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 .
ELECTION
Applicant’s election of Group I is acknowledged. Such has been treated as an election without traverse.
35 USC 102 REJECTION
Claim(s) 1,2,12,14,20 are rejected under 35 U.S.C. 102a1 as being anticipated by Ravid et al ‘131 (listed 1449).
As to claims 1,12, Ravid et al ‘131 teaches a cloud-implemented method of determining a utility meter abnormality, the method comprising:
receiving, from a utility meter (Para 210,1908), at a profile sharing server 1902 comprising one or more processors, a plurality of utility meter updates (Para 31);
generating, with the one or more processors, a utility meter profile based on the one or more utility meter updates (Para 320);
receiving, at the utility meter, from the profile sharing server, the utility meter profile (496);
automatically determining the utility meter abnormality by comparing the utility meter profile to a measured flow rate of fluid through the utility meter (495); and
in response to determining the utility meter abnormality, sending an alert (485).
As to claims 2,14, Para 14 teaches employing historical data.
As to claims 12,14, the method is carried out by hardware, and the hardware employs registers (Para 66,146), and such includes clocks
As to claim 20, the method is carried out by program via processor 220.
PRIOR ART OF RECORD
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kent et al 20200132565 teaches use of a remote server to implement computationally demanding techniques when implementing leak detection. The meter sends flow rates values to the server, and the server determines leakage (Para 19). The extraction and comparison of “shape patterns of fluid flow events” and “flow duration patterns” reflect the differences between normal and abnormal fluid usage events (Para 20). The fluid flow meter generates, using fluid flow rates, a training fluid flow duration pattern indicative of a threshold value. The time threshold value is an estimate of a maximum fluid flow duration within a given fluid flow event. During a detection phase , the flow meter can determine in real time a fluid flow duration associated with a current fluid flow event. As such, the meter can detect a leak with the fluid flow duration exceeds the time threshold value (Para 22.) Such training can last a predetermined time such as a few days (Para 29). Such training can be repeated, and as such reflect changes in fluid usage habit in a dwelling or building (Para 30). A pattern can include a plurality of value ranges or intervals (of fluid flow rate) and one or more time duration threshold values associated with the respective value ranges of the flow rate (Para 31). As such, during operation the flow meter 102 reports to the computer server 108 to report duration patterns or updates, and then the flow meter 102 receives instructions from the server 108 to start training. The server 108 merely keeps track of the training process of the meter, and subsequently determines when to instruct the meter 102 to initiate new training (Para 34).1 It is the flowmeter102 that determines abnormality by comparing the meter created/determined meter profile to a measured flow, and it is the meter 102 that sends an alert signal (Para 37) The communication network 112 includes wireless and a wide area network (Para 25). The server 108 incudes a processor, and the server 108 does receive updates from the meter 102 (Para 37). However, the processor of the server 108 does not generate a meter profile based upon the updates as called in each of claim 1 (lines 5-6), claim 12 (lines 8-9) and claim 20 (lines 7-8).
Cornwall 20120326884 teaches (Para 55) determination of an abnormal consumption by comparing current consumption of resource through the utility meter with predetermined normal consumption patterns (Para 55).
Rinshaus CN 115077644 teach a Coriolis flow meter that sends raw data to a computer that is part of a central server, which computer compensate the flow meter flow measurement.
Sabamori et al CN114623903 teach (Figure 1) a flowmeter 10 and cloud accessed computer 190, which computer sends a single to the flowmeter regarding abnormality. However, such signal is not that of a profile.
CONCLUSION
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROBERT R RAEVIS whose telephone number is (571)272-2204. The examiner can normally be reached on Monday to Friday from 8AM to 4PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kristina DeHerrera, can be reached at telephone number 303-297-4237. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from Patent Center. Status information for published applications may be obtained from Patent Center. Status information for unpublished applications is available through Patent Center to authorized users only. Should you have questions about access to the USPTO patent electronic filing system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free).
Examiner interviews are available via a variety of formats. See MPEP § 713.01. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) Form at https://www.uspto.gov/InterviewPractice.
/ROBERT R RAEVIS/ Primary Examiner, Art Unit 2855
1 Contrary to Applicant’s claims 1,12 and 20, Kent’s server does not generate a meter profile based upon the updates.