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 .
Information Disclosure Statement
The references listed in the Information Disclosure Statement filed on 12/22/2025 have been considered by the examiner (see attached PTO-1449 forms).
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
The claimed invention is directed to an abstract idea without significantly more.
Claim 1 recites a method of monitoring tire tread for tires of a vehicle, the method comprising: obtaining, via one or more sensors of the vehicle, images of tread for the tires of the vehicle after tire wear monitoring is initiated for the vehicle; determining, via a processor that is coupled to the one or more sensors, a depth of the tread for the tires of the vehicle, using the images, when tire wear monitoring is initiated for the vehicle; and providing a notification for a user of the vehicle as to the depth of the tread for the tires of the vehicle, based on instructions provided by the processor.…
Claim 13 recites a system for monitoring tire tread for tires of a vehicle, the system comprising: one or more sensors of the vehicle, the one or more sensors configured to obtain images of tread for the tires of the vehicle after tire wear monitoring is initiated for the vehicle; and a processor that is coupled to the one or more sensors and that is configured to at least facilitate: determining a depth of the tread for the tires of the vehicle, using the images, when tire wear monitoring is initiated for the vehicle; and providing a notification for a user of the vehicle as to the depth of the tread for the tires of the vehicle, based on instructions provided by the processor…
Claim 18 recites a vehicle comprising: one or more wheels; one or more tires disposed on the one or more wheels; one or more sensors that are configured to obtain images of tread for the tires after tire wear monitoring is initiated for the vehicle; and a processor that is coupled to the one or more sensors and that is configured to at least facilitate: determining a depth of the tread for the tires of the vehicle, using the images, when tire wear monitoring is initiated for the vehicle; and providing a notification for a user of the vehicle as to the depth of the tread for the tires of the vehicle, based on instructions provided by the processor…
and thus grouped as Mental Processes – concepts performed in the human mind (including an observation, evaluation, judgement, opinion).
These judicial exceptions are not integrated into a practical application because the additional elements, the data gathering step, (claim 1) “obtaining, via one or more sensors of the vehicle, images of tread for the tires of the vehicle after tire wear monitoring is initiated for the vehicle” (claim 13) “one or more sensors of the vehicle, the one or more sensors configured to obtain images of tread for the tires of the vehicle after tire wear monitoring is initiated for the vehicle” (claim 18) “one or more sensors that are configured to obtain images of tread for the tires after tire wear monitoring is initiated for the vehicle” are mere data gathering that do not add a meaningful limitation to the method as they are insignificant extra-solution activity. Furthermore, the additional elements (claims 1, 13 and 18) the “processor” are recited as performing generic computer functions routinely used in computer applications. Generic computer components recited as performing generic computer functions amount to no more than using a computer as a tool to perform an abstract idea. Regarding claims 1, 1 and 18, “providing a notification for a user of the vehicle as to the depth of the tread for the tires of the vehicle, based on instructions provided by the processor” the elements are considered insignificant extra-solution activity to the judicial exception – see MPEP 2106.05(g). All of which are considered not indicative of integration into a practical application (see MPEP 2106.04(d)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are considered extra-solution activity of pre-solution and post-solution activity which fall under insignificant extra solution activity and deemed insufficient to qualify as “significantly more” - see MPEP 2106.05(g). The additional elements of the processors are mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and deemed insufficient to qualify as “significantly more” see MPEP 2106.05(f).
Dependent claims 2-12, 14-17 and 19-20 when analyzed as a whole are patent ineligible under 35 U.S.C. §101 because the dependent claims fail to establish that the claims are not directed to an abstract idea as they are directed mathematical concepts and/or mental processes and do not add significantly more to the abstract idea.
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 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.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Puranik [US 2020/0130420 A1].
Regarding claim 1, Puranik teaches a method of monitoring tire tread for tires of a vehicle (monitor the physical condition of the tires - 0017), the method comprising:
obtaining, via one or more sensors of the vehicle, images of tread for the tires of the vehicle after tire wear monitoring is initiated for the vehicle (At step 302, the system 100 captures image data of the tires 12. The system 100 may capture image data using one or more image sensors 14 – 0043);
determining, via a processor that is coupled to the one or more sensors, a depth of the tread for the tires of the vehicle, using the images (tire wear characteristics (e.g., tread depth – 0055, 0057), when tire wear monitoring is initiated for the vehicle (used to determine various tire conditions, for example, a wear condition of the tire 12 - 0045); and
providing a notification for a user of the vehicle as to the depth of the tread for the tires of the vehicle, based on instructions provided by the processor (if the image data indicates an alert condition (i.e., “yes” at step 310), an alert to the driver may be generated at step 312. The alert may be displayed, for example, on the display 126 - 0048) (an actual alert could be generated if conditions equivalent to the expected alert condition actually occur – 0058).
Regarding claim 2, Puranik teaches the step of obtaining the images of the tread comprises obtaining the images from one or more cameras of the vehicle; and the step of determining the depth of the tread comprises determining, via the processor, the depth of the tread using camera images from the one or more cameras in connection with a calibrated camera projection matrix (figure 1, 0015, 0016, 0017, one or more image sensors 14 described herein could include one or more LIDAR sensors, radar sensors, sonar sensors, or other types of sensors - 0026).
Regarding claim 3, Puranik teaches the step of obtaining the images of the tread comprises obtaining the images from a plurality of cameras of the vehicle, including a first camera proximate a side view mirror of the vehicle, and further comprising a second camera on an underbody of the vehicle (figure 1, 0015, 0016, 0017).
Regarding claim 4, Puranik teaches providing, via the processor, instructions for movement of wheels of the vehicle during initiating of monitoring of the tread, to thereby allow for clarity of view of the tread of the tires via the one or more cameras and repeatability of generation of the images of the tread (detect objects and movement from sequential or individual frames of image data - 0027) (movement of the vehicle – 0030).
Regarding claim 5, Puranik teaches the instructions are provided via the processor to the user of the vehicle via a display of the vehicle for the user to engage a steering wheel of the vehicle, to thereby move the wheels of the vehicle and allow for the clarity of view of the tread of the tires via the one or more cameras and repeatability of generation of the images of the tread (The display 126 may provide visual output such as, for example, information or notifications pertaining to the status of the tires – 0036, 0037) ( alert may be displayed – 0048).
Regarding claim 6, Puranik teaches the instructions are provided via the processor to one or more actuators (accelerate and/or brake at a particular magnitude – 0039) of the vehicle for autonomous movement of the wheels of the vehicle and allow for the clarity of view of the tread of the tires via the one or more cameras and repeatability of generation of the images of the tread (vehicle 10 may be an autonomous or semi-autonomous vehicle – 0016).
Regarding claim 7, Puranik teaches storing, in computer memory, a tire tread pattern for the tires based on the images of the tread ( library or lookup table of current conditions factors may be stored in a memory of the vehicle – 0047) (The memory module 106 may store vehicle identification data and/or tire identification data – 0023), in accordance with instructions provided by the processor (tread measurements or tread pattern data over time – 0058).
Regarding claim 8, Puranik teaches determining, via the processor, decolorization of the tires based on the images; and adjusting, via the processor, the tire tread pattern based on the determining of the decolorization for storing in the computer memory (measurable aspects include, but are not limited to, shape, pattern, and color - 0055).
Regarding claim 9, Puranik teaches determining, via the processor based on the tire tread pattern, whether tire rotation, replacement, or both are recommended, including based on whether the tire tread pattern is representative of uneven tread depth between front tires versus rear tears, between left tires versus right tires, or both (Other exemplary measurable aspects include, but are not limited to, shape, pattern, and color - 0055) (comparing the tire wear patterns of vehicles - 0052) ( tread measurements or tread pattern data over time – 0058).
Regarding claim 10, Puranik teaches storing, in computer memory, an identification of a tire pressure monitoring system (TPMS) identification for the tires, for identification of a particular tire for recognizing whether the particular tire has been replaced or rotated, in accordance with instructions provided by the processor (memory module 106 may store vehicle identification data and/or tire identification data - 0023).
Regarding claim 11, Puranik teaches determining, via the processor, whether sufficient light is present for obtaining the images of the tread (a light sensor may be used to determine the external lighting characteristics of the environment in which the vehicle 10 is operating - 0032); and automatically activating a light system outside the vehicle for illumination of the tires while the images of the tread are obtained, in accordance with instructions provided by the processor (used as inputs to affect one or more changes to system – 0032).
Regarding claim 12, Puranik teaches obtaining additional sensor data from one or more additional sensors of the vehicle, including as to values of time of acceleration, braking, tire pressure, terrain of roadways in which the vehicle has travelled, and outside air temperature surrounding the vehicle as the vehicle has been operated; wherein the tire wear monitoring is initiated with a frequency that is based upon the additional sensor data for the vehicle, including each of the acceleration, braking, tire pressure, terrain of roadways in which the vehicle has travelled, and the outside air temperature surrounding the vehicle as the vehicle has been operated (speedometer, tire pressure sensor, motion sensor, location sensor, weather sensor, brake sensor, etc. - 0028-0034).
Regarding claim 13, Puranik teaches a system for monitoring tire tread for tires of a vehicle (monitor the physical condition of the tires - 0017), the system comprising: one or more sensors of the vehicle, the one or more sensors configured to obtain images of tread for the tires of the vehicle after tire wear monitoring is initiated for the vehicle (At step 302, the system 100 captures image data of the tires 12. The system 100 may capture image data using one or more image sensors 14 – 0043); and a processor that is coupled to the one or more sensors and that is configured to at least facilitate: determining a depth of the tread for the tires of the vehicle, using the images (tire wear characteristics (e.g., tread depth – 0055, 0057), when tire wear monitoring is initiated for the vehicle (used to determine various tire conditions, for example, a wear condition of the tire 12 - 0045); and providing a notification for a user of the vehicle as to the depth of the tread for the tires of the vehicle, based on instructions provided by the processor (if the image data indicates an alert condition (i.e., “yes” at step 310), an alert to the driver may be generated at step 312. The alert may be displayed, for example, on the display 126 - 0048) (an actual alert could be generated if conditions equivalent to the expected alert condition actually occur – 0058).
Regarding claim 14, Puranik teaches the one or more sensors comprise a plurality of cameras of the vehicle, including: a first camera disposed proximate a side view mirror of the vehicle; and a second camera disposed on an underbody of the vehicle; and the processor is further configured to at least facilitate determining the depth of the tread using camera images from the plurality of cameras in connection with a calibrated camera projection matrix (figure 1, 0015, 0016, 0017, one or more image sensors 14 described herein could include one or more LIDAR sensors, radar sensors, sonar sensors, or other types of sensors - 0026).
Regarding claim 15, Puranik teaches the processor is further configured to at least facilitate providing instructions for movement of wheels of the vehicle during initiating of monitoring of the tread, to thereby allow for clarity of view of the tread of the tires via the plurality of cameras. and repeatability of generation of the images of the tread (detect objects and movement from sequential or individual frames of image data - 0027) (movement of the vehicle – 0030).
Regarding claim 16, Puranik teaches the processor is further configured to at least facilitate: storing, in computer memory, a tire tread pattern for the tires based on the images of the tread ( library or lookup table of current conditions factors may be stored in a memory of the vehicle – 0047) (The memory module 106 may store vehicle identification data and/or tire identification data – 0023), in accordance with instructions provided by the processor (tread measurements or tread pattern data over time – 0058); and determining, based on the tire tread pattern, whether tire rotation, replacement, or both are recommended, including based on whether the tire tread pattern is representative of uneven tread depth between front tires versus rear tears, between left tires versus right tires, or both (Other exemplary measurable aspects include, but are not limited to, shape, pattern, and color - 0055) (comparing the tire wear patterns of vehicles - 0052) ( tread measurements or tread pattern data over time – 0058).
Regarding claim 17, Puranik teaches one or more additional sensors of the vehicle that are configured to obtain additional sensor data, including as to values of time of acceleration, braking, tire pressure, terrain of roadways in which the vehicle has travelled, and outside air temperature surrounding the vehicle as the vehicle has been operated; wherein the processor is further configured to at least facilitate initiating the tire wear monitoring with a frequency that is based upon the additional sensor data for the vehicle, including each of the acceleration, braking, tire pressure, terrain of roadways in which the vehicle has travelled, and the outside air temperature surrounding the vehicle as the vehicle has been operated (speedometer, tire pressure sensor, motion sensor, location sensor, weather sensor, brake sensor, etc. - 0028-0034).
Regarding claim 18, Puranik teaches a vehicle comprising: one or more wheels; one or more tires disposed on the one or more wheels; one or more sensors that are configured to obtain images of tread for the tires (figure 1, 0015, 0016, 0017) after tire wear monitoring is initiated for the vehicle (At step 302, the system 100 captures image data of the tires 12. The system 100 may capture image data using one or more image sensors 14 – 0043); and a processor that is coupled to the one or more sensors and that is configured to at least facilitate: determining a depth of the tread for the tires of the vehicle, using the images (tire wear characteristics (e.g., tread depth – 0055, 0057), when tire wear monitoring is initiated for the vehicle (used to determine various tire conditions, for example, a wear condition of the tire 12 - 0045); and providing a notification for a user of the vehicle as to the depth of the tread for the tires of the vehicle, based on instructions provided by the processor (if the image data indicates an alert condition (i.e., “yes” at step 310), an alert to the driver may be generated at step 312. The alert may be displayed, for example, on the display 126 - 0048) (an actual alert could be generated if conditions equivalent to the expected alert condition actually occur – 0058).
Regarding claim 19, Puranik teaches the one or more sensors comprise a plurality of cameras of the vehicle, including: a first camera disposed proximate a side view mirror of the vehicle; and a second camera disposed on an underbody of the vehicle (figure 1, 0015, 0016, 0017); and the processor is further configured to at least facilitate: providing instructions for movement of wheels of the vehicle during initiating of monitoring of the tread, to thereby allow for clarity of view of the tread of the tires via the plurality of cameras and repeatability of generation of the images of the tread (detect objects and movement from sequential or individual frames of image data - 0027) (movement of the vehicle – 0030).; and determining the depth of the tread using camera images from the plurality of cameras in connection with a calibrated camera projection matrix (figure 1, 0015, 0016, 0017, one or more image sensors 14 described herein could include one or more LIDAR sensors, radar sensors, sonar sensors, or other types of sensors - 0026)..
Regarding claim 20, Puranik teaches one or more additional sensors that are configured to obtain additional sensor data for the vehicle, including as to values of time of acceleration, braking, tire pressure, terrain of roadways in which the vehicle has travelled, and outside air temperature surrounding the vehicle as the vehicle has been operated; wherein the processor is further configured to at least facilitate initiating the tire wear monitoring with a frequency that is based upon the additional sensor data for the vehicle, including each of the acceleration, braking, tire pressure, terrain of roadways in which the vehicle has travelled, and the outside air temperature surrounding the vehicle as the vehicle has been operated (speedometer, tire pressure sensor, motion sensor, location sensor, weather sensor, brake sensor, etc. - 0028-0034).
Relevant Prior Art / Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Wang et al. (US Patent Number 10,078,892 B1) discloses methods and systems for vehicle tire analysis using vehicle mounted cameras;
Weston et al. (US Patent Application Publication 2025/0332869 A1) discloses an uneven tire wear identification system using a machine learning model;
JO et al. (US Patent Application Publication 2023/0419469 A1) discloses a tire tread wear determination system using a deep artificial neural network.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RICKY GO whose telephone number is (571)270-3340. The examiner can normally be reached on Monday through Friday from 9:00 a.m. to 5:30 p.m.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Arleen M. Vazquez can be reached on (571) 272-2619. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RICKY GO/Primary Examiner, Art Unit 2857
