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 .
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-12 have been considered but are moot because the new ground of rejection is changed from a 102 rejection into a 103 rejection. In claims 1-5, 7-12, Abbas teaches the newly added claim limitations.
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) 1-5, 7-12 is/are rejected under 35 U.S.C. 102(a)(1) as being unpatentable by US 20220004949 A1 to Goncharov et. al. (“Goncharov”) and further in view of US 11671566 B2 to Abbas.
As to claim 1, Goncharov teaches computer implemented method for identifying an event using video surveillance data from a video camera having a field of view comprising the steps of: (1) using a trained machine learning algorithm to detect a person in the video surveillance data and determine a location of the person in the field of view (¶0022, detect a person zone of interest); (2) using a trained machine learning algorithm to classify a posture of he detected person, and, only when the posture is classified as a predetermined posture (¶0022, the human activity tracking engine 102 is configured to utilize the plurality of trained AI models to recognize, identify, and classify a certain human posture), carrying out the further steps of: (3) defining a detection zone within the field of view around the location of the detected person, wherein the detection zone is not a pre-defined area (¶0021, systematically define/mark out the zones of interest such that if an activity, a person, or an object is detected in the zones of interest by the human activity tracking engine 102, a series of actions will be triggered to ascertain if the set of protocols for the zones of interest is followed, herein the zones of interest are a pre-defined/prescribed space or area where the set of compliance protocols must be followed. For non-limiting examples, each of the one or more zones of interest can be but is not limited to a factory floor area where personal protection equipment (PPE) must be used or a designated area for health care where physical therapy has to be performed); (4) using a trained machine learning algorithm to search for an object of a predetermined type overlapping the detection zone (¶0022, the human activity tracking engine 102 can detect a forklift in an unauthorized factory work area, or a person in a dangerous no-go zone in a manufacturing equipment area. ); and (5) identifying an event based on the posture detection and the result of the object detection (¶0024, escalation event based onThe purpose is to enforce the set of protocols to ensure the well-being or the patients, the safety of the employees, or even the efficiency of the workforce. In some embodiments, the protocol compliance engine 106 is configured to accept input from an existing alarm system (e.g., Andon lights, Sound alarms etc.) to identify/classify an escalation event when a safety compliance protocol or an operation procedure is being violated. In some embodiments, the protocol compliance engine 106 is configured to utilize any existing alarm system (e.g., sound or light) to notify the person of the violation event in order to minimize the risk to the person and/or other affected/surrounding person(s), e.g., a forklift out of control in a work zone or a chemical spill due to non-compliance of maintenance protocols. In some embodiments, all communications between the protocol compliance engine 106 and the user are encrypted to ensure data security).
Abbas teaches detection, wherein, when the posture is classified as a predetermined posture and no object of the predetermined type is detected overlapping the detection zone, then it is determined that a specific event has occurred (Col. 3, line 10-40). In view of the teachings of Abbas, it would have been obvious before the effective filing date of the invention to modify the teachings of Goncharov. The suggestion/motivation would be monitoring multiple patients simultaneously and detect where the patient is.
As to claim 2, Goncharov and Abbas teaches the method according to claim 1, further comprising a step of generating metadata identifying the event, a time of the event in the video, and a location of the event within the field of view (¶0020, the human activity tracking engine 102 builds a sequence of events/activities executed by a person or object at the one or more zones of interest over a certain amount of time. Such sequence of events/activities enables the users (e.g., employers, healthcare professionals, production/safety managers etc.) of the system 100 to ensure that a set of pre-defined protocols is followed by the person, who can be but is not limited to an employee, a factory operator, a recovering patient, elderly in therapy etc., ¶0024, protocol database, ¶0019, the secured local storage 103 resides onsite behind a user's firewall. Note that none of the sensitive video/audio of the person leaves the secured local storage 103, hence guaranteeing the person being monitored at the location/zone of interest has full control of his/her data, which is particularly important in highly confidential manufacturing or work areas as well as in sensitive/private hospital or healthcare environment).
As to claim 3, Goncharov and Abbas teaches the method according to claim 1, wherein the search in step (4) is limited to an area defined by the detection zone (¶0021, monitor, track, and identify the sequence of activities of the person at the one or more zones/locations of interest, wherein the zones of interest are a pre-defined/prescribed space or area where the set of compliance protocols must be followed. For non-limiting examples, each of the one or more zones of interest).
As to claim 4, Goncharov and Abbas teaches the method according to claim 1, wherein, in step (5), when the posture is classified as a predetermined posture and no object of the predetermined type is detected overlapping the detection zone, then it is determined that a specific event has occurred (¶0026, the posture of the contractor indicates that a dangerous situation is apparent because he might not be visible to the truck driver, ¶0021, each of the one or more zones of interest can be but is not limited to a factory floor area where personal protection equipment (PPE) must be used or a designated area for health care where physical therapy has to be performed. In some embodiments, the human activity tracking engine 102 is configured to systematically define/mark out the zones of interest such that if an activity, a person, or an object is detected in the zones of interest by the human activity tracking engine 102, a series of actions will be triggered to ascertain if the set of protocols for the zones of interest is followed).
As to claim 5, Goncharov and Abbas teaches the method according to claim 4, wherein, if an object of the predetermined type is detected overlapping the detection zone by less than a predetermined amount, then it is determined that the specific event has occurred (¶0020, builds a sequence of events/activities executed by a person or object at the one or more zones of interest over a certain amount of time. Such sequence of events/activities enables the users (e.g., employers, healthcare professionals, production/safety managers etc.) of the system 100 to ensure that a set of pre-defined protocols is followed by the person, who can be but is not limited to an employee, a factory operator, a recovering patient, elderly in therapy.
As to claim 6, Goncharov and Abbas teaches the method according to claim 4, Goncharov does not teach wherein the predetermined posture is a lying posture and the object is an item of furniture for resting (Col. 3, line 10-40).
As to claim 7, Goncharov and Abbas teaches the method according to claim 1, wherein steps (2) to (4) are carried out by the same trained machine learning algorithm (¶0020, the human activity tracking engine 102 is configured to generate, train, and utilize a plurality of AI models to track and identify the sequence of activities of the person at the monitored location/zone of interest. In some embodiments, the human activity tracking engine 102 is configured to maintain the plurality of AI models in an AI model database 104. In some embodiments, the human activity tracking engine 102 is configured to train the plurality of AI models using the collected information of the person and/or other persons being monitored over a period of time).
As to claim 8, see the rejection of claim 1.
As to claim 9, Goncharov teaches the system according to claim 8, comprising the video camera, wherein the at least one processing unit includes a processing unit in the camera, wherein at least steps (1) and (2) are carried out by the processing unit in the camera (Fig. 1, cameras perform steps 1 and 2).
As to claim 10, Goncharov teaches the system according to claim 8, comprising a video management system including at least one server configured to receive video data from the camera and wherein the at least one processing unit includes a processing unit in the video management system, wherein at least steps (4) and (5) are carried out by the processing unit in the video management system (Fig. 1, cameras and send it to the human activity tracking).
As to claim 11, see the rejection of claim 1.
As to claim 12, see the rejection of claim 3.
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.
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/CHRISTINE A KURIEN/Examiner, Art Unit 2421
/NATHAN J FLYNN/Supervisory Patent Examiner, Art Unit 2421
