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 .
Compact Prosecution
Examiner would like to initiate an Examiner interview to discuss to case.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 14 and 15 are rejected under 35 USC 101 because Claims 14 and 15 claims “Computer program (905) … and A Computer readable storage medium comprising instruction …..” However, the claims do not define the Computer program code … to be a functional descriptive material encoded on a non-transitory memory/disk/computer-readable medium, and is thus non-statutory for that reason (i.e., “When functional descriptive material is recorded on some non-transitory computer-readable medium it becomes structurally and functionally interrelated to the medium and will be statutory in most cases since use of technology permits the function of the descriptive material to be realized”). Moreover, a “Computer program and a computer readable storage medium … which run in a transmitting node” is neither a process (“action”), nor machine, nor manufacture, nor composition of matter (i.e., non-transitory”) and therefore non-statutory.
Such claimed “a Computer program … and A computer -readable storage medium… code which run in a transmitting node …” (software) does not define any structural and functional interrelationships between the computer program and other claimed elements of a computer, which permit the computer program’ s functionality to be realized.
One ordinary skilled in the art will conclude that a Computer program and a computer-readable storage medium for identifying deviations from planned activities.
Examiner suggests amending the claim to include “a non-transitory computer readable medium that identifies deviations from planned activities…”.
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.
Claims 1-15 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar (US11531943) in view of Wang (US20220044680).
Claim 1, Kumar discloses a method for identifying deviations from planned activities at an industrial site, (Col. 9 lines 2-3 “Construction phase”) the method comprises:
obtaining a reference data of the industrial site; (Col. 8 lines 40-42 “expected construction” project requirement reads on the reference data)
predefining a time period for recording conversations occurring at the industrial site; (Fig. 4B shows time period of activities where the activities may be conversations)
recording one or more conversations occurring during the predefined time period by one or more audio recording devices; (Col. 9 lines 5-7 the data feeds during construction phase can be recording one or more conversations during constructions)
during the recording, performing an analysis of the recorded one or more conversations against the reference data; (Col. 19 lines 65-67, the voice assistant ML reads on recording and analyzing conversations which are recorded).
(NB: Col. 12 lines 48-50 thus a Natural Language Processing (NLP) algorithms to monitor construction progression in order to ensure compliance)
identifying deviations (Col. 9 lines 1-3 progression deviate significantly) from planned activities at the industrial site based on the analyzed one or more conversations and the reference data. (Col. 11, lines 65-67 “monitors work progression” means that the system will know if there is no progress and therefore there is variations, also Col. 12 lines 6-9 actual status of a task will show deviations within the project).
Kumar does not discloses implementing a privacy function upon detecting a privacy trigger.
Wang discloses a privacy function in Section 0022 “identifiers associated with privacy mode flags to interact with the speech processing system”.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the voice annotation taught by Kumar to include the teaching of privacy function. The motivation/benefit is that it enables the Voice or speech processing system to operate without invading the privacy of user.
Claim 2, Kumar in view of Wang discloses wherein obtaining the reference data comprises at least one of using a predefined template to generate the reference data;
obtaining the reference data through integration with one or more existing systems;
obtaining the reference data by leveraging machine learning algorithms; using natural language processing techniques to analyze and extract relevant information from existing documents; or
utilizing computer vision techniques to capture and process visual data related to the industrial site. (Kumar: Col. 20 lines 30-36 monitor 118 accessing the plurality data feeds from one or more sources reads on image capturing).
Claim 3, Kumar in view of Wang discloses wherein predefining the time period for recording conversations occurring at the industrial site comprises at least one of:
- using a schedule of planned activities; (Kumar: Col. 21 lines 4-11 schedule variance which is generated based on the weighted tasks).
- using machine learning algorithms to predict and adjust the time period based on historical data;
- setting different time periods for different areas of the industrial site; or
- by integrating with existing scheduling or project management tools.
Claim 4, Kumar in view of Wang discloses The method according to any of the preceding claims, wherein implementing the privacy function comprises at least one of:
- using a manual on/off function in the audio recording device;
- using an automatic on/off function;
- providing a standalone device at private zones configured to switch off all audio recording devices in range;
- automatically switching another audio recording device into privacy mode if nearby a first audio recording device is already in privacy mode; (Wang: Section 0124: Privacy mode flag is sent to various components)
- using a user-controllable privacy timer functionality on the audio recording device to temporarily deactivate recording; (Kumar: Fig. 4B shows the timers on the activity table) or
- limiting the number of privacy sessions per predefined period and/or restricting privacy sessions to specific times according to a schedule.
Claim 5, Kumar in view of Wang discloses wherein detecting the privacy trigger comprises at least one of using audio signal processing techniques to identify key-words indicating a requirement of privacy; analyzing environmental factors; (Kumar: Col. 12 lines 48-50 thus a Natural Language Processing (NLP) algorithms to monitor construction progression in order to ensure compliance)
identifying another audio recording device in privacy mode nearby;
integrating with other devices to gather additional data for detecting privacy triggers;
determining if the standalone device at the private zone is present and active; (Wang: Section 0142 lines 3-14 thus the recipient device along with a privacy mode flag)
detecting the scheduled time for restricted privacy sessions; or receiving user input to initiate the detection of the privacy trigger. (Kumar: in fig. 4B teaches using a schedule time to record the activities of the construction)
Claim 6, Kumar in view of Wang discloses wherein preforming the analysis of the recorded one or more conversations against the reference data comprises one or more artificial intelligence techniques selected from a group comprising topic modeling, sentiment analysis, keyword extraction, trend analysis, anomaly detection, automated summarizations, or action item identification. (Kumar: Col. 5 lines 18-25 artificial intelligence)
Claim 7, Kumar in view of Wang discloses wherein the method further comprises identifying which recording belongs to which worker. (Kumar: Col. 21 lines 11, Fig. 4B shows the recordings in a table form).
Claim 8, Kumar in view of Wang discloses wherein the method further comprises transferring the recorded conversations from the audio recording device directly a server; to a central hub located at the industrial site and then from the central hub to the server; or downloading the recorded conversations to a temporary storage device and then uploading recorded conversations from the temporary storage device to a server. (Wang: Section 0134, lines 1-6 privacy mode flag are received the by the servers 125 see Section 0137)
Claim 9, Kumar in view of Wang discloses wherein the method further comprises timestamping the recorded conversations with a first time stamp indicating the start of each sub-session of the conversation and a second time stamp indicating the end of each sub-session of the conversations. (Kumar: Col. 21 lines 11-23, Fig. 4B shows different construction activities where the activities can be the recording of conversations)
Claim 10, Kumar in view of Wang discloses wherein the method further comprises creating a data layer per the predefined time period comprising a data component and a time com-ponent. (Kumar: Based on fig. 4B shows the predefined time period)
Claim 11, Kumar discloses an audio recording device for use in a method for identifying deviations from planned activities at an industrial site, (Col. 9 lines 2-3 “Construction phase”) the method comprises:
obtaining a reference data of the industrial site; (Col. 8 lines 40-42 “expected construction” project requirement reads on the reference data)
predefining a time period for recording conversations occurring at the industrial site; (Fig. 4B shows time period of activities where the activities may be conversations)
recording one or more conversations occurring during the predefined time period by one or more audio recording devices; (Col. 9 lines 5-7 the data feeds during construction phase can be recording one or more conversations during constructions)
during the recording, performing an analysis of the recorded one or more conversations against the reference data; (Col. 19 lines 65-67, the voice assistant ML reads on recording and analyzing conversations which are recorded).
(NB: Col. 12 lines 48-50 thus a Natural Language Processing (NLP) algorithms to monitor construction progression in order to ensure compliance)
identifying deviations (Col. 9 lines 1-3 progression deviate significantly) from planned activities at the industrial site based on the analyzed one or more conversations and the reference data. (Col. 11, lines 65-67 “monitors work progression” means that the system will know if there is no progress and therefore there is variations, also Col. 12 lines 6-9 actual status of a task will show deviations within the project).
Kumar does not discloses implementing a privacy function upon detecting a privacy trigger and wherein the audio recording device comprises
a microphone array;
a processor and memory module configured to control an operation of the audio recording device, and one or more software modules,
buffer audio, and manage wireless communication; a wireless connectivity module;
a privacy timer activation means; and a battery.
.
Wang discloses a privacy function (Section 0022) and a microphone array (Section 0147 lines 7-8 array of microphones) ;
a processor and memory module configured to control an operation of the audio recording device, and one or more software modules, (Section 0145 using the memory (1106/1206) as temporary working storage at runtime)
buffer audio, and manage wireless communication; a wireless connectivity module; (Section 0147 wireless headset)
a privacy timer activation means; and a battery. (Section 0022 “identifiers associated with privacy mode flags to interact with the speech processing system”)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the voice annotation taught by Kumar to include the teaching of privacy function. The motivation/benefit is that it enables the Voice or speech processing system to operate without invading the privacy of user.
Claim 12, Kumar in view of Wang discloses a data processing system for identifying deviations from planned activities at an industrial site, (Kumar: Col. 11, lines 65-67 “monitors work progression” means that the system will know if there is no progress and therefore there is variations, also Col. 12 lines 6-9 actual status of a task will show deviations within the project).
the system comprises one or more servers comprising an audio data processing unit, (Col. 12 lines 48-50 thus a Natural Language Processing (NLP) algorithms to monitor construction progression in order to ensure compliance)
wherein the one or more servers are integrable with a management software platform; (Wang Servers shown in Fig. 6A)
one or more audio recording devices wirelessly connected to the audio data processing unit; (Wang: Section 0147 wireless headset)
one or more user devices configured to run a user interface. (Wang: Fig. 6A show a speech Detection device 110 which is a user interface)
Claim 13, Kumar in view of Wang discloses a user interface data processing system for identifying deviations from planned activities at an industrial site, (Kumar: Col. 11, lines 65-67 “monitors work progression” means that the system will know if there is no progress and therefore there is variations, also Col. 12 lines 6-9 actual status of a task will show deviations within the project).
the user interface comprising one or more of the following a graphical dashboard configured to receive and display analytics of the conversations and noisy environment; (Kumar: Fig. 4B shows a table that shows the analytics of the constructions events take place).
user input mechanisms configured to receive inputs from the user for managing functionalities of the data processing system; . (Wang: Fig. 6A show a speech Detection device 110 which is a user interface for inputting speech)
indicators configured to display a status of performance indicators of the audio recording device and customizable privacy settings. (Wang: Section 0022 “identifiers associated with privacy mode flags to interact with the speech processing system”)
Claim 14, Kumar discloses a computer program for identifying deviations from planned activities at an industrial site, the computer program comprising instructions which, when the program is executed by a data processing system, (Kumar: Col. 11, lines 65-67 “monitors work progression” means that the system will know if there is no progress and therefore there is variations, also Col. 12 lines 6-9 actual status of a task will show deviations within the project)
cause the data processing system to carry out the method of discloses an audio recording device for use in a method for identifying deviations from planned activities at an industrial site, (Col. 9 lines 2-3 “Construction phase”) the method comprises:
obtaining a reference data of the industrial site; (Col. 8 lines 40-42 “expected construction” project requirement reads on the reference data)
predefining a time period for recording conversations occurring at the industrial site; (Fig. 4B shows time period of activities where the activities may be conversations)
recording one or more conversations occurring during the predefined time period by one or more audio recording devices; (Col. 9 lines 5-7 the data feeds during construction phase can be recording one or more conversations during constructions)
during the recording, performing an analysis of the recorded one or more conversations against the reference data; (Col. 19 lines 65-67, the voice assistant ML reads on recording and analyzing conversations which are recorded).
(NB: Col. 12 lines 48-50 thus a Natural Language Processing (NLP) algorithms to monitor construction progression in order to ensure compliance)
identifying deviations (Col. 9 lines 1-3 progression deviate significantly) from planned activities at the industrial site based on the analyzed one or more conversations and the reference data. (Col. 11, lines 65-67 “monitors work progression” means that the system will know if there is no progress and therefore there is variations, also Col. 12 lines 6-9 actual status of a task will show deviations within the project).
Kumar does not discloses implementing a privacy function upon detecting a privacy trigger and wherein the audio recording device comprises
a microphone array;
a processor and memory module configured to control an operation of the audio recording device, and one or more software modules,
buffer audio, and manage wireless communication; a wireless connectivity module;
a privacy timer activation means; and a battery.
.
Wang discloses a privacy function (Section 0022) and a microphone array (Section 0147 lines 7-8 array of microphones) ;
a processor and memory module configured to control an operation of the audio recording device, and one or more software modules, (Section 0145 using the memory (1106/1206) as temporary working storage at runtime)
buffer audio, and manage wireless communication; a wireless connectivity module; (Section 0147 wireless headset)
a privacy timer activation means; and a battery. (Section 0022 “identifiers associated with privacy mode flags to interact with the speech processing system”)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the voice annotation taught by Kumar to include the teaching of privacy function. The motivation/benefit is that it enables the Voice or speech processing system to operate without invading the privacy of user.
Claim 15, Kumar discloses a computer-readable storage medium comprising instructions for identifying deviations from planned activities at an industrial site, which. when executed by data processing system, cause the data processing system to carry out the method of (Kumar: Col. 11, lines 65-67 “monitors work progression” means that the system will know if there is no progress and therefore there is variations, also Col. 12 lines 6-9 actual status of a task will show deviations within the project)
cause the data processing system to carry out the method of discloses an audio recording device for use in a method for identifying deviations from planned activities at an industrial site, (Col. 9 lines 2-3 “Construction phase”) the method comprises:
obtaining a reference data of the industrial site; (Col. 8 lines 40-42 “expected construction” project requirement reads on the reference data)
predefining a time period for recording conversations occurring at the industrial site; (Fig. 4B shows time period of activities where the activities may be conversations)
recording one or more conversations occurring during the predefined time period by one or more audio recording devices; (Col. 9 lines 5-7 the data feeds during construction phase can be recording one or more conversations during constructions)
during the recording, performing an analysis of the recorded one or more conversations against the reference data; (Col. 19 lines 65-67, the voice assistant ML reads on recording and analyzing conversations which are recorded).
(NB: Col. 12 lines 48-50 thus a Natural Language Processing (NLP) algorithms to monitor construction progression in order to ensure compliance)
identifying deviations (Col. 9 lines 1-3 progression deviate significantly) from planned activities at the industrial site based on the analyzed one or more conversations and the reference data. (Col. 11, lines 65-67 “monitors work progression” means that the system will know if there is no progress and therefore there is variations, also Col. 12 lines 6-9 actual status of a task will show deviations within the project).
Kumar does not discloses implementing a privacy function upon detecting a privacy trigger and wherein the audio recording device comprises
a microphone array;
a processor and memory module configured to control an operation of the audio recording device, and one or more software modules,
buffer audio, and manage wireless communication; a wireless connectivity module;
a privacy timer activation means; and a battery.
.
Wang discloses a privacy function (Section 0022) and a microphone array (Section 0147 lines 7-8 array of microphones) ;
a processor and memory module configured to control an operation of the audio recording device, and one or more software modules, (Section 0145 using the memory (1106/1206) as temporary working storage at runtime)
buffer audio, and manage wireless communication; a wireless connectivity module; (Section 0147 wireless headset)
a privacy timer activation means; and a battery. (Section 0022 “identifiers associated with privacy mode flags to interact with the speech processing system”
Therefore it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the voice annotation taught by Kumar to include the teaching of privacy function. The motivation/benefit is that it enables the Voice or speech processing system to operate without invading the privacy of user.
Cited Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Correll et al. discloses A project management system comprising a first , second, third, fourth and fifth processing sequences embodied in a computer readable medium . The first processing sequence is operable to provide a user interface to display a plurality of alert indicia corresponding to a plurality of alert status of a plurality of project requirements . The second processing sequence is operable to convert an incomplete requirement to a complete requirement upon completion of a task corresponding to the incomplete requirement .
Conclusion
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/AKWASI M SARPONG/SPE, Art Unit 2681 12/14/2025