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 Status
Claims 26-45 have been added. Claims 1-25 were canceled. Claims 26-45 remain pending and are ready for examination.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that use the word “means,” and are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “means for receiving” and “means for determining” in claim 43-45.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 26-45 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 26:
Step 1: This part of the eligibility analysis evaluates whether the claim falls within any statutory category. MPEP 2106.03.
The claim is to a compute device, i.e. one of the statutory categories.
Step 2A prong one: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04(11) and the October 2019 Update, a claim "recites" a judicial exception when the judicial exception is "set forth" or "described" in the claim.
The claim recites:
“…determine, based on accelerometer data from an accelerometer of the compute device, a current activity of a user of the compute device;
…determine, based on the current activity, whether the compute device is indoors.”
These limitations recite concepts that can be practically performed in the human mind but for the recitation of generic computer components. Thus, the limitations fall into the “Mental Processes” grouping of abstract ideas. (Step 2A prong one: YES).
Step 2A prong two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. 2019 PEG Section lll{A){2), 84 Fed. Reg. at 54-55.
This judicial exception is not integrated into a practical application because: Besides the abstract idea, the claim recites the additional limitations of:
“A compute device comprising:
accelerometer data classifier circuitry…
environment determiner circuitry…”
The compute device, accelerometer data classifier circuitry, and environment determiner circuitry are a recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications. Thus, these limitations represent no more than mere instructions to apply the judicial exceptions on a computer.
It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of compute device, accelerometer data classifier circuitry, and environment determiner circuitry do not affect this analysis. See MPEP 2106.05(1) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank lnt'I, 573 U.S. 208, 224-26 (2014).
The claim does not have any additional elements which integrate the recited judicial exception into a practical application (Step 2A prong two: NO).
Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. MPEP 2106.05
Regarding the additional elements:
The compute device, accelerometer data classifier circuitry, and environment determiner circuitry are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications. Thus, these limitations represent no more than mere instructions to apply the judicial exceptions on a computer. See MPEP 2106.05(f) Implementing an abstract idea on generic electronic components as a tool to perform an abstract idea does not amount to significantly more. See Elec. Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1355 (Fed. Cir. 2016) (“Nothing in the claims, understood in light of the specification, requires anything other than off-the-shelf, conventional computer, network, and display technology for gathering, sending, and presenting the desired information.”)
The claim does not include any additional elements that are sufficient to amount to significantly more than the judicial exception. Accordingly, the claims are not patent eligible. (Step 2B: NO).
Regarding claims 27-31, under their broadest reasonable interpretation, the limitations of claims 27-31, 35-36, and 39 further defines the determining, claims 32-33 further defines the receiving the sensor data, claim 34 further defines an integrated hub, claims 37-38 further defines the environment determiner circuitry, which have been established to include abstract ideas. There are no additional limitations in the claims to apply, rely on, or use the judicial exception in a manner that would impose a meaningful limit on the judicial exception, such that claims 27-39 are not more than drafting efforts designed to monopolize the exception. Accordingly, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Thus, claims 27-39 are not patent eligible.
Regarding claims 40 and 43, the claims have similar limitations as claim 26; moreover, claim 40 recites a compute device, claim 43 recites a compute device, which are generic computer components and do not practically integrate the invention nor amount to significantly more. The claims 40 and 43 are not patent eligible.
Regarding claims 41-42, under their broadest reasonable interpretation, the limitations of claim 41 further defines the determining, claims 42 further defines accelerometer data classifier, which have been established to include abstract ideas. There are no additional limitations in the claims to apply, rely on, or use the judicial exception in a manner that would impose a meaningful limit on the judicial exception, such that claims 41-42 are not more than drafting efforts designed to monopolize the exception. Accordingly, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Thus, claims 41-42 are not patent eligible.
Regarding claims 44-45, under their broadest reasonable interpretation, the limitations of claims 44-45 further defines the determining, which have been established to include abstract ideas. There are no additional limitations in the claims to apply, rely on, or use the judicial exception in a manner that would impose a meaningful limit on the judicial exception, such that claims 41-42 are not more than drafting efforts designed to monopolize the exception. Accordingly, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Thus, claims 44-45 are not patent eligible.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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) 26, 29-30, 40-41, 43, and 45 is/are rejected under 35 U.S.C. 102(a)(1) as anticipated by Swaminathan et al. (US20170078854A1 -hereinafter Swaminathan).
Regarding Claim 26, Swaminathan teaches a compute device comprising:
accelerometer data classifier circuitry to determine, based on accelerometer data from an accelerometer of the compute device, a current activity of a user of the compute device; and (see [0032]; Swaminathan: “As shown in FIG. 1, mobile device 100 comprises an accelerometer 181. Accelerometer 181 can be used to measure acceleration of the mobile device 100. The accelerometer may include a single-axis or a multi-axis accelerometer, and can be used to detect a magnitude and a direction of the measured acceleration as a vector quantity. Input received from the accelerometer can be used to determine, for example, when a user begins to move from rest, or when a user comes to a stop.” See [0042]: “The accelerometer measures the amount of acceleration of the mobile device, and can hence detect most kinds of motion.”)
environment determiner circuitry to determine, based on the current activity, whether the compute device is indoors. (see Abstract; Swaminathan: “At least the sensor reading and the information related to a local condition are provided as input to an indoor/outdoor detection model selected from a plurality of trained models. Based on the model, the mobile device is classified as indoors or outdoors.” See [0042]: “based on the fact that the earth's magnetic field may not be influenced greatly outdoors, reading from accelerometer 181 can be used in conjunction with the magnetometer reading to detect an indoor/outdoor state of mobile device 100. The accelerometer measures the amount of acceleration of the mobile device, and can hence detect most kinds of motion. When motion is detected by the accelerometer, several readings from the magnetometer may be measured. Low variability in the magnetometer readings during motion can indicate that the mobile device is outdoors. Whereas, the earth's magnetic field may be influenced significantly indoors by various appliances and structures. Hence detection of motion in conjunction with a high variability in magnetometer measurement may indicate that the mobile device is indoors.”)
Regarding Claim 29, Swaminathan teaches all the limitations of claim 26 above, Swaminathan further teaches wherein the accelerometer data classifier circuitry is to determine, at a previous time before receipt of the accelerometer data, a previous activity of the user of the compute device, (see [0079]; Swaminathan: “In the example equation above, probabilities on the right hand side of the equation can be estimated using various approaches. For example, the probability that a person is present outdoors can be estimated based on his or her daily activities. On a week day, during work hours, the probability of outdoors may be low. The probability of a certain lux value can be estimated based on the geographic location (latitude), time of the year, etc. Using the formulation above based on conditional probabilities, the decision on whether the mobile device is located indoors or outdoors can be formulated as a machine learning problem.”)
wherein the environment determiner circuitry is to determine, based on the previous activity, whether the compute device is indoors at the previous time, (see [0080]; Swaminathan: “In other implementations, the classification can depend on factors apart from the determined probability, such as a previous determination of the indoor/outdoor state of the device.”)
wherein to determine the current activity of the user comprises to determine that the current activity of the user is being sedentary, (see [0011]; Swaminathan: “In some embodiments, the determining whether the mobile device is indoors can further be based on a determination of a previous indoor/outdoor state of the device.”)
wherein to determine, in response to a determination that the current activity of the user is being sedentary, whether the compute device is indoors based on a determination of whether the compute device was indoors at the previous time. (see [0097]; Swaminathan: “In regions such as between 940 b and 950 b, determining whether the mobile device is indoors can be further based on a determination of a previous indoor/outdoor state of the device. In the example shown in plot 900 b, if the device has been determined as indoors once, the state of the device can be classified as indoors until the ALS reading crosses line 950 b. If the ALS reading is higher than the value marked by line 950 b, the classified state can remain outdoors until the ALS reading turns to lower than the value marked by line 940 b. This way a “hysteresis” effect can be incorporated into the IOD to prevent false rapid switching between states.”)
Regarding Claim 30, Swaminathan teaches all the limitations of claim 26 above, Swaminathan further teaches wherein to determine the current activity of the user comprises to:
perform feature extraction on the accelerometer data; and (see [0052]; Swaminathan: “device data used for the feature extraction can include sensor reading from one or more sensors, such as sensors 180 described previously.”)
classify the accelerometer data based on the feature extraction and with use of a neural network to determine the current activity of the user. (see [0048]; Swaminathan: “Returning to FIG. 1, in the embodiment illustrated, indoor/outdoor detection (IOD) engine 190 comprises database 191, model trainer engine 192, and indoor/outdoor classifier 193.” See [006]: “Device data provided as input to the classification can include one or more sensor readings. The selected IOD model can be used to estimate a probability that the mobile device is indoors for the given value of the sensor reading. Based on the obtained probability, the mobile device can be assigned a ‘class label’—of whether the mobile device is detected to be indoors or outdoors.” See [0079]: “Using the formulation above based on conditional probabilities, the decision on whether the mobile device is located indoors or outdoors can be formulated as a machine learning problem.”)
Regarding Claim 40, Swaminathan teaches a compute device comprising:
sensor hub controller circuitry to: (see [0031]; Swaminathan: “Mobile device 100 can also include or have access to one or more sensors 180.”)
receive accelerometer data from an accelerometer of the compute device; (see [0032]; Swaminathan: “Accelerometer 181 can be used to measure acceleration of the mobile device 100.”)
receive magnetometer data from a magnetometer of the compute device; and (see [0033]; Swaminathan: “Magnetometer 184 can be used to measure the strength and direction a magnetic field at or surrounding the mobile device 100.”)
receive ambient light data from an ambient light sensor of the compute device; and (see [0035]; Swaminathan: “Mobile device 100 can also comprise Ambient Light Sensor (ALS) 185. The ALS can measure the amount of light falling on the sensor, and hence the brightness of an area surrounding the mobile device 100.”)
environment determiner circuitry to determine, based on the accelerometer data, the magnetometer data, and the ambient light data, whether the compute device is indoors. (see [0038]; Swaminathan: “The IOD engine can be configured to receive input from transceiver 170, sensors 180, and output a detected indoor/outdoor state of mobile device 100.”)
Regarding Claim 41, Swaminathan teaches all the limitations of claim 40 above, Swaminathan further teaches wherein to determine whether the compute device is indoors comprises to determine whether the compute device is outdoors without use of satellite positioning data. (see [0039]; Swaminathan: “In some embodiments, a sensor that mobile device 100 has access to, such as from the suite of sensors 180, can be used individually by the indoor/outdoor detection engine 190 to detect an indoor/outdoor state of mobile device 100.” See [0040]: “In some examples, Ambient Light Sensor (ALS) 185 reading can be used to predict whether a mobile device is indoors or outdoors. High readings from an ALS may be indicative of the mobile device being outdoors, because light intensity inside buildings is typically lower than outdoor light intensity on a sunny day.”)
Regarding Claim 43, the limitations in this claim is taught by Swaminathan as discussed connection with claim 26.
Regarding Claim 45, the limitations in this claim is taught by Swaminathan as discussed connection with claim 29.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claim(s) 27-28 is/are rejected under 35 U.S.C. 103 as being unpatentable over Swaminathan in view of Tinnakornsrisuphap et al. (US20130237245A1 -hereinafter Tinnakornsrisuphap).
Regarding Claim 27, Swaminathan teaches all the limitations of claim 26 above; however, Swaminathan does not explicitly teach wherein to determine the current activity of the user comprises to determine that the current activity of the user is biking or riding in a vehicle, wherein to determine, based on the current activity, whether the compute device is indoors comprises to determine that the compute device is outside based on a determination that the current activity of the user is biking or riding in a vehicle.
Tinnakornsrisuphap from the same or similar field of endeavor teaches:
wherein to determine the current activity of the user comprises to determine that the current activity of the user is biking or riding in a vehicle, (see [0042]; Tinnakornsrisuphap: “the measurement component 212 may use accelerometer and/or gyroscope measurements of the mobile device 204 for location determination. For example, certain motion patterns detected by the accelerometer and/or gyroscope can indicate whether the mobile device 204 is inside a moving vehicle (i.e., outdoors) or is carried by a user walking up/down the stairs (i.e., indoors).”)
wherein to determine, based on the current activity, whether the compute device is indoors comprises to determine that the compute device is outside based on a determination that the current activity of the user is biking or riding in a vehicle. (see [0042]; Tinnakornsrisuphap: “the measurement component 212 may use accelerometer and/or gyroscope measurements of the mobile device 204 for location determination. For example, certain motion patterns detected by the accelerometer and/or gyroscope can indicate whether the mobile device 204 is inside a moving vehicle (i.e., outdoors) or is carried by a user walking up/down the stairs (i.e., indoors).”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Swaminathan to include Tinnakornsrisuphap’s features of wherein to determine the current activity of the user comprises to determine that the current activity of the user is biking or riding in a vehicle, wherein to determine, based on the current activity, whether the compute device is indoors comprises to determine that the compute device is outside based on a determination that the current activity of the user is biking or riding in a vehicle. Doing so would improve its coverage area and frequency selection. (Tinnakornsrisuphap, [0036])
Regarding Claim 28, the combination of Swaminathan and Tinnakornsrisuphap teaches all the limitations of claim 27 above, Tinnakornsrisuphap further teaches wherein to determine that the compute device is outside based on a determination that the current activity of the user is biking or riding in a vehicle comprises to determine that the compute device is outside based on a determination that the current activity of the user is biking or riding in a vehicle without use of sensor data other than the accelerometer data. (see [0042]; Tinnakornsrisuphap: “the measurement component 212 may use accelerometer and/or gyroscope measurements of the mobile device 204 for location determination. For example, certain motion patterns detected by the accelerometer and/or gyroscope can indicate whether the mobile device 204 is inside a moving vehicle (i.e., outdoors) or is carried by a user walking up/down the stairs (i.e., indoors).”)
The same motivation to combine Swaminathan and Tinnakornsrisuphap a set forth for Claim 27 equally applies to Claim 28.
Claim(s) 31-35, 37-38, 42, and 44 is/are rejected under 35 U.S.C. 103 as being unpatentable over Swaminathan in view of Grokop et al. (US20140179298A1 -hereinafter Grokop).
Regarding Claim 31, Swaminathan teaches all the limitations of claim 26 above, Swaminathan further teaches
wherein to determine, based on the current activity, whether the compute device is indoors comprises to: (see [0042]; Swaminathan: “When motion is detected by the accelerometer, several readings from the magnetometer may be measured. Low variability in the magnetometer readings during motion can indicate that the mobile device is outdoors.”)
receive… sensor data from a magnetometer of the compute device, an ambient light sensor of the compute device, or a gyroscope of the compute device; and (see [0043]; Swaminathan: “In some embodiments, readings from gyroscope 182 can be used in conjunction with readings from magnetometer 184 to detect and indoor/outdoor state”. See [0035]: “Mobile device 100 can also comprise Ambient Light Sensor (ALS) 185. The ALS can measure the amount of light falling on the sensor, and hence the brightness of an area surrounding the mobile device 100.”)
determine, based on the sensor data, whether the compute device is indoors. (see [0043]; Swaminathan: “The gyroscope can measure changes in rotation of the mobile device. For example, high variability in magnetometer readings in combination with a low variability in gyroscope may indicate that the mobile device is indoors.”)
However, Swaminathan does not explicitly teach
wherein to determine the current activity of the user comprises to determine that the current activity of the user is walking or running,
receive, in response to a determination that the current activity of the user is walking or running, sensor data…
Grokop from the same or similar field of endeavor teaches:
wherein to determine the current activity of the user comprises to determine that the current activity of the user is walking or running, (see [0065]; Grokop: “In step 215, the system 100 can gate intensive processing based primarily on an absence of movement. Step 215 can be implemented in many different ways. For instance, a motion detector can be used to gate a slightly more intensive motion state classifier which determines user's motion (e.g., walking, running, sitting, standing, fiddling with device, resting, driving).”)
receive, in response to a determination that the current activity of the user is walking or running, sensor data… (see [0065]; Grokop: “If a sufficient amount of motion (e.g., pedestrian, vehicular) has been detected, then it is likely the user has changed location and it is necessary for the system to perform more intensive sensor scans in step 225 and processing using high power sensors 150 in order to reestablish the current state.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Swaminathan to include Grokop’s features of determining the current activity of the user comprises to determine that the current activity of the user is walking or running, receiving, in response to a determination that the current activity of the user is walking or running, sensor data. Doing so would accurately determine the indoor/outdoor state of a device. (Grokop, [0006])
Regarding Claim 32, the combination of Swaminathan and Grokop teaches all the limitations of claim 31 above, Swaminathan further teaches wherein to receive the sensor data from the magnetometer, the ambient light sensor, or the gyroscope comprises to receive sensor data from the magnetometer and sensor data from the ambient light sensor. (see [0043]; Swaminathan: “In some embodiments, readings from gyroscope 182 can be used in conjunction with readings from magnetometer 184 to detect and indoor/outdoor state”. See [0035]: “Mobile device 100 can also comprise Ambient Light Sensor (ALS) 185. The ALS can measure the amount of light falling on the sensor, and hence the brightness of an area surrounding the mobile device 100.”)
Regarding Claim 33, the combination of Swaminathan and Grokop teaches all the limitations of claim 31 above, Swaminathan further teaches wherein to receive the sensor data from the magnetometer, the ambient light sensor, or the gyroscope comprises to receive sensor data from the gyroscope. (see [0033]: “The gyroscope can be used to measure the orientation, and hence rotation of the mobile device 100.”)
Regarding Claim 34, the combination of Swaminathan and Grokop teaches all the limitations of claim 31 above, Swaminathan further teaches wherein the accelerometer, the magnetometer, the ambient light sensor, and the gyroscope are in an integrated sensor hub of the compute device. (see [0031]; Swaminathan: “Mobile device 100 can also include or have access to one or more sensors 180. As used herein, a sensor includes a location sensor or a position locator (e.g., a Global Positioning System (GPS) sensor, an Estimote sensor, a location Beacon, an iBeacon sensor, or other suitable location sensor), an altimeter, a gyroscope, a magnetometer, an impact sensor, an accelerometer, an infra-red sensor, an ambient light sensor, a motion sensor, a gesture sensor, a temperature sensor or thermometer, or any other suitable sensor.”)
Regarding Claim 35, the combination of Swaminathan and Grokop teaches all the limitations of claim 31 above, Swaminathan further teaches wherein to determine whether the compute device is indoors comprises to:
perform feature extraction on the sensor data from the magnetometer and on the sensor data from the ambient light sensor; and (see [0051]; Swaminathan: “At block 210, features can be extracted from obtained data… Alternatively, or in addition, data can be obtained from a mobile device, for example, from sensors on the mobile device in the form of sensor readings… Some example of elements for a feature vector for IOD can include logarithm of the average light intensity over the last second, average intensity of the magnetic field over the last second, standard deviation of the magnetic field intensity over the last second, direction of the magnetic field vector, current angular velocity measured from the gyroscope, time of the day, output of the proximity sensor, local temperature/humidity/pressure, average acceleration, standard deviation of the acceleration, and average temperature/humidity/pressure from neighboring weather stations.”)
classify the accelerometer data based on the feature extraction and with use of a neural network to determine whether the compute device is indoors. (see [0048]; Swaminathan: “Returning to FIG. 1, in the embodiment illustrated, indoor/outdoor detection (IOD) engine 190 comprises database 191, model trainer engine 192, and indoor/outdoor classifier 193.” See [006]: “Device data provided as input to the classification can include one or more sensor readings. The selected IOD model can be used to estimate a probability that the mobile device is indoors for the given value of the sensor reading. Based on the obtained probability, the mobile device can be assigned a ‘class label’—of whether the mobile device is detected to be indoors or outdoors.” See [0062]: “FIG. 3 is a simplified diagram showing the application of training models to classify a mobile device as indoors or outdoors according to one embodiment.” See [0079]: “Using the formulation above based on conditional probabilities, the decision on whether the mobile device is located indoors or outdoors can be formulated as a machine learning problem.”)
Regarding Claim 37, Swaminathan teaches all the limitations of claim 26 above; however, Swaminathan does not explicitly teach wherein the environment determiner circuitry is further to modify a wireless scanning procedure based on the determination of whether the compute device is indoors.
Grokop from the same or similar field of endeavor teaches: wherein the environment determiner circuitry is further to modify a wireless scanning procedure based on the determination of whether the compute device is indoors. (see [0023]; Grokop: “This may enable the device to make an accurate low power always-on determination of its indoor/outdoor state. High power sensors 150 can include, but are not limited to, GPS receiver 155, WLAN receiver 160, audio receiver 170, Bluetooth receiver 180, cellular receiver 190 and camera 195. Low power sensors 105 can include, but are not limited to, accelerometer 110, ambient light sensor (ALS) 120, clock 130 and weather/temperature sensor 140.” See [0031]: “Furthermore, in FIG. 1, the system 100 can use an ALS 120 to determine the indoor/outdoor state. Additionally, the system 100 can use an ALS 120 as a gating mechanism to the high power sensors 150. For example, the range of lux (i.e., light intensity) values observed outdoors is typically far greater than the range of lux values observed indoors. Therefore, if the ALS outputs a very high reading (e.g., high_threshold=500 lux), then the system can assume that the device is outdoors. Alternatively, for example, if the ALS reading is low (e.g., in step 260 where low_threshold=5 lux), the system can assume that the device is concealed and gate the use of the camera 195. The system can utilize any ALS 120 available on the device (e.g., an ALS may be present on the front and/or back of the device).”)
The same motivation to combine Swaminathan and Grokop a set forth for Claim 31 equally applies to Claim 37.
Regarding Claim 38, Swaminathan teaches all the limitations of claim 26 above; however, Swaminathan does not explicitly teach wherein the environment determiner circuitry is further to change a mode of a camera or a microphone based on the determination of whether the compute device is indoors.
Grokop from the same or similar field of endeavor teaches: wherein the environment determiner circuitry is further to change a mode of a camera or a microphone based on the determination of whether the compute device is indoors. (see [0031]; Grokop: “Furthermore, in FIG. 1, the system 100 can use an ALS 120 to determine the indoor/outdoor state. Additionally, the system 100 can use an ALS 120 as a gating mechanism to the high power sensors 150. For example, the range of lux (i.e., light intensity) values observed outdoors is typically far greater than the range of lux values observed indoors. Therefore, if the ALS outputs a very high reading (e.g., high_threshold=500 lux), then the system can assume that the device is outdoors. Alternatively, for example, if the ALS reading is low (e.g., in step 260 where low_threshold=5 lux), the system can assume that the device is concealed and gate the use of the camera 195.)
The same motivation to combine Swaminathan and Grokop a set forth for Claim 31 equally applies to Claim 38.
Regarding Claim 42, Swaminathan teaches all the limitations of claim 40 above, Swaminathan further teaches further comprising accelerometer data classifier to determine that an activity of a user of the compute device… (see [0032]; Swaminathan: “As shown in FIG. 1, mobile device 100 comprises an accelerometer 181. Accelerometer 181 can be used to measure acceleration of the mobile device 100. The accelerometer may include a single-axis or a multi-axis accelerometer, and can be used to detect a magnitude and a direction of the measured acceleration as a vector quantity. Input received from the accelerometer can be used to determine, for example, when a user begins to move from rest, or when a user comes to a stop.” See [0042]: “The accelerometer measures the amount of acceleration of the mobile device, and can hence detect most kinds of motion.”)
wherein to receive the magnetometer data comprises to receive the magnetometer data in response to a determination that the activity of the user… (see [0042]; Swaminathan: “When motion is detected by the accelerometer, several readings from the magnetometer may be measured. Low variability in the magnetometer readings during motion can indicate that the mobile device is outdoors.”)
wherein to receive the ambient light data comprises to receive the ambient light data in response to a determination that the activity of the user… (see [0035]; Swaminathan: “Mobile device 100 can also comprise Ambient Light Sensor (ALS) 185. The ALS can measure the amount of light falling on the sensor, and hence the brightness of an area surrounding the mobile device 100.”)
However, Swaminathan does not explicitly teach:
…determine that an activity of a user of the compute device is walking or running,
… in response to a determination that the activity of the user is walking or running.
Grokop from the same or similar field of endeavor teaches:
…determine that an activity of a user of the compute device is walking or running, (see [0065]; Grokop: “a motion detector can be used to gate a slightly more intensive motion state classifier which determines user's motion (e.g., walking, running, sitting, standing, fiddling with device, resting, driving).”)
… in response to a determination that the activity of the user is walking or running. (see [0065]; Grokop: “If a sufficient amount of motion (e.g., pedestrian, vehicular) has been detected, then it is likely the user has changed location and it is necessary for the system to perform more intensive sensor scans in step 225 and processing using high power sensors 150 in order to reestablish the current state.”)
The same motivation to combine Swaminathan and Grokop a set forth for Claim 31 equally applies to Claim 42.
Regarding Claim 44, the limitations in this claim is taught by the combination of Swaminathan and Grokop as discussed connection with claim 31.
Claim(s) 36 is/are rejected under 35 U.S.C. 103 as being unpatentable over Swaminathan in view of Grokop in view of Wakrat et al. (US20180285985A1 -hereinafter Wakrat).
Regarding Claim 36, the combination of Swaminathan and Grokop teaches all the limitations of claim 35 above; however, it does not explicitly teach wherein to determine whether the compute device is indoors comprises to apply a temporal filter to a plurality of determinations of whether the compute device is indoors.
Wakrat from the same or similar field of endeavor teaches wherein to determine whether the compute device is indoors comprises to apply a temporal filter to a plurality of determinations of whether the compute device is indoors. (see [0043]; Wakrat: “In some embodiments, the action filter 265 filters temporal values based on other types of parameters. For example, the action filter 265 determines amenities (e.g., wireless Internet, free breakfast, room service, an indoor or outdoor pool or spa, a Jacuzzi, a gym, vending machines, airport shuttle, pet accommodation, laundry, rollaway bed, etc.) that the user may want at the lodging.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Swaminathan and Grokop to include Wakrat’s features of applying a temporal filter to a plurality of determinations of whether the compute device is indoors. Doing so would customize information in order to process efficiently. (Wakrat, [0003])
Claim(s) 39 is/are rejected under 35 U.S.C. 103 as being unpatentable over Swaminathan in view of Grokop in view of Lam et al. (US20190353749A1 -hereinafter Lam).
Regarding Claim 39, Swaminathan teaches all the limitations of claim 26 above; however, Swaminathan does not explicitly teach wherein to determine whether the compute device is indoors comprises to determine, by a sensor hub, whether the compute device is indoors with use of less than 5 milliwatts of power.
Lam from the same or similar field of endeavor teaches wherein to determine whether the compute device is indoors comprises to determine, by a sensor hub, whether the compute device is indoors with use of less than 5 milliwatts of power. (see [0026]; Lam: “Given that the positioning system 100 can be used indoors (as described in further detailed herein), in some implementations, an output power of the optical source 110 will be low enough such that it does not pose a risk to human eyes (e.g., less than 5 mW).”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Swaminathan to include Lam’s features of determining, by a sensor hub, whether the compute device is indoors with use of less than 5 milliwatts of power. Doing so would accurately and efficiently predict or estimate the position of objects in both indoor and outdoor spaces. (Lam, [0004])
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ananny (US20160007889A1) discloses sensing the activity correspond to walking or running by a user.
Kay (US20160080911A1) discloses determining whether a mobile computing device is indoors or outdoors.
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/V.N.T./Examiner, Art Unit 2117
/ROBERT E FENNEMA/Supervisory Patent Examiner, Art Unit 2117
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