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 .
This Action is non-final and is in response to the claims filed July 25, 2023. Claims 1- 20 are currently pending.
Examiner’s note
Claims 17-20 are not being rejected under 35 USC 101 considering para 24 of applicant’s specification as filed.
Allowable Subject Matter
Claims 4, 9, 16, and 20 are 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.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or no obviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-3, 5, 7, 8, 10, 11, 12, 14, 15, 17 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (US 20260121577 A1.), and in view (NUSnews, “Using the ‘shadow-effect’ to generate electricity”, 21 May 2020).
As per claim 1, Liu et al. teach
A computer-implemented method of facilitating energy harvesting (para 48, public database with historical data that is establishing a relationship formula to predict solar radiation), the computer-implemented method comprising:
obtaining a data-analysis-based control to facilitate energy harvesting using road-based, photovoltaic power generation, the data-analysis-based control comprising (para 7, obtaining measurement time series data, para 30, Fig. 1, step S1 -step S3, obtaining collection of nearby solar radiation observation data for calculating sun movement path, solar altitude angle, and solar azimuthal angle, also see para 55 for glare impact analysis based on traffic lane or traffic data):
determining, for multiple road segments of a road, a photovoltaic value (para 4, photovoltaic modules are installed on the roadside, especially on a straight section of the roadside. para 8, S1 teaches obtaining a spatial position coordinate such as a latitude, longitude and a ground elevation of a contour vertex of each photovoltaic module based on a proposed installation location and an installation manner of photovoltaic array. Para 8 also teaches calculating and analyzing the sun movement path based on the latitude and longitude and the time zone of the proposed installation location. Paras 9-11, based on the fixed arrangement as the installation manner, the photovoltaic energy generator creates an optimal tilt angle and optimal azimuthal angle in various ways such as monthly average irradiance, direct component irradiance, and diffuse component irradiance. The optimal tilt angle maximize the annual radiation on inclined surfaces of the photovoltaic array. Also see para 16 for comparing solar radiation in respect to critical tilt angle and the optimal tilt angle and evaluating the differences between them. A less than 5% difference value of the critical tilt angle is considered to be an accepted value. These photovoltaic values are calculated in response to a grid connected photovoltaic power generation system to identify the larger radiation on the inclined surface. Overall, it teaches determining the road segment based on the photovoltaic energy value.);
based on the respective photovoltaic values, identifying one or more road segments of the multiple road segments for photovoltaic power generation (See Fig. 1, steps S1-S4, for identifying one or more road segments based on the photovoltaic values.); and
initiating install of a photovoltaic power generator in a road segment of the identified one or more road segments to facilitate energy harvesting from the road segment (para 29, a roadside site selection method provides siting guidance for installing power generation system on the curved road section or idle land for improving utilization rate. Also see paras 7-11 for installation process).
Liu et al. do not teach shadow effect energy generation based on the illumination to shadow contrast.
However, in the same field of endeavor, NUSnews teaches of a device called shadow-effect energy generator (SEG) which uses the contrast in illumination between lit and shadowed areas to generate electricity (see entire article). Liu et al. teach a roadside selection of photovoltaic module with glare impact analysis from the direct sunlight. Whereas, using an SEG would produce energy using the illumination contrast caused by shadows and illuminated section that results in an electric current (NUSnews, “Using the “shadow -effect’ to generate electricity”).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the photovoltaic energy module taught by Liu et al. and to include the SEG system taught by NUSnews. This would have been obvious because both Liu et al. and NUSnews generate energy based on sunlight. By adding the SEG system, it will enhance the method to use both sun and shade to generate energy (para 3, NUSnews, “Using the “shadow -effect’ to generate electricity”).
As per claim 2, the combination of Liu et al. and NUSnews teach
The computer-implemented method of claim 1, wherein the identifying comprises identifying the one or more road segments with respective photovoltaic values within a specified contrast value range (Liu et al. , para 4, photovoltaic modules are installed on the roadside, especially on a straight section of the roadside, See paras 8-11, for identifying road segment based on the sunlight movement, various direction of irradiance and critical values of different angles. Also see para 16 for comparing solar radiation in respect to critical tilt angle and the optimal tilt angle and evaluating the differences between them. A less than 5% difference value of the critical tilt angle is considered to be an accepted value. These photovoltaic values are calculated in response to a grid connected photovoltaic power generation system to identify the larger radiation on the inclined surface. The less than 5% value teaches a limit or range. Also see paras 21-24, an impact range of the reflected lights is determined after calculating directions of the reflected lights. Also see para 3, NUSnews for illumination to shadow contrast) with respective illumination-to-shadow contrast values within a specified contrast value range indicative of a desired shadow-effect energy generation potential, (NUSnews teaches of a device called shadow-effect energy generator (SEG) which uses the contrast in illumination between lit and shadowed areas to generate electricity. Liu et al. teach a roadside selection of photovoltaic module with glare impact analysis from the direct sunlight. Whereas using an SEG would produce energy using the illumination contrast caused by shadows and illuminated section that results in an electric current (para 3, NUSnews, “Using the “shadow -effect’ to generate electricity”).
As per claim 3, the combination of Liu et al. and NUSnews teach
The computer-implemented method of claim 1, wherein the data-analysis-based control further comprises:
determining, for each road segment of the multiple road segments, an energy harvest potential for the road segment using the respective photovoltaic value (Liu et al. , para 4, photovoltaic modules are installed on the roadside, especially on a straight section of the roadside, para 8 S1 teaches obtaining a spatial position coordinate such as a latitude, longitude and a ground elevation of a contour vertex of each photovoltaic module based on a proposed installation location and an installation manner of photovoltaic array. Para 8 also teaches calculating and analyzing the sun movement path based on the latitude and longitude and the time zone of the proposed installation location. This teaches determining the road segment of a road. Paras 9-11, based on the fixed arrangement as the installation manner, the photovoltaic energy generator creates an optimal tilt angle and optimal azimuthal angle in various points such as monthly average irradiance, direct component irradiance, and diffuse component irradiance as well as quarter basis. The optimal tilt angle maximize the annual radiation on inclined surfaces of the photovoltaic array. Also see para 16 for comparing solar radiation in respect to critical tilt angle and the optimal tilt angle and evaluating the differences between them. A less than 5% difference value of the critical tilt angle is considered to be an accepted value. These photovoltaic values are calculated in response to a grid connected photovoltaic power generation system to identify the larger radiation on the inclined. Also see Fig. 1, step S4, determining an affected road length range based on the glare impact analysis. Also see, para 3, NUSnews, “Using the “shadow -effect’ to generate electricity” for the illumination to shadow contrast.)
wherein the identifying the one or more road segments comprises identifying the one or more road segments of the multiple road segments with energy harvest potential above a specified energy harvest potential threshold (Liu et al., abstract, a roadside photovoltaic site selection method includes a comparison of solar radiation received on the inclined surface between the critical tilt angle and the optimal tilt angle. The difference of solar radiation is determined in response to a difference value less than a set value. The set value teaches the threshold. Also see para 16, the difference in the solar radiation less than a set value such as 5%.).
As per claim 5, the combination of Liu et al. and NUSnews teach
The computer-implemented method of claim 1, wherein the identifying comprises identifying two or more road segments of the multiple road segments for road-based (Liu et al., Fig 1, step S4, determining an affected road length range based on the glare impact analysis, also see claim 4 S4, “determining an affected road length range based on a spatial geometric relationship between the reflected lights and adjacent roads”, also see para 12, analyzing spatial positions relationship between the angles within the adjacent roads, arranging observations points within certain distance within effected road section, obtaining one or more observation paths based on road positions and traffic directions.) shadow-effect energy generation ( NUSnews teaches of a device called shadow-effect energy generator (SEG) which uses the contrast in illumination between lit and shadowed areas to generate electricity. Whereas using an SEG would produce energy using the illumination contrast caused by shadows and illuminated section that results in an electric current (para 3, NUSnews, “Using the “shadow -effect’ to generate electricity”), and wherein at least two road segments of the two or more road segments are adjacent road segments ( Liu et al. para 12, analyzing spatial positions relationship between the angles within the adjacent roads, arranging observations points within certain distance within effected road section, obtaining one or more observation paths based on road positions and traffic directions. ) and the identifying comprises:
aggregating the at least two road segments into an aggregated road segment, the aggregated road segment having a photovoltaic value in comparison to the respective photovoltaic value of the at least two road segments individually (Liu et al., abstract, comparing solar radiation between critical tilt angle and optimal tilt angle, in response to the difference in the solar radiation less than a set value, performing analysis and providing recommendation for installation location, also see Liu et al., paras 8-11, calculating various sun movements and optimal angles obtained by the photovoltaic modules based on a proposed installation location and installation manner of photovoltaic array . Also see para 5, in response to photovoltaic power generation, the roadside photovoltaic site election method considers a comprehensive glare impact analysis during siting stage. It identifies all installation sites that generates adverse glare effects and provides beneficial reference for sitting design for a planning stage.); and
wherein the initiating install includes initiating install of a shadow-effect energy generator spanning (NUSnews, page 1, para 3), the aggregated at least two road segments (Liu et al., para 12, “arranging observation points at certain distances within affected road sections, obtaining one or more observation paths based on road position and traffic direction”).
As per claim 7, The combination of Liu et al. and NUSnews teach
The computer-implemented method of claim 1 (para 48, public database with historical data that is establishing a relationship formula to predict solar radiation) further comprises:
obtaining traffic data for the road (para 12, analyzing spatial positions relationship between the angles within the adjacent roads, arranging observations points within certain distance within effected road section, obtaining one or more observation paths based on road positions and traffic directions, para 7, obtaining measurement time series data, para 82, driver’s view in terms of traffic light, driving speed, para 30, Fig. 1, step S1 -step S3, obtaining collection of nearby solar radiation observation data for calculating sun movement path, solar altitude angle, and solar azimuthal angle); and
using, at least in part, the traffic data in determining for the multiple road segments the respective photovoltaic values (para 2, integrating highway traffic with solar power photovoltaic power generation, paras 80- 82, glare analysis based on traffic data, such as driver’s view, traffic light, horizontal and vertical view, direction of the driving lane).
As per claim 8, The combination of Liu et al. and NUSnews teach
The computer-implemented method of claim 1, wherein the data-analysis-based control further comprises:
identifying an optimal placement for a structure along a side of the road to enhance energy harvesting ( Liu et al. ,abstract, comparing solar radiation between critical tilt angle and optimal tilt angle, in response to the difference in the solar radiation less than a set value, performing analysis and providing recommendation for installation location, also see Liu et al., paras 8-11, calculating various sun movements and optimal angles obtained by the photovoltaic modules based on a proposed installation location and installation manner of photovoltaic array, the optimal tilt angle and optimal azimuth angle teaches the enhance energy ) using the road-based, shadow-effect energy generation ( para 3, NUSnews, “Using the “shadow -effect’ to generate electricity” ,NUSnews teaches of a device called shadow-effect energy generator (SEG) which uses the contrast in illumination between lit and shadowed areas to generate electricity. Liu et al. teach a roadside selection of photovoltaic module. Whereas using an SEG would produce energy using the illumination contrast caused by shadows and illuminated section that results in an electric current); and
initiating install of the structure based on the identified optimal placement for the structure along the side of the road to enhance energy harvesting using the road-based, shadow-effect energy generation (Liu et al., para 29, a roadside site selection method provides siting guidance for installing power generation system on the curved road section or idle land for improving utilization rate. Also see paras 7-11 for installation process.).
As per claim 10, The combination of Liu et al. and NUSnews teach
A computer system comprising:
a memory ( para 48, public database with historical data that is establishing a relationship formula to predict solar radiation, it implies there is a computer with memory);
at least one processor in communication with the memory, wherein the computer system is configured to perform a method, the method comprising( para 48, public database with historical data that is establishing a relationship formula to predict solar radiation, it implies there is a computer with memory and processor):
wherein the computer system is configured to perform a method, the method comprising:
obtaining a data-analysis-based control to facilitate energy harvesting using road-based, shadow-effect energy generation, the data-analysis-based control comprising (please refer to the analysis of claim 1 above):
determining, for multiple road segments of a road, a respective illumination-to-shadow contrast value (please refer to the analysis of claim 1 above);
based on the respective illumination-to-shadow values, identifying one or more road segments of the multiple road segments for shadow-effect energy generation (please refer to the analysis of claim 1 above); and
initiating install of a shadow-effect energy generator in a road segment of the identified one or more road segments to facilitate energy harvesting from the road segment (please refer to the analysis of claim 1 above).
As per claim 17, Liu et al. teach
A computer program product comprising:
one or more computer readable storage media and program instructions collectively stored on the one or more computer readable storage media readable by at least one processer to (Liu et al. para 48, public database with historical data that is establishing a relationship formula to predict solar radiation),:
obtain a data-analysis-based control to facilitate energy harvesting using road-based, shadow-effect energy generation, the data-analysis-based control comprising (Please refer to the analysis of claim 1 above):
determining, for multiple road segments of a road, a respective illumination-to-shadow contrast value (Please refer to the analysis of claim 1 above);
based on the respective illumination-to-shadow values, identifying one or more road segments of the multiple road segments for shadow-effect energy generation (Please refer to the analysis of claim 1 above); and
initiating install of a shadow-effect energy generator in a road segment of the identified one or more road segments to facilitate energy harvesting from the road segment (Please refer to the analysis of claim 1 above).
As per claim 11, please refer to the analysis of claim 3 above, as they recite the same limitations.
As per claim 12, please refer to the analysis of claim 5 above, as they recite the same limitations.
As per claim 14, please refer to the analysis of claim 7 above, as they recite the same limitations.
As per claim 15, please refer to the analysis of claim 8 above, as they recite the same limitations.
As per claim 18, please refer to the analysis of claim 5 above, as they recite the same limitations.
Claims 6, 13, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (US 20260121577 A1.) in view (NUSnews, “Using the ‘shadow-effect’ to generate electricity”, 21 May 2020), and further In view of ( “High-entropy energy modeling and its integration with the microgrid of intelligent connected transportation system”, 12 September 2024).
As per claim 6, the combination of Liu et al. and NUSnews teach
The computer-implemented method of claim 1 (Liu et al., para 48, public database with historical data that is establishing a relationship formula to predict solar radiation) wherein the data-analysis-based control further comprises:
shadow-effect energy generation (para 3, NUSnews, “Using the “shadow -effect’ to generate electricity NUSnews teaches of a device called shadow-effect energy generator (SEG) which uses the contrast in illumination between lit and shadowed areas to generate electricity. Whereas using an SEG would produce energy using the illumination contrast caused by shadows and illuminated section that results in an electric current); and
The combination of Liu et al. and NUSnews do not teach
training a machine learning model to control traffic on the road;
dynamically controlling, at least in part, the traffic on the road using the trained machine learning model, the dynamically controlling increasing energy generation from the road-based energy generation.
In the same field of endeavor, Xu et al. teach
training a machine learning model to control traffic on the road (Xu et al., page 2, left col. First paragraph, employed convolution neural network (CNN) to capture spatial dependencies in traffic flow, while recursive neural network (RNN) were utilized to use to learn dynamic correlation within traffic flow),
dynamically controlling, at least in part, the traffic on the road using the trained machine learning model, the dynamically controlling increasing energy generation from the road-based energy generation (Xu et al. ,abstract, a PDF former model for traffic flow prediction based on analysis dispatch of a microgrid involving potential high energy generation. Also see page 2,Fig. 1 and Fig. 2, left col. para, below Fig. 1, right col. all paragraphs. A traffic flow prediction based on PDF former, using correlation of network traffic flow, road network, traffic flow and traffic flow node, and traffic data embedding layer modelling an entropy energy generating photovoltaic power.).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the roadside data collection for energy generation system taught by Liu et al. and to include the data analysis for road information taught by Xu et al. This would have been obvious because both Liu et al. and Xu et al. perform data analysis with traffic and roadside data. By incorporating data analysis based on neural network, the system can collect data dynamically for energy generation (Xu et al., page 2, Fig. 1 and Fig. 2).
As per claim 13, please refer to the analysis of claim 6 above, as they recite the same limitations.
As per claim 19, please refer to the analysis of claim 6 above, as they recite the same limitations.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please refer to the form 892.
The following art has been found relevant but has not been used in the rejection:
US 12160197 B1, Duggal, (Fig. 6- Fig. 10, displays roadside photovoltaic energy generation for electric vehicle charging and installing the charging station)
US 7791503 B2, Breed et al.( col. 76, lines 59-60, map database subsystem 8 contains memory module, Fig. 5, road based dynamic data analysis)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Rokeya Alam whose telephone number is (571) 272-0083. The examiner can normally be reached between 7:30am - 4:30pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mr. Scott Baderman can be reached at telephone number (571-272-3644). 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 for authorized users only. Should you have questions about access to Patent Center, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form.
/ROKEYA SHAWALI ALAM/Examiner, Art Unit 2118
/SCOTT T BADERMAN/Supervisory Patent Examiner, Art Unit 2118
Prosecution Insights