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 § 102
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.
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-5 and 7-12 are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Elinsenberg et al. (US20170231071), hereinafter referred to as ‘Elinsenberg’.
Regarding Claim 1, Elinsenberg discloses a system for determining a mounting pattern in which a plurality of LED luminaires comprising second-hand LED luminaires that have been retrieved from one or more previous lighting environments will be installed, the system comprising: a memory unit and a processor, the processor being configured to (In accordance with yet other embodiments of the present system, there is disclosed a computer program stored on a computer readable memory medium [0010];The controller 102 may control the overall operation of the system 100 and may communicate with one of more of the light-points 106-x, the sensors 108, the memory 112, the consolidators 114, etc., via the network 110. [0023]): obtain data comprising at least a used lifetime of each LED luminaire of a plurality of LED luminaires and store the obtained data in the memory unit (FIG. 3B shows a graph illustrating an output of test results for determining variable importance for a LED lamp in accordance with embodiments of the present system [0017];The lighting system 100 may include a lighting logging data (LLD) portion 120 and a consolidator 114. The LLD portion 120 may include a plurality of information sources such as a lamp electrical information portion 120-1 which may provide lamp electrical information, a system operating information portion 120-2 which may provide system operating information, sensors 120-3 which may provide sensor information…The configuration information may include information related to one or more of lamp location (e.g., determined using any suitable method such as by using a global positioning system (GPS)), lamp type (e.g., SON, LED, fluorescent, incandescent, etc.), brand name (e.g. Xitanium™ 80led350 mA 96 W Speedstar™ BGP322GRN84), lamp wattage, lamp installation date, and average lifetime of one or more lamps 106-x of the system 100. [0029]), determine, from the obtained data, at least one of the used lifetime and a remaining expected lifetime of each LED luminaire of the plurality of LED luminaires (Then, given the full input data set X and the lamp pole parameters L, the process may determine the informative data features. The informative data features determined by the process can be more informative than standard data such as actual hours (e.g., 800 hrs.) and lifetime hours (e.g., 950 hrs.) when used to predict future lighting system performance [0064]), determine a mounting pattern of the plurality of LED luminaires, the mounting pattern (6) comprising (For example, the process may determine locations of all lamps of a certain cluster which are to be replaced by a certain date. Thereafter, the process may determine a route that is to be used to replace these lamps of the cluster that need to be replaced. This route may be a least-cost route (e.g., to minimize a desired variable such as time and/or distance traveled) and may set forth a route to be used for lamp replacement [0132]); one or more groups of LED luminaires, the one or more groups of LED luminaires being determined based on the determined one of the used lifetime and the remaining expected lifetime of each LED luminaire of the plurality of LED luminaires (Then, given the full input data set X and the lamp pole parameters L, the process may determine the informative data features. The informative data features determined by the process can be more informative than standard data such as actual hours (e.g., 800 hrs.) and lifetime hours (e.g., 950 hrs.) when used to predict future lighting system performance [0064]), and at least one location in which to install the one or more groups of LED luminaires (During act 231, the process may form a maintenance schedule in accordance with the failure prediction model formed during act 229. For example, the process may determine locations of all lamps of a certain cluster which are to be replaced by a certain date. Thereafter, the process may determine a route that is to be used to replace these lamps of the cluster that need to be replaced [0132]), the at least one location being based on the determined one of the used lifetime and the remaining expected lifetime of each LED luminaire of the respective group of the one or more groups of LED luminaires, such that LED luminaires with similar used lifetime and/or remaining expected lifetime are identified and installed in the same location (During act 231, the process may form a maintenance schedule in accordance with the failure prediction model formed during act 229. For example, the process may determine locations of all lamps of a certain cluster which are to be replaced by a certain date. Thereafter, the process may determine a route that is to be used to replace these lamps of the cluster that need to be replaced [0132]; Then, given the full input data set X and the lamp pole parameters L, the process may determine the informative data features. The informative data features determined by the process can be more informative than standard data such as actual hours (e.g., 800 hrs.) and lifetime hours (e.g., 950 hrs.) when used to predict future lighting system performance [0064]), and outputting the determined mounting pattern (The GUI 400 may include a map 402 which may include a depiction of one or more portions of the lighting system such as all installed lamps 404 of the system that lie along a street 406 which is within a displayed portion of the map 402. The process may obtain information related to predicted (cumulative) lamp failures on the selected date and may render this information using any suitable method such as using open circles 409 which indicate lamps which are predicted to have failed on the selected date [0136]).
Regarding Claim 2, Elinsenberg discloses the claimed invention discussed in claim 1.
Elinsenberg discloses the processor is configured to further base the determination of the at least one location in which to install each of the one or more groups of LED luminaires on one or more of an expected renovation or refreshment time for the location, and ease or difficulty of installing or changing a LED luminaire in the location (The lighting system 100 may include a lighting logging data (LLD) portion 120 and a consolidator 114. The LLD portion 120 may include a plurality of information sources such as a lamp electrical information portion 120-1 which may provide lamp electrical information, a system operating information portion 120-2 which may provide system operating information, sensors 120-3 which may provide sensor information…The configuration information may include information related to one or more of lamp location (e.g., determined using any suitable method such as by using a global positioning system (GPS)), lamp type (e.g., SON, LED, fluorescent, incandescent, etc.), brand name (e.g. Xitanium™ 80led350 mA 96 W Speedstar™ BGP322GRN84), lamp wattage, lamp installation date, and average lifetime of one or more lamps 106-x of the system 100. [0029]).
Regarding Claim 3, Elinsenberg discloses the claimed invention discussed in claim 1.
Elinsenberg discloses the obtained data further comprises any one or more of: a remaining expected lifetime of each LED luminaire of the plurality of LED luminaires (The lighting system 100 may include a lighting logging data (LLD) portion 120 and a consolidator 114. The LLD portion 120 may include a plurality of information sources such as a lamp electrical information portion 120-1 which may provide lamp electrical information, a system operating information portion 120-2 which may provide system operating information, sensors 120-3 which may provide sensor information…The configuration information may include information related to one or more of lamp location (e.g., determined using any suitable method such as by using a global positioning system (GPS)), lamp type (e.g., SON, LED, fluorescent, incandescent, etc.), brand name (e.g. Xitanium™ 80led350 mA 96 W Speedstar™ BGP322GRN84), lamp wattage, lamp installation date, and average lifetime of one or more lamps 106-x of the system 100. [0029]), and information retrieved from a code provided on each LED luminaire of the plurality of LED luminaires, the code indicating at least one of a used lifetime and a remaining expected lifetime (Upon receiving the fi, the fi may be processed as follows. For example, assuming an observation o be formed by the process and which may represent one particular realization value of a particular feature for a particular lamp at some time t and which may be denoted by: where custom-character indicates the observation value of a lamp l (of a lightpoint) at time t from feature f, id is a unique identifier of the lamp and l may mathematically define a lamp pole of nL lamp poles of the lighting system as described with reference to Eq. (14) below, and L is the set of all of nL lamp poles as defined in Eq. (15) below and R represents a set of all real numbers [0042]).
Regarding Claim 4, Elinsenberg discloses the claimed invention discussed in claim 1.
Elinsenberg the system further comprises a reading device , and wherein the system is configured to read, by the reading device (The lighting system 100 may include a controller 102, lightpoints 106-1-106-N (generally 106-x), sensors 108, a network 110, a memory 112, information consolidators 114-1 through 114-P (generally 114-x), etc [0022];Upon receiving the fi, the fi may be processed as follows. For example, assuming an observation o be formed by the process and which may represent one particular realization value of a particular feature for a particular lamp at some time t and which may be denoted by: where custom-character indicates the observation value of a lamp l (of a lightpoint) at time t from feature f, id is a unique identifier of the lamp and l may mathematically define a lamp pole of nL lamp poles of the lighting system as described with reference to Eq. (14) below, and L is the set of all of nL lamp poles as defined in Eq. (15) below and R represents a set of all real numbers [0042]), a code provided on each LED luminaire of the plurality of LED luminaires, the code indicating at least one of a used lifetime and a remaining expected lifetime (Upon receiving the fi, the fi may be processed as follows. For example, assuming an observation o be formed by the process and which may represent one particular realization value of a particular feature for a particular lamp at some time t and which may be denoted by: where custom-character indicates the observation value of a lamp l (of a lightpoint) at time t from feature f, id is a unique identifier of the lamp and l may mathematically define a lamp pole of nL lamp poles of the lighting system as described with reference to Eq. (14) below, and L is the set of all of nL lamp poles as defined in Eq. (15) below and R represents a set of all real numbers [0042]).
Regarding Claim 5, Elinsenberg discloses the claimed invention discussed in claim 1.
Elinsenberg discloses the processor further is configured to obtain the data by for each LED luminaire of the plurality of LED luminaires providing at least one of a modeled used lifetime and a modeled remaining expected lifetime (During act 507, the process may model predicted component failures which are predicted to occur at a future time in accordance with the lighting prediction data and maintenance cost. This act may be performed using any suitable method such as the method described with respect to act 225 above. Accordingly, the process may predict component failures such as lamp failures in the lighting system in the future time period (e.g., from a current time to some future time such as Jan. 1, 2040) in light of a costs such as maintenance costs and form a corresponding model of predicted component failures which may optionally be stored in a memory of the system for later use [0144]), wherein the at least one of a modeled used lifetime and a modeled remaining expected lifetime are provided based on a usage pattern of the LED luminaire and on environmental parameters (During act 507, the process may model predicted component failures which are predicted to occur at a future time in accordance with the lighting prediction data and maintenance cost. This act may be performed using any suitable method such as the method described with respect to act 225 above. Accordingly, the process may predict component failures such as lamp failures in the lighting system in the future time period (e.g., from a current time to some future time such as Jan. 1, 2040) in light of a costs such as maintenance costs and form a corresponding model of predicted component failures which may optionally be stored in a memory of the system for later use [0144]; The sensor information may include information related to one or more of light level, ambient temperature, lamp internal temperature, humidity, and presence, and sensed traffic of the system 100. The configuration information may include information related to one or more of lamp location (e.g., determined using any suitable method such as by using a global positioning system (GPS)), lamp type (e.g., SON, LED, fluorescent, incandescent, etc.), brand name (e.g. Xitanium™ 80led350 mA 96 W Speedstar™ BGP322GRN84), lamp wattage, lamp installation date, and average lifetime of one or more lamps 106-x of the system 100 [0029]).
Regarding Claim 7, Elinsenberg discloses the claimed invention discussed in claim 1.
Elinsenberg discloses the processor further is configured to output the determined mounting pattern by any one or more of (For example, the process may determine locations of all lamps of a certain cluster which are to be replaced by a certain date. Thereafter, the process may determine a route that is to be used to replace these lamps of the cluster that need to be replaced. This route may be a least-cost route (e.g., to minimize a desired variable such as time and/or distance traveled) and may set forth a route to be used for lamp replacement [0132]): presenting the determined mounting pattern on a display of the system (During act 235, the process may render a visualization of the system on a user interface such as a display of the system for the convenience of a user [0134]), storing the determined mounting pattern in the memory unit, storing the determined mounting pattern in a memory unit being external to the system (The process 500 may be performed using one or more computers communicating over a network and may obtain information from, and/or store information to one or more memories which may be local and/or remote from each other [0141]), and providing installation instructions based on the determined mounting pattern (For example, in the present embodiment it will be assumed that the selected date is a user has selected date in the future such as Feb. 2, 2020. The GUI 400 may include a map 402 which may include a depiction of one or more portions of the lighting system such as all installed lamps 404 of the system that lie along a street 406 which is within a displayed portion of the map 402 [0136]).
Regarding Claim 8, Elinsenberg discloses a computer implemented method for determining a mounting pattern in which a plurality of LED luminaires comprising second-hand LED luminaires that have been retrieved from one or more previous lighting environments will be installed, the method comprising: by a computer processor (The controller 102 may control the overall operation of the system 100 and may communicate with one of more of the light-points 106-x, the sensors 108, the memory 112, the consolidators 114, etc., via the network 110. [0023]): obtaining data comprising at least a used lifetime of each LED luminaire of a plurality of LED luminaires and store the obtained data in a memory unit (The lighting system 100 may include a lighting logging data (LLD) portion 120 and a consolidator 114. The LLD portion 120 may include a plurality of information sources such as a lamp electrical information portion 120-1 which may provide lamp electrical information, a system operating information portion 120-2 which may provide system operating information, sensors 120-3 which may provide sensor information…The configuration information may include information related to one or more of lamp location (e.g., determined using any suitable method such as by using a global positioning system (GPS)), lamp type (e.g., SON, LED, fluorescent, incandescent, etc.), brand name (e.g. Xitanium™ 80led350 mA 96 W Speedstar™ BGP322GRN84), lamp wattage, lamp installation date, and average lifetime of one or more lamps 106-x of the system 100. [0029]), determining, from the obtained data, at least one of the used lifetime and a remaining expected lifetime of each LED luminaire of the plurality of LED luminaires (Then, given the full input data set X and the lamp pole parameters L, the process may determine the informative data features. The informative data features determined by the process can be more informative than standard data such as actual hours (e.g., 800 hrs.) and lifetime hours (e.g., 950 hrs.) when used to predict future lighting system performance [0064]), determining (103) a mounting pattern (6) of the plurality of LED luminaires, the mounting pattern comprising: (For example, the process may determine locations of all lamps of a certain cluster which are to be replaced by a certain date. Thereafter, the process may determine a route that is to be used to replace these lamps of the cluster that need to be replaced. This route may be a least-cost route (e.g., to minimize a desired variable such as time and/or distance traveled) and may set forth a route to be used for lamp replacement [0132]); one or more groups of LED luminaires, the one or more groups of LED luminaires based on the determined one of the used lifetime and the remaining expected lifetime of each LED luminaire of the plurality of LED luminaires (Then, given the full input data set X and the lamp pole parameters L, the process may determine the informative data features. The informative data features determined by the process can be more informative than standard data such as actual hours (e.g., 800 hrs.) and lifetime hours (e.g., 950 hrs.) when used to predict future lighting system performance [0064]), and at least one location in which to install the one or more groups of LED luminaires (During act 231, the process may form a maintenance schedule in accordance with the failure prediction model formed during act 229. For example, the process may determine locations of all lamps of a certain cluster which are to be replaced by a certain date. Thereafter, the process may determine a route that is to be used to replace these lamps of the cluster that need to be replaced [0132]), the at least one location being based on the determined one of the used lifetime and the remaining expected lifetime of each LED luminaire of the respective group of the one or more groups of LED luminaires, such that LED luminaires with similar used lifetime and/or remaining expected lifetime are identified and installed in the same location (During act 231, the process may form a maintenance schedule in accordance with the failure prediction model formed during act 229. For example, the process may determine locations of all lamps of a certain cluster which are to be replaced by a certain date. Thereafter, the process may determine a route that is to be used to replace these lamps of the cluster that need to be replaced [0132]; Then, given the full input data set X and the lamp pole parameters L, the process may determine the informative data features. The informative data features determined by the process can be more informative than standard data such as actual hours (e.g., 800 hrs.) and lifetime hours (e.g., 950 hrs.) when used to predict future lighting system performance [0064]), and outputting the determined mounting pattern (The GUI 400 may include a map 402 which may include a depiction of one or more portions of the lighting system such as all installed lamps 404 of the system that lie along a street 406 which is within a displayed portion of the map 402. The process may obtain information related to predicted (cumulative) lamp failures on the selected date and may render this information using any suitable method such as using open circles 409 which indicate lamps which are predicted to have failed on the selected date [0136]).
Regarding Claim 9, Elinsenberg discloses the claimed invention discussed in claim 8.
Elinsenberg discloses determining the at least one location in which to install each of the one or more groups of LED luminaires is furthermore based on one or more of an expected renovation or refreshment time for the location, and ease or difficulty of installing or changing the luminaire in the location (The lighting system 100 may include a lighting logging data (LLD) portion 120 and a consolidator 114. The LLD portion 120 may include a plurality of information sources such as a lamp electrical information portion 120-1 which may provide lamp electrical information, a system operating information portion 120-2 which may provide system operating information, sensors 120-3 which may provide sensor information…The configuration information may include information related to one or more of lamp location (e.g., determined using any suitable method such as by using a global positioning system (GPS)), lamp type (e.g., SON, LED, fluorescent, incandescent, etc.), brand name (e.g. Xitanium™ 80led350 mA 96 W Speedstar™ BGP322GRN84), lamp wattage, lamp installation date, and average lifetime of one or more lamps 106-x of the system 100. [0029]).
Regarding Claim 10, Elinsenberg discloses the claimed invention discussed in claim 8.
Elinsenberg discloses obtaining data further comprises any one or more of: a remaining expected lifetime of each LED luminaire of the plurality of LED luminaires (The lighting system 100 may include a lighting logging data (LLD) portion 120 and a consolidator 114. The LLD portion 120 may include a plurality of information sources such as a lamp electrical information portion 120-1 which may provide lamp electrical information, a system operating information portion 120-2 which may provide system operating information, sensors 120-3 which may provide sensor information…The configuration information may include information related to one or more of lamp location (e.g., determined using any suitable method such as by using a global positioning system (GPS)), lamp type (e.g., SON, LED, fluorescent, incandescent, etc.), brand name (e.g. Xitanium™ 80led350 mA 96 W Speedstar™ BGP322GRN84), lamp wattage, lamp installation date, and average lifetime of one or more lamps 106-x of the system 100. [0029]), and retrieving from a code provided on each LED luminaire of the plurality of LED luminaires, the code indicating at least one of a used lifetime and a remaining expected lifetime (Upon receiving the fi, the fi may be processed as follows. For example, assuming an observation o be formed by the process and which may represent one particular realization value of a particular feature for a particular lamp at some time t and which may be denoted by: where custom-character indicates the observation value of a lamp l (of a lightpoint) at time t from feature f, id is a unique identifier of the lamp and l may mathematically define a lamp pole of nL lamp poles of the lighting system as described with reference to Eq. (14) below, and L is the set of all of nL lamp poles as defined in Eq. (15) below and R represents a set of all real numbers [0042]).
Regarding Claim 11, Elinsenberg discloses the claimed invention discussed in claim 10.
Elinsenberg discloses determining, from the obtained data, the at least one of the used lifetime and the remaining expected lifetime of each LED luminaire of the plurality of LED luminaires comprises, by the computer processor, reading the codes of the LED luminaires of the plurality of LED luminaires (The lighting system 100 may include a lighting logging data (LLD) portion 120 and a consolidator 114. The LLD portion 120 may include a plurality of information sources such as a lamp electrical information portion 120-1 which may provide lamp electrical information, a system operating information portion 120-2 which may provide system operating information, sensors 120-3 which may provide sensor information…The configuration information may include information related to one or more of lamp location (e.g., determined using any suitable method such as by using a global positioning system (GPS)), lamp type (e.g., SON, LED, fluorescent, incandescent, etc.), brand name (e.g. Xitanium™ 80led350 mA 96 W Speedstar™ BGP322GRN84), lamp wattage, lamp installation date, and average lifetime of one or more lamps 106-x of the system 100. [0029]),
Regarding Claim 12, Elinsenberg discloses the claimed invention discussed in claim 8.
Elinsenberg discloses obtaining data comprises, for each LED luminaire of the plurality of LED luminaires, providing at least one of a modeled used lifetime and a modeled remaining expected lifetime (During act 507, the process may model predicted component failures which are predicted to occur at a future time in accordance with the lighting prediction data and maintenance cost. This act may be performed using any suitable method such as the method described with respect to act 225 above. Accordingly, the process may predict component failures such as lamp failures in the lighting system in the future time period (e.g., from a current time to some future time such as Jan. 1, 2040) in light of a costs such as maintenance costs and form a corresponding model of predicted component failures which may optionally be stored in a memory of the system for later use [0144]), wherein the at least one of a modeled used lifetime and a modeled remaining expected lifetime are provided based on a usage pattern of the LED luminaire and on environmental parameters (During act 507, the process may model predicted component failures which are predicted to occur at a future time in accordance with the lighting prediction data and maintenance cost. This act may be performed using any suitable method such as the method described with respect to act 225 above. Accordingly, the process may predict component failures such as lamp failures in the lighting system in the future time period (e.g., from a current time to some future time such as Jan. 1, 2040) in light of a costs such as maintenance costs and form a corresponding model of predicted component failures which may optionally be stored in a memory of the system for later use [0144]; The sensor information may include information related to one or more of light level, ambient temperature, lamp internal temperature, humidity, and presence, and sensed traffic of the system 100. The configuration information may include information related to one or more of lamp location (e.g., determined using any suitable method such as by using a global positioning system (GPS)), lamp type (e.g., SON, LED, fluorescent, incandescent, etc.), brand name (e.g. Xitanium™ 80led350 mA 96 W Speedstar™ BGP322GRN84), lamp wattage, lamp installation date, and average lifetime of one or more lamps 106-x of the system 100 [0029]).
Allowable Subject Matter
Claims 6 and 13 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claims 6 and 13 are allowable.
Claims 6 and 13 are allowable because the closest prior art Elinsenberg, either singularly or in combination, fail to anticipate or render obvious performing a periodic assessment of each LED luminaire of the plurality of LED luminaires, and based on the assessment provide a recommendation as to at least one of which groups require new LED luminaires and in which locations second-hand LED luminaires could be still used based on the prevailing conditions, and identify, based on the determined at least one of the used lifetime and the remaining expected lifetime of each LED luminaire of the plurality of LED luminaires, the second-hand LED luminaires amongst the plurality of LED luminaires and determine the mounting pattern of the plurality of LED luminaires or each of the one or more groups of LED luminaires based on the determined one of the used lifetime and the remaining expected lifetime of each LED luminaire of the plurality of LED luminaires as well as the identified second- hand LED luminaires, in combination with all other limitations in the claim as claimed and defined by applicant.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Anil Agrawal (US20170013698) discloses the method also includes presenting a representation of the streetlight in a graphical user-interface in accordance with the received location and status information, and receiving information representing a selection of the streetlight for inclusion in a group of streetlights from the network.
J. Barilleaux (US20110307112) discloses the controller has a goal module (202) receiving a set of management goals for operation of a lighting system. A demand model converts the management goals into a power level (220) for multiple light fixtures.
G Harbers (US20110254554) discloses the method involves determining an incremental acceleration factor for a period of time of operation of an LED based illumination module (100) based on a nominal value of an operating condition and an actual value of the operating condition.
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/SHARAH ZAAB/Examiner, Art Unit 2857
/Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2857
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