DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim 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.
Claim 15 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 15 recites the limitation "said number of occupants" in line 1 of the claim. There is insufficient antecedent basis for this limitation in the claim.
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.
Claim(s) 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 17, 18, 19, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rudd (US 20200393324) in view of Burke (US 20180330597).
Regarding claim 1, A method of inhibiting damage from fluid leaks in a structure, the method comprising: providing a flow detection system which detects fluid flow into a at least a portion of the structure; (“The smart water valve includes a water flow sensor that is capable of measuring a wide range of flow rates, such as high flow rates (3600 liters per hour or 60 liters per minute, for example), to ultra-low flow rates (0-6 liters per hour) in plumbing systems” Rudd: paragraph 31)
providing an occupancy detection system which detects that if said portion of said structure is occupied or not; (“In some implementations, determining the expected rate of water consumption at the property includes: receiving, from one or more sensors, occupancy data that reflects an occupancy of the property” Rudd: paragraph 15)
detecting a fluid flow in the portion of the structure; (“The smart water valve 126 can determine a current rate of water consumption at the property 102, e.g., using the leak sensor. Determining with a leak sensor that a water leak is occurring at the property can include determining that a water flow rate through a pipe, e.g., the cold water input 124, is greater than zero liters per hour. In some cases, the leak sensor 214 may determine that the water flow rate through the pipe is greater than zero liters per hour and less than six liters per hour. For example, the leak sensor 214 may determine that the water flow rate through the cold water input 124 is 0.5 liters per hour.” Rudd: paragraph 109)
determining if said fluid flow corresponds to an amount which is anomalous for that portion at a current time; (“determining, based on the occupancy data, the expected rate of water consumption at the property” Rudd: paragraph 15 & “The process 400 includes, after determining that the water leak is occurring at the property, determining that a water usage profile of a particular water consuming device matches characteristics of the water leak (404). The smart water valve 126 can store device water usage profiles that can be used to predict which device is potentially leaking water. A device water usage profile describes how a particular device, such as the faucet 134c, consumes and/or uses water. Additionally, the device water usage profiles can store timestamped data of previous water consumption events corresponding to the particular device” Rudd: paragraph 115)
determining if said portion of the structure is currently occupied; (“Determining the expected rate of water consumption at the property can include receiving, from one or more sensors, occupancy data that reflects an occupancy of the property. For example, occupancy data can include an estimated occupancy of the property 102 based on motion sensor data, video image data, audio data, monitoring system arming status, etc. The occupancy data may reflect that the property 102 is unoccupied. The smart water valve 126 can determine, based on the occupancy data, the expected rate of water consumption at the property 102. For example, based on the occupancy data reflecting that the property 102 is unoccupied, the smart water valve 126 may determine that the expected rate of water consumption at the property 102 is zero liters per hour” Rudd: paragraph 108)
initiating an alarm; (“In some implementations, the security system 148 can produce a likelihood that a device found within the monitored property 102 is leaking. The likelihood can be a statistical likelihood, such as a percentage that indicates how likely the device is currently leaking water. The likelihood with the greatest value, for example, can be deemed the predicted device that is leaking water. The security system 148 can inform the property owner 120 of the possibility that the smart water valve 126 has detected a water leak with the predicted device. In particular, the security system 148 can transmit a notification to the client device 122 of the property owner 120.” Rudd: paragraph 51)
The claimed and if said portion of said structure is currently occupied, initiating a first level of alarm; and if said portion of said structure is currently unoccupied, initiating a second level of alarm different from said first level or alarm is not specifically disclosed by Rudd. Burke discloses a home monitoring system that includes detecting water leaks that teaches altering the level of alarm based on detected occupancy state (“With regard to the step of selecting an action to be taken responsive to the potential alarm event and the selected confidence level 120, action to be taken represents the action that could be taken by the alarm system in response to the occurrence of a specific potential alarm event in the designated area in a given confidence level of an occupancy state” Burke: paragraph 139 & “Raise an alarm: this action to be taken is a critical response to an active threat situation. Depending on the level of service, the following may be relevant: [0161] if central station monitoring is subscribed, then send a threat message to the appropriate central station; [0162] if the confidence level of the occupancy state is at the lowest level (e.g., homeowner input to UI that s/he is on vacation), then raise an alarm to a delegated trusted group, if any; [0163] raise an alarm to the designated area (home) owner; [0164] if the home owner does not respond to the alarm, raise an alarm to all other adult users of the designated area; and [0165] sound the siren installed in the designated area” Burke: paragraph 160). Modifying Rudd to include additional alarm levels based on detected occupancy of the premises would increase the overall usefulness of the system by providing tailored alerts to the users. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Rudd according to Burke.
Regarding claim 2, The method of claim 1 wherein said first level of alarm comprises monitoring said amount of flow for further anomalies. (“In some examples, determining with a leak sensor that a water leak is occurring at the property can include determining that the water flow rate through the pipe is greater than zero liters per hour for a time duration that is greater than a threshold time duration. For example, a threshold time duration may be twenty minutes. The smart water valve 126 may determine that the water flow rate through the cold water input 124 is 1.0 liters per hour for a time duration of twenty-one minutes. Thus, the smart water valve 126 can determine that the water flow rate through the pipe is greater than zero liters per hour for a time duration that is greater than the threshold time duration.” Rudd: paragraph 110; detecting the flow and then monitoring it for an additional period of time to determine if the flow has gone on for long enough to be an alarm worth raising)
Regarding claim 3, The method of claim 2 wherein said second level of alarm comprises an indicator to occupants of said structure. (“During stage (E), the security system 148 can transmit a notification 150 to the client device 122 of the property owner 120. In particular, the notification 150 can indicate to the property owner 120 that the predicted or determined device is potentially leaking water. For example, the notification can recite, “Shower head is potentially leaking water.”” Rudd: paragraph 77)
Regarding claim 4, The method of claim 2 wherein said second level of alarm comprises notifying a mobile device of said second level of alarm. (Rudd: figure 1)
Regarding claim 5, The method of claim 2 wherein said second level of alarm comprises said flow detection system shutting off said flow to said portion. (“In some implementations, users can enable rule-based events corresponding to the smart water valve 126. Through the client device 122 or interfacing directly with the smart water valve 126, a property owner 120 or other user can set up rules on the smart water valve 126. The rules can include threshold based flow rules and temperature event rules based on the water that flows through the smart water valve. In particular, the rules can use threshold values, time stamps, flow rates, and water temperature to execute responses. For example, a user can configure the smart water valve 126 to shut off water supply to the monitored property 102 if the rate of water from the cold water input 124 is above 24 gallons per minute. In another example, the smart water valve 126 can shut off water supply to the monitored property 102 if the water pressure from the cold water input 124 is supplied at a pressure less than 10 PSI” Rudd: paragraph 62)
Regarding claim 6, The method of claim 1 wherein said first level of alarm comprises an indicator to occupants of said structure. (“Passively notify designated area (e.g., house) occupants: the corresponding potential alarm event, while a normal event in the house, is at a high enough priority that it warrants notifying the occupants in a passive manner.” Burke: paragraph 150)
Regarding claim 7, The method of claim 6 wherein said second level of alarm comprises notifying a mobile device of said second level of alarm. (Rudd: figure 1 & “Broadcast to all locally connected mobile communication device applications a notification that an unidentified person may have entered and that authentication is required.” Burke: paragraph 145)
Regarding claim 8, The method of claim 6 wherein said second level of alarm comprises said flow detection system shutting off said flow to said portion. (“In some implementations, users can enable rule-based events corresponding to the smart water valve 126. Through the client device 122 or interfacing directly with the smart water valve 126, a property owner 120 or other user can set up rules on the smart water valve 126. The rules can include threshold based flow rules and temperature event rules based on the water that flows through the smart water valve. In particular, the rules can use threshold values, time stamps, flow rates, and water temperature to execute responses. For example, a user can configure the smart water valve 126 to shut off water supply to the monitored property 102 if the rate of water from the cold water input 124 is above 24 gallons per minute. In another example, the smart water valve 126 can shut off water supply to the monitored property 102 if the water pressure from the cold water input 124 is supplied at a pressure less than 10 PSI” Rudd: paragraph 62)
Regarding claim 9, The method of claim 1 wherein said portion of said structure comprises a specific room in said structure. (Rudd: figure 1; showing individual rooms being monitored)
Regarding claim 10, The method of claim 1 wherein said at least a portion of said structure comprises the entirety of said structure. (Rudd: figure 1; showing the entire house being monitored through the water line entering the house)
Regarding claim 11, The method of claim 1 wherein said detecting requires a level of flow above a predetermined threshold. (“In some implementations, users can enable rule-based events corresponding to the smart water valve 126. Through the client device 122 or interfacing directly with the smart water valve 126, a property owner 120 or other user can set up rules on the smart water valve 126. The rules can include threshold based flow rules and temperature event rules based on the water that flows through the smart water valve. In particular, the rules can use threshold values, time stamps, flow rates, and water temperature to execute responses. For example, a user can configure the smart water valve 126 to shut off water supply to the monitored property 102 if the rate of water from the cold water input 124 is above 24 gallons per minute. In another example, the smart water valve 126 can shut off water supply to the monitored property 102 if the water pressure from the cold water input 124 is supplied at a pressure less than 10 PSI” Rudd: paragraph 62)
Regarding claim 13, The method of claim 1 wherein said occupancy detection system detects and tracks a specific occupant within said structure. (“One embodiment of the invention further contemplates tracking one or more identified users (“identified user tracking”). For each user identified in the designated area, the alarm system attempts to track their presence. An identified user's presence is set to “away” from the designated area when the alarm system transitions to the lowest confidence level of occupancy state 210 and presumes all individuals are no longer on the designated premises (e.g., no longer in in the house).” Burke: paragraph 77 & “A histogram of previous activity strongly suggests that the designated area is occupied or likely occupied only by one or more unidentified occupants (for example, people not positively tracked by identified user tracking as described elsewhere herein)” Burke: paragraph 188)
Regarding claim 17, The method of claim 1 wherein said flow detection system utilizes machine learning in determining if said flow corresponds to said amount which is anomalous for that portion at said current time. (“In some implementations, the security system 148 can store, train, and manage a machine-learning algorithm for each of the monitored properties. For example, the machine-learning algorithm can be trained with data provided from the control unit server 104, data provided by the smart water valve 126, and data associated with the security system 148 to predict devices that are leaking water. For example, the security system 160 can use a stored machine-learning algorithm such as a deep learning algorithm, an anomaly detecting algorithm, a linear regression algorithm, or a logistic regression algorithm, or a combination of various machine-learning algorithms, to name a few examples.” Rudd: paragraph 44)
Regarding claim 18, The method of claim 1 wherein machine learning is utilized in determining said first level of alarm and said second level of alarm after each anomalous flow detection. (“In some implementations, the security system 148 can store, train, and manage a machine-learning algorithm for each of the monitored properties. For example, the machine-learning algorithm can be trained with data provided from the control unit server 104, data provided by the smart water valve 126, and data associated with the security system 148 to predict devices that are leaking water. For example, the security system 160 can use a stored machine-learning algorithm such as a deep learning algorithm, an anomaly detecting algorithm, a linear regression algorithm, or a logistic regression algorithm, or a combination of various machine-learning algorithms, to name a few examples.” Rudd: paragraph 44 & “In one embodiment, the alarm system receiving input regarding the sensitivity level for the alarm system comprises receiving machine-learned input and/or user input, for example, user input via the user interfaces described above, regarding the sensitivity level for the alarm system.” Burke: paragraph 167)
Regarding claim 19, The method of claim 1 wherein said detection system communicates with an automated fluid using system in determining if said flow corresponds to said amount which is anomalous for that portion at said current time. (Rudd: figure 1; the Hot Water Heater is automated to control the temperature of the water inside the water tank).
Regarding claim 20, The method of claim 1 wherein said fluid is water. (Rudd: figure 1)
Claim(s) 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rudd in view of Burke and further in view of Aliakseyeu (US 20220413125).
Regarding claim 12, The method of claim 1 wherein said occupancy detection utilizes Network Presence Sensing (NPS) detection is not specifically disclosed by Rudd and Burke. Aliakseyeu discloses a home monitoring system that teaches using a Network Presence Sensing system to manage a plurality of sensing nodes (“The method may be performed by a controller of a network presence sensing system, for example. A network presence sensing system comprises a plurality of sensing nodes and the controller may be one of these nodes” Aliakseyeu: paragraph 62). Modifying Rudd and Burke to use a Network Presence Sensing system would increase the flexibility of the system by providing the user with alternate means to implement the sensing. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Rudd and Burke according to Aliakseyeu.
Claim(s) 14, 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rudd in view of Burke and further in view of Ellenbogen (US 20170099200).
Regarding claim 14, The method of claim 1 wherein said occupancy detection system counts a number of occupants within said structure is not specifically disclosed by Rudd and Burke. Ellenbogen discloses monitoring a security system that teaches using a count of people to determine if anomalies exist (“The security system can be implemented in many ways. For example, the security system can include a system to detect for physical intrusion into a space (e.g., whether a person is trespassing in a restricted area); a system to determine whether an individual should or should not be allowed access (e.g., a security gate); a system to detect for objects, people, or vehicles loitering in a region; a system to detect for certain behavior exhibited by a person (e.g., suspicious behavior); a system to detect track a person or object viewed from one asset (e.g., camera) to another asset; a system to determine the status of an object in the asset field of view (e.g., whether there is snow on a walkway); a system to count people or objects (e.g., vehicles) in a scene; a system to detect for abnormal conditions (e.g., as compared to a baseline condition); a system to detect license plates over time; a system to detect for weapons, contraband, or dangerous materials on a person or within a container (e.g., a security checkpoint); and the like” Ellenbogen: paragraph 141). Modifying Rudd and Burke to include a count of people would increase the overall capabilities of the system by providing additional means for making alarm determinations. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Rudd and Burke according to Ellenbogen.
Regarding claim 15, The method of claim 1 wherein said number of occupants is used to determine if said flow is anomalous is not specifically disclosed by Rudd and Burke. Ellenbogen discloses monitoring a security system that teaches using a count of people to determine if anomalies exist (“The security system can be implemented in many ways. For example, the security system can include a system to detect for physical intrusion into a space (e.g., whether a person is trespassing in a restricted area); a system to determine whether an individual should or should not be allowed access (e.g., a security gate); a system to detect for objects, people, or vehicles loitering in a region; a system to detect for certain behavior exhibited by a person (e.g., suspicious behavior); a system to detect track a person or object viewed from one asset (e.g., camera) to another asset; a system to determine the status of an object in the asset field of view (e.g., whether there is snow on a walkway); a system to count people or objects (e.g., vehicles) in a scene; a system to detect for abnormal conditions (e.g., as compared to a baseline condition); a system to detect license plates over time; a system to detect for weapons, contraband, or dangerous materials on a person or within a container (e.g., a security checkpoint); and the like” Ellenbogen: paragraph 141). Modifying Rudd and Burke to include a count of people for anomaly determinations would increase the overall capabilities of the system by providing additional means for making alarm determinations. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Rudd and Burke according to Ellenbogen.
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rudd in view of Burke and further in view of Zhu (US 20240125888).
Regarding claim 16, The method of claim 1 wherein said occupancy detection system segregates human occupants from non-human occupants within said structure is not specifically disclosed by Rudd and Burke. Zhu discloses a home monitoring system that teaches differentiating between detecting humans and non-humans (“The present teaching discloses a novel system called “WI-MOID”: WiFi-based human and non-human motion identification, which can accurately identify various human and non-human subjects through walls. In some embodiments, the system passively and unobtrusively distinguishes moving human and various non-human subjects using a single pair of commodity WiFi transceivers, without requiring any device on the subjects or restricting their movements. WI-MOID leverages a novel statistical electromagnetic wave theory-based multipath model to detect moving subjects, extracts physically and statistically explainable features of their motion, and accurately differentiates human and various non-human movements through walls, even in complex environments. In addition, WI-MOID is suitable for edge devices, requiring minimal computing resources and storage, and is environment-independent, making it easy to deploy in new environments with minimum effort. The performance of WI-MOID has been validated in four distinct buildings with various moving subjects, including pets, vacuum robots, humans, and fans, and the results demonstrate that it achieves high accuracy and low false alarm rate for identification of human and non-human motion, including high accuracy in unseen environments without model tuning, demonstrating its robustness for ubiquitous use” Zhu: paragraph 135). Modifying Rudd and Burke to differentiate between humans and non-humans would increase the overall accuracy of the system by allowing it to ignore non-humans when determining leaks. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Rudd and Burke according to Zhu.
Conclusion
Related Art:
US 20240144807 A1 – structure monitoring for water damage
US 20200092742 A1 – counting people and detecting abnormal occurrences
US 20190294136 A1 – monitoring fluid flow with occupancy monitoring
US 20170357275 A1 – monitoring fluid flow with occupancy monitoring
US 20170130430 A1 – monitoring fluid flow with occupancy monitoring
US 20110166714 A1 – monitoring fluid flow with occupancy monitoring
US 20030192600 A1 – monitoring fluid flow with occupancy monitoring
US 5038820 A – monitoring fluid flow with occupancy monitoring
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TRAVIS R HUNNINGS whose telephone number is (571)272-3118. The examiner can normally be reached M: 6-7:30a, 9:30a-4:45p, 8:30-10p; T: 6-7:30a, 12-4p, 7:30p-12a; W: 6-7:30a, 9:30a-4:45p; H: 6-7:30a, 8:15a-4:45p; F: 12:00-4:45p.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Davetta Goins can be reached at 571-272-2957. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/TRAVIS R HUNNINGS/ Primary Examiner, Art Unit 2689