DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 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.
Claims 1, 3, 5-8, 10, 11, 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over Horstman [US 4,742,761] in view of Seidman [US 6,416,479] and Tomimatsu et al [US 2023/0226556]
Claim 1. A method of controlling a non-homogeneous cohort of ozone gas generating
devices (the non-homogeneous distribution of carbon dioxide CO2 in the seating area
12, see Fig. 1, col. 4, lines 49-51), the method comprising:
identifying, at a computing device, a non-homogeneous cohort of ozone gas generating devices (read upon the microprocessor automatically controls the non-homogeneous CO2 in a space, see Figs. 1, 3, col. 2, lines 44-54, col. 6, lines 38-68), that including at least a ceiling-mounted, an in-duct mounted (the ceiling mounted sensors 40 and 41 and any such sensors, see Fig. 1, col. 4, lines 63-68); and
continuously detecting, via at least one remote ozone gas sensor device located in a
spatial area associated with the non-homogeneous cohort, in conjunction with one or
more processors of the computing device (the microprocessor controls remote sensors
41 and 42 and any such sensors detect CO2 gas within an aircraft cabin 11, see Figs.
1, 3, col. 4, lines 46-68, col. 6, lines 38-51),
a concentration of ozone gas constituent within ozonated air of the spatial area (the
concentration of CO2 in the space, see col. 2, lines 18-27); and
causing, by the one or more processors responsive to continuously detecting the
concentration of the ozone gas constituent as being one of above and below a
predetermined threshold concentration (the microprocessor controls or instructs to
detect CO2 level is higher than or does not exceed the desired limit, Fig. 3, col. 6, lines
38-54). But
Horstman fails to disclose a portable ozone gas generating devices. However,
Horstman discloses the non-homogeneous distribution of carbon dioxide CO2 in the
seating area 12, and ceiling mounted sensors 40, 41 and any such sensors positioned
within cabin 11 (see Fig. 1, col. 4, lines 49-51).
Seidman suggests that the End-tidal carbon monoxide ("ETCO") concentrations,
sometimes referred to as alveolar concentrations, can be measured in a variety of ways.
For example, a breath sample is continuously drawn from the patient's breath stream
and directed to a fast-responding carbon dioxide (CO.sub.2) sensor and a slower
responding CO sensor. The signals from the CO.sub.2 sensor, the CO sensor and a
measurement of inhaled CO concentration are used to calculate the end-tidal CO
concentration (see col. 4, lines 17-27).
The ETCO concentration measurements were obtained using a portable automated CO analyzer (see col. 7, lines 17-18).
Therefore, it would have been obvious to one skill in the art before the effective filing
date of the invention to use or substitute the portable automated CO measurement and
analyzer of Seidman for the CO2 sensors or any such sensors of Horstman for
providing convenience and flexibility of using a portable CO/CO2 gas sensor to a
particular situation or a special person to be monitored of CO/CO2 concentration levels
in any environments.
Horstman fails to disclose at least one of the at least a ceiling-mounted, an in-duct mounted and a portable ozone gas generating devices to perform one of increasing and decreasing a rate of ozone gas generation associated therewith in accordance with switching from a first mode to a second mode of ozone gas generation, the second mode of ozone gas generation being associated with one of a higher and a lower rate of generation of ozone gas than the first mode. However,
Horstman teaches that the control and method for maintaining the concentration of carbon dioxide in the cabin (11) comprising ceiling mounting and suppling duct 16 and exhaust ducts, 24, 25, 31, 32, see Fig. 1, col. 3, lines 27-68, col. 4, lines 1-9).
Once the cabin pressure is within the predetermined limits, program logic ascertains if the concentration of carbon dioxide is within predetermined upper and lower limits, in blocks 107 and 109. If the CO.sub.2 level is too high, the control causes air pack 37 to increase the flow of pressurized fresh air into the cabin, in block 108, or conversely, if the CO.sub.2 level is too low, to decrease the flow of pressurized fresh air into the cabin, in block 110. Following either action, the control recycles to start, as it also does if the level of carbon dioxide concentration is within limits, in block 111, see Figs. 3, 4, col. 6, lines 38-60, col. 7, lines 39-49).
Tomimatsu et al suggests that when a switch to the second mode is performed in a time slot when no one stays in the space 50 or in a state where no one is allowed to enter the space 50, the outside air intake at the AHU 3 may be stopped and the ratio of the amount of recirculation air to the total intake air amount of the AHU 3 may be caused to reach 100% (see the AHU intake amount in FIG. 12) so that the ozone concentration is efficiently increased. When the outside air intake at the AHU 3 is stopped after a switch to the second mode, the amount of recirculation air may be reduced more than the amount of recirculation air in the first mode (see the broken line portion of the AHU intake amount in FIG. 12). As a result, the ozone concentration of the air supplied from the AHU 3 to the space 50 can be increased (see Fig. 12, para [0112]).
In the case of returning from a state where the ozone concentration in the space 50 is high to a state where the ozone concentration is low and satisfies the environmental standard value, a switch is performed from the second mode of high concentration to the first mode of low concentration. At this time, the return can be expedited by temporarily increasing the amount of outside air taken into the AHU 3 as compared with the normal operation. At this time, the operation of the electrical precipitator unit 10 may be stopped in order to efficiently reduce the ozone concentration. As a result, the ozone removal unit 14 acts only to remove the ozone in the space. In a case where the ozone removal unit 14 is of high removal capacity, the operation of the electrical precipitator unit 10 does not necessarily have to be stopped (see para [0116, 0176, 0181]).
Therefore, it would have been obvious to one skill in the art before the effective filing date of the invention to modify or implement the switching to second mode for higher and lower concentration than the first mode of Tomimatsu et al to the control program logic of Horstman and Seidman for improving of air regulation and purification with deodorized and sterilized to provide a greater heath environmental conditions and safety to people in a building, cabin, house or facility.
Claim 3. The method of claim 1 wherein the at least one ceiling mounted ozone gas
generating device comprises an optical lamp module including a plurality of optical
lamps (the IR light, see col. 5, lines 19-26), and a fan apparatus arranged for forcibly
dispersing ozonated air in a downward direction relative to a ceiling portion of an at
least partially enclosed building wherein the ceiling mounted ozone gas generating
device is housed (the fans 27 for forcing the pressurized fresh air into the cabin 11
when the CO2 level is too high, see Figs. 1, 3, col. 6, lines 50-57, col. 7, lines 42-44).
Claim 5. The method of claim 3 wherein the optical lamp module is disposed at one of
upstream and downstream of the fan apparatus (as cited in respect to claims 1 and 3
above, wherein the system controls the exhaust air and return air passing through a
carbon dioxide sensor 40 and/or air vented overboard, see Figs. 1-3, col. 3, lines 39-67,
col. 4, lines 1-39, col. 6, lines 38-60).
Claim 6. The method of claim 5 wherein, in the upstream disposition, the optical lamp
module is at least partially obscured by the fan apparatus from a view relative to an
observer distally situated below the ceiling portion (as cited in respect to claims 1, 3 and
5 above, such as the IR light, see Fig. 1, col. 5, lines 19-26).
Claim 7. The method of claim 1 wherein the in-duct mounted ozone generating device
comprises an optical lamp module including a plurality of optical lamps and a fan
apparatus arranged for forcibly dispersing ozonated air along at least a portion of an air
supply duct that houses the in-duct mounted ozone generating device (as cited in
respect to claim 1 above, and including the air pack 37, see Fig. 1, col. 4, lines 1-15).
Claim 8. The method of claim 1 wherein the in-duct mounted ozone generating device
comprises an optical lamp module including a plurality of optical lamps and a fluid flow
sensor device that detects passage of air along the duct (as cited in respect to claim 1
above, and including the fluid communication, see Fig. 1, col. 4, lines 6-9).
Claim 10. The method of claim 1 wherein the at least one remote ozone gas sensor
device comprises a plurality of remote ozone gas sensor devices located within the
spatial area associated with the non-homogeneous cohort (as cited in respect to claim 1
above). But
Horstman fails to disclose the spatial area including an at least partially enclosed
building. However, Horstman teaches that the control and method for maintaining the
concentration of carbon dioxide in the cabin 11 of an aircraft at a desired level. A carbon
dioxide sensor 40, 41 is disposed to monitor the concentration of carbon dioxide CO2 in
the cabin of the aircraft (see Fig. 1, abstract).
Seidman suggests that the method for early detection of pathological conditions in
pregnancy by measuring breath CO or ETCOc and can be applied in a hospital, clinic,
or physician's office (see col. 5, lines 6-9).
Therefore, it would have been obvious to one skill in the art before the effective filing
date of the invention to applying or using the controlling of CO2 inside the enclosed
cabin of an aircraft of Horstman to the controlling of CO in a hospital building, clinic
building or physician office of Seidman as a design choice to expanding applications
and uses of the monitoring and controlling of carbon and/or gaseous within an
enclosure, building, house, office, premises, school campus and/or warehouse without
changing the results to save a life.
Claim 11. The method of claim 10 wherein the spatial area associated with the non-
homogeneous cohort includes multiple buildings within a campus infrastructure that
includes the at least partially enclosed building (as discussed in respect to claims 1 and
10 above).
Claim 16. The method of claim 1 wherein the at least one ozone gas generating device
of the non-homogeneous cohort performs ozone gas generation in accordance with
applying ultraviolet (UV) irradiation provided in a wavelength of 185 nanometer (nm) to
at least a portion of the gaseous oxygen constituted in an incoming stream of air to
produce ozonated air, the ozonated air having a higher concentration of ozone gas than
the incoming stream of air.
Claim 17. A computing device comprising: a processor (the microprocessor, see col. 6,
lines 15-60); and a non-transitory memory including instructions, the instructions when
executed by the processor causing the processor to perform operations (read upon the
programmed microprocessor and memory ROM, see Figs. 2-4, col. 6, lines 15-60, col.
7, lines 13-30), comprising: identifying a non-homogenous cohort of ozone gas generating devices that include at least a ceiling-mounted, an in-duct mounted and a portable ozone gas generating devices; continuously detecting, via at least one remote ozone gas sensor device located in a spatial area associated with the non- homogeneous cohort, in conjunction with one or more processors of the computing device, a concentration of ozone gas constituent within ozonated air of the spatial area; and causing, by the one or more processors responsive to continuously detecting the concentration of the ozone gas constituent as being one of above and below a predetermined threshold concentration, at least one of the at least a ceiling-mounted, an in-duct mounted and a portable ozone gas generation device to perform one of increasing and decreasing a rate of ozone gas generation associated therewith
therewith in accordance with switching from a first mode to a second mode of ozone gas generation, the second mode of ozone gas generation being associated with one of a higher and a lower rate of generation of ozone gas than the first mode (as the combination between Horstman and Seidam and Tomimatsu et al in respect to claim 1 above).
Claim 18. A non-transitory computer-readable memory storing instructions, the
instructions being executable in one or more processor devices to cause the one or
more processor to perform operations comprising: identifying, at a computing device, a
a non-homogeneous cohort of ozone gas generating devices that include at least a ceiling-mounted, an in-duct mounted and a portable ozone gas generating devices; continuously detecting, via at least one remote ozone gas sensor device located in a spatial area associated with the non-homogeneous cohort, in conjunction with one or more processors of the computing device, a concentration of ozone gas constituent within ozonated air of the spatial area; and instructing, by the one or more processors responsive to continuously detecting the concentration of the ozone gas constituent as being one of above and below a predetermined threshold concentration, at least one ozone gas generating device of the non-homogeneous cohort to perform one of increasing and decreasing a rate of ozone gas generation associated therewith in accordance with switching from a first mode to a second mode of ozone gas generation, the second mode of ozone gas generation being associated with one of a higher and a lower rate of generation of ozone gas than the first mode (as the combination between Horstman and Seidam and Tomimatsu et al in respect to claims 1 and 17 above).
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Horstman
[US 4,742,761] and Seidman [US 6,416,479] and Tomimatsu et al [US 2023/0226556] and further in view of Cooner [US 2020/0027096]
Claim 2. Horstman fails to disclose wherein the non-homogeneous cohort of ozone
gas generating devices are communicatively coupled to the computing device within a
cloud communication network. However,
Horstman teaches that the non-homogeneous distribution of carbon dioxide CO2 in the seating area 12, and ceiling mounted sensors 40, 41 and any such sensors positioned within cabin 11 (see Fig. 1, col. 4, lines 49-51).
Cooner suggests that the "Edge" is the "Internet of Things" (loT for short) front-line of
where technology intersects with business and people, capturing raw data used by the
rest of the loT system. Data is captured by embedding sensors in consumer devices
(i.e. fitness trackers, thermostats) appliances or industrial systems (i.e. heating &
cooling systems, factory automation) or more specialized applications such as remotely
monitoring food temperature and humidity. Such devices can be referred to in this
discussion as "Sensor Devices". Data can then be passed to a "Router" and/or
"Gateway" or other "Aggregation Points" that can provide some basic data analytics
(parsing raw data) before being sent to the loT Platform via an Internet connection and
beyond. "Routers" can be thought of as local grid or mesh networks whereby
implementations such as Bluetooth, Zigbee, WiFi, ANT, OpenWare, LoRa, Sigfox, or
other short to mid-range wireless transmissions are used to communicate between
Sensor Devices and Gateways. Gateways can be thought of as Internet-enabled
hardware devices (usually through a wireless WiFi, cellular based such as GSM,
CDMA, or other mobile phone carrier network, or landline connection) that communicate
either directly to sensors, to sensors through Routers, or a hybrid of both Routers and
sensors directly to allow for data to be passed bi-directionally to an Internet platform
such as a cloud computing environment or computer network. Also, loT is not just about
capturing data but can also alter the operation of a device with an actuator or other
configurable components (see Figs. 1, 2, para [0320]).
The loT sensor market is divided into two broad categories. Original Device
Manufacturers (ODMs) and Original Equipment Manufacturers (OEMs). ODMs design
manufacture the core sensor technology (pressure, temperature, accelerometers, light,
chemical, etc.) with over 100,000 types of sensors currently available for loT solutions.
These sensors typically do not include any of the communication or intelligence
capabilities needed for loT solutions so OEMs embed ODM sensors into their loT
devices while adding the communications, analytics and other potential capabilities
needed for their specified markets. For example, an OEM who builds
a Building Automation loT application may include various sensor types such as light
(IR or visual), temperature, chemical (CO2) (see Figs. 1, 2, para -0341]).
Therefore, it would have been obvious to one skill in the art before the effective filing
date of the invention to add or implement the Internet platform such as a cloud
computer network for communicating data information of the LoT sensors and CO
sensor of Cooner to the non-homogeneous distribution of carbon dioxide CO2 and any
such sensors of Horstman and Seidman and Tomimatsu et al for eliminating of communication cables/wires and to providing a faster data transmissions therebetween.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Horstman
[US 4,742,761] and Seidman [US 6,416,479] and Tomimatsu et al [US 2023/0226556] and further in view of Forbis et al [US 2017/0257925]
Claim 4. Horstman fails to disclose wherein the ceiling portion of the at least partially
enclosed building comprises a ceiling tile of a predetermined size, and the at least one
ceiling mounted ozone gas generating device further comprises a mounted
configuration that is generally coincident with a footprint of the ceiling tile. However,
Horstman teaches that the non-homogeneous distribution of carbon dioxide CO2 in the
seating area 12, and ceiling mounted sensors 40, 41 and any such sensors positioned
within cabin 11 (see Fig. 1, col. 4, lines 49-51).
Forbis et al suggests that the artificial lighting system 100 or a light engine 2004 may
be configured in a form factor adapted to fit into the space of a standard ceiling tile and
to create the appearance of a skylight. A configuration may be a two-foot-by-two-foot
configuration, a two-foot-by-four-foot configuration, a four-foot-by-four-foot configuration
and the like. The form factor may be a standard configurable form factor. A standard
configurable form factor may be a skylight feature form factor or a design form factor. A
standard configurable form factor may be sized. A standard configurable form factor
may be sized for ceiling tile replacement, sized for standard window replacement and
sized to match standard features (see Figs. 5-8, 13, 18, para [0245, 0266]). When
the space is replaced with another medium that is non-homogenous, like the
atmosphere, it may be absorbed by atmospheric gases or altered by spatial variations in
refractive index (see Fig. 34, para [0316]).
Therefore, it would have been obvious to one skill in the art before the effective filing
date of the invention to use or implement the non-homogenous artificial lighting system
fixed to a standard ceiling tile of Forbis et al to the non-homogenous gas sensors
mounted into the ceiling of Horstman and Seidman and Tomimatsu et al for easily installation and reducing cost by the ceiling tiles.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Horstman
[US 4,742,761] and Seidman [US 6,416,479] and Tomimatsu et al [US 2023/0226556] and further in view of Wang et al [US 2017/0261357]
Claim 9. Horstman fails to disclose wherein the optical lamp module including the plurality of optical lamps is operationally switched on for generation of ozonated air
responsive to detecting passage of air along the duct that exceeds a predetermined flow
rate. However,
Horstman teaches that the microprocessor control checks to determine if cabin pressure is below a desired setting. If the pressure is too low, the microprocessor causes the air pack to increase its flow of pressurized fresh air into cabin 11, as indicated in block 62. Thereafter (or if the cabin pressure is not too low), in block 63, the microprocessor control checks to determine if cabin pressure exceeds an upper limit. If the cabin pressure is too high, in block 64, the control causes air pack 37 to decrease the flow of pressurized fresh air into mixing manifold 23. In block 65, the control determines if the carbon dioxide level sensed by sensor 40 (41) is higher than a desirable limit. If the carbon dioxide level does exceed the desired limit, in block 66, the control checks to determine if the cabin pressure is less than a minimum set point. If the pressure is less than the set point, in block 69, the control decreases the flow of air vented overboard by causing three-way valve 29 to recirculate back into cabin 11 more of the air drawn out through exhaust ducts 24 and 25. Otherwise, in block 67, three-way valve 29 is caused to increase the amount of air vented overboard (see Figs. 1, 3, col. 6, lines 38-60).
Wang et al suggests that for a vertical gas-oil-water three-phase (water-continuous)
flow, an EIT technique with dual-plane sensors is used to extract local volume fraction
distribution, local flow velocity and flow rate of the dispersed phases, e.g. gas and oil,
see para [0182]). By observing the trend of measured oil flow rates, it can be seen that
the level of deviation is more pronounced than that of the measured water flow rates
and that of the measured gas flow rates; the deviation grows more with the increase of
oil flow rate. On the other hand, the comparison results of gas flow rate between the
measured and reference values suggest that higher deviation in the oil flow rate is
associated with higher gas flow rates (see Fig. 19, 19c, para [0188]).
Therefore, it would have been obvious to one skill in the art before the effective filing
date of the invention to use or implement the EIT technique with dual-plane sensors is
used to extract local volume fraction distribution, local flow velocity and flow rate of the
dispersed phases, e.g. gas and oil of Wang et al to the microprocessor controls to
increasing/decreasing of air flow overboard of Horstman and Seidman and Tomimatsu et al for maintaining the CO1 gas levels and air pressure levels within a safety desired level as well as to prevent of dangerous situations to people inside a cabin, building and/ or office.
Claims 12-16 are rejected under 35 U.S.C. 103 as being unpatentable over
Horstman [US 4,742,761] and Seidman [US 6,416,479] and Tomimatsu et al [US 2023/0226556] and further in view of Borshch et al [US 2019/0103182]
Claim 12. Horstman fails to disclose continuously detecting the concentration of ozone
gas constituent of ozonated air at least partly using a trained machine learning model in
conjunction with the plurality of remote ozone gas sensor devices. However,
Horstman teaches that the apparatus includes means for sensing the non-homogenous
distribution of carbon dioxide and producing a signal indicative of the concentration
thereof in the enclosed space. The programmed microprocessor operates to automatically maintain the enclosed space at a desired air pressure while at the same time maintaining the concentration of carbon dioxide in the space at an acceptable level. The present invention accomplishes this object by venting only air that is relatively higher in carbon dioxide, while recirculating air that is lower in carbon dioxide concentration. Thus, the environmental quality of the air in the enclosed space is maintained at a desirable level, but only the minimum air necessary to accomplish this object is vented from the space (see Figs. 1-4, col. 2, lines 18-20, 44-54, col. 6, lines 15-37).
Borshch et al suggests that at each environment, any or all environmental
characteristic information may be sensed by device 100 from any or all features of the
environment, e.g., directly via sensor assembly 114 of device 100 and/or via any
suitable auxiliary environment subsystem(s) 200 of the environment (see Fig. 1).
As another example, as shown, at environment E1 during time T1, vehicle(s) V may
provide one or more types of vehicle effects VE that may be sensed by sensor
assembly 114 of device 100 for determining one or more environmental characteristics
of environment E1 during time T1, including, but not limited to, a noise environmental
characteristic of environment E1 that may be at least partially detected from a sensed
noise vehicle effect VE generated by vehicle(s) V, a harmful gas level environmental
characteristic of environment E1, such as in an office, laboratory, etc. (see Fig. 2, para
[0052, 0062]).
A neural network may use any suitable machine learning techniques to optimize a
training process. The neural network may be used to estimate or approximate functions
that can depend on a large number of inputs and that may be generally unknown.
The neural network may generally be a system of interconnected "neurons" that may
exchange messages between each other, where the connections may have numeric
weights (e.g., initially configured with initial weight values) that can be tuned based on
experience, making the neural network adaptive to inputs and capable of learning (e.g.,
learning pattern recognition (see Figs. 1, 2, para [0037]).
Therefore, it would have been obvious to one skill in the art before the effective filing
date of the invention to use or implement of any suitable machine learning of Borshch
et al to the programmed microprocessor for automatically control of CO gas in an
enclosed cabin, building of Horstman and Seidman and Tomimatsu et al for providing on-the-spot instant results vital for rapid treatment of such serious conditions of a person, since the system is a programmed microprocessor to operate automatically as a self-learning, processing and executing operation functions.
Claim 13. The method of claim 12 further comprising producing the trained machine
learning model via a training process comprising: receiving a plurality of input datasets
at respective ones of a plurality of input layers of a neural network, the neural network
being instantiated in the one or more processors and having an output layer
interconnected to the plurality of input layers via a set of intermediate layers, each of the
plurality of input datasets comprising an input attribute associated with ones of the
plurality of ozone gas generating devices, ones of the set of intermediate layers being
configured in accordance with an initial matrix of weights; and training the neural
network in accordance with the respective ones of the plurality of input layers based at
least in part upon recursively adjusting the initial matrix of weights by back propagation
in generating, at the output layer, an output attribute in accordance with diminishment of
an error matrix computed at the output layer of the neural network (as the combination
of any suitable machine learning techniques to optimize a training process between
Horstman, Seidman, Tomimatsu et al and Borschch et al in respect to claim 12 above, wherein Borschch et al teaches that the neural network or neuronal network or artificial neural network may be hardware-based, software-based, or any combination thereof, such as any suitable model (e.g., an analytical model, a computational model, etc.), which, in some embodiments, may include one or more sets or matrices of weights (e.g., adaptive weights, which may be numerical parameters that may be tuned by one or more learning algorithms or training methods or other suitable processes) and/or may be capable of approximating one or more functions (e.g., non-linear functions or transfer functions) of its inputs. The weights may be connection strengths between neurons of the network, which may be activated during training and/or prediction. A neural network may generally be a system of interconnected neurons that can compute values from inputs and/or that may be capable of machine learning and/or pattern recognition (e.g., due to an adaptive nature). A neural network may use any suitable machine learning techniques to optimize a training process. The neural network may be used to estimate or approximate functions that can depend on a large number of inputs and that may be generally unknown. The neural network may generally be a system of interconnected "neurons" that may exchange messages between each other, where the connections may have numeric weights (e.g., initially configured with initial weight values) that can be tuned based on experience, making the neural network adaptive to inputs and capable of learning (e.g., learning pattern recognition). A suitable optimization or training process may be operative to modify a set of initially configured weights assigned to the output of one, some, or all neurons from the input(s) and/or hidden layer(s). A non-linear transfer function may be used to couple any two portions of any two layers of neurons, including an input layer, one or more hidden layers, and an output, e.g., an input to a hidden layer, a hidden layer to an output, etc. (see Figs. 1-3, para [0037]).
Claim 14. The method of claim 13 wherein the plurality of input datasets comprises one
or more of: ozone gas generation capacity in regular mode of operation, location
coordinates defining external boundaries or perimeter of a given spatial area, coordinate
location of ozone gas generating device within the spatial area, model identification of
ozone gas generating device, device operational reliability metrics (as discussed
between Horstman and Seidman in respect to claim 1 above, see Figs. 1-3). But
Horstman fails to disclose device wireless communication reliability metrics and device
historical, cumulative ozone gas generating metrics (as the combination of any suitable
machine learning techniques to optimize a training process between Horstman,
Seidman and Tomimatsu et al and Borschch et al in respect to claims 12, 13 above, and furthermore,
Borshch et al teaches that the electronic device 100 may include a processor
assembly 102, a memory assembly 104, a communications assembly 106, a power
supply assembly 108, an input assembly 110, an output assembly 112, and a sensor
assembly 114. Electronic device 100 may also include a bus 116 that may provide one
or more wired or wireless communication links or paths for transferring data and/or
power to, from, or between various assemblies of electronic device 100 (see Fig. 1,
para [0015, 0016]).
Therefore, it would have been obvious to one skill in the art before the effective filing
date of the invention to use or implement the wireless communication assembly of
Borshch et al to the system and programmed microprocessor of Horstman and
Seidman and Tomimatsu et al for eliminating of cables/wires running throughout the cabin, building and/or office while provides a higher speed and communication therebetween.
Claim 15. The method of claim 13 wherein the output attribute comprises a desired
concentration of ozone gas as constituted in ozonated air of the spatial area (as cited in
respect to claim 1 above).
Claim 16. Horstman fails to disclose wherein the at least one ozone gas generating
device of the non-homogeneous cohort performs ozone gas generation in accordance
with applying ultraviolet (UV) irradiation provided in a wavelength of 185 nanometer
(nm) to at least a portion of the gaseous oxygen constituted in an incoming stream of air
to produce ozonated air, the ozonated air having a higher concentration of ozone gas
than the incoming stream of air.
Borshch et al suggests that the sensor assembly 114 may include any suitable sensor
components or subassemblies for detecting any suitable characteristics of any suitable
condition of the lighting of the environment of device 100. For example, sensor
assembly 114 may include any suitable light sensor that may include, but is not limited
to, one or more ambient visible light color sensors, illuminance ambient light level
sensors, ultraviolet ("UV") index and/or UV radiation ambient light sensors, and/or the
like. Any suitable light sensor or combination of light sensors may be provided for
determining the illuminance or light level of ambient light in the environment of
device 100 (e.g., in lux or lumens per square meter, etc.) and/or for determining the
ambient color or white point chromaticity of ambient light in the environment of
device 100 (e.g., in hue and colorfulness or in xly parameters with respect to an x-y
chromaticity space, etc.) and/or for determining the UV index or UV radiation in the
environment of device 100 (e.g., in UV index units, etc.). A suitable light sensor may
include, for example, a photodiode, a phototransistor, an integrated photodiode and
amplifier, or any other suitable photo-sensitive device. For example, a plot of a
chromaticity curve from the Commission International de l'Eclairage ("CIE") may be
accessible to system 1 (e.g., as a portion of data stored by memory assembly 104),
wherein the circumference of the chromaticity curve may represent a range of
wavelengths in nanometers of visible light. Different input neurons of the neural
network may be associated with respective different types of environment categories
and may be activated by environment category data of the respective environment
categories (e.g., each possible category of environmental characteristic information
(e.g., temperature, illuminance/light level, ambient color/white point chromaticity, UV
index, noise level, oxygen level, air velocity, humidity, various gas levels (e.g., various
VOC levels, pollen level, dust level, etc.), geo-location, location type, time of day, day of
week, week of month, week of year, month of year, season, holiday, time zone, and/or
the like (see Fig. 1, para [0026, 0038, 0052, 0063]).
Therefore, it would have been obvious to one skill in the art before the effective filing
date of the invention to use or supplement the ultraviolet UV wavelength of Borshch et
al to the IR light of Horstman and Seidman and Tomimatsu et al for greater accuracy and reliable results to provide a comfortable and safety to people inside the cabin, building and/or office if any environmental conditions.
Response to Arguments
Applicant’s arguments, see the amendment, filed 05/21/2026, with respect to the rejection(s) of claims 1, 17 and 18 under Horstman and Seidman have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Tomimatsu et al [US 2023/0226556] to make the rejection smoother.
Applicant’s arguments:
(A) Horstman does not disclose the features of Claim 1 as amended herein, because Horstman does not disclose "causing, by the one or more processors responsive to continuously detecting the concentration of the ozone gas constituent as being one of above and below a predetermined threshold concentration, at least one of the at least a ceiling- mounted, an in-duct mounted and a portable ozone gas generating devices to perform one of increasing and decreasing a rate of ozone gas
generation associated therewith in accordance with switching from a first mode to a second mode of ozone gas generation, the second mode of ozone gas generation being associated with one of a higher and a lower rate of generation of ozone gas than the first mode".
(B) None of Seidman, Cooner, Forbis, Wang and Borshch rectify the shortcomings of Horstman in regard to the Claim 1 features as amended herein. Independent Claim 1.
Response to the arguments:
(A) It is obvious to one skill in the art to combine the switching to second mode for higher and lower concentration than the first mode of Tomimatsu et al to the control program logic of Horstman and Seidman for improving of air regulation and purification with deodorized and sterilized to provide a greater heath environmental conditions and safety to people in a building, cabin, house or facility. Since the references are in the field of endeavor of the invention to monitoring and controlling air circulations within an interior environment.
(B) It is obvious to combine the other references of Seidman, Cooner, Forbis, Wang and Borshch with the combination between Horstman and Tomimatsu et al in respect to Claim 1.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from examiner should be directed to primary examiner craft is Van Trieu whose telephone number is (571) 2722972. The examiner can normally be reached on Mon-Fri from 8:00 AM to 3:00 PM. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Mr. Wang Quan-Zhen can be reached on (571) 272-3114.
Examiner interviews are available via telephone, 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) at http://www.uspto.gov/interviewpractice.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only.
For more information about the PAIR system, see http://pair- direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786- 9199 (IN USA OR CANADA) or 571-272-1000.
/VAN T TRIEU/
Primary Examiner, Art Unit 2685
06/08/2026
Prosecution Insights