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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/03/2025 has been entered.
Response to Amendment
The amendment filed 12/03/2025 has been acknowledged and entered. Claims 1-3 and 5-11 are pending.
Response to Arguments
Applicant’s arguments, see pages 9-10, filed 12/03/2025, with respect to the rejections of claims 1 and 7-10 under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Ueda (JP 2018146244 A, portions of an attached translation are cited below). Ueda, related to a toilet stool device and toilet seat device, does teach adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected ([0033]: Shape of feces is determined where Fig. 7 shows different shapes of feces.) to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces [0047]: “As shown in FIG. 16, in the second embodiment, as a feature amount, a lateral width Wn of stool indicating a fecal area in the obtained line data Ln is extracted. The determining unit calculates the volume Vn of the truncated cone having the width Wn and the lateral width Wn-1 of the previous line data Ln-1 as the diameter at both ends and the height h. Then, the volume Vn is calculated for all the line data Ln, and the volume of feces is determined by integrating them. The height h of each truncated cone is the fall height of the stool per time interval and is substantially constant.” Shown in Fig. 16). Please see the detailed rejections below.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2, 5, 7-10 are rejected under 35 U.S.C. 103 as being unpatentable over Kashyap (US 20180303466 A1) in view of Iwayama (US 2019/0258214 A1) and further in view of Ueda (JP2018146244A, with portions of an attached translation cited below).
Regarding Claim 1, Kashyap teaches an excrement management system configured to collect and manage information about excrement (Abstract: “Provided is a biomonitoring device that measures a parameter of a material expelled during use of a toilet by a user.”), the excrement management system comprising:
a closet bowl in which a bowl part for receiving excrement is formed (Fig. 1: toilet 200; para. [0031]);
a light emitting unit (Fig. 2C: electromagnetic radiation source 210; [0036]) configured to emit light toward an inner part of the closet bowl ([0036]: “An electromagnetic radiation source 210 can emit electromagnetic radiation in the visible and invisible range of the electromagnetic spectrum into a toilet bowl.”).
a light receiving unit comprising an image sensor (Fig. 2C: CMOS sensor 211, para. [0036]) configured to receive light.
a cloud server (cloud computing environment 50 from [0100]) configured to analyze light reception data received by the light receiving unit ([0100]: “Once defecation and/or urination is complete, which is detected through software-based image detection, the sample collection is disengaged and the images are processed locally or sent through access point 30 to networked computing resources in a cloud computing environment 50.”);
a first communication device (access point 30 from [0100]) configured to transmit the light reception data to the cloud server ([0100]: Images are processed locally or sent through access point 30 (analogous to a communication device) to a cloud computing environment 50.) wherein
the cloud server ([0100]) analyzes the light reception data to determine a characteristic of feces ([0025]: Fig. 15B shows an image classification method for classifying stool consistency (also described in [0104] where stool consistency ranges from hard and lumpy to unformed and liquid). Fig. 15C shows an image classification for detecting colors in the excreta with Fig. 15D showing classification of stool that has blood or no blood. Fig. 15E shows the estimation of stool voiding volume of a person ([0106]).).
and if determined to include feces, determines the light reception data as data to be transmitted to the cloud server ([0100]: Once defecation is complete, which is detected through software-based image detection, the images are processed locally or through an access point to a cloud server.) and transmits the light reception data to the cloud server by the first communication device (access point 30 from [0100]);
and the cloud server ([0100] analyzes the light reception data to determine at least one of three characteristic amounts including a color, a shape ([0104]: stool consistency is determined from a range of hard and lumpy to unformed and liquid), and an amount of feces ([0106]: Fig. 15E shows the estimation of stool voiding volume or a person),
wherein, in a case in which there are a plurality of pieces of feces excreted by a user (voiding volume includes both a plurality or pieces and a whole piece of feces), the cloud server analyzes the amount of feces (stool voiding volume from [0106]. As best understood and interpreted, in the field of endeavor, voiding volume is the amount of feces that is excreted by the user.) by analyzing the shape of each piece of feces (Fig. 15D: separate hard lumps of stool can be identified [0025]) that is excreted through one time of excretion action performed by the user.
Kashyap does not teach an edge server;
a second communication device configured to transmit light reception data to the edge server;
wherein the edge server analyzes the light reception data to determine whether feces is included in the light reception data, and if determined not to include feces, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server.
Iwayama, related to information processing, does teach an edge device (analogous to edge server) configured for information processing ([0022]: The edge device 10 collects data of field devices.) The edge device here is equivalent to the edge server mentioned in the claimed invention as they both perform the same function, which is to analyze data. Furthermore, an edge server is a type of edge device.
Iwayama also teaches a second communication device ((access network 43 from [0026] and Fig. 1)) configured to transmit data to the edge device (Fig. 3 as seen below: communication unit 21; para. [0040-0041]: “The cloud server 20 includes a communication unit 21 that performs transmission and reception of data with the edge device 10…”); and if determined not to include a feature defined by the user, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server ([0038]: “The data sorting unit 16 reads the field information (analogous to light reception data) from the data holding unit 13, and sorts the field information 70 into data to be transmitted in the cloud server 20 and data not to be transmitted to the cloud server 20.” The sorting of the data here could be adapted so that the determination of whether the data is to be transmitted to the cloud server or not transmitted to the cloud server is dependent on whether there is feces in the light reception data.).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap to incorporate an edge server/device configured to analyze light reception data received by the light receiving unit and a second communication device configured to transmit the light reception data to the edge server; and to determine whether feces is included in the light reception data, and if determined not to include feces, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server, as disclosed by Iwayama. Data analysis on cloud servers have had a problem where the validity of the analysis result in the cloud server cannot be determined which causes a risk on system management ([0006] from Iwayama). Edge servers are closer to the location of the data being transmitted ([0004] from Iwayama) than cloud servers, therefore, edge servers enable real-time processing and control while reducing the risk on the system management ([0007] from Iwayama).
Incorporating an edge server would require an additional communication device, therefore, it would have been obvious that the user would have wanted to incorporate an additional communication device to transmit the light reception data to the edge server.
By minimizing the amount of data the cloud server needs to process reduces the processing time. Therefore, it is advantageous for a user to want to incorporate a data processing step where data can be sorted and determined to not be transmitted to the cloud server so that the cloud server spends less time analyzing data that does not to be analyzed which optimizes the data processing.
Kashyap modified by Iwayama appears to be silent to adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces.
Ueda, related to a toilet stool device and toilet seat device, does teach adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected ([0033]: Shape of feces is determined where Fig. 7 shows different shapes of feces.) to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces [0047]: “As shown in FIG. 16, in the second embodiment, as a feature amount, a lateral width Wn of stool indicating a fecal area in the obtained line data Ln is extracted. The determining unit calculates the volume Vn of the truncated cone having the width Wn and the lateral width Wn-1 of the previous line data Ln-1 as the diameter at both ends and the height h. Then, the volume Vn is calculated for all the line data Ln, and the volume of feces is determined by integrating them. The height h of each truncated cone is the fall height of the stool per time interval and is substantially constant.” Shown in Fig. 16).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Kashyap combined with Iwayama to incorporate adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces, as disclosed by Ueda. Being able to analyze properties of stool (which includes shape and volume) can be used to observe the health condition of the human body ([0002] from Ueda).
Regarding Claim 2, Kashyap modified by Iwayama and Ueda teaches the excrement management system according to claim 1.
Kashyap modified by Iwayama and Ueda further teaches that the first communication device transmits the light reception data to the cloud server (Kashyap, [0100]) by using a wide-area information communication network (Kashyap, [0095]: “Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”).”),
Kashyap modified by Iwayama and Ueda (for claim 1) does not teach that the second communication device which transmits light reception data to the edge device by using a local-area information communication network.
Iwayama, related to information processing, does teach a second communication device (access network 43 from [0026] and Fig. 1) which transmits data to the edge device by using a local-area information communication network ([0026]: “Note that, the edge device 10 may be directly connected to the cloud server 20 or may be indirectly connected to the cloud server 20 via an access network 43. The access network 43 may be a wired network such as Ethernet, or a wireless network such as a wireless local area network (LAN) or a mobile communication network.”).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap combined with Iwayama and Ueda (for claim 1) so that the second communication device transmits light reception data to the edge device by using a local-area information communication network, as disclosed by Iwayama. Using a local-area information communication network (LAN) to transmit data/information to an edge device is well-known in the field of data processing. Therefore, one of ordinary skill in the art would have known to combine prior art elements (using a LAN with an edge device) according to known methods (for information processing) to yield predictable results (for transmitting data to an edge device) (MPEP 2143 (I)(A)).
Regarding Claim 5, Kashyap modified by Iwayama and Ueda teaches the excrement management system according to claim 1.
Kashyap modified by Iwayama and Ueda further teaches a user identification device (Kashyap, fingerprint sensor 404 from [0054]) configured to acquire user information who uses the closet bowl (Kashyap, [0054]); a first communication device (Kashyap, access point 30 from [0100]) and a cloud server (Kashyap, cloud computing environment 50 from [0100]).
Kashyap modified by Iwayama and Ueda (according to claim 1) does not teach that the first communication device does not transmit the user information to the cloud server.
Iwayama does teach a communication device (data sorting unit 16 from [0038]) that does not transmit the user information to the cloud server ([0038]: “The data sorting unit 16 reads the field information 70 (analogous to user information) from the data holding unit 13, and sorts the field information 70 into data to be transmitted to the cloud server 20 and data not to be transmitted to the cloud server 20.”)
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap combined with Iwayama and Ueda (according to claim 1) so that the communication device does not transmit the user information to the cloud server, as disclosed by Iwayama. The choice of not transmitting unneeded data to the cloud optimizes data processing by reducing the amount of data to be processed.
Regarding Claim 7, Kashyap teaches an excretion information management method (Abstract: “Provided is a biomonitoring device that measures a parameter of a material expelled during use of a toilet by a user.”) for managing, on a cloud server (cloud computing environment 50 from [0100]) information about feces ([0025]: Fig. 15B shows an image classification method for classifying stool consistency (also described in [0104] where stool consistency ranges from hard and lumpy to unformed and liquid). Fig. 15C shows an image classification for detecting colors in the excreta with Fig. 15D showing classification of stool that has blood or no blood. Fig. 15E shows the estimation of stool voiding volume of a person ([0106]).) collected in a toilet room in which a closet bowl is disposed (Fig. 1: toilet 200; para. [0031]), the excretion information management method comprising:
a detection step of receiving, by a light receiving unit (Fig. 2C: CMOS sensor 211, [0036]) for receiving light reflected light from feces corresponding to light that is emitted toward an inner part of the closet bowl (Shown in Fig. 2C) by a light emitting unit (Fig.2C: electromagnetic radiation source 210, [0036]: “An electromagnetic radiation source 210 can emit electromagnetic radiation in the visible and invisible range of the electromagnetic spectrum into a toilet bowl.”);
an analysis step of analyzing, by a cloud server (cloud computing environment 50 from [0100]), light reception data detected in the detection step to determine whether feces is included in the light reception data ([0100]: Once defecation and/or urination is complete, the sample collection is complete and the images are processed locally or sent to a cloud server for analysis.), and
if determined to include feces, determines the light reception data as data to be transmitted to the cloud server ([0100]) and transmits the light reception data to the cloud server by the first communication device (access point 30 from [0100]);
and an analysis of analyzing the light reception data ([0100]: analysis is done by the cloud computing environment 50) to determine at least one of three characteristic amounts including a color, a shape ([0104]: stool consistency is determined from a range of hard and lumpy to unformed and liquid), and an amount of feces ([0106]: Fig. 15E shows the estimation of stool voiding volume or a person);
in a case in which there are a plurality of pieces of feces excreted by a user (voiding volume includes both a plurality or pieces and a whole piece of feces), a step of determining the amount of the plurality of pieces of feces (stool voiding volume from [0106]. As best understood and interpreted, in the field of endeavor, voiding volume is the amount of feces that is excreted by the user.) by analyzing the shape of each piece of feces detected (Fig. 15D: separate hard lumps of stool can be identified [0025]) that is excreted through one time of excretion action performed by the user ([0106]).
Kashyap does not teach a first analysis step of analyzing, by an edge server and when analyzing the light reception data, if determined not to include feces, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server.
Iwayama, related to information processing, does teach a first analysis step of analyzing by an edge server (Fig. 1 and [0027]: “The edge device 10 that is a primary analysis device is a computer that collects and performs primary analysis on the field information 70 that is the data of the field devices 50A to 50D. The edge device 10 extracts data necessary for the cloud server 20 from the field information 70.”) and when analyzing data, if determined not to include a feature defined by the user determines the data as data not required to be processed by the cloud server and not to be transmitted to the cloud server ([0038]: “The data sorting unit 16 reads the field information (analogous to light reception data) from the data holding unit 13, and sorts the field information 70 into data to be transmitted in the cloud server 20 and data not to be transmitted to the cloud server 20.” The sorting of the data here could be adapted so that the determination of whether the data is to be transmitted to the cloud server or not transmitted to the cloud server is dependent on whether there is feces in the light reception data.).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap to incorporate an edge server/device with a first analysis step, and to determine whether feces is included in the light reception data, and if determined not to include feces, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server, as disclosed by Iwayama. Data analysis on cloud servers have had a problem where the validity of the analysis result in the cloud server cannot be determined which causes a risk on system management ([0006] from Iwayama). Edge servers are closer to the location of the data being transmitted ([0004] from Iwayama) than cloud servers, therefore, edge servers enable real-time processing and control while reducing the risk on the system management ([0007] from Iwayama).
By minimizing the amount of data the cloud server needs to process reduces the processing time. Therefore, it is advantageous for a user to want to incorporate a data processing step where data can be sorted and determined to not be transmitted to the cloud server so that the cloud server spends less time analyzing data that does not to be analyzed which optimizes the data processing.
Kashyap combined with Iwayama appears to be silent to a second analysis step of analyzing the light reception data to determine at least one characteristic amounts including a color, a shape, and an amount of feces. However, it necessarily follows that with the first analysis step which occurs at the edge server so that the edge server analyzes data to then be transmitted to the cloud server, that the second analysis which consist of using the cloud server would occur at the cloud server to analyze the light reception data to determine at least one characteristic amounts including a shape, and an amount of feces.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap combined with Iwayama where a second analysis of analyzing the light reception data to determine at least one characteristic amounts including a color, a shape, and an amount of feces, disclosed by Kashyap combined with Iwayama. Iwayama discloses that the edge server has a first analysis step where the edge server first processes the data before that data is then transmitted to the cloud server ([0027] and Fig. 1 from Iwayama). Data analysis on cloud servers have had a problem where the validity of the analysis result in the cloud server cannot be determined which causes a risk on system management ([0006] from Iwayama). Edge servers are closer to the location of the data being transmitted ([0004] from Iwayama) than cloud servers, therefore, edge servers enable real-time processing and control while reducing the risk on the system management ([0007] from Iwayama).
Kashyap modified by Iwayama appears to be silent to an adding step of adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces.
Ueda, related to a toilet stool device and toilet seat device, does teach an adding step of adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected ([0033]: Shape of feces is determined where Fig. 7 shows different shapes of feces.) to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces [0047]: “As shown in FIG. 16, in the second embodiment, as a feature amount, a lateral width Wn of stool indicating a fecal area in the obtained line data Ln is extracted. The determining unit calculates the volume Vn of the truncated cone having the width Wn and the lateral width Wn-1 of the previous line data Ln-1 as the diameter at both ends and the height h. Then, the volume Vn is calculated for all the line data Ln, and the volume of feces is determined by integrating them. The height h of each truncated cone is the fall height of the stool per time interval and is substantially constant.” Shown in Fig. 16).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Kashyap combined with Iwayama to incorporate adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces, as disclosed by Ueda. Being able to analyze properties of stool (which includes shape and volume) can be used to observe the health condition of the human body ([0002] from Ueda).
Regarding Claim 8, Kashyap teaches a computer-readable medium having stored a computer program (computer-readable medium from [0079]) executed by a cloud server (cloud computing environment 50 from [0100]) configured to be able to communicate with a closet bowl (Fig. 1: toilet 200 and Fig. 14 shown below: The toilet apparatus 200 can communicate with the cloud computing environment 50 through an access point 30; [0031] and [0102]) and a cloud server ([0100]), the computer program (computer program from [0080] configured to cause a cloud server to perform:
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a reception procedure of receiving light reception data that is detected by receiving, by a light receiving unit (Fig. 2C: CMOS sensor 211, [0036]), reflected light from feces corresponding to light that is emitted toward an inner part of a closet bowl ([0036]: “An electromagnetic radiation source 210 can emit electromagnetic radiation in the visible and invisible range of the electromagnetic spectrum into a toilet bowl.”);
a transmission procedure of analyzing the light reception data to determine whether feces is included in the light reception data, and
if determined to include feces, determining the light reception data as data to be transmitted to the cloud server ([0100]: “Once defecation and/or urination is complete, which is detected through software-based image detection, the sample collection is disengaged and the images are processed locally or sent through access point 30 to networked computing resources in a cloud computing environment 50. Locally or remotely through memory 51 and processor 52 the images are then analyzed.”) and transmitting a determination result (Once defecation is complete, which is the determination result, as described in [0100]) to a device configured to control a communication device (access point from [0100] and shown in Fig.14) that transmits the light reception data to the cloud server (cloud computing environment 50 from [0100]), the determination result being obtained by determining the light reception data as data to be transmitted to the cloud server ([0100]);
and a transmission procedure of analyzing the light reception data to determine at least one of three characteristic amounts including a color, a shape ([0104]: stool consistency is determined from a range of hard and lumpy to unformed and liquid), and an amount of feces ([0106]: Fig. 15E shows the estimation of stool voiding volume or a person);
in a case in which there are a plurality of pieces of feces excreted by a user (voiding volume includes both a plurality or pieces and a whole piece of feces), a procedure of determining the amount of the plurality of pieces of feces (Kashyap, stool voiding volume from [0106]. As best understood and interpreted, in the field of endeavor, voiding volume is the amount of feces that is excreted by the user.) by analyzing the shape of each piece of feces detected (Fig. 15D: separate hard lumps of stool can be identified [0025]) that is excreted through one time of excretion action performed by the user (Kashyap, [0106]).
Kashyap does not teach an edge server, the computer program configured to cause an edge server to perform; and
a determination step where if the light reception data is determined to not include feces, then the light reception data is data not required to be processed by the cloud server and not to be transmitted to the cloud server.;
Iwayama, related to information processing, does teach an edge server (Fig. 1 shown below: field device 50A-50D, edge device 10 is analogous to an edge server here, and cloud server 20) configured to be able to communicate with a device and a cloud server (shown in Fig. 1), the computer program configured to cause an edge server to perform ([0100]: “The client 30 is implemented by the processor 301 reading and executing a program stored in the memory 302 for executing operation of the client 30. In addition, it can also be said that the program causes a computer to execute a procedure or a method of the client 30.”). As seen from Fig. 1 below, the client 30 is implemented by the processor 301 (analogous to a computer program) reading and executing a program stored in the memory 302 for executing operation of the client 30. The client 30 is connected to an edge device (analogous to edge server here) by a communication line 45 which communicates to the edge device to perform a program implemented by the processor 301.;
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and if determined not to include a feature identified by the user, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server ([0038]: The data sorting unit 16 reads the field information (analogous to light reception data) from the data holding unit 13, and sorts the field information 70 into data to be transmitted in the cloud server 20 and data not to be transmitted to the cloud server 20. The sorting of the data here could be adapted so that the determination of whether the data is to be transmitted to the cloud server or not transmitted to the cloud server is dependent on whether there is feces in the light reception data.).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap to incorporate an edge server/device to be able to communicate with the cloud server and a closet bowl device with a data processing step of checking the light reception data for feces and if determined not to include feces, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server, as disclosed by Iwayama. Data analysis on cloud servers have had a problem wherein the validity of the analysis result in the cloud server cannot be determined which causes a risk on system management ([0006] from Iwayama). Edge servers are closer to the location of the data being transmitted ([0004] from Iwayama) than cloud servers, therefore, edge servers enable real-time processing and control while reducing the risk on the system management ([0007] from Iwayama).
By minimizing the amount of data the cloud server needs to process reduces the processing time. Therefore, it is advantageous for a user to want to incorporate a data processing step where data can be sorted and determined to not be transmitted to the cloud server so that the cloud server spends less time analyzing data that does not to be analyzed which optimizes the data processing.
Kashyap combined with Iwayama appears to be silent to a second transmission procedure of analyzing the light reception data to determine at least one characteristic amounts including a color, a shape, and an amount of feces. However, it necessarily follows that with the first transmission procedure which occurs at the edge server where the edge server analyzes data to then be transmitted to the cloud server, that the second transmission procedure which consist of using the cloud server would occur at the cloud server to analyze the light reception data to determine at least one characteristic amounts including a color, a shape and an amount of feces.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap combined with Iwayama where a second analysis of analyzing the light reception data to determine at least one characteristic amounts including a color, a shape, and an amount of feces, disclosed by Kashyap combined with Iwayama. Iwayama discloses that the edge server has a first analysis step where the edge server first processes the data before that data is then transmitted to the cloud server ([0027] and Fig. 1 from Iwayama). Data analysis on cloud servers have had a problem where the validity of the analysis result in the cloud server cannot be determined which causes a risk on system management ([0006] from Iwayama). Edge servers are closer to the location of the data being transmitted ([0004] from Iwayama) than cloud servers, therefore, edge servers enable real-time processing and control while reducing the risk on the system management ([0007] from Iwayama).
Kashyap modified by Iwayama appears to be silent to an adding procedure of adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces.
Ueda, related to a toilet stool device and toilet seat device, does teach an adding procedure of adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected ([0033]: Shape of feces is determined where Fig. 7 shows different shapes of feces.) to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces [0047]: “As shown in FIG. 16, in the second embodiment, as a feature amount, a lateral width Wn of stool indicating a fecal area in the obtained line data Ln is extracted. The determining unit calculates the volume Vn of the truncated cone having the width Wn and the lateral width Wn-1 of the previous line data Ln-1 as the diameter at both ends and the height h. Then, the volume Vn is calculated for all the line data Ln, and the volume of feces is determined by integrating them. The height h of each truncated cone is the fall height of the stool per time interval and is substantially constant.” Shown in Fig. 16).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Kashyap combined with Iwayama to incorporate adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces, as disclosed by Ueda. Being able to analyze properties of stool (which includes shape and volume) can be used to observe the health condition of the human body ([0002] from Ueda).
Regarding Claim 9, Kashyap teaches a cloud server (cloud computing environment 50 from [0100]) and a closet bowl device (Fig. 1: toilet 200; para. [0031]);
a first communication device (assess point 30 from [0100] and shown in Fig. 14 below) configured to be able to communicate with the cloud server;
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a second communication device (assess point 40 from [0102] and in shown in Fig. 14 above) configured to be able to communicate with a portable apparatus.
a memory (memory 51 from [0100-0102] and shown in Fig. 14 above) configured to store detection data related to feces that is optically detected and transmitted from the closet bowl device ([0100-0102]) via the second communication device (shown in Fig. 14 above)
and an arithmetic processing device (processor 52 from [0100-0102] and Fig. 14) configured to analyze the light reception data stored in the memory (Fig. 14: memory 51), wherein
the arithmetic processing device analyzes the light reception data to determine whether feces is included in the light reception data ([0100]), and
if determined to include feces, determines the light reception data as data to be transmitted to the cloud server, and transmits the light reception data to the cloud server by the first communication device ([0100]: “Once defecation and/or urination is complete, which is detected through software-based image detection, the sample collection is disengaged and the images are processed locally or sent through access point 30 (first communication device) to networked computing resources in a cloud computing environment 50. Locally or remotely through memory 51 and processor 52 the images are then analyzed.”).;
and the arithmetic processing device (processor 52 from [0100]) analyzes the light reception data ([0100]) to determine at least one of three characteristic amounts including a color, a shape ([0104]: stool consistency is determined from a range of hard and lumpy to unformed and liquid) and an amount of feces ([0106]: Fig. 15E shows the estimation of stool voiding volume or a person);
wherein, in a case in which there are a plurality of pieces of feces excreted by a user (voiding volume includes both a plurality or pieces and a whole piece of feces), the arithmetic processing device (processor 52 from [0100]) determines the amount of the plurality of pieces of feces (Kashyap, stool voiding volume from [0106]. As best understood and interpreted, in the field of endeavor, voiding volume is the amount of feces that is excreted by the user.) by analyzing the shape of each piece of feces detected (Fig. 15D: separate hard lumps of stool can be identified [0025]) that is excreted through one time of excretion action performed by the user (Kashyap, [0106]).
Kashyap appears silent to a second communication device (assess point 40 from [0102] and in shown in Fig. 14 above) configured to be able to communicate with the closet bowl device. However, Kashyap does disclose a second communication device (Fig. 14: access point 40) which is capable of communication with a portable apparatus and another communication device (Fig. 14: access point 30) which is capable of communication with a toilet apparatus.
One of ordinary skill in the art before the effective filing date would have found it obvious to combine prior art elements (a communication device configured to be able communicate with a closet bowl device or any other device) according to known methods to yield predictable results (to transfer data between all the devices and provide communication between all the devices) (MPEP 2143 (I)(A)).
Kashyap does not teach an edge server configured to be able to communicate with a cloud server and a closet bowl device.
Iwayama does teach an edge server configured to be able to communicate with a cloud server (Para. [0026]: “Note that, the edge device 10 may be directly connected to the cloud server 20 or may be indirectly connected to the cloud server 20 via an access network 43.”; Fig. 1 shown below: (access network 43).
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It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap to incorporate an edge server configured to be able to communicate with a cloud server and a closet bowl device. Data analysis on cloud servers have had a problem wherein the validity of the analysis result in the cloud server cannot be determined which causes a risk on system management ([0006] from Iwayama). Edge servers are closer to the location of the data being transmitted ([0004] from Iwayama) than cloud servers, therefore, edge servers enable real-time processing and control while reducing the risk on the system management ([0007] from Iwayama).
Kashyap modified by Iwayama does not teach the data processing step of checking the light reception data for feces and if determined not to include feces, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server.
Iwayama does teach if determined not to include a feature defined by the user, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server ([0038]: The data sorting unit 16 reads the field information (analogous to light reception data) from the data holding unit 13, and sorts the field information 70 into data to be transmitted in the cloud server 20 and data not to be transmitted to the cloud server 20. The sorting of the data here could be adapted so that the determination of whether the data is to be transmitted to the cloud server or not transmitted to the cloud server is dependent on whether there is feces in the light reception data.).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap and Iwayama with a data processing step of checking the light reception data for feces and if determined not to include feces, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server, as disclosed by Iwayama. By minimizing the amount of data the cloud server needs to process reduces the processing time. Therefore, it is advantageous for a user to want to incorporate a data processing step where data can be sorted and determined to not be transmitted to the cloud server so that the cloud server spends less time analyzing data that does not need to be analyzed which optimizes the data processing.
Kashyap modified by Iwayama appears to be silent to adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces.
Ueda, related to a toilet stool device and toilet seat device, does teach adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected ([0033]: Shape of feces is determined where Fig. 7 shows different shapes of feces.) to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces [0047]: “As shown in FIG. 16, in the second embodiment, as a feature amount, a lateral width Wn of stool indicating a fecal area in the obtained line data Ln is extracted. The determining unit calculates the volume Vn of the truncated cone having the width Wn and the lateral width Wn-1 of the previous line data Ln-1 as the diameter at both ends and the height h. Then, the volume Vn is calculated for all the line data Ln, and the volume of feces is determined by integrating them. The height h of each truncated cone is the fall height of the stool per time interval and is substantially constant.” Shown in Fig. 16).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Kashyap combined with Iwayama to incorporate adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces, as disclosed by Ueda. Being able to analyze properties of stool (which includes shape and volume) can be used to observe the health condition of the human body ([0002] from Ueda).
Regarding Claim 10, Kashyap teaches a toilet seat device disposed on an upper part of a closet bowl (Fig. 2C: toilet seat), the toilet seat device comprising:
a light emitting unit (Fig. 2C: electromagnetic radiation source 210; [0036]) configured to emit light toward an inner part of the closet bowl ([0036]: “An electromagnetic radiation source 210 can emit electromagnetic radiation in the visible and invisible range of the electromagnetic spectrum into a toilet bowl.");
a light receiving unit comprising an image sensor (Fig. 2C: CMOS sensor 211; [0036]) configured to receive light;
a memory (Fig. 14: memory 51; [0100]) configured to store light reception data received by the light receiving unit (Figs. 2C and 14: CMOS sensor 211 on toilet apparatus 200) ([0100]: Once defecation and/or urination is complete, which is detected through software-based image detection, the sample collection is disengaged and the images are processed locally or sent through access point 30 to networked computing resources in a cloud computing environment 50. Locally or remotely through memory 51 and processor 52 the images are then analyzed.);
a communication device (access point 30 from [0100]) configured to transmit the light reception data to a cloud server ([0100]: Once defecation and/or urination is complete, which is detected through software-based image detection, the sample collection is disengaged and the images are processed locally or sent through access point 30 (analogous to a communication device) to networked computing resources in a cloud computing environment 50.);
and an arithmetic processing device (Fig. 14: processor 52; [0100-0102]) configured to analyze the light reception data stored in the memory (Fig. 14: memory 51), wherein
the arithmetic processing device analyzes the light reception data to determine whether feces is included in the light reception data ([0100]), and
if determined to include feces, determines the light reception data as data to be transmitted to the cloud server, and transmits the light reception data to the cloud server by the first communication device ([0100]: “Once defecation and/or urination is complete, which is detected through software-based image detection, the sample collection is disengaged and the images are processed locally or sent through access point 30 to networked computing resources in a cloud computing environment 50. Locally or remotely through memory 51 and processor 52 the images are then analyzed.”).
and the arithmetic processing device (processor 52 from [0100]) analyzes the light reception data ([0100]) to determine at least one of three characteristic amounts including a color, a shape ([0104]: stool consistency is determined from a range of hard and lumpy to unformed and liquid) and an amount of feces ([0106]: Fig. 15E shows the estimation of stool voiding volume or a person);
wherein, in a case in which there are a plurality of pieces of feces excreted by a user (voiding volume includes both a plurality or pieces and a whole piece of feces), the arithmetic processing device (processor 52 from [0100]) determines the amount of the plurality of pieces of feces (stool voiding volume from [0106]. As best understood and interpreted, in the field of endeavor, voiding volume is the amount of feces that is excreted by the user.) by analyzing the shape of each piece of feces detected (Fig. 15D: separate hard lumps of stool can be identified [0025]) that is excreted through one time of excretion action performed by the user ([0106]).
Kashyap does not teach the data processing step of checking the light reception data for feces and if determined not to include feces, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server.
Iwayama does teach if determined not to include a feature defined by the user, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server ([0038]: The data sorting unit 16 reads the field information (analogous to light reception data) from the data holding unit 13, and sorts the field information 70 into data to be transmitted in the cloud server 20 and data not to be transmitted to the cloud server 20. The sorting of the data here could be adapted so that the determination of whether the data is to be transmitted to the cloud server or not transmitted to the cloud server is dependent on whether there is feces in the light reception data.).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap with a data processing step of checking the light reception data for feces and if determined not to include feces, determines the light reception data as data not required to be processed by the cloud server and not to be transmitted to the cloud server. By minimizing the amount of data the cloud server needs to process reduces the processing time. Therefore, it is advantageous for a user to want to incorporate a data processing step where data can be sorted and determined to not be transmitted to the cloud server so that the cloud server spends less time analyzing data that does not to be analyzed which optimizes the data processing.
Kashyap modified by Iwayama appears to be silent to adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces.
Ueda, related to a toilet stool device and toilet seat device, does teach adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected ([0033]: Shape of feces is determined where Fig. 7 shows different shapes of feces.) to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces [0047]: As shown in FIG. 16, in the second embodiment, as a feature amount, a lateral width Wn of stool indicating a fecal area in the obtained line data Ln is extracted. The determining unit calculates the volume Vn of the truncated cone having the width Wn and the lateral width Wn-1 of the previous line data Ln-1 as the diameter at both ends and the height h. Then, the volume Vn is calculated for all the line data Ln, and the volume of feces is determined by integrating them. The height h of each truncated cone is the fall height of the stool per time interval and is substantially constant.” Shown in Fig. 16).
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Kashyap combined with Iwayama to incorporate adding up an amount of the plurality of pieces of feces by analyzing the shape of each piece of feces detected to calculate an estimated volume for each piece of feces based on a detected two-dimensional area and an estimated height, and adding up the estimated volumes to analyze the amount of the feces, as disclosed by Ueda. Being able to analyze properties of stool (which includes shape and volume) can be used to observe the health condition of the human body ([0002] from Ueda).
Claims 3 and 6 is rejected under 35 U.S.C. 103 as being unpatentable over Kashyap (US 20180303466 A1) in view of Iwayama (US 2019/0258214 A1) and Ueda (JP 2018146244A, where portions of an attached translation are cited below), and further in view of Shino (“A Task Allocation Method Based on Application Features and Network Conditions in Edge Computing”).
Regarding Claim 3, Kashyap modified by Iwayama and Ueda teaches the excrement management system according to claim 2.
Kashyap modified by Iwayama and Ueda further teaches a first communication device (Kashyap, access point 30 from [0100]) configured to perform transmission/reception of data to the cloud server (Kashyap, cloud computing environment 50 from [0100] and shown in Fig. 14).
Kashyap modified by Iwayama and Ueda (for claim 2), does not teach that the first communication device is configured to perform transmission/reception of data between the cloud server and the edge server.
Iwayama, related to information processing, does teach that a communication device (Fig. 1, shown below: access network 43) is configured to perform transmission/reception of data (Fig. 1: information processing system 100) between the cloud server and the edge server (Para. [0026]: “Note that, the edge device 10 may be directly connected to the cloud server 20 or may be indirectly connected to the cloud server 20 via an access network 43”).
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It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap combined with Iwayama and Ueda (for claim 2), so that the first communication device is configured to perform transmission/reception of data between the cloud server and the edge server, as disclosed by Iwayama. It is known within the field of information processing that edge servers have been used in combination with cloud servers with the advantage of minimizing the risk on system management that occurs when using only cloud servers to analyze large quantities of data ([0002-0004] and [0006-0007] from Iwayama).
Kashyap combined with Iwayama and Ueda does not teach data capacity that is transmitted from the cloud server to the edge server via the first communication device is smaller than data capacity of the light reception data that is transmitted from the edge server to the cloud server via the first communication device.
Shino, related to information processing, does teach data capacity that is transmitted from a device to an edge device is smaller than data capacity of the data that is transmitted to a cloud server (page 3, section 2: “Proposed method” to page 7, section 3.3: “Experiment 2”).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap combined with Iwayama and Ueda so that data capacity that is transmitted from a device to an edge device is smaller than data capacity of the data that is transmitted to a cloud server, as disclosed by Shino. Shino discloses how cloud servers, which have higher processing capability are more beneficial to use when processing large amounts of data than edge servers because the cloud servers would have lower response times (shown in Fig. 2 and described in section 3.2 on pages 6-7). Shino further discloses that edge servers are more advantageous to use when processing smaller amounts of data wherein the edge servers would have a lower response time compared to cloud servers (Fig. 2). Therefore, it is obvious to one of ordinary skill in the art that the data capacity transmitted from the cloud server to the edge server is smaller than the data capacity transmitted from the edge server to the cloud server as this would overall optimize the data processing times of both the edge and the cloud server.
Regarding Claim 6, Kashyap modified by Iwayama and Ueda teaches the excrement management system according to claim 1.
Kashyap modified by Iwayama and Ueda discloses an edge server (Iwayama, edge device 10 from [0022]).
Kashyap modified by Iwayama and Ueda appears to be silent to the user information about a user who uses the closet bowl is previously recorded in the cloud server.
However, Kashyap is related to a biomonitoring device (Abstract) which can identify a user using a closet bowl ([0054]: “Fingerprint sensor 404 is an example of an identification method that uniquely identifies the user. Passive infrared sensor 405 can be used to detect user presence.”) and with identifying the user would be able to detect an illness in the user (by analyzing the user’s excrement) and dispenses medication to the user. Kashyap also discloses the use of a cloud computing environment 50 ([0100]) which can store user information. It would have been obvious to one of ordinary skill in the art before the effective filing date to have devised of a biomonitoring device which can identify a user to also record/store said user information as it is beneficial to be able to record the user’s information to be able to document and monitor information relevant to the user’s health.
Kashyap modified by Iwayama and Ueda appears to be silent to the light reception data that is determined to be transmitted by the edge server is associated with the user information that is previously recorded in the cloud server.
Shino, related to information processing, does disclose how edge and cloud servers are commonly used in information processing systems and the processes performed by either a cloud server or an edge server can be decided by the user as needed (page 3, section 2 “Proposed Method” to page 7, section “Conclusion).
Therefore, the choice of the light reception data, which is associated with the user information that is previously recorded, being transmitted by an edge server (or the cloud server) is arbitrary and one of ordinary skill of the art before the effective filing date would have known to choose the device (edge or cloud server) which would best optimize the data processing.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Kashyap (US 20180303466 A1) in view of Iwayama (US 2019/0258214 A1) and Ueda (JP 2018146244 A, where portions of an attached translation are cited below), and further in view of Sathyanarayana (US 20180167434 A1).
Regarding Claim 11, Kashyap modified by Iwayama and Ueda teaches the excrement management system according to claim 1.
Kashyap modified by Iwayama and Ueda further teaches analysis of the light reception data to determine that the light reception data is not the light reception data to transmitted to the cloud server (Iwayama, [0038]: “The data sorting unit 16 reads the field information (analogous to light reception data) from the data holding unit 13, and sorts the field information 70 into data to be transmitted in the cloud server 20 and data not to be transmitted to the cloud server 20.”), and an edge server (Iwayama, Fig. 1: edge device).
Kashyap modified by Iwayama and Ueda appears to be silent to the edge server deletes the light reception data from a storage region of the edge server.
Sathyanarayana, related to information processing of edge servers, does teach data to be deleted from the storage region of the edge server ([0050]: “…the edge server deletes expired segments from the central storage cluster...”).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Kashyap combined with Iwayama and Ueda to have created an excrement management system wherein upon analysis of the light reception data to determine that the light reception data is not the light reception data to be transmitted to the cloud server, the edge server deletes the light reception data from a storage region of the edge server, as disclosed by Sathyanarayana. It is advantageous for the user to want to delete unused data from the data storage region as this would offload the information management system of the central storage cluster (Abstract and [0010] from Sathyanarayana).
Conclusion
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/JUDY DAO TRAN/Examiner, Art Unit 2877
/MICHELLE M IACOLETTI/Supervisory Patent Examiner, Art Unit 2877