring spectral images of food received ([0031] the camera 31 includes an image sensor that is sensitive to the visible light region and generates color image data, including images of food, for example the camera may include an optical sensor that is sensitive to the visible light region; [0032] the infrared spectroscopy unit 32 irradiates the food with infrared light, detects the infrared light from the surface of the food, and detects the infrared spectrum by infrared spectroscopy; [0049] storage container 1 stores food placed in storage space 10S); and
a processor functionally connected to the at least one spectral camera ([0037] the information processing unit 4 receives the detection result data from the detection unit 3 and identifies the degree of maturity of the food; [0029] the detection unit includes a camera 31, an infrared spectrometer 32), the processor configured to:
receive food-related information of the received food ([0037] the information processing unit 4 receives the detection result data from the detection unit 3 and identifies the degree of maturity of the food; [0036] the humidity sensor 36…detects the humidity of the air in the storage space 10S),
acquire the spectral images of the food at regular intervals by activating the at least one spectral camera ([0042] the image data acquisition unit 41 acquires image data from the camera 31 of the detection unit 3 and stores it in the storage unit 6 as time-series image data with time information attached), and
monitor a change in a state of the food by analyzing the acquired spectral images ([0044] the surface condition detection unit 43 detects the surface condition of the food from the image IM of the food captured by the camera 31; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data…and the food surface detection result).
Nakano fails to disclose wherein the food is received in a storage warehouse and the food-related information is received from the storage warehouse.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses wherein the food is received in a storage warehouse ([0036] the third sensor 106 is deployed at a first robot 122 at a distribution center or warehouse 124, the produce 118 is delivered to the distribution center or warehouse124 via the shipment vehicle) and the food-related information is received from the storage warehouse ([0036] the third sensor 106 is deployed at a first robot 122 at a distribution center or warehouse 124, the third sensor 106 is configured to determine third information concerning the condition and grade of the produce 118).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein the food is received in a storage warehouse and the food-related information is received from the storage warehouse, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Regarding claim 2, Nakano in view of Bohling discloses the device of claim 1 as applied above. Nakano further discloses activate the spectral camera disposed at the location of the food ([0028] the detection unit 3…detects a physical quantity that changes according to the state of the food placed in the storage space 10S; [0029] the detection unit 3 includes a camera 31; [0042] the image data acquisition unit 41 acquires image data from the camera 31 of the detection unit 3 and stores it in the storage unit 6 as time-series image data with time information attached).
Nakano fails to disclose wherein the processor is configured to: identify a location of the received food from the food-related information.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses wherein the processor is configured to: identify a location of the received food from the food-related information, and activate the spectral camera disposed at the location of the food ([0049] at step 206, the shipment vehicle moves the produce from the production area; [0050] at step 208 and at a third sensor that is deployed at a first robot at a distribution center or warehouse, third information concerning the condition and grade of the produce is determined).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein the processor is configured to: identify a location of the received food from the food-related information, and activate the spectral camera disposed at the location of the food, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Regarding claim 3, Nakano in view of Bohling discloses the device of claim 2 as applied above. Nakano further discloses wherein the processor is configured to: deactivate the spectral camera disposed at the location when receiving a message regarding shipment of the food from the storage warehouse ([0060] once the information processing unit 4 has complete the above processing, it finishes the series of processes related to this flowchart, the processes in this flowchart are executed at predetermined intervals (i.e. when the processing unit receives a message that the steps re completed, the steps (such as [0057] image data acquisition unit acquiring image data from the camera) are deactivated)).
Regarding claim 4, Nakano in view of Bohling discloses the device of claim 1 as applied above. Nakano further discloses wherein the processor is configured to: acquire an initial spectral image at a time the food is received, and track the change in the state of the food by comparing the initial spectral image with the spectral images acquired at regular intervals thereafter ([0054] the food type determination unit 42 of the information processing unit 4 may use the image data generated by the camera 31 to identify the type of food and the time when it was stored; [0056] the measurement control unit 46 activates each sensor unit of the detection unit 3 corresponding to the type of food after a predetermined time has elapsed; [0086] camera 31 captures images of the area where the bananas are placed and detects the color of the bananas from the images taken every hour).
Regarding claim 5, Nakano in view of Bohling discloses the device of claim 1 as applied above. Nakano further discloses wherein the processor is configured to: if the change in the state of the food is greater than or equal to a predefined reference value, notify the change in the state of the food to a designated terminal ([0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit; [0063] a first threshold is predetermined to determine whether or not the product is in the later stages of maturation; [0133] the second learning model is a neural network trained to output a result for identifying the degree of ripeness of food based on the surface condition of the food depicted in the image IM captured by the camera 31 (see also the example in [0100])).
Regarding claim 6, Nakano in view of Bohling discloses the device of claim 1 as applied above. Nakano further discloses wherein the processor is configured to: if the change in the state of the food is greater than or equal to a predefined reference value, collect information on a storage environment corresponding to the changed state of the food ([0100] when detecting banana ripeness, the first condition in the process shown in Fig. 4 above is met when the banana changes color from green to yellow and similarly the second condition is met when the banana changes color from yellow to brown), create change information for changing a storage environment of the food based on the collected information, and transmit the change information ([0156] The linked processing unit 241 adds the acquired various measurement data and image data to the storage unit 25A…The linked processing unit 241 obtains the estimated degree of maturity of the food through the processing of each of the above-mentioned units and displays the estimated result on the operation panel 27, the coordinating processing unit 241 may determine the timing of the measurement by the detection unit 3 to avoid the timing of the cooling control of the refrigerator 2, and control the acquisition of measurement data in the storage container 1A).
Nakano fails to disclose wherein the change information is transmitted to the storage warehouse.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses wherein the change information is transmitted to the storage warehouse ([0028] at a third sensor that is deployed at a first robot at a distribution center or warehouse, third information concerning the condition and grade of the produce is determined to obtained; [0029] at a database at a central processing center, the first information, the second information, and the third information and the target shipping date are stored).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein the change information is transmitted to the storage warehouse, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Regarding claim 7, Nakano in view of Bohling discloses the device of claim 6 as applied above. Nakano further discloses wherein the processor is configured to: create the change information for changing at least one of temperature, humidity, and light amount in the storage environment of the food ([0020] the storage control unit 24 controls the cooling unit 26 to adjust the temperature and humidity of the cold air in the storage room 20S so that the temperature of the cold air in the storage room 20S reaches a desire temperature and the humidity of the cold air in the storage room 20S reaches a desired humidity).
Regarding claim 8, Nakano discloses a food state tracking method based on a spectral image ([0158] refrigerator 2A may also function as a so-called server (maturity estimation device) connected to a network; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data), the method comprising:
by a processor of a food management device that manages storage of food ([0037] the information processing unit 4 receives the detection result data from the detection unit 3 and identifies the degree of maturity of the food; [0029] the detection unit includes a camera 31, an infrared spectrometer 32; [0158] refrigerator 2A may also function as a so-called server (maturity estimation device) connected to a network; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data),
establishing a communication channel with where the food is stored ([0037] the information processing unit 4 receives the detection result data from the detection unit 3 and identifies the degree of maturity of the food; [0049] storage container 1 stores food placed in storage space 10S);
receiving food-related information on the food received ([0037] the information processing unit 4 receives the detection result data from the detection unit 3 and identifies the degree of maturity of the food; [0036] the humidity sensor 36…detects the humidity of the air in the storage space 10S);
acquiring spectral images of the food at regular intervals by using a spectral camera disposed to capture the spectral images of the food ([0042] the image data acquisition unit 41 acquires image data from the camera 31 of the detection unit 3 and stores it in the storage unit 6 as time-series image data with time information attached); and
monitoring a change in a state of the food by analyzing the acquired spectral images ([0044] the surface condition detection unit 43 detects the surface condition of the food from the image IM of the food captured by the camera 31; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data…and the food surface detection result).
Nakano fails to disclose wherein the communication is established with a storage warehouse and the food-related information is received on received in the storage warehouse from the storage warehouse.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses wherein the communication is established with a storage warehouse ([0036] the third sensor 106 is deployed at a first robot 122 at a distribution center or warehouse 124, the produce 118 is delivered to the distribution center or warehouse124 via the shipment vehicle) and the food-related information is received on food received in the storage warehouse from the storage warehouse ([0036] the third sensor 106 is deployed at a first robot 122 at a distribution center or warehouse 124, the third sensor 106 is configured to determine third information concerning the condition and grade of the produce 118).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein the communication is established with a storage warehouse and the food-related information is received on food received in the storage warehouse from the storage warehouse, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Regarding claim 9, Nakano in view of Bohling discloses the method of claim 8 as applied above. Nakano in view of Bohling further discloses everything claimed as applied above (see rejection of claim 2).
Regarding claim 10, Nakano in view of Bohling discloses the method of claim 9 as applied above. Nakano in view of Bohling further discloses everything claimed as applied above (see rejection of claim 3).
Regarding claim 11, Nakano in view of Bohling discloses the method of claim 8 as applied above. Nakano in view of Bohling further discloses everything claimed as applied above (see rejections of claims 5 and 6).
Regarding claim 12, Nakano discloses a food management device supporting a food management function based on a spectral image ([0158] refrigerator 2A may also function as a so-called server (maturity estimation device) connected to a network; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data), the device comprising:
at least one spectral camera for acquiring spectral images of a ripened food received ([0031] the camera 31 includes an image sensor that is sensitive to the visible light region and generates color image data, including images of food, for example the camera may include an optical sensor that is sensitive to the visible light region; [0032] the infrared spectroscopy unit 32 irradiates the food with infrared light, detects the infrared light from the surface of the food, and detects the infrared spectrum by infrared spectroscopy; [0044] the surface condition detection unit 43 detects the surface condition of the food from the image IM of the food captured by the camera 31; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data…and the food surface detection result; [0049] storage container 1 stores food placed in storage space 10S); and
a processor functionally connected to the at least one spectral camera ([0037] the information processing unit 4 receives the detection result data from the detection unit 3 and identifies the degree of maturity of the food; [0029] the detection unit includes a camera 31, an infrared spectrometer 32), the processor configured to:
when the ripened food is received at a point ([0049] storage container 1 stores food placed in storage space 10S; [0086] camera 31 captures images of the area where the bananas are placed and detects for example the color of the bananas from the images taken every hour),
activate a spectral camera disposed to photograph the point of the storage warehouse ([0056] the measurement control unit 46 activates each sensor unit of the detection unit 3 corresponding to the type of food; [0042] the image data acquisition unit 41 acquires image data from the camera 31 of the detection unit 3 and stores it in the storage unit 6 as time-series image data with time information attached),
acquire a spectral image of the ripened food through the activated spectral camera ([0042] the image data acquisition unit 41 acquires image data from the camera 31 of the detection unit 3 and stores it in the storage unit 6 as time-series image data with time information attached),
detect a ripening state of the ripened food by comparing the spectral image with a pre- stored reference model ([0044] the surface condition detection unit 43 detects the surface condition of the food from the image IM of the food captured by the camera 31; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data…and the food surface detection result; [0133] the second learning model is a neural network trained to output a result for identifying the degree of ripeness of food based on the surface condition of the food depicted in the image IM captured by the camera 31; [0086] as the bananas stored in storage container 1 ripen, the color of their peels gradually changes from green to yellow, and then to brown), and
output a message according to the ripening state ([0060] the measurement control unit 46 causes the maturity estimation processing unit 45 to perform a process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit).
Nakano fails to disclose wherein the food is received at a storage warehouse.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses wherein food is received at a storage warehouse ([0036] the third sensor 106 is deployed at a first robot 122 at a distribution center or warehouse 124, the produce 118 is delivered to the distribution center or warehouse124 via the shipment vehicle, the third sensor 106 is configured to determine third information concerning the condition and grade of the produce 118).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein the food is received at a storage warehouse, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Regarding claim 13, Nakano in view of Bohling discloses the device of claim 12 as applied above. Nakano further discloses wherein the processor is configured to: check a current degree of ripening through comparison between the detected ripening state and the reference model ([0054] the food type determination unit 42 of the information processing unit 4 may use the image data generated by the camera 31 to identify the type of food and the time when it was stored; [0056] the measurement control unit 46 activates each sensor unit of the detection unit 3 corresponding to the type of food after a predetermined time has elapsed; [0086] camera 31 captures images of the area where the bananas are placed and detects the color of the bananas from the images taken every hour; [0086] as the bananas stored in storage container 1 ripen, the color of their peels gradually changes from green to yellow, and then to brown), and if the degree of ripening is within a target reference range, output a message based on completion of ripening ([0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit; [0100] when detecting banana ripeness, the first condition in the process shown in Fig. 4 above is met when the banana changes color from green to yellow; [0063] when the result of the above determination using the first threshold is positive, the state of the food is considered to satisfy the first condition).
Regarding claim 14, Nakano in view of Bohling discloses the device of claim 13 as applied above. Nakano further discloses wherein the processor is configured to: if the degree of ripening is below the reference range, output a message including at least one of a message indicating an underripe state ([0064] if the food does not meet the first condition, the maturity estimation processing unit 45 determines that the food is in the early stages of maturation; [0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit).
Nakano fails to disclose a remaining time until a time of the ripening completion.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses a remaining time until a time of the ripening completion ([0068] setting an alarm or a time that when expired activates an alarm is action 436 associated with controlling the amount of time 426 spent in the chamber by the produce (i.e. the timer/alarm would indicate the remaining time until the food should be removed from the ripening chamber).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein a remaining time until a time of the ripening completion, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Regarding claim 15, Nakano in view of Bohling discloses the device of claim 14 as applied above. Nakano further discloses wherein the processor is configured to: if a storage environment of the storage warehouse needs to be changed based on the underripe state ([0064] if the food does not meet the first condition, the maturity estimation processing unit 45 determines that the food is in the early stages of maturation; [0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit), create change information related to the change of the storage environment and transmit the change information ([0156] The linked processing unit 241 adds the acquired various measurement data and image data to the storage unit 25A…The linked processing unit 241 obtains the estimated degree of maturity of the food through the processing of each of the above-mentioned units and displays the estimated result on the operation panel 27, the coordinating processing unit 241 may determine the timing of the measurement by the detection unit 3 to avoid the timing of the cooling control of the refrigerator 2, and control the acquisition of measurement data in the storage container 1A).
Nakano fails to disclose wherein the change information is transmitted to the storage warehouse.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses wherein the change information is transmitted to the storage warehouse ([0028] at a third sensor that is deployed at a first robot at a distribution center or warehouse, third information concerning the condition and grade of the produce is determined to obtained; [0029] at a database at a central processing center, the first information, the second information, and the third information and the target shipping date are stored).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein the change information is transmitted to the storage warehouse, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Regarding claim 16, Nakano in view of Bohling discloses the device of claim 13 as applied above. Nakano further discloses wherein the processor is configured to: if the degree of ripening exceeds the reference range, output a message indicating an overripe state ([0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit; [0063] a first threshold is predetermined to determine whether or not the product is in the later stages of maturation; [0133] the second learning model is a neural network trained to output a result for identifying the degree of ripeness of food based on the surface condition of the food depicted in the image IM captured by the camera 31 (see also [0065] indicating that exceeding the second condition indicates a spoiled (i.e. overripe) state, as well as the example in [0100])).
Regarding claim 17, Nakano discloses a food management method based on a spectral image ([0158] refrigerator 2A may also function as a so-called server (maturity estimation device) connected to a network; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data), the method comprising:
by a processor of a food management device ([0037] the information processing unit 4 receives the detection result data from the detection unit 3 and identifies the degree of maturity of the food; [0029] the detection unit includes a camera 31, an infrared spectrometer 32),
receiving food-related information related to storage of a ripened food ([0037] the information processing unit 4 receives the detection result data from the detection unit 3 and identifies the degree of maturity of the food; [0036] the humidity sensor 36…detects the humidity of the air in the storage space 10S; [0049] storage container 1 stores food placed in storage space 10S; [0086] camera 31 captures images of the area where the bananas are placed and detects for example the color of the bananas from the images taken every hour);
activating a spectral camera disposed to photograph a point, based on the food-related information ([0056] the measurement control unit 46 activates each sensor unit of the detection unit 3 corresponding to the type of food; [0042] the image data acquisition unit 41 acquires image data from the camera 31 of the detection unit 3 and stores it in the storage unit 6 as time-series image data with time information attached);
acquiring a spectral image of the ripened food through the activated spectral camera ([0042] the image data acquisition unit 41 acquires image data from the camera 31 of the detection unit 3 and stores it in the storage unit 6 as time-series image data with time information attached);
detecting a ripening state of the ripened food by comparing the spectral image with a pre- stored reference model ([0044] the surface condition detection unit 43 detects the surface condition of the food from the image IM of the food captured by the camera 31; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data…and the food surface detection result; [0133] the second learning model is a neural network trained to output a result for identifying the degree of ripeness of food based on the surface condition of the food depicted in the image IM captured by the camera 31; [0086] as the bananas stored in storage container 1 ripen, the color of their peels gradually changes from green to yellow, and then to brown); and
outputting a message according to the ripening state ([0060] the measurement control unit 46 causes the maturity estimation processing unit 45 to perform a process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit).
Nakano fails to disclose wherein the information is received of food from a storage warehouse and wherein the photographs are of a point of a storge warehouse.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses wherein the information is received of food from a storage warehouse ([0036] the third sensor 106 is deployed at a first robot 122 at a distribution center or warehouse 124, the third sensor 106 is configured to determine third information concerning the condition and grade of the produce 118) and wherein the photographs are of a point of a storge warehouse ([0036] the third sensor 106 is deployed at a first robot 122 at a distribution center or warehouse 124, the produce 118 is delivered to the distribution center or warehouse124 via the shipment vehicle…for example the third sensor 106 may gather images of the produce 118, which can be analyzed to determine the grade of the produce 118).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein the information is received of food from a storage warehouse and wherein the photographs are of a point of a storge warehouse, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Regarding claim 18, Nakano in view of Bohling discloses the method of claim 17 as applied above. Nakano further discloses wherein detecting a ripening state of the ripened food includes: checking a current degree of ripening through comparison between the detected ripening state and the reference model ([0054] the food type determination unit 42 of the information processing unit 4 may use the image data generated by the camera 31 to identify the type of food and the time when it was stored; [0056] the measurement control unit 46 activates each sensor unit of the detection unit 3 corresponding to the type of food after a predetermined time has elapsed; [0086] camera 31 captures images of the area where the bananas are placed and detects the color of the bananas from the images taken every hour; [0086] as the bananas stored in storage container 1 ripen, the color of their peels gradually changes from green to yellow, and then to brown); and
if the degree of ripening is within a target reference range, outputting a message based on completion of ripening ([0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit; [0100] when detecting banana ripeness, the first condition in the process shown in Fig. 4 above is met when the banana changes color from green to yellow; [0063] when the result of the above determination using the first threshold is positive, the state of the food is considered to satisfy the first condition),
if the degree of ripening is below the reference range, outputting a message including at least one of a message indicating an underripe state ([0064] if the food does not meet the first condition, the maturity estimation processing unit 45 determines that the food is in the early stages of maturation; [0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit), or
if the degree of ripening exceeds the reference range, outputting a message indicating an overripe state ([0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit; [0063] a first threshold is predetermined to determine whether or not the product is in the later stages of maturation; [0133] the second learning model is a neural network trained to output a result for identifying the degree of ripeness of food based on the surface condition of the food depicted in the image IM captured by the camera 31 (see also [0065] indicating that exceeding the second condition indicates a spoiled (i.e. overripe) state, as well as the example in [0100])).
Nakano fails to disclose a remaining time until a time of the ripening completion.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses a remaining time until a time of the ripening completion ([0068] setting an alarm or a time that when expired activates an alarm is action 436 associated with controlling the amount of time 426 spent in the chamber by the produce (i.e. the timer/alarm would indicate the remaining time until the food should be removed from the ripening chamber).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein a remaining time until a time of the ripening completion, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Regarding claim 19, Nakano in view of Bohling discloses the method of claim 18 as applied above. Nakano further discloses if a storage environment of the storage warehouse needs to be changed based on the underripe state ([0064] if the food does not meet the first condition, the maturity estimation processing unit 45 determines that the food is in the early stages of maturation; [0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit), creating change information related to the change of the storage environment and transmitting the change information ([0156] The linked processing unit 241 adds the acquired various measurement data and image data to the storage unit 25A…The linked processing unit 241 obtains the estimated degree of maturity of the food through the processing of each of the above-mentioned units and displays the estimated result on the operation panel 27, the coordinating processing unit 241 may determine the timing of the measurement by the detection unit 3 to avoid the timing of the cooling control of the refrigerator 2, and control the acquisition of measurement data in the storage container 1A).
Nakano fails to disclose wherein the change information is transmitted to the storage warehouse.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses wherein the change information is transmitted to the storage warehouse ([0028] at a third sensor that is deployed at a first robot at a distribution center or warehouse, third information concerning the condition and grade of the produce is determined to obtained; [0029] at a database at a central processing center, the first information, the second information, and the third information and the target shipping date are stored).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein the change information is transmitted to the storage warehouse, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Regarding claim 20, Nakano discloses a food management device supporting a food management function based on a spectral image ([0158] refrigerator 2A may also function as a so-called server (maturity estimation device) connected to a network; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data), the device comprising:
a server communication circuit establishing a communication channel with a food management device ([0158] refrigerator 2A may also function as a so-called server (maturity estimation device) connected to a network; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data); and
a server processor functionally connected to the server communication circuit ([0158] refrigerator 2A may also function as a so-called server connected to a network, a so-called server connected to a network may perform some of the processing related to the analysis of the maturity of the food), the server processor configured to:
when receiving a message about reception of a ripened food, request a spectral image of the ripened food from the food management device that controls the spectral camera disposed at a location where the ripened food is received ([0056] the measurement control unit 46 activates each sensor unit of the detection unit 3 corresponding to the type of food; [0042] the image data acquisition unit 41 acquires image data from the camera 31 of the detection unit 3 and stores it in the storage unit 6 as time-series image data with time information attached),
when receiving the spectral image from the food management device, detect a ripening state of the ripened food by comparing the spectral image with a pre-stored reference model ([0044] the surface condition detection unit 43 detects the surface condition of the food from the image IM of the food captured by the camera 31; [0046] the maturity estimation processing unit 45 detects the maturity of the food based on the time-series image data…and the food surface detection result; [0133] the second learning model is a neural network trained to output a result for identifying the degree of ripeness of food based on the surface condition of the food depicted in the image IM captured by the camera 31), and
output a message based on the detected ripening state ([0060] the measurement control unit 46 causes the maturity estimation processing unit 45 to perform a process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit).
Nakano fails to disclose wherein the communication channel is with a storage warehouse and wherein the message is received about food from a storage warehouse.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses wherein the communication channel is with a storage warehouse ([0015] a system that is configured to adjust ripening conditions for produce includes a first sensor, a second sensor, a third sensor, an electronic user device, and electronic communication network, a database, and a control circuit; [0036] the third sensor 106 is deployed at a first robot 122 at a distribution center or warehouse 124) and wherein the message is received about food from a storage warehouse ([0036] the third sensor 106 is deployed at a first robot 122 at a distribution center or warehouse 124, the third sensor 106 is configured to determine third information concerning the condition and grade of the produce 118).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein the communication channel is with a storage warehouse and wherein the message is received about food from a storage warehouse, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Regarding claim 21, Nakano in view of Bohling discloses the device of claim 20 as applied above. Nakano further discloses wherein the server processor is configured to: check a current degree of ripening through comparison between the detected ripening state and the reference model ([0054] the food type determination unit 42 of the information processing unit 4 may use the image data generated by the camera 31 to identify the type of food and the time when it was stored; [0056] the measurement control unit 46 activates each sensor unit of the detection unit 3 corresponding to the type of food after a predetermined time has elapsed; [0086] camera 31 captures images of the area where the bananas are placed and detects the color of the bananas from the images taken every hour; [0086] as the bananas stored in storage container 1 ripen, the color of their peels gradually changes from green to yellow, and then to brown), and
if the degree of ripening is within a target reference range, output a message based on completion of ripening ([0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit; [0100] when detecting banana ripeness, the first condition in the process shown in Fig. 4 above is met when the banana changes color from green to yellow; [0063] when the result of the above determination using the first threshold is positive, the state of the food is considered to satisfy the first condition),
if the degree of ripening is below the reference range, output a message including at least one of a message indicating an underripe state ([0064] if the food does not meet the first condition, the maturity estimation processing unit 45 determines that the food is in the early stages of maturation; [0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit), or
if the degree of ripening exceeds the reference range, output a message indicating an overripe state ([0060] if the state of the food has changed since it was stored, the measurement control unit 46 causes the maturity estimation processing unit 45 to perform to process to determine the state of the food and outputs information regarding the maturity result of that process to the outside from the output processing unit 5, for example to be displayed on an external display unit; [0063] a first threshold is predetermined to determine whether or not the product is in the later stages of maturation; [0133] the second learning model is a neural network trained to output a result for identifying the degree of ripeness of food based on the surface condition of the food depicted in the image IM captured by the camera 31 (see also [0065] indicating that exceeding the second condition indicates a spoiled (i.e. overripe) state, as well as the example in [0100])).
Nakano fails to disclose a remaining time until a time of the ripening completion.
Bohling, in a related system from the same field of endeavor of tracking food status such as ripening using images (Abstract, [0024]), discloses a remaining time until a time of the ripening completion ([0068] setting an alarm or a time that when expired activates an alarm is action 436 associated with controlling the amount of time 426 spent in the chamber by the produce (i.e. the timer/alarm would indicate the remaining time until the food should be removed from the ripening chamber).
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to combine Bohling with Nakano wherein a remaining time until a time of the ripening completion, as disclosed by Bohling, as part of a food management device supporting food state tracking based on a spectral image, as disclosed by Nakano, for the purpose of enabling stores to monitor food state, such as produce ripening, in order to present food to consumers in the optimal conditions (See Bohling: [0003]-[0005]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ogawa (US 20220091024 A1) discloses a multi-spectral camera as part of a system for imaging selecting food items based on spectra and determining freshness and ripeness of the food.
Pi (US 10788418 B2) discloses a food state measuring device including an optical spectrum acquiring unit to compare an optical spectrum of a food for a stored reference spectrum.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAROLINE DEPALMA whose telephone number is (571)270-0769. The examiner can normally be reached Mon-Thurs 9:00am-4pm Eastern Time.
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/CAROLINE E. DEPALMA/Examiner, Art Unit 2675
/SJ Park/Primary Examiner, Art Unit 2675
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