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 .
Claims 1-20 have been presented for examination.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-4, 7 and 11-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Carter et al1 in view of Khalate et al [Khalate] PGPUB 2018/0373234.
Referring to claim 1, Carter teaches the bather load detection system for a swimming pool system having a pool and at least one pool device, the bather load detection system comprising:
a data capture device associated with the pool system designed to capture at least one image [70 Fig. 3].
a controller communicatively coupled to the data capture device, the controller designed to:
detect one or more bathers based on the at least one image [72 Fig. 3, 0017, 0019].
determine a bather load based on the one or more detected bathers [78 Fig. 3, 0017, 0019].
predict at least one operational change for the at least one pool device based on the bather load [80 Fig. 3, 0017-0019].
provide instructions to the at least one pool device of the pool system to change at least one operational parameter of the at least one pool device based on the predicted operational change [82 Fig. 3, 0017-0019].
In summary Carter teaches a pool monitoring system where a camera images a pool to determine the bather load and calculates (i.e., predicts) the adjustments to sanitation and pump operation accordingly.
While Carter teaches predicting operational change based on bather load, it is not explicitly taught to further consider historical load data corresponding to one or more previous time periods. Khalate teaches determining operational changes based on occupancy that also covers historical occupancy (i.e., equivalent to historical load) [0138-0142]. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the teachings of Khalate into Carter because it would allow Carter to predictably operate the sanitation and pump operation to pre-dose ahead of the expected load rather than once the bathers are already in the pool.
While Khalate does not explicitly teach pool control, Khalate does highlight the benefit to adjust operational parameters based on occupancy and predicted occupancy. Such a concept would be obviously applicable to all systems which could benefit from anticipating operation based on occupancy which Carter does.
Referring to claim 2, Carter teaches the camera is an infrared or thermal camera [0013].
Referring to claims 3-4, Carter teaches adjusting sanitation and/or pump speed [0018-0019].
Referring to claim 7, this is rejected on the same basis as set forth hereinabove with respect to claims 1-2. Carter teaches the system and therefore teaches the method performed by the system.
Referring to claim 11, Carter teaches that the image processing and operational parameter prediction discussed above is performed via CPU executing video processing algorithms [Fig. 4 and 0022].
Referring to claims 12-13, because the image data is being analyzed via algorithms executed by the CPU, it is inherent that the image data is stored in memory. Without saving the image data in memory, the image data would not be available to be analyzed by the CPU as it would not be retained. As stated above, the image data is processed in order to predict the change to an operational parameter (i.e., adjustments to the sanitation system and/or pump operation).
Referring to claim 14, Carter teaches transmitting “alerts or commands to pool/spa users and devices to modify operation thereof” [abstract]. It is presumed that the commands to modify operation would include the operational parameter to modify sanitation and/or pump operation. While Carter teaches that indicated above, it is not explicitly taught that the commands are sent to the devices to modify operation while simultaneously notifying the users of the action taken. In other words, it is unclear if notifying the user is an alternative to automatic control to allow the user to modify operation in place of allowing the system to modify itself. The examiner is taking official notice that the concept of providing operational information to users is a well-known practice in the art of control systems and it would have been obvious to one of ordinary in the art to provide the user with the operational parameter that the system is using to modify sanitation/pump operation because it would provide the predictable benefit of keeping the user informed with how the pool is operating.
Claim(s) 1-2, 4, 7-9 and 11-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eames2 in view of Khalate.
Referring to claim 1, Eames teaches the bather load detection system for a swimming pool system having a pool and at least one pool device, the bather load detection system comprising:
a data capture device associated with the pool system designed to capture at least one image [0028].
a controller communicatively coupled to the data capture device; the controller designed to:
detect one or more bathers based on the at least one image [0028, 0050].
determine a bather load based on the one or more detected bathers [0050].
predict at least one operational change for the at least one pool device based on the bather load [0050].
provide instructions to the at least one pool device of the pool system to change at least one operational parameter of the at least one pool device based on the predicted operational change [0050].
In summary Eames teaches a pool monitoring system where a camera images a pool to determine the bather load and calculates (i.e., predicts) how to sanitize the water based on the load and implements chemical dosing to sanitize the water accordingly.
While Eames teaches predicting operational change based on bather load, it is not explicitly taught to further consider historical load data corresponding to one or more previous time periods. Khalate teaches determining operational changes based on occupancy that also covers historical occupancy (i.e., equivalent to historical load) [0138-0142]. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the teachings of Khalate into Eames because it would allow Eames to predictably operate the sanitation and pump operation to pre-dose ahead of the expected load rather than once the bathers are already in the pool.
While Khalate does not explicitly teach pool control, Khalate does highlight the benefit adjust operational parameters based on occupancy and predicted occupancy. Such a concept would be obviously applicable to all systems which could benefit from anticipating operation based on occupancy which Eames does.
Referring to claim 2, Eames teaches the camera is an infrared camera [0028].
Referring to claim 4, Eames teaches the pool device sanitizing the water [0050].
Referring to claim 7, this is rejected on the same basis as set forth hereinabove with respect to claims 1-2. Eames teaches the system and therefore teaches the method performed by the system.
Referring to claims 8-9, Eames teaches the infrared camera can be integrated with a robotic pool cleaner or pool light [0021, 0030].
Referring to claim 11, Eames teaches that the image data is received by controller (114) and the image processing and operational parameter prediction discussed above is performed via controller including a processor and memory [104, 114 Fig. 2, 0031, 0033].
Referring to claims 12-13, Eames teaches that the controller which performs the image processing and control is performed via computer processor and memory [0031]. The examiner is taking official notice that a computer processor performs execution on stored data. As indicated above with respect to Carter, the same applies to Eames in that without saving the image data in memory, the image data would not be available to be analyzed by the CPU as it would not be retained. Therefore, it is interpreted that Eames also stores the image data for processing so that the controller can determine how to adjust sanitation operation.
Referring to claim 14, Eames teaches sending a summary of the actions taken (i.e., adjustments to sanitation operation) based on a number of occupants detected (i.e., bather load) [0046].
Claim(s) 5-6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Carter and Khalate as applied to claims 1-4, 7 and 11-14 above, and further in view of Zima3.
Referring to claims 5-6, while Carter teaches adjusting the sanitation according to bather load, it is not explicitly taught to measure at least one chemical at a first and second time after the instruction to adjust sanitation is issued. Zima teaches testing chlorine/acidity/alkalinity in the water over time to determine trends in the water chemistry [0025-0026]. Identifying trends implies that comparisons are made between the samples to determine if the chlorine/pH levels are increasing or decreasing over time. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the teachings of Zima into Carter because it would allow the user to detect trends in the water chemistry to determine if there is need for further pool maintenance.
Claim(s) 8-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Carter and Khalate as applied to claims 1-4, 7 and 11-14 above, and further in view of Eames.
Referring to claims 8-9, while Carter teaches including an infrared camera, it is not explicitly taught that the camera is provided in a robotic pool cleaner or within at least one light or drain of the pool. Eames teaches the infrared camera can be integrated with a robotic pool cleaner or pool light [0021, 0030]. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the teachings of Eames into Carter because Carter does not explicitly teach where cameras could be placed and Eames teaches where cameras can be placed to determine bather load which Carter is also directed towards.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Carter and Khalate as applied to claims 1-4, 7 and 11-14 above, and further in view of Mullaly4.
Referring to claim 10, while Carter teaches determining bather load via analyzing thermal imaging [0013, 0018-0019] it is not explicitly taught that imaging data is provided as a rolling average of a pixel count. The examiner is taking official notice that occupancy detection via thermal imaging is based on pixel count data5. Mullaly teaches determining real-time occupancy by using either real-time values or using short-term moving averages (i.e., rolling averages) of an occupancy sensor [0026, 0057]. While Mullaly determining a rolling average of occupancy is not necessarily for identifying bather load, it still would have been obvious to one of ordinary skill in the art before the effective filing date to include modify Carter to identify occupancy as a rolling average because Mullaly teaches that both real-time and short-term rolling averages are both usable metrics for real time occupancy detection and a person of ordinary skill has good reason to pursue the known options within his or her technical grasp. Because Carter detects swimmers via thermal imaging, determining a rolling average of swimmers via thermal imaging would necessarily involve a rolling average of the thermal imaging pixels (see above). Lastly, utilizing a rolling average additionally provides the known benefit of presenting the bather load data in a non-erratic manner. In an environment where swimmers are constantly entering and exiting a pool, this could cause erratic operation (known in some arts as “thrashing”) where operations change erratically due to a measured value changing about a triggering threshold(s). For example, Carter adjusts both chemical dosing and pump operation based on bather load. If the number of swimmers briefly exceeds a threshold that would trigger increased dosing, too much chlorine could be added to the pool because the instantaneous measurement would not be representative of the overall pool occupancy. Additionally, constant varying occupancy could also cause the pump to constantly adjust its speed leading to inefficient operation and possible premature wear.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eames and Khalate as applied to claims 1-2, 4, 7-9 and 11-14 above, and further in view of Carter.
Referring to claim 3, while Eames teaches on controlling bather load and adjusting sanitation accordingly, it is not further taught to also control a pool pump. Carter teaches not only adjusting sanitation but also that a pump speed can also be adjusted in response to bather load [0018-0019]. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the teachings of Carter into Eames because Carter teaches that both sanitation and pool pump speed are necessary to adjust to optimize their usage in response to bather load [0019].
Claim(s) 5-6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eames and Khalate as applied to claims 1-2, 4, 7-9 and 11-14 above, and further in view of Zima6.
Referring to claims 5-6, while Eames teaches adjusting the sanitation according to bather load, it is not explicitly taught to measure at least one chemical at a first and second time after the instruction to adjust sanitation is issued. Zima teaches testing chlorine/acidity/alkalinity in the water over time to determine trends in the water chemistry [0025-0026]. Identifying trends implies that comparisons are made between the samples to determine if the chlorine/pH levels are increasing or decreasing over time. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the teachings of Zima into Eames because it would allow the user to detect trends in the water chemistry to determine if there is need for further pool maintenance.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eames and Khalate as applied to claims 1-2, 4, 7-9 and 11-14 above, and further in view of Mullaly.
Referring to claim 10, while Eames teaches determining bather load via analyzing thermal imaging [0028, 0050] it is not explicitly taught that imaging data is provided as a rolling average of a pixel count. The examiner is taking official notice that occupancy detection via thermal imaging is based on pixel count data7. Mullaly teaches determining real-time occupancy by using either real-time values or using short-term moving averages (i.e., rolling averages) of an occupancy sensor [0026, 0057]. While Mullaly determining a rolling average of occupancy is not necessarily for identifying bather load, it still would have been obvious to one of ordinary skill in the art before the effective filing date to include modify Eames to identify occupancy as a rolling average because Mullaly teaches that both real-time and short-term rolling averages are both usable metrics for real time occupancy detection and a person of ordinary skill has good reason to pursue the known options within his or her technical grasp. Because Eames detects swimmers via thermal imaging, determining a rolling average of swimmers via thermal imaging would necessarily involve a rolling average of the thermal imaging pixels (see above). Lastly, utilizing a rolling average additionally provides the known benefit of presenting the bather load data in a non-erratic manner. In an environment where swimmers are constantly entering and exiting a pool, this could cause erratic operation (known in some arts as “thrashing”) where operations change erratically due to a measured value changing about a triggering threshold(s). For example, Eames adjusts chemical dosing based on bather load. If the number of swimmers briefly exceeds a threshold that would trigger increased dosing, too much chlorine could be added to the pool because the instantaneous measurement would not be representative of the overall pool occupancy.
Response to Arguments
Applicant’s arguments, see the REMARKS, filed 6/3/26, with respect to the rejection(s) of claim(s) 1-14 under 35 USC 102 and 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 Khalate.
Allowable Subject Matter
Claims 15-20 are allowed.
Prior Art Not Relied Upon
PGPUB 2012/0310376 to Krumm et al teaches looking at historical occupancy patterns to identify future occupancy probability [abstract].
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARK A CONNOLLY whose telephone number is (571)272-3666. The examiner can normally be reached Monday-Friday 9am-5pm.
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/MARK A CONNOLLY/Primary Examiner, Art Unit 2115 7/28/26
1 Cited in the previous office action
2 Cited in the previous office action
3 Cited in the previous office action
4 Cited in the previous office action
5 Please refer below to Montavon and Schulte cited below in the REASONS FOR ALLOWANCE who show that counts of pixels (i.e., pixel clusters and volume/average pixel intensities respectively) are used to determine people count.
6 Cited in the previous office action
7 Please refer Montavon and Schulte cited in the previous office action in the REASONS FOR ALLOWANCE section who show that counts of pixels (i.e., pixel clusters and volume/average pixel intensities respectively) are used to determine people count.
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