PATENT DOCUMENT

Publication Number: US-11280774-B2
Application Number: US-201816115478-A
Country: US
Kind Code: B2

Title: Enhanced location detection using sensors integrated in electronic devices

Abstract:
A portable communication device includes one or more miniature sensors to sense one or more environmental gases. A processor is coupled to the miniature sensors and is configured to enhance location detection by determining a sensor signal transition. The sensor signal transition is caused by subsequent exposures of at least one of the miniature sensors to environmental gases of a first air composition and a second air composition. The first air composition and the second air composition are respectively associated with a first location and a second location.

Claims:
What is claimed is: 
     
       1. A portable communication device, the device comprising:
 one or more miniature sensors configured to sense one or more environmental gases in a location; and 
 a processor coupled to the one or more miniature sensors and configured to provide an enhanced position detection accuracy within the location by determining a sensor signal transition when at least one of the one or more miniature sensors is moved within the location between a first position having a first air composition and a second position having a second air composition, wherein the location comprises a building. 
 
     
     
       2. The device of  claim 1 , wherein the first air composition is associated with an indoor position and the second air composition is associated with an outdoor position. 
     
     
       3. The device of  claim 2 , wherein the first air composition and the second air composition include different concentration levels of a signature gas, wherein the one or more environmental gases includes particulate matter, and wherein the first air composition and the second air composition include different concentration levels of particulate matter. 
     
     
       4. The device of  claim 3 , wherein the signature gas comprises ozone (O 3 ), and wherein a first concentration level of the signature gas in the first position is different from a second concentration level of the signature gas in the second position by at least a threshold value. 
     
     
       5. The device of  claim 3 , wherein the signature gas comprises carbon dioxide (CO 2 ), and wherein the first position and the second position are two different spaces of a building. 
     
     
       6. The device of  claim 1 , wherein the processor is configured to determine the sensor signal transition based on an analysis of sensor data collected over time, and wherein the sensor data comprises data corresponding to a single gas species or multiple gas species. 
     
     
       7. The device of  claim 1 , wherein the processor is configured to determine a confidence index (CI) based on sensor data collected over time. 
     
     
       8. The device of  claim 1 , wherein the processor is configured to determine the sensor signal transition corresponding to a change in a position of the device between the first position and the second position. 
     
     
       9. The device of  claim 1 , wherein the first position and the second position are different spaces of a smart home, and wherein the device is in network communication with other devices of the smart home. 
     
     
       10. The device of  claim 1 , wherein the miniature sensor comprises a miniature gas sensor. 
     
     
       11. The device of  claim 10 , wherein the miniature gas sensor is based on at least one of a list of gas sensing technologies including optical, electrochemical and chemi-resistive gas sensing technologies, and wherein chemi-resistive-based miniature gas sensors include metal-oxide semiconductors-based, graphene-based or carbon nanotubes-based gas sensors. 
     
     
       12. A device comprising:
 one or more miniature sensors configured to measure concentrations of one or more environmental gases in a location; and 
 a processor configured to receive and perform processing of signals received from the one or more miniature sensors, 
 wherein: 
 the signals comprise gas concentration versus time signals, 
 the processing of signals includes: 
 identifying a signal indicative of a position transition within the location when at least one of the one or more miniature sensors is moved between a first position having a first air composition and a second position having a second air composition, and 
 enhancing a position detection accuracy by using the identified signal indicative of the position transition, wherein the location comprises a building. 
 
     
     
       13. The device of  claim 12 , wherein the one or more environmental gases include particulate matter, wherein the first position and the second position comprise indoor and outdoor positions, and wherein the first air composition and the second air composition are associated with at least one of different concentration levels of a signature gas or different concentration levels of the particulate matter. 
     
     
       14. The device of  claim 13 , wherein the signature gas comprises ozone (O 3 ), and wherein the different concentration levels of the signature gas are different by at least a threshold value. 
     
     
       15. The device of  claim 13 , wherein the signature gas comprises carbon dioxide (CO 2 ), and wherein the building comprises a smart home. 
     
     
       16. The device of  claim 12 , wherein the processor is configured to identify the signal indicative of the position transition based on analysis of sensor data collected over time, and wherein the sensor data comprises data corresponding to a single gas species or multiple gas species. 
     
     
       17. The device of  claim 12 , wherein the processor is configured to identify the signal indicative of the position transition corresponding to a change in a position of the device between the first position and the second position of a building, wherein the building comprises a smart home equipped with multiple sensors in network communication with the device. 
     
     
       18. The device of  claim 12 , wherein the processor is configured to enable use of the one or more miniature sensors in a plurality of applications including barometer improvement, smart home integration, device power saving and context awareness applications. 
     
     
       19. A system comprising:
 a portable communication device; 
 one or more sensors integrated with the portable communication device; and 
 a processor coupled to the one or more sensors, 
 wherein: 
 the one or more sensors are configured to sense one or more environmental gases in a location, and 
 the processor is configured to: 
 determine a sensor signal transition when at least one of the one or more miniature sensors is moved within the location between a first position having a first air composition and a second position having a second air composition&#39; and 
 enhance a position detection accuracy within the location by using the identified signal indicative of the position transition, wherein the location comprises a building. 
 
     
     
       20. The system of  claim 18 , wherein the one or more environmental gases include particulate matter, wherein the first air composition and the second air composition include different concentration levels of a signature gas and are associated with a first position and a second position, and wherein the first position and a second position comprise indoor and outdoor positions and the signature gas comprises ozone (O 3 ) gas or the particulate matter. 
     
     
       21. The device of  claim 6 , wherein the sensor data includes data from a global positioning system (GPS), device occlusion data from a proximity sensor and motion data from one or more inertial measurement units (IMUs).

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit of priority under 35 U.S.C. § 119 from U.S. Provisional Patent Application 62/552,311 filed Aug. 30, 2017, which is incorporated herein by reference in its entirety. 
    
    
     TECHNICAL FIELD 
     The present description relates generally to location detection, and more particularly, to enhanced location detection using gas and particulate matter sensors integrated in electronic devices. 
     BACKGROUND 
     Many mobile electronic platforms including portable communication devices such as smart phones and smart watches are enabled to provide location based contextual awareness. Indoor-outdoor detection is an enhanced location detection, which may be useful in a number of applications, for example, environmental and health monitoring and smart home applications. Current technologies for outdoor detection are mostly based on GPS signals (e.g., geo-fencing). Other technologies such as cellular signal strength, Wi-Fi fingerprinting, Bluetooth connectivity, beacon technology, near-field communications (NFC) or other near field radios and/or signal fusion may be used to achieve indoor detection. These technologies typically require the pretense of certain infrastructure to function, such as cell phone towers and or Wi-Fi routers. 
     Indoor and outdoor environments typically differ by their air compositions and concentrations, which can be captured by gas sensors and potentially used for indoor-outdoor (I-O) detection. Single gas composition and/or concentration or multi-gas identification could be used. One particular example is tropospheric ozone (O 3 ) gas, the ground level of which is usually formed outdoors, by photochemical and chemical reactions between nitrogen oxides (NOx) and volatile organic compounds (VOCs) in the presence of sunlight. Ozone naturally breaks down in indoor environments, especially on surfaces where unsaturated carbon-carbon bonds are present, which results in a lower ozone concentration indoors than outdoors. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Certain features of the subject technology are set forth in the appended claims. However, for purposes of explanation, several embodiments of the subject technology are set forth in the following figures. 
         FIG. 1  is a schematic diagram illustrating an example of portable communication devices with enhanced location detection capability, in accordance with one or more aspects of the subject technology. 
         FIG. 2  shows a chart and a schematic diagram illustrating an example sensor signal transition used to enhance location detection, in accordance with one or more aspects of the subject technology. 
         FIG. 3  shows charts illustrating examples of raw and filtered sensor data showing signal transitions with location change, in accordance with one or more aspects of the subject technology. 
         FIG. 4  is a flow diagram illustrating an example method of indoor-outdoor transition detection based on sensor data and a baseline reference, in accordance with one or more aspects of the subject technology. 
         FIG. 5  is a flow diagram illustrating an example method of I-O transition detection based on sensor data, in accordance with one or more aspects of the subject technology. 
         FIG. 6  is a flow diagram illustrating an example method of providing a portable communication device with enhanced location detection capability, in accordance with one or more aspects of the subject technology. 
         FIG. 7  is a block diagram illustrating an example wireless communication device, within which one or more sensors of the subject technology can be integrated. 
     
    
    
     DETAILED DESCRIPTION 
     The detailed description set forth below is intended as a description of various configurations of the subject technology and is not intended to represent the only configurations in which the subject technology may be practiced. The appended drawings are incorporated herein and constitute a part of the detailed description. The detailed description includes specific details for the purpose of providing a thorough understanding of the subject technology. However, the subject technology is not limited to the specific details set forth herein and may be practiced without one or more of the specific details. In some instances, structures and components are shown in block diagram form in order to avoid obscuring the concepts of the subject technology. 
     In one or more aspects, the subject technology is directed to enhanced location detection using gas and/or particulate matter sensors integrated in electronic devices. It is understood that integration of miniature gas and/or particulate matter sensors into consumer electronic platforms is valuable as it could enable new features such as environmental, health monitoring and other various features. In particular, integration of one or more miniature sensors with a consumer electronic platform such as a portable communication device can enhance location detection accuracy of the device. This enables the device to more accurately distinguish a transition between indoor and outdoor based on detected transition in concentration of a signature gas, for example, ozone (O 3 ) or carbon dioxide (CO 2 ) or based on composition difference of indoor and outdoor gases or particulate matter. A processor coupled to the miniature sensors can determine a sensor signal transition when a user of the device moves the device from indoor to outdoor or from one location in a building to another location. In one or more implementations, the miniature sensors of the subject technology can be used in a number of applications including barometer improvement, smart home integration, device power saving and context awareness applications. For example, the processor can enable use of the miniature sensors in such applications by controlling sensor operations and performing suitable processing of the corresponding measured signals. 
       FIG. 1  is a schematic diagram illustrating an example of portable communication devices  100  and  110  with enhanced location detection capability, in accordance with one or more aspects of the subject technology. The portable communication devices  100  and  110  can be a smart phone and a smart watch as shown in  FIG. 1  and discussed herein, although examples of portable communication devices that can include the features of the subject technology are not limited to the smart phone and a smart watch and can be any other portable communication device such as a personal digital assistant (PDA). In some aspects, the features of the subject technology can be implemented in any consumer electronic platform or as a stand-alone device. 
     The portable communication devices  100  and  110  include one or more sensors  122  (e.g.,  122 - 1 ,  122 - 2  . . .  122 -N) and a processing circuit  125 . The sensors  122  are miniature sensors that can be readily integrated with a host device such as the portable communication devices  100  and  110 . The miniature sensors may be gas sensors based on one of a number of gas sensing technologies including optical, electrochemical and chemo-resistive gas sensing technologies. In some implementations, one or more of the sensors  122  can be ozone (O 3 ) sensors, carbon dioxide (CO 2 ) sensors or sensors of other gases that may be associated with various neighboring locations. In some implementations, the sensor  122  can be a multi-pixel gas sensor, for example formed of an array of gas sensors, each of which can be sensitive to a particular gas. In some embodiments, the sensors  122  can be particulate matter sensors. 
     The processing circuit  125  is capable of processing data received from the sensors  122 . In some aspects, the processing circuit  125  may provide DC bias and an AC voltage for the operation of the sensor  122 . The processing circuit  125  may include suitable analog and digital circuitry that preprocesses the data received from the sensors  122 . In one or more aspects, the processing circuit  125  can include one or more filters (e.g., a median filter) that can remove noise and smooth the raw data. The median filter can be implemented digitally and when applied to the data from the sensors  122  can improve edge detection when data transitions are studied. At least some part of the functionalities of the processing circuit  125  (e.g., after the preprocessing of the raw sensors data) can be performed by a central processor of the host device (e.g., the portable communication devices  100  and  110 ). The processing circuit  125  may be in communication with other components and modules of the host device for example a memory (e.g., volatile or non-volatile) of the host device that can store or buffer at least portions of the sensor data. In some aspects, certain signals such as a Bluetooth signal, for example, from detection of a car connection or a home speaker connection can help improve indoor-outdoor (I-O) location accuracy. Signals from other sensors and components of the host device such ambient light sensors (ALSs), proximity sensors, ultraviolet (UV) sensors, barometers, accelerometer, gyroscope, speakers, or other component of the host device can be used by the processor to enhance the I-O detection of the host device. 
     For example, the ALS and proximity sensor signals can, for example, help determine if the sensor (e.g.,  122 ) is occluded by clothing fabrics or pockets and/or bags, which can impact gas sensor accuracy, UV sensors can help improve accuracy of I-O detection, and barometers can be used to detect if the gas sensor and its port is occluded by water. The host device may use signals from an accelerometer and a gyroscope to detect user motion to reject false I-O transition signals, or use a haptic engine or a speaker to pump air to the gas sensor for active sampling. 
       FIG. 2  shows a chart and a schematic diagram illustrating an example sensor signal transition  222  used to enhance location detection, in accordance with one or more aspects of the subject technology. The raw data from sensors  122  of  FIG. 1 , after processing by the processing circuit  125  of  FIG. 1  is converted to a sensor signal  220  that may show a sensor signal transition  222 . The sensor signal transition  222  can be due to a change of concentration of a signature gas or due to a change in air composition that the sensor is exposed to. For example, if the sensor is an ozone sensor and the user of the host device (e.g.,  100  or  110  of  FIG. 1 ) moves the host device from indoor (e.g., a space in the building  250 , such as the living room (LR)  255 ) to outdoor (e.g., balcony  252 ), the ozone signal (e.g.,  220 ) shows the sensor signal transition  222 , which is an indication of a change in concentration of ozone gas. It is understood that the concentration of the ozone gas is significantly higher outdoor than indoor. This is because the ground level ozone is usually formed outdoors (e.g., by reactions between sunlight, nitrogen oxides, and volatile organic compounds), and naturally breaks down in indoor environments. This results in a higher O 3  concentration outdoors than indoors. 
     In some aspects, other gases such as carbon dioxide can be a signature gas for detecting indoor-outdoor (I-O) transition or transition from a room with more people (e.g., a LR  255  or a dining room (DR)  256  to a bedroom (e.g., BR 1 ). In one or more aspects, the change in air composition in a first location (e.g., kitchen  254 ) may be different from the air composition in a bedroom (e.g., BR 1 , BR 2 , or BR 3 ). This can result in a transition in sensors response when data from a number of sensors  122  are analyzed. For example, air composition percentages of at least one of the different gases that different sensors  122  are sensitive to a change in a location of the host device from a first location to a second location, which can cause a transition in a combined sensor signals. There may be different ways that signals from multiple sensors  122  can be combined to result in a stronger signal transition. The transition may be associated with a change Δ in the signal amplitude, for example, when the amplitude changes from a first level  224  (e.g., 10% of a highest amplitude represented by line  228 ) to a second level  226  (e.g., 90% of the highest amplitude). In some implementations, the I-O transition detection can be based on concentration of particulate matters, which can be higher outdoors as compared to indoors. 
     The indoor-outdoor (I-O) transition detection can enable new features and/or improvement of performance of existing features in the host device. For example, improvement in barometer performances can be achieved by identifying I-O transition and using the I-O transition information to reject portions of a signal (e.g., pressure signal) as noise or false positive, as opposed to being interpreted as a change in altitude (e.g., flight of stairs). The host device may benefit from the I-O transition identification in a number of other ways. For instance, in a health-related application on a host device such as a smart watch or smart phone, the relevance of possible workout options can be increased by knowing whether the user of the host device is indoors or outdoors. As another example, the power saving mode of a host device can be enabled when it is detected that the user is outdoors (e.g., by turning off Wi-Fi). Further, the user can be alerted to enable air quality measurement to contribute to crowdsourcing of air quality data, when it is detected that the user is outdoors. The I-O transition identification feature may also enable features such as cumulative indoors/outdoors time measurement, providing additional confidence to home automation and home kit integrations (e.g., by reducing level of HVAC when detecting a window is open), enhancing location sensing, for example, to find the host device, improving indoor navigation (e.g., between kitchen, bedroom, garage, balcony, etc.) and enhancing existing host device features (e.g., “remind me when” feature) based on location (e.g., I-O) knowledge. 
       FIG. 3  shows charts illustrating example of raw sensor data  300  and filtered sensor data  320  showing signal transitions with location change, in accordance with one or more aspects of the subject technology. The example raw sensor data  300  indicate variation of concentration of a signature gas (e.g., ozone or particulate matter) over time as the host device is placed alternately in a first place (e.g., balcony  252  of  FIG. 2 ) and a second place (e.g., a closed space such as BR 1  of  FIG. 2  with windows closed). The measured data rate can be a few data points per minute (e.g., 1 data point per 10 seconds). The sensor raw data may include data corresponding to a single gas species, multiple gas species or particulate matter. 
     The processing circuit  125  of  FIG. 1  can process the raw sensor data, for example, by filtering (e.g., using a median filter or other filters) the raw sensor data  300  to generate a filtered (e.g., smooth) sensor data  325  shown with lines (rather than data points). The processing circuit  125  can further determine the sensor signal transitions  330  and/or  332  based on an analysis of the filtered sensor data  320 . The sensor signal transitions  330  can be associated with an I-O transition and the sensor signal transitions  332  can an indication of an outdoor-indoor (O-I) transition. 
       FIG. 4  is a flow diagram illustrating an example method  400  of I-O transition detection based on sensor data and a baseline reference, in accordance with one or more aspects of the subject technology. The method  400  describes a method to detect whether the user is indoors or outdoors, by comparing the gas sensor signal with a baseline or reference value extracted from another source, such as air quality monitoring stations (EPA stations) or crowdsourced air quality data. The method  400  begins with an operation block  410 , where the gas sensor data S(t) (e.g.,  325  of  FIG. 2 ) collected over time (t) by the gas sensors (e.g.,  122  of  FIG. 1 ) are analyzed. Further, at an operation block  420 , outdoor baseline or reference value is prepared based on the other source. At an operation block  430 , a ratio R(t)=S(t)/H(t) is determined. Other sensor data (e.g., location from a global positioning system (GPS), device occlusion status from a proximity sensor, motion from inertial measurement units (IMU)) are collected and used to determine a confidence index Y(t), at an operation block  440 . The confidence index Y(t) is compared, at a control operation block  455 , with Y 0 , a confidence index threshold value established at operation block  450 . If Y(t) is less than Y 0 , data is automatically rejected, at operation block  458 , due to low confidence. If Y(t) is greater than or equal to Y 0 , the confidence index Y(t) is multiplied, at an operation block  460 , by the ratio R(t) to generate Y(t)*R(t). At an operation block  470 , a predefined signal threshold value T 0  is established. In some implementations, the value of T 0  can be optimized. In some aspects, the value of about 3 or greater can be used for T 0 . At a decision block  465 , a value of Y(t)*R(t) is compared with the predefined threshold value T 0 . If the value of Y(t)*R(t) is larger than or equal to T 0 , at operation block  480 , it is established that the device is outdoors. Otherwise, if the value of Y(t)*R(t) is smaller than T 0 , at operation block  490 , it is established that the device is indoors. 
       FIG. 5  is a flow diagram illustrating an example method  500  of I-O transition detection based on sensor data, in accordance with one or more aspects of the subject technology. The method  500  begins with an operation block  510 , where the gas sensor data S(t) (e.g.,  325  of  FIG. 2 ) collected over time (t) by the gas sensors (e.g.,  122  of  FIG. 1 ) are analyzed. Further, at an operation block  520 , historic rolling average data H(t) related to the same sensor is prepared based on stored data. At an operation block  530 , a ratio R(t)=S(t)/H(t) is determined. Other sensor data (e.g., location from a global positioning system (GPS), device occlusion status from a proximity sensor, motion from inertial measurement units (IMU)) are collected and used to determine a confidence index Y(t), at an operation block  550 . The confidence index Y(t) is compared, at a control operation block  555 , with Y 0 , a confidence index threshold value established at operation block  550 . If Y(t) is less than Y 0 , data is automatically rejected ( 558 ) due to low confidence. If Y(t) is greater than or equal to Y 0 , the confidence index Y(t) is multiplied, at an operation block  560 , by the ratio R(t) to generate Y(t)*R(t). At an operation block  570 , a predefined signal threshold value T 0  is established. In some implementations, the value of T 0  can be optimized. In some aspects, the value of about 3 or greater can be used for T 0 . At a decision block  565 , a value of Y(t)*R(t) is compared with the predefined threshold value T 0 . If the value of Y(t)*R(t) is larger than or equal to T 0 , at operation block  580 , it is established that the transition signal (e.g.,  330  of  FIG. 3 ) corresponds to an indoor-to-outdoor transition. Otherwise, if the value of Y(t)*R(t) is smaller than T 0  and in the meantime the value of Y(t)/R(t) is larger than or equal to T 0 , at operation block  590 , it is established that the transition signal corresponds to an outdoor-to-indoor transition. In all other scenarios, either the signal does not correspond to an I-O transition or the confidence is low, at operation block  558 , the signal is rejected. 
       FIG. 6  is a flow diagram illustrating an example method  600  of providing a portable communication device with enhanced location detection capability, in accordance with one or more aspects of the subject technology. The method begins with providing a portable communication device (e.g.,  100  or  110  of  FIG. 1 ) ( 610 ). One or more sensors (e.g.,  122  of  FIG. 1 ) are integrated with the portable communication device ( 620 ). A processor (e.g.,  125  of  FIG. 1 ) is coupled to the one or more sensors ( 630 ). The sensors are configured to sense one or more environmental gases (e.g., ozone, particulate matter or carbon dioxide) ( 640 ). The processor is configured to enhance location detection by identifying concentration transitions (e.g.,  222  of  FIG. 2 ) caused by subsequent exposures of at least one of the one or more sensors to environmental gases having a first air composition and a second air composition ( 650 ). 
       FIG. 7  is a block diagram illustrating an example wireless communication device  700 , within which one or more sensors of the subject technology can be integrated. The wireless communication device  700  may comprise a radio-frequency (RF) antenna  710 , a duplexer  712 , a receiver  720 , a transmitter  730 , a baseband processing module  740 , a memory  750 , a processor  760 , a local oscillator generator (LOGEN)  770  and one or more sensors  780 . In various embodiments of the subject technology, one or more of the blocks represented in  FIG. 7  may be integrated on one or more semiconductor substrates. For example, the blocks  720 - 770  may be realized in a single chip or a single system on a chip, or may be realized in a multi-chip chipset. 
     The receiver  720  may comprise suitable logic circuitry and/or code that may be operable to receive and process signals from the RF antenna  710 . The receiver  720  may, for example, be operable to amplify and/or down-convert received wireless signals. In various embodiments of the subject technology, the receiver  720  may be operable to cancel noise in received signals and may be linear over a wide range of frequencies. In this manner, the receiver  720  may be suitable for receiving signals in accordance with a variety of wireless standards, Wi-Fi, WiMAX, Bluetooth, and various cellular standards. In various embodiments of the subject technology, the receiver  720  may not require any SAW filters and few or no off-chip discrete components such as large capacitors and inductors. 
     The transmitter  730  may comprise suitable logic circuitry and/or code that may be operable to process and transmit signals from the RF antenna  710 . The transmitter  730  may, for example, be operable to up-convert baseband signals to RF signals and amplify RF signals. In various embodiments of the subject technology, the transmitter  730  may be operable to up-convert and amplify baseband signals processed in accordance with a variety of wireless standards. Examples of such standards may include Wi-Fi, WiMAX, Bluetooth, and various cellular standards. In various embodiments of the subject technology, the transmitter  730  may be operable to provide signals for further amplification by one or more power amplifiers. 
     The duplexer  712  may provide isolation in the transmit band to avoid saturation of the receiver  720  or damaging parts of the receiver  720 , and to relax one or more design requirements of the receiver  720 . Furthermore, the duplexer  712  may attenuate the noise in the receive band. The duplexer may be operable in multiple frequency bands of various wireless standards. 
     The baseband processing module  740  may comprise suitable logic, circuitry, interfaces, and/or code that may be operable to perform processing of baseband signals. The baseband processing module  740  may, for example, analyze received signals and generate control and/or feedback signals for configuring various components of the wireless communication device  700 , such as the receiver  720 . The baseband processing module  740  may be operable to encode, decode, transcode, modulate, demodulate, encrypt, decrypt, scramble, descramble, and/or otherwise process data in accordance with one or more wireless standards. 
     The processor  760  may comprise suitable logic, circuitry, and/or code that may enable processing data and/or controlling operations of the wireless communication device  700 . In this regard, the processor  760  may be enabled to provide control signals to various other portions of the wireless communication device  700 . The processor  760  may also control transfers of data between various portions of the wireless communication device  700 . Additionally, the processor  760  may enable implementation of an operating system or otherwise execute code to manage operations of the wireless communication device  700 . In some aspects, the processor  760  may partially or entirely perform operations described in the methods  400  and  500  of  FIGS. 4 and 5 . 
     The memory  750  may comprise suitable logic, circuitry, and/or code that may enable storage of various types of information such as received data, generated data, code, and/or configuration information. The memory  750  may comprise, for example, RAM, ROM, flash, and/or magnetic storage. In various embodiment of the subject technology, information stored in the memory  750  may be utilized for configuring the receiver  720  and/or the baseband processing module  740 . In some embodiments, the memory  750  may store sensor data, for example, collected from sensors  780  for the processor  760  to identify indoor-outdoor or other location changes based on, for example, sensor signal transitions as shown in  FIG. 2 . 
     The local oscillator generator (LOGEN)  770  may comprise suitable logic, circuitry, interfaces, and/or code that may be operable to generate one or more oscillating signals of one or more frequencies. The LOGEN  770  may be operable to generate digital and/or analog signals. In this manner, the LOGEN  770  may be operable to generate one or more clock signals and/or sinusoidal signals. Characteristics of the oscillating signals such as the frequency and duty cycle may be determined based on one or more control signals from, for example, the processor  760  and/or the baseband processing module  740 . 
     In operation, the processor  760  may configure the various components of the wireless communication device  700  based on a wireless standard according to which it is desired to receive signals. Wireless signals may be received via the RF antenna  710  and amplified and down-converted by the receiver  720 . The baseband processing module  740  may perform noise estimation and/or noise cancellation, decoding, and/or demodulation of the baseband signals. In this manner, information in the received signal may be recovered and utilized appropriately. For example, the information may be audio and/or video to be presented to a user of the wireless communication device, data to be stored to the memory  750 , and/or information affecting and/or enabling operation of the wireless communication device  700 . The baseband processing module  740  may modulate, encode, and perform other processing on audio, video, and/or control signals to be transmitted by the transmitter  730  in accordance with various wireless standards. 
     The one or more sensors  780  may include the gas and particulate matter sensors of the subject technology (e.g.,  122  of  FIG. 1 ) that can detect a signature gas such as ozone (O 3 ), carbon dioxide (CO2), and/or particulate matter as described above. The miniature gas sensors of the subject technology can be readily integrated into the communication device  700 , in particular when the communication device  700  is a smart mobile phone or a smart watch. 
     The previous description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects. Thus, the claims are not intended to be limited to the aspects shown herein, but are to be accorded the full scope consistent with the language claims, wherein reference to an element in the singular is not intended to mean “one and only one” unless specifically so stated, but rather “one or more.” Unless specifically stated otherwise, the term “some” refers to one or more. Pronouns in the masculine (e.g., his) include the feminine and neuter gender (e.g., her and its) and vice versa. Headings and subheadings, if any, are used for convenience only and do not limit the subject disclosure. 
     The predicate words “configured to”, “operable to”, and “programmed to” do not imply any particular tangible or intangible modification of a subject, but, rather, are intended to be used interchangeably. For example, a processor configured to monitor and control an operation or a component may also mean the processor being programmed to monitor and control the operation or the processor being operable to monitor and control the operation. Likewise, a processor configured to execute code can be construed as a processor programmed to execute code or operable to execute code. 
     A phrase such as an “aspect” does not imply that such aspect is essential to the subject technology or that such aspect applies to all configurations of the subject technology. A disclosure relating to an aspect may apply to all configurations, or one or more configurations. A phrase such as an aspect may refer to one or more aspects and vice versa. A phrase such as a “configuration” does not imply that such configuration is essential to the subject technology or that such configuration applies to all configurations of the subject technology. A disclosure relating to a configuration may apply to all configurations, or one or more configurations. A phrase such as a configuration may refer to one or more configurations and vice versa. 
     The word “example” is used herein to mean “serving as an example or illustration.” Any aspect or design described herein as “example” is not necessarily to be construed as preferred or advantageous over other aspects or designs. 
     All structural and functional equivalents to the elements of the various aspects described throughout this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the claims. No claim element is to be construed under the provisions of 35 U.S.C. § 112, sixth paragraph, unless the element is expressly recited using the phrase “means for” or, in the case of a method claim, the element is recited using the phrase “step for.” Furthermore, to the extent that the term “include,” “have,” or the like is used in the description or the claims, such term is intended to be inclusive in a manner similar to the term “comprise” as “comprise” is interpreted when employed as a transitional word in a claim.

Metadata:
Filing Date: 20180828
Publication Date: 20220322
Grant Date: 20220322
Priority Date: 20170830
Inventors: YAN, MIAOLEI
RIBEIRO, ROBERTO M.
YEH, RICHARD
Assignee: APPLE INC
CPC Classifications: [{"code": "G01N33/0073", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N33/0062", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N2035/00881", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N35/00871", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N33/0031", "inventive": true, "first": true, "tree": "[]"}, {"code": "G01N35/00871", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N33/0039", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N2001/021", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N33/004", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N33/0037", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N33/0062", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N33/004", "inventive": true, "first": false, "tree": "[]"}, {"code": "Y02A50/20", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N33/0047", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N33/0039", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N2001/021", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N33/0031", "inventive": true, "first": true, "tree": "[]"}, {"code": "G01N33/0073", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N33/0062", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N33/0047", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N33/0073", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N35/00871", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N33/004", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N33/0031", "inventive": true, "first": true, "tree": "[]"}, {"code": "G01N33/0037", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N2001/021", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N2033/0068", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N2035/00881", "inventive": false, "first": false, "tree": "[]"}, {"code": "G01N33/0039", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N33/0068", "inventive": true, "first": false, "tree": "[]"}, {"code": "G01N33/0068", "inventive": false, "first": false, "tree": "[]"}]
Family ID: 66171061