DETAILED ACTION
This office action is in response to the initial filing dated November 30, 2023.
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 Status
Claims 1-20 are currently pending.
Claim Objections
Claims 1, 5, 18, and 19 are objected to because of the following informalities:
Claim 1 recites “a rider accessories” in line 4 of the claim where that phrase is not grammatically correct. Proper grammar would either be “a rider accessory” or “one or more rider accessories”, for example.
Further, claim 1 recites a system comprising a driving assistance device and a drive monitoring and analyzing unit, but does not recite the conjunction “and” at the end of line 10 to properly recite these elements.
Further, claim 1 recites “wherein the first computing device and the second computing device operatively coupled” in lines 12-13, which is not grammatically correct. It appears that the phrase is missing the term “are” before the term “operatively”.
Further, claim 1 recites “the drive monitoring and analyzing module configured to” in line 14 which is not grammatically correct. It appears that the phrase is missing the term “is” before the term “configured”.
Further, claim 1 recites “transfer” in line 19 where the term “transfers” is appropriate so that the claim reads that the drive monitoring and analyzing modules reads and stores or transfers.
Claim 5 recites “the group consisting of impact events,… impacts,…” which is redundant since an impact event would include an impact.
Claim 18 recites “alert generating module” in lines 3-4. The inclusion of this limitation appears to be in error because the drive analyzing module does not receive information from the alert generating module (as claimed), but instead the alert generating module generates alerts based on the analyzing done by the drive analyzing module (Figure 6, Items 618 and 620).
Claim 19 recites “a rider accessories” in line 4 of the claim where that phrase is not grammatically correct. Proper grammar would either be “a rider accessory”, “an accessory of a rider”, “one or more rider accessories”, or “one or more accessories of a rider”, for example.
Further, claim 19 recites “to detect gyroscope” in line 8 and “calculating lean angle of an object using gyroscope” in line 10. In both instances, the context of the claim refers to data types, whereas, a gyroscope is a device. A possible correction to clarify this language would be replacing the term “gyroscope” with “orientation”, which is a typical data type determined using a gyroscope.
Further, line 10 lacks a proper modifier, such as “a”, prior to the phrase “lean angle”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 2 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 2 recites “wherein the first set of sensors comprises at least one of an accelerometer, a gyroscope, a direction sensor, or a speed sensor”, however, this claim depends from claim 1 which states “wherein the first set of sensors are configured to measure linear acceleration and angular acceleration”. The specification does not provide adequate support for how a gyroscope, direction sensor, or speed sensor is configured to measure linear acceleration and angular acceleration. Therefore, the claim contains subject matter which is not described in the specification in a way to reasonably convey that the inventor had possession of the claimed invention at the time the application was filed.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1, the phrase "such as" renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d). Lines 16-17 recite “via the network such as Bluetooth, Wi-Fi, or internet”. For purposes of examination, the claim is interpreted as any network since it is not clear if the specific network type is intended to limit the scope of the claimed invention.
Claim 1 recites the limitation "the sensor data received from the driving assistance device" in line 18. There is insufficient antecedent basis for this limitation in the claim.
Claims 2-18 are rejected as being dependent from a rejected base claim.
Claim 3 recites “wherein the second set of sensors comprises… any other orientation measurement sensor”. This limitation fails to particularly point out and distinctly claim the subject matter of the invention.
Claim 4 recites “wherein the third set of sensors comprises… any other physical parameter sending component”. This limitation fails to particularly point out and distinctly claim the subject matter of the invention.
Claim 13 recites the limitation “the gyroscope” in line 3. There is insufficient antecedent basis for this limitation in the claim since claim 13, including the subject matter of claim 1, from which it depends, does not previously recite the limitation of “a gyroscope”.
Claim 18 recites the limitations “the acceleration detection module”, “the gyroscope detection module”, and “the image processing module” in lines 2-3. There is insufficient antecedent basis for these limitations in the claim since these limitations are introduced in claims 7, 8, and 12, respectively.
Claim 19 recites the limitation “the lean angle” in line 14. There is insufficient antecedent basis for these limitations in the claim since it is not clear if this lean angle is the same as the lean angle calculated in line 10. For purposes of examination, the claim is interpreted as two separate lean angles, the first being calculated by a driving assistance device and the second being predicted by a drive monitoring and analyzing module.
Claim 20 is rejected as being dependent from a rejected base claim.
Claim Rejections - 35 USC § 103
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.
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.
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 nonobviousness.
Claims 1-9 and 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over Agnihotram (US PG Pub #2021/0097370) in view of Bose et al. (Bose; US PG Pub #2022/0301594).
As to claim 1, Agnihotram teaches a system for driving monitoring, analyzing, and generating alerts to users in real-time (Paragraph [0017] teaches a system for providing personalized driving assistance to a driver of a vehicle; Paragraph [0006] teaches a system that receives sensor data, determines and analyzes events, and provides a personalized driving recommendation), comprising:
a driving assistance device integrated into at least one of a vehicle, a vehicle peripheral components or to a rider accessories (Paragraph [0017]), the driving assistance device comprising a first set of sensors, a second set of sensors, and a third set of sensors electrically connected to a processing device, wherein the first set of sensors are configured to measure linear acceleration of an object (Paragraph [0018] teaches an accelerometer for acquiring instant acceleration of the vehicle; Paragraph [0050]), the second set of sensors are configured to measure orientations of the object (Paragraph [0018] teaches a gyroscope and magnetometer for acquiring absolute and instant orientation of the vehicle; Paragraph [0050]), the third set of sensors are configured to monitor vital parameters of the rider (Paragraph [0019] teaches capturing voice/speech inside the vehicle and breath of the driver; Paragraph [0050]) and a rotational angle of the rider's head (Paragraph [0019] teaches an inside camera; Paragraphs [0042]-[0043] teaches head right, left, up, and down; Paragraph [0050] teaches an inside camera);
a drive monitoring and analyzing module incorporated in a first computing device and a second computing device, wherein the first computing device and the second computing device operatively coupled to each other through a network (Paragraph [0021] teaches the driver assistance device may interact with one or more external devices or with the vehicle over a communication network; Paragraph [0022] teaches each module of a driver assistance device may reside, in whole or in parts, on one device or multiple devices in communication with each other), whereby the drive monitoring and analyzing module configured to facilitate communication between the driving assistance device and the first computing device and the second computing device via the network such as Bluetooth, Wi-Fi, or internet (Paragraphs [0062]-[0063] teach 802.11 and Bluetooth communication; Paragraph [0064] teaches communication via the internet), and the drive monitoring and analyzing module reads the sensor data received from the driving assistance device and stores the sensor data in a central database or onboard memory component or transfer it to another computing device (Paragraph [0021] teaches the computer readable medium, or memory, storing sensory data with respect to the vehicle and multi-channel input data with respect to the passengers);
the drive monitoring and analyzing module comprising machine learning techniques, logical algorithms, double authentication and validation algorithms, and computer implemented pattern recognition techniques for analyzing the sensor data received from the driving assistance device (Paragraph [0022] teaches a data fusion module, a multi-modal fusion model (i.e., supervised machine learning), an incremental module (i.e., unsupervised machine learning), and a contextual generation module; Paragraphs [0044], [0047], and [0057] teach pattern recognition algorithms), thereby generating alerts in real-time (Paragraph [0028] teaches analyzing and predicting to provide necessary alerts/warnings to assist the driver).
However, Agnihotram does not explicitly teach the first set of sensors are configured to measure angular acceleration and the second set of sensors are configured to calibrate orientations.
In the field of sensor data analyzation, Bose teaches the first set of sensors are configured to measure angular acceleration (Paragraphs [0022], [0061], [0102], and [0246] teach measuring angular acceleration) and the second set of sensors are configured to calibrate orientations (Paragraph [0197] teaches calibrating orientation). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Agnihotram with the teaching of Bose because this ensures that sensors are aligned and/or set up with the same values for a given input motion (Paragraph [0197]) which is part of capturing data more accurately or efficiently (Paragraphs [0226] and [0365]).
As to claim 2, depending from the system of claim 1, Agnihotram teaches wherein the first set of sensors comprises at least one of an accelerometer, a gyroscope, a direction sensor, or a speed sensor (Paragraph [0018] teaches an accelerometer and a gyroscope).
As to claim 3, depending from the system of claim 1, Agnihotram teaches wherein the second set of sensors comprises at least one of an ultrasonic sensor or a magnetometer or any other orientation measurement sensor (Paragraph [0018] teaches a magnetometer).
As to claim 4, depending from the system of claim 1, Agnihotram teaches wherein the third set of sensors comprises at least one of a heart rate monitor, a head rotation sensor, or a temperature sensor or any other physical parameter sending component (Paragraph [0019] teaches a face camera for capturing the face of the driver; Paragraph [0031] teaches image data to predict driver’s emotions or intentions; Paragraphs [0042]-[0043] teach predicting head right, left, up, and down as gaze directions for the driver looking up, down, left, or right).
As to claim 5, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module is configured to detect events selected from the group consisting of impact events, emergency events, leaning and turning events, physical motion and movement interrupts, impacts, and anomalies occurring to the object or rider (Paragraph [0027] teaches events include vehicle and driver anomalies).
As to claim 6, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises a drive monitoring module configured to read the sensor data (Paragraphs [0022]-[0023] teach an input module receiving data from various sensors and monitoring devices) and store it in the central database or onboard memory component or transfer it to an another computing device (Paragraph [0021] teaches a computer-readable medium, when executed by a processor, storing sensory data and multi-channel input data with respect to the passengers).
As to claim 7, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises an acceleration detection module configured to sense the acceleration information of the object (Paragraph [0018] teaches an accelerometer for acquiring acceleration of the vehicle).
As to claim 8, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises a gyroscope detection module configured to measure and maintain the orientation and angular velocity of the object (Paragraph [0018] teaches a gyroscope).
As to claim 9, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises a position detection module configured to fetch the object's orientation coordinates (Paragraph [0018] teaches a GPS sensor for acquiring instant position, or current location, of the vehicle).
As to claim 11, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises a location detection module configured to provide accurate geolocation information for determining turns in the road (Paragraph [0018] teaches a GPS sensor for acquiring instant position, or current location, of the vehicle; Paragraph [0030] teaches predicting turning deviations; Paragraph [0049] teaches providing a personalized driving recommendation to a driver passenger or a navigation device).
As to claim 12, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises an image capturing module and an image processing module (Paragraph [0019] teaches an inside camera and a face camera; Paragraph [0031] teaches data derived from cameras and analyzing data; Paragraph [0033] teaches extracting data from raw video/images).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Agnihotram (US PG Pub #2021/0097370) in view of Bose et al. (Bose; US PG Pub #2022/0301594) as applied to claim 1 above, and further in view of Sicconi et al. (Sicconi; US PG Pub #2019/0213429).
As to claim 10, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises a movement tracking module configured to track rider head movements (Paragraphs [0042]-[0043] teach predicting head right, left, up, and down as gaze directions for the driver looking up, down, left, or right), but does not explicitly teach tracking head movements with yaw, pitch, and roll data.
In the field of driver monitoring, Sicconi teaches tracking head movements with yaw, pitch, and roll data (Paragraphs [0054] and [0056]-[0057]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Agnihotram with the head tracking of Sicconi because providing for dynamic models allows for accurate feedback in real time (Paragraph [0031]) such that observing and modeling driver behavior can save lives (Paragraph [0033]).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Agnihotram (US PG Pub #2021/0097370) in view of Bose et al. (Bose; US PG Pub #2022/0301594) as applied to claim 1 above, and further in view of Serita et al. (Serita; US PG Pub #2019/0271543).
As to claim 13, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises a turn predicting module (Paragraph [0028] teaches predicting lane change or overtaking; Paragraph [0030] teaches predicting turning deviations), but does not explicitly teach the turn predicting module is configured to predict a lean angle of the rider on the road based on received information, including data from the gyroscope, speed, and acceleration of the rider.
In the field of vehicle monitoring, Serita teaches a turn predicting module is configured to predict a lean angle of the rider on the road based on received information, including data from the gyroscope, speed, and acceleration of the rider (Paragraphs [0027]-[0028] teach storing an estimated lean angle from processed data from sensors on a mobile device including GPS, gyroscope, accelerometer, and magnetometer; Paragraph [0034] teaches velocity information). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Agnihotram with that of Serita because monitoring driver behavior and vehicle status can be helpful for many applications and lean angle is a known parameter to characterize a motorcycle rider (Paragraph [0002]).
Claims 14-17 are rejected under 35 U.S.C. 103 as being unpatentable over Agnihotram (US PG Pub #2021/0097370) in view of Bose et al. (Bose; US PG Pub #2022/0301594) as applied to claim 1 above, and further in view of Aarts et al. (Aarts; US PG Pub #2019/0357834).
As to claim 14, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises an alert generating module configured to generate notifications or alerts indicating the direction of turn of the object or rider (Paragraphs [0020] and [0028] teach an alert or early warning generation module providing necessary alerts/warnings to assist the driver when changing lanes or overtaking) to the second computing device through audio, visual signaling including light-emitting diode indications (Paragraph [0063] teaches an I/O interface for communicating with I/O devices such as output devices including an audio speaker or video display including LEDs), and indications within a mobile application (Paragraph [0021] teaches the driver assistance device interacts with one or more external devices or with the vehicle over a communication network for sending or receiving various data, where the external devices may include a remote server, digital device, or another computing system; Paragraphs [0063]-[0064] teach a processor communicating via a transceiver and network with mobile devices; Paragraph [0066] teaches user interface application; Paragraph [0067] teaches a web browser application, messaging application, and mail viewing application). However, Agnihotram does not explicitly teach haptic feedback.
In the field of vehicle safety, Aarts teaches haptic feedback (Paragraph [0068] teaches providing tactile feedback to the driver). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Agnihotram with the tactile feedback of Aarts because providing feedback influences each occupant to make for a positive driving experience and safe travels (Paragraph [0008]).
As to claim 15, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises an alert generating module configured to generate notifications or alerts indicating the direction of turn to the rider (Paragraphs [0020] and [0028] teach an alert or early warning generation module providing necessary alerts/warnings to assist the driver when changing lanes or overtaking; Paragraph [0043] teaches necessary alerts/warnings/preventative steps may be provided to the driver) through audio, visual signaling including light-emitting diode indications (Paragraph [0063] teaches an I/O interface for communicating with I/O devices such as output devices including an audio speaker or video display including LEDs), and indications within a mobile application (Paragraph [0021] teaches the driver assistance device interacts with one or more external devices or with the vehicle over a communication network for sending or receiving various data, where the external devices may include a remote server, digital device, or another computing system; Paragraphs [0063]-[0064] teach a processor communicating via a transceiver and network with mobile devices; Paragraph [0066] teaches user interface application; Paragraph [0067] teaches a web browser application, messaging application, and mail viewing application). However, Agnihotram does not explicitly teach haptic feedback.
In the field of vehicle safety, Aarts teaches haptic feedback (Paragraph [0068] teaches providing tactile feedback to the driver). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Agnihotram with the tactile feedback of Aarts because providing feedback influences each occupant to make for a positive driving experience and safe travels (Paragraph [0008]).
As to claim 16, depending from the system of claim 15, Agnihotram does not explicitly teach wherein the haptic feedback is generated by vibration motors, thereby enabling the rider to navigate lanes on the road without having to take their eyes off the road.
In the field of vehicle safety, Aarts teaches wherein the haptic feedback is generated by vibration motors, thereby enabling the rider to navigate lanes on the road without having to take their eyes off the road (Paragraph [0068] teaches tactile feedback by one or more vibratory motors). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Agnihotram with the tactile feedback of Aarts because providing feedback influences each occupant to make for a positive driving experience and safe travels (Paragraph [0008]).
As to claim 17, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises an alert generating module configured to generate notifications or alerts indicating the direction of turn of the object or rider (Paragraphs [0020] and [0028] teach an alert or early warning generation module providing necessary alerts/warnings to assist the driver when changing lanes or overtaking; Paragraph [0043] teaches providing necessary alerts/warnings/preventative steps) through audio, visual signaling including light-emitting diode indications (Paragraph [0063] teaches an I/O interface for communicating with I/O devices such as output devices including an audio speaker or video display including LEDs), and indications within a mobile application (Paragraph [0021] teaches the driver assistance device interacts with one or more external devices or with the vehicle over a communication network for sending or receiving various data, where the external devices may include a remote server, digital device, or another computing system; Paragraphs [0063]-[0064] teach a processor communicating via a transceiver and network with mobile devices; Paragraph [0066] teaches user interface application; Paragraph [0067] teaches a web browser application, messaging application, and mail viewing application). However, Agnihotram does not explicitly teach generating notifications or alerts to other individual riders through haptic feedback.
In the field of vehicle safety, Aarts teaches generating notifications or alerts to other individual riders through haptic feedback (Paragraphs [0006], [0008], [0064], and [0068] teach providing tactile feedback to the passenger). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Agnihotram with the tactile feedback of Aarts because providing feedback influences each occupant to make for a positive driving experience and safe travels (Paragraph [0008]).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Agnihotram (US PG Pub #2021/0097370) in view of Bose et al. (Bose; US PG Pub #2022/0301594) as applied to claim 1 above, and further in view of Pfau (US PG Pub #2024/0199161).
As to claim 18, depending from the system of claim 1, Agnihotram teaches wherein the drive monitoring and analyzing module comprises a drive analyzing module configured to receive information from the acceleration detection module, the gyroscope detection module (Paragraph [0018] teaches an accelerometer and gyroscope), and the image processing module (Paragraph [0019] teaches an inside camera and a face camera; Paragraph [0031] teaches data derived from cameras and analyzing data; Paragraph [0033] teaches extracting data from raw video/images) and analyze the information (Paragraph [0006] teaches receiving sensor data, then determining and analyzing events; Paragraph [0028] teaches analyzing and predicting), but does not explicitly teach calculating the rate of change of deceleration (jerk), lean angle, and rate of change of angular displacement.
In the field of rider assistance systems, Pfau teaches calculating the rate of change of deceleration (jerk), lean angle, and rate of change of angular displacement (Paragraph [0024] teaches receiving information including change rate of acceleration, change rate of angular velocity, and a degree of a bank; Paragraphs [0035]-[0036] teaches acquiring information about in a degree of banking of a leaning vehicle, a rate of change in lateral acceleration, and a rate of change in angular velocity). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Agnihotram with the data of Pfau because this helps improve rider safety (Paragraph [0004]).
Allowable Subject Matter
Claims 19-20 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter:
Claim 19 recites calculating lean angle of an object, transmitting the lean angle of the object from a driving assistance device to a drive monitoring and analyzing module, predicting lean angle of the object based on a machine learning algorithm, determining whether a difference between the calculated lean angle of the object and the predicted lean angle of the object is in a predetermined range, and generating and sending alerts to a rider and an emergency authority.
Although relevant art is disclosed below, the prior art of record does not teach, suggest, or render obvious the claimed limitation.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Baino (US PG Pub #2010/0168958) teaches determining a difference between a detected bank angle and estimated bank angle (Paragraph [0061]).
Sakamoto et al. (US PG Pub #2012/0067122) teach an estimated bank angle on the basis of speed and angular velocity (Paragraphs [0052], [0054], and [0059]) and determining a difference between the estimated bank angle and a lamp angle (Paragraph [0105]).
Azuma et al. (US PG Pub #2017/0089699) teach a difference value calculator between the inertia force and estimated bank angle (Paragraph [0051]).
Hong et al. (US PG Pub #2014/0305204) teach a bicycle leaning into the turn to maintain stability (Paragraph [0445]) and analyzing data for angular acceleration smoothness based on angular jerk (Paragraph [0449]).
Akiva et al. (US PG Pub #2015/0194035) teach a system of alerting a vehicle’s driver (Paragraph [0012]) where head movements are measured to indicate yaw, roll, pitch, and/or tilt (Paragraph [0045]).
Moffat et al. (US PG Pub #2020/0367789) teach a movement sensor includes a gyroscope, accelerometer, and magnetometer (Paragraph [0170]) and analyzing pitch, roll, and yaw of a user’s head (Paragraph [0143]) using machine learning techniques (Paragraphs [0065] and [0125]).
Ren et al. (US PG Pub #2023/0065399) teach a vehicle with inertia measurement unit sensors including accelerometers, magnetometers, and gyroscopes (Paragraph [0244]) and determines a head pose, such as roll, pitch, and yaw (Paragraph [0044]).
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RYAN W SHERWIN whose telephone number is (571)270-7269. The examiner can normally be reached M-F, 7:00-8:00, 9:00-3:00 and 4:00-5:00 EST.
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/RYAN W SHERWIN/ Primary Examiner, Art Unit 2688