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 .
Response to Amendment
The following is a non-final office action in response to the request for continued examination filed on 01/14/2026 of the claims filed on 12/23/2025. Claims 1 and 5 have been amended. Claims 3 and 7 have been cancelled. Claims 1, 4-5 and 8-9 are currently pending and have been examined.
Response to Arguments
Applicant’s arguments and remarks filed on 12/23/2025 have been fully considered.
Applicant’s arguments provided for the U.S.C. §103 rejections of claims 1, 3-5 and 7-9 have been considered but are not persuasive.
(A) Applicant argues, “Claims 1, 3-5 and 7-9 were rejected under 35 U.S.C. §103 as being obvious over Zeng et al. (US 2021/0409067 Al) in view of Guntur et al. (US 2023/0292047 Al) and Jain et al. (US 2020/0348406 Al).
“Specifically, Zeng, Guntur, and Jain do not teach or suggest the following:
an electronic control unit configured to control one or more vehicle
functions based on the determined occupancy of the vehicle seat, wherein the
one or more vehicle functions include:
a safety belt warning system of the vehicle seat
a controller of an airbag assigned to the vehicle seat
an airbag warning system assigned to the vehicle seat
a ventilation and/or climate control system assigned to the vehicle seat
a seat heater assigned to the vehicle seat
an entertainment system assigned to the vehicle seat and
a child safety lock assigned to the vehicle seat of a corresponding
vehicle door or a corresponding vehicle window.
“Specifically, Zeng, Guntur and Jain do not teach or suggest that the vehicle functions controlled by the ECU include "an entertainment system assigned to the vehicle seat" and "a child safety lock assigned to the vehicle seat of a corresponding vehicle door or a corresponding vehicle window" in addition to the other functions recited.
“In contrast to these specific limitations of the claim, Zeng merely discloses "vehicles may detect occupancy in front seats to provide seat belt reminders. Such a system can also provide additional features such as airbag control and enhanced user experience with regards to climate and audio controls. Vehicle occupancy information is also a component for effective shared autonomy, such as human sensing, shared perception-control, and deep personalization, for human-centered autonomous vehicle systems." [0002].
“Guntur simply discloses ‘automobiles include electronic systems that may provide both entertainment such as music and information such as navigational assistance.’ [0002].
“Jain merely discloses ‘The system and method may also detect a difference between an inanimate object and a user, or between an adult and a child.’ [0005].
“Thus, the disclosures of the cited references do not correspond to the specific limitations of amended claim 1. Therefore, amended claim 1 is patentable over the cited references.
“Amended claim 5 is patentable for reasons analogous to those for claim 1,” (from remarks pages 6-7).
As to point (A), Examiner respectfully disagrees. Applicant asserts that Zeng, Guntur and Jain do not teach every vehicle function in the list of vehicle functions included in amended claims 1 and 5. However, a careful reading of the claim shows that the amended claims require only one of the listed functions (see amended claim 1, line 20: “an electronic control unit configured to control one or more vehicle functions…”). Examiner has consulted with SPE Vladimir Magloire to confirm this claim interpretation. Therefore, the previously-cited prior art is sufficient to reject amended claim 1. Purely as an aid to the applicant, Examiner at the end of the claim 1 rejection below cites additional art relevant to other items on the list.
(B) Applicant argues, “Claims 4, 8 and 9 are patentable due to their incorporation of the limitations of claims 1 and 5, respectively,” (from remarks page 7).
As to point (B), see point (A).
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 nonobviousness.
Claims 1, 4-5 and 8-9 are rejected under 35 U.S.C. 103 as being unpatentable over Zeng et al. (US-20210409067-A1; hereinafter, Zeng) in view of Guntur et al. (US-20230292047-A1; hereinafter, Guntur) and Jain et al. (US-20200348406-A1; hereinafter, Jain).
Regarding claim 1, Zeng discloses [Note: what Zeng fails to disclose is strike-through]
A device for exact seat occupancy identification (see at least [0021]; “perform per-seat occupancy classification”) in a vehicle (see at least [0021]; system operates in a vehicle cabin), comprising:
an ultra-wideband (UWB) (see at least [0039]; “In an example, one of the UWB transceiver nodes 102 may operate as the transmitter and the remaining nodes UWB transceiver node 102 may operate as receivers. Continuing with the example UWB transceiver node 102 layout of FIG. 1, one of the UWB transceiver node 102 may be a transmitter while the other seven UWB transceiver nodes 102 may be receivers.”), wherein
the transmitter is configured to emit a plurality of (see at least [0024]; “The transmit signal of an UWB transceiver node 102 operating as a transmitter is a sequence of pre-defined symbols in the IEEE 802.15.4 format. These UWB data packets are sometimes referred to as ‘blinks.’”) in a direction of a vehicle seat of the vehicle (see at least Fig. 1, transceiver nodes 102 located in proximity to the seats; see also [0052]; “For example, when a person is sitting in the driver seat, the presence of the person introduces multi-path signal reflections for the UWB transceiver nodes 102 near the driver seat.”), and
the at least two receivers are configured to receive the (see at least [0031]; “Since CIRs are impacted by multi-path signal reflections from objects and humans in the vehicle, CIR variations in heatmaps and average and standard variation can be used for vehicle occupancy sensing. Thus, as vehicle occupancy monitoring is useful in support of regulatory requirements and for providing a customized user experience, the keyless infrastructure supported by the UWB transceiver nodes 102 may be additionally utilized in an orthogonal sensing modality to detect vehicle occupancy.”);
a computer (see at least Fig. 14, computing device 1400) configured to:
generate Channel Impulse Responses (CIRs) from the received, reflected (see at least [0024]; “These signals may travel through multiple paths and arrive at a UWB transceiver node 102 operating as a receiver with different amplitude attenuation and time of flight. The received signal may be compared with the known sequence of transmit symbols to compute the CIR as follows…”),
process the generated CIRs using a machine learning algorithm (see at least [0030]; “In addition to amplitude and standard deviation, different features, such as peaks/valleys, distances between peaks/valleys, number of peaks/valleys, etc., can be calculated and also fed to machine learning algorithms for different sensing purposes.”),
carry out an (see at least [0035]; “Using CIR data as input, the system 100 may use a deep learning model, having a multiple-input-multiple-output (MIMO) model with a multi-task mask (e.g., a Mask MIMO), to learn spatial/time features by 2D convolutions and per-seat attentions by the multi-task mask.”);
determine an occupancy of the vehicle seat from the processed generated CIRs and the performed (see at least [0053]; “Having completed the CIR processing for converting the raw signals from the UWB transceiver nodes 102 into normalized CIR tensors, the machine learning classification model 608 uses the normalized CIR tensors to predict per-seat occupancy from the normalized CIR tensors.”); and
in the processing of the CIRs, perform a classification of a person determined in the determination of the occupancy of the vehicle seat with respect to an age or age group of the person and a health status of the person; and
an electronic control unit (see at least [0077]; “The processes, methods, or algorithms disclosed herein can be deliverable to/implemented by a processing device, controller, or computer, which can include any existing programmable electronic control unit or dedicated electronic control unit.”) configured to control one or more vehicle functions based on the determined occupancy of the vehicle seat, wherein the one or more vehicle functions include:
a safety belt warning system of the vehicle seat (see at least [0002]; “At the base level, vehicles may detect occupancy in front seats to provide seat belt reminders. Such a system can also provide additional features such as airbag control and enhanced user experience with regards to climate and audio controls. Vehicle occupancy information is also a component for effective shared autonomy, such as human sensing, shared perception-control, and deep personalization, for human-centered autonomous vehicle systems.”);
a controller of an airbag assigned to the vehicle seat;
an airbag warning system assigned to the vehicle seat;
a ventilation and/or climate control system assigned to the vehicle seat;
a seat heater assigned to the vehicle seat;
an entertainment system assigned to the vehicle seat; and
a child safety lock assigned to the vehicle seat of a corresponding vehicle door and/or a corresponding vehicle window.
However, Zeng does not explicitly teach that the UWB transceivers perform UWB radar, that the transmitted symbols comprise preamble symbols, or that the calculation of spatial features employs an angle-of-arrival calculation. Zheng furthermore does not explicitly teach:
in the processing of the CIRs, perform a classification of a person determined in the determination of the occupancy of the vehicle seat with respect to an age or age group of the person and a health status of the person.
Zeng discloses occupancy sensing using UWB keyless infrastructure, and Guntur is directed to determining spatial orientation of objects such as seats in a vehicle through returns from pulsed UWB signals for the purposes of tuning the sound of an audio system. Guntur teaches:
an ultra-wideband (UWB) radar (see at least [0021]; “The UWB device can be configured to operate in a radar mode in which it transmits pulsed probe signals and receives the reflected return signals.”) comprising a transmitter and at least two receivers (see at least [0024]; “In one or more embodiments, a UWB sensing device can be equipped with multiple antennas and/or transmitters and receivers in a multi-static radar configuration.”), wherein
the transmitter is configured to emit a plurality of preamble symbols (see at least [0037]; “signal processing circuitry of both the initiator device and the responder device can estimate the channel impulse response by correlating a predefined part of a received frame preamble (a training sequence) with the expected training sequence…”) in a direction of a vehicle seat of the vehicle (see at least [0027]; “The UWB circuitry 150 may be used to transmit pulsed probe signals 190 and to receive return signals that scatter off (or otherwise originate from) objects such as the seats 102, or windows 101 of the vehicle 100. One return signal 192 is shown schematically in FIG. 1 originating from the seatback 103 of one of the seats 102 of the vehicle 100 and propagating along a straight line path to the UWB circuitry 150.”), and
the receivers are configured to receive the preamble symbols reflected by the vehicle seat (see at least [0023]; “One UWB device can be used for sensing the seating configuration and one or more other UWB devices can be configured to communicate with the reference sensing device. ToF and AoA can be measured between pairs of devices to determine locations and orientations of the seats… The process can be repeated with other seats or can be jointly estimated with single or multiple ranging cycles.”); and
a computer configured to:
generate Channel Impulse Responses (CIRs) from the received, reflected preamble symbols (see at least [0037]; “signal processing circuitry of both the initiator device and the responder device can estimate the channel impulse response by correlating a predefined part of a received frame preamble (a training sequence) with the expected training sequence resulting in correlation peaks at different time lags corresponding to the different multipath signal components.”,
carry out an angle-of-arrival calculation based on the reflected preamble symbols (see at least [0037]; “For AoA computation multiple antennas and receivers can be used to compute the direction of arrival from which seat orientations are calculated or otherwise determined.”).
Zeng uses UWB transceivers to transmit a sequence of symbols into a vehicle interior, generate channel impulse responses, and determine seat-specific occupancy using machine learning. Guntur similarly uses UWB transceivers to transmit a sequence of symbols (including preamble symbols) into a vehicle interior, generate channel impulse responses, and use time of flight and angle of arrival to calculate positions. Due to the significant similarities in the techniques, it would have been obvious to one of ordinary skill in the art at the time of the claimed invention to incorporate into the invention of Zeng correlations using preamble symbols and angle of arrival calculations, as taught by Guntur. One of ordinary skill would be motivated to use these techniques in order to sense the interior layout of a vehicle, as taught by Guntur (see at least [0045]; “…because the seats in a vehicle (e.g., the seats 102 in the vehicle 100) are located at certain angles with respect to the reference device (e.g. 150 in FIG. 1), the value of the AoA estimate can be used to identify the seat (e.g. to distinguish a driver seat from a front passenger seat).”).
However, neither Zheng nor Guntur explicitly teach:
in the processing of the CIRs, perform a classification of a person determined in the determination of the occupancy of the vehicle seat with respect to an age or age group of the person and a health status of the person.
Zeng discloses occupancy sensing using UWB keyless infrastructure, and Jain is directed to a UWB sensing system. Jain teaches:
in the processing of the CIRs (see at least [0063]; “Signal processing may be programmed with various algorithms for determining breathing rate and heart rate based on the CIR data received.”), perform a classification of a person determined in the determination of the occupancy of the vehicle seat with respect to an age or age group of the person and a health status of the person (see at least [0062]; “System 100 may also be operable to monitor vital signs of users within the vehicle 102. For instance, system 100 may be able to determine breathing and heart rate of the passengers because nodes 110-136 may operate at a higher timing resolution (e.g., 200 picoseconds)… Using any number of vital sign parameters, system 100 may be able to detect medical emergency situations… It is also contemplated that nodes 110-136 may operate at an even higher timing resolution (e.g., 100 picoseconds) such that system 100 may be able to differentiate between an adult and child present within the vehicle. System 100 may be operable to make this distinction due to the differences between the breathing rate, heart rate, and movement between adults and children.”).
Both Zeng and Jain process the channel impulse response of UWB transceiver measurements to determine the position of vehicle occupants. Zeng discloses detecting movement from occupant breathing (see at least [0052]; “The multi-path profiles of nearby UWB transceiver nodes 102 also change over time due to human activities such as gestures and breathing.”), and Jain discloses tracking the vital signs (see [0063]) of occupants. 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 system of Zeng to include tracking of occupant vital signs as taught by Jain. Such a modification would have a reasonable expectation of success because the system of Zeng is taught to be able to detect breathing movements. One of ordinary skill would be motivated to include tracking of vital signs in order to detect emergency medical situations, as recognized by Jain (see Jain at least [0063]).
Although not required for the claim rejection, Examiner furnishes the additional citations and references below relevant to the list of vehicle functions controlled by the electronic control unit as recited in claim 1:
Zeng teaches controlling a controller of an airbag assigned to the vehicle seat based on detected seat occupancy (see at least [0002], quoted above).
Kamizono (US-20060164254-A1) teaches controlling an airbag warning system based on detected seat occupancy (see at least [0079]; “Thus, for example, when the occupant and CRS absent state of the passenger seat is detected, an air bag OFF lamp, which is lit to indicate the air bag deployment disabled state, may be turned off. In this way, the annoyance, which is caused by the lighting of the unnecessary warning lamp, can be reduced.”).
Zeng teaches controlling a ventilation and/or climate control system assigned to the vehicle seat based on detected seat occupancy (see at least [0002], quoted above).
Terashima (US-20220314917-A1) teaches controlling a seat heater assigned to the vehicle seat based on detected seat occupancy (see at least [0115]; “Occupied seat detection device 10 is capable of outputting the calculated seat occupancy signal to, for example, an electronic control unit (ECU) that controls vehicle 30. This enables the ECU that controls vehicle 30 to, for example, prevent an unrequired expansion of the air-bag in an unoccupied seat. Also, the ECU that controls vehicle 30 is capable, for example, of turning off the seat heater of an unoccupied seat to reduce battery consumption.”).
Jain teaches controlling an entertainment system based on detected seat occupancy (see at least [0059]; “System 100 may also be operable to detect (1) user occupancy within vehicle 102; and (2) location of users within vehicle 102. Upon detecting user occupancy within vehicle 102, system 100 may activate additional vehicle systems (e.g., HVAC or infotainment system, front passenger airbag systems) to provide better user experience and safety.”).
Raj (US-20220317246-A1) teaches controlling a child safety lock assigned to the vehicle seat of a corresponding vehicle door or a corresponding vehicle window based on detected seat occupancy (see at least [0077]; “The radar-based system 100 as presented in the example is targeted for the child/pet left behind detection application, however, the intermediate output can be used to determine the following features for an in-cabin vehicle use case like life presence detection, seat occupancy detection or occupancy detection, adult vs infant/child detection, passenger classification system, seat belt reminder, airbag deployment system, airbag suppression, airbag low-risk deployment system, auto child lock, vital signs detection, and intrusion detection.”).
Regarding claim 4, Zeng in view of Guntur and Jain teaches the device according to claim 1. Zeng further teaches:
A vehicle (see at least Fig. 1, vehicle 100) comprising a device according to claim 1.
The method of claim 5 is analogous to the functions of the device of claim 1 and is rejected for similar reasons.
Regarding claim 8, Zeng in view of Guntur and Jain teaches the method of claim 5. Zeng further teaches:
A non-transitory computer-readable medium comprising instructions operable, when executed by one or more computing systems, to carry out the method (see at least [0077]; “The processes, methods, or algorithms disclosed herein can be deliverable to/implemented by a processing device, controller, or computer, which can include any existing programmable electronic control unit or dedicated electronic control unit. Similarly, the processes, methods, or algorithms can be stored as data and instructions executable by a controller or computer in many forms including, but not limited to, information permanently stored on non-writable storage media such as ROM devices and information alterably stored on writeable storage media such as floppy disks, magnetic tapes, CDs, RAM devices, and other magnetic and optical media.”) of claim 5.
Regarding claim 9, Zeng in view of Guntur and Jain teaches the method of claim 5. Zeng further teaches:
An electronic device, comprising:
a processor; and
a memory in communication with the processor and storing instructions executable by the processor to configure the electronic device to perform the method (see at least [0077]; “The processes, methods, or algorithms disclosed herein can be deliverable to/implemented by a processing device, controller, or computer, which can include any existing programmable electronic control unit or dedicated electronic control unit. Similarly, the processes, methods, or algorithms can be stored as data and instructions executable by a controller or computer in many forms including, but not limited to, information permanently stored on non-writable storage media such as ROM devices and information alterably stored on writeable storage media such as floppy disks, magnetic tapes, CDs, RAM devices, and other magnetic and optical media.”) according to claim 5.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ashley B. Raynal whose telephone number is (703)756-4546. The examiner can normally be reached Monday - Friday, 8 AM - 4 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vladimir Magloire can be reached at (571) 270-5144. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ASHLEY BROWN RAYNAL/Examiner, Art Unit 3648
/VLADIMIR MAGLOIRE/Supervisory Patent Examiner, Art Unit 3648