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 § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kim et al (US 2020/0042823), Hong et al (US 2024/0081730), Qingdao (CN113310181) OR Lee et al (US 2025/0099028).
A. Claims 1, 11 and 20, Kim teaches an electronic device, a server and a method of controlling a home appliance (See Abstract) comprising:
obtaining sleep information of a user (user sleep mode, [0008]) and operation information of each of a plurality of home appliances (a variety of apparatus used at home, IoT apparatus such as air conditioning, an air cleaner, a furnace, a refrigerator, lighting, an automated blind, a robotic vacuum, [0002]; a washing machine, a refrigerator, a desktop computer, a digital signage, a robot, a vehicle, and the like, [0046]);
determining a noise source device which causes noise outside a deep sleep range (a variety of apparatus used at home, IoT apparatus such as air conditioning, an air cleaner, a furnace, a refrigerator, lighting, an automated blind, a robotic vacuum, [0002]; a washing machine, a refrigerator, a desktop computer, a digital signage, a robot, a vehicle, and the like, [0046]) from among the plurality of home appliances, at a time when a sleep phase of the user included in the sleep information is changed, (Thereafter, the processor 180 may determine a sleep state of the user by regarding the sound signals from which the noises are separated and removed in the process of S430 as the input value of the AI model (S440). The process above will be described in detail in FIGS. 5 and 6, [0145-0147]), and
controlling operation of the noise source device so that noise caused from the noise source device is generated within the deep sleep range. (Kim: the home appliance provided with a personalized AI apparatus by controlling the peripheral home appliances to improve an actual sleep environment of the user, and re-learning the AI model when the output value of the AI model is different from the state of the actual user or is unclear, can be supplied to the user, [0010]).
B. Claims 1, 11 and 20, Hong teaches an electronic device, a server and a method of controlling a home appliance ([0095] For example, the environment adjustment unit 140 may be implemented as a smart air conditioner, a smart heater, a smart boiler, a smart window, a smart humidifier, a smart dehumidifier, and a smart lighting based on links through the Internet of Things. The specific description of the above-described environment adjustment unit is only an example, and the present invention is not limited thereto) comprising:
obtaining sleep information of a user (Fig. 7, [0177-0181]) and operation information of each of a plurality of home appliances ([0095]);
determining a noise source device which causes noise outside a deep sleep range ([0090] The one or more environment sensing modules may include, for example, at least one sensor module among a temperature sensor, an air flow sensor, a humidity sensor, a sound sensor, and an illuminance intensity sensor. However, they are not limited thereto, and may further include various sensors that may affect the user's sleep) from among the plurality of home appliances, at a time when a sleep phase of the user included in the sleep information is changed, (0132] For example, as shown in FIG. 5, each spectrogram may be configured to have a frequency spectrum of different concentrations according to various sleep stages. That is, it may be difficult to predict at least one of an awake state, a REM sleep state, a light sleep state, and a deep sleep state by only changing the energy level of the sleep sound information, but by converting the sleep sound information into a spectrogram, each frequency change of a spectrum can be easily detected. Therefore, analyses corresponding to small sounds (e.g., breathing and body movements) can be implemented), and
controlling operation of the noise source device so that noise caused from the noise source device is generated within the deep sleep range. ( [0171-0173] the processor 150 may determine to transmit external environment adjustment information to an environment adjustment unit. That is, the processor 150 may improve the quality of a user's sleep by generating external environment adjustment information that allows the user to easily fall asleep or wake up naturally based on the sleep plan information).
C. Claims 1, 11 and 20, Qingdao teaches an electronic device, a server and a method of controlling a home appliance (Figure 4 is a schematic diagram of the application of the control method of the environmental
regulation system according to an embodiment of the present invention in a sleep scenario),comprising:
obtaining sleep information of a user (in terms of indoor environment, in addition to temperature and humidity, people are also increasingly demanding higher levels of comfort in other aspects such as noise, page 3. For elderly people with light sleep or those with neurasthenia, the noise threshold can be set to a lower value, page 26) and operation information of each of a plurality of home appliances (The environmental control equipment 200 can operate according to user settings or other automatic operation modes, [0038])
determining a noise source device which causes noise outside a deep sleep range from among the plurality of home appliances, at a time when a sleep phase of the user included in the sleep information is changed; (noise level by air conditioner, fresh air system, and/or humidifier, page 44, 45 wherein The entire sleep process consists of five stages: stage one (t, t+ 1), stage two (t+ 1, t+2), stage three (t+2, t+S), stage four (t+S, t+ 7), and stage five (t+ 7, t+8), page 37); and
controlling operation of the noise source device so that noise caused from the noise source device is generated within the deep sleep range (The control method of the environmental control system in this embodiment detects and judges the equipment noise emitted by the environmental control equipment 200 when the operating state of the environmental control equipment 200 arranged in the target environment changes. If the equipment noise exceeds the noise threshold, some functions of the environmental control equipment 200 are restricted and/or turned off to limit the equipment noise below the noise threshold, thereby effectively avoiding the discomfort caused by noise to users, pages 27-28).
D. Claims 1, 11 and 20, Lee teaches an electronic device, a server and a method of controlling a home appliance (an air conditioner, an air purifier, a humidifier, a dehumidifier, a blind, a curtain, a light, a smart speaker, a smart bed, a smart diffuser, and a smart device on which a healthcare application is installed, [0033]), comprising:
obtaining sleep information of a user (Based on the sleep analysis model, sleep information regarding a user's sleep quality may be inferred, [0213, 0413, 0445, 0480, 0512, 0679]) and operation information of each of a plurality of home appliances (display information, e.g., air purifier, [1044]);
determining a noise source device (ambient noise, [0042]; air conditioning noise, [0176]; (de)humidifier operating noise, [0180]) which causes noise outside a deep sleep range (sleep stage information may refer to information about whether a user's sleep was light sleep, moderate sleep, deep sleep, or REM sleep at each point during a user's last eight hours of sleep, [0138], the user's circadian rhythm may be adjusted to a normal range (e.g., falling asleep around 12:00 p.m. and waking up around 7:00 a.m.), [0597]), from among the plurality of home appliances, at a time when a sleep phase of the user included in the sleep information is changed, (the sleep stage information may be information about changing sleep stages during a user's sleep. For example, the sleep stage information may refer to information that the user's sleep has changed to light sleep, normal sleep, deep sleep, or REM sleep at each time point during the user's last eight hours of sleep, [0344]); and
controlling operation of the noise source device so that noise caused from the noise source device is generated within the deep sleep range. (it is possible to build an AI sleep stage analysis model by learning various ambient noises including noises that occur routinely in the surrounding space of a user's sleep environment, noises that occur abnormally or intermittently, etc, [0042]; adjusting air purifier or air conditioner operating noise,… if the environment adjustment device (30) is an air conditioner, the environment adjustment information may include adjusting temperature and humidity of a sleep space, adjusting blowing intensity, [0176]; adjusting dehumidification/humidification, adjusting blowing intensity, adjusting operation noise of the environment adjustment device (30), [0180]; The present invention may remove noise from sleep sound information, convert it into a spectrogram (Mel spectrogram), and generate a sleep analysis model by learning the spectrogram, [0275, 0278, 0346, 0349, 0529, 0711, 0712]).
Claims 2 and 12. The method of claim 1, wherein the obtaining of the sleep information and the operation information comprises obtaining noise information caused from each of the plurality of home appliances in an operation mode of each of the plurality of home appliances. (Lee: See Fig. 23; Hong, [0165]; Kim, [0090]. Qingdao, page 38).
Claims 3 and 13. The method of claim 1, wherein the obtaining of the sleep information and the operation information comprises excluding data about environmental factors which affect sleep of the user, except for noise. (Lee: ambient noise, [0042, 0458-0459]. Hong: [0001]; Kim, [0005-0010]).
Claims 4 and 14. The method of claim 1, wherein the determining of the noise source device comprises: identifying identification information and operation mode information of the noise source device which changes the sleep phase; and determining the deep sleep range of the user based on at least one of critical noise loudness or critical noise frequency of the user. (Lee: FIG. 52 is a table describing exemplary operations by a location where each environment adjustment device is placed, an activation status according to sleep state information for each specific device, a sleep mode, and a wake-up mode, [0184]. Here examiner maps identification to location. Kim: The object identification information may include a name, a type, a distance, and a position. [0106]. Here examiner maps identification to position).
Claims 5 and 15. The method of claim 1, wherein the controlling of the noise source device comprises controlling the noise source device to perform, in advance, at least part of a performance-preferred mode in which noise outside the deep sleep range occurs in a first sleep phase. (Lee: For example, the processor (130) may determine the wake-up induction time to be 30 minutes before the time the user wishes to wake up. As a specific example, if the user-set desired time to wake up (i.e., the wake-up prediction time) is 7:00 a.m., the processor (130) may determine 6:30 a.m. as the wake-up induction time, [0539]. Beside Lee, See respective other independent claims).
Claims 6 and 16. The method of claim 1, wherein the obtaining of the sleep information and the operation information comprises: monitoring the sleep information and the operation information in real time; and determining a time when the sleep phase of the user is changed based on the sleep information monitored in real time. (Lee: it is possible to monitor a user's physical activity states in real time for 24 hours using a smart home appliance and/or a smartphone, [0046]; The user may acquire monitoring information regarding his or her own sleep through the user terminal (10). For example, monitoring information related to a sleep may include sleep state information related to a time a user went to sleep, a length of time a user slept, and a time a user woke up, or sleep stage information related to changes in sleep stages during a sleep, [0138]. Hong: since the sleep sound information 210 is time-sequential data acquired time-sequentially during the user's sleep, [0150]. Kim: Specifically, the processor 180 may control the sound signal of the input interface 120 to be received during the sleep detection mode execution time set by the user, [0139]).
Claims 7 and 17. The method of claim 1, further comprising: obtaining, in real time, operation information of at least one device located within a critical distance likely to affect sleep of the user from the user among the plurality of home appliances; determining the deep sleep range based on the obtained operation information; and controlling operation of the at least one device located within the critical distance based on the determined deep sleep range. (Lee: at least one smart home appliance that is located at a distance around the user and simultaneously collects the sleep sound information and transmits it to the smartphone, [0020]; The user terminal (10) may generate a discrete waveform (respiration information) corresponding to the user's breathing by processing the user's movement and distance measured through the radar sensor, [0166]; the environment sensing information may include movement and distance information related to the user's movements during sleep, and breathing information generated based on the movement, [0186, 0374-0375]. Kim: The object identification information may include a name, a type, a distance, and a position, [0106]. Hong: [0138]).
Claims 8 and 18. The method of claim 1, further comprising: registering type and location information of each of a plurality of devices; identifying the at least one of the plurality of devices which is operating at the time when sleep phase of the user is changed; and determining the noise source device among the identified at least one device and controlling operation of the noise source device. (Lee: monitoring information related to a sleep may include sleep state information related to a time a user went to sleep, a length of time a user slept, and a time a user woke up, or sleep stage information related to changes in sleep stages during a sleep, [0138, 0178, 0223, 0287] Wherein FIG. 3 depicts the probability of belonging to one of the four classes (Wake, Light, Deep, REM) at 30-second intervals when predicting sleep stages based on the user's sound information. The four classes represent wakefulness, a light sleep, a deep sleep and a REM sleep, respectively, [0225]). Beside Lee, See respective other independent claims).
Claims 9 and 19. The method of claim 1, further comprising outputting at least one notification user interface (UI) which indicates control of the noise source device. (Lee: user interfaces (e.g., PUI, VUI, and/or GUI), [0514] OR see Figs. 23a, b, c and d with displaying unit to control various units, [0967] for controlling air purifier, [1057]. Beside Lee, See respective other independent claims)
Claim 10. The method of claim 1, further comprising outputting at least one proposal UI which includes guide information relating to an operation or placement of a home appliance to prevent sleep disturbance in relation to the noise source device. (Lee: FIG. 41 is a table describing exemplary operations of a bedtime preparation stage among specific scenarios of a plurality of smart home appliances chronologically operating according to a user's sleep stages using a sleep analysis method according to the present invention, [0102]. Beside Lee, Beside Lee, See respective other independent claims, specifically the last limitation).
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PHUNG-HOANG J. NGUYEN whose telephone number is (571)270-1949. The examiner can normally be reached Reg. Sched. 6:00-3:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Duc Nguyen can be reached at 571-272-7503. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PHUNG-HOANG J NGUYEN/Primary Examiner, Art Unit 2691