Abstract: A method includes detecting, with a passive infrared sensor (PIR), a level of infrared radiation in a field of view (FOV) of the PIR, generating a signal based on detected levels over a period of time, the signal having values that exhibit a change in the detected levels, extracting a local feature from a sample of the signal, wherein the local feature indicates a probability that a human in the FOV caused the change in the detected levels, extracting a global feature from the sample of the signal, wherein the global feature indicates a probability that an environmental radiation source caused the change in the detected levels, determining a score based on the local feature and the global feature, and determining that a human motion has been detected in the FOV based on the score.

Abstract: A method for guiding installation of smart-home devices may include capturing, by a camera of a mobile computing device, a view of an installation location for a smart-home device; rendering, by the mobile computing device, a view of a virtual object that represents a real-world obstruction that will interfere with the operation or installation of the smart-home device; and displaying, by the mobile computing device, the view of a virtual object that represents real-world obstruction with the view of the installation location on the display of the mobile computing device.

Abstract: A method for guiding installation of smart-home devices may include capturing, by a camera of a mobile computing device, a view of an installation location for a smart-home device; determining, by the mobile computing device, an instruction for installing the smart-home device at the location; and displaying, by a display of the mobile computing device, the view of the installation location for a smart-home device with the instruction for installing the smart-home device.

Abstract: A method includes detecting, with a passive infrared sensor (PIR), a level of infrared radiation in a field of view (FOV) of the PIR, generating a signal based on detected levels over a period of time, the signal having values that exhibit a change in the detected levels, extracting a local feature from a sample of the signal, wherein the local feature indicates a probability that a human in the FOV caused the change in the detected levels, extracting a global feature from the sample of the signal, wherein the global feature indicates a probability that an environmental radiation source caused the change in the detected levels, determining a score based on the local feature and the global feature, and determining that a human motion has been detected in the FOV based on the score.

Abstract: A method for guiding installation of smart-home devices may include capturing, by a camera of a mobile computing device, a view of an installation location for a smart-home device; determining, by the mobile computing device, an instruction for installing the smart-home device at the location; and displaying, by a display of the mobile computing device, the view of the installation location for a smart-home device with the instruction for installing the smart-home device.

Abstract: A method includes detecting, with a passive infrared sensor (PIR), a level of infrared radiation in a field of view (FOV) of the PIR, generating a signal based on detected levels over a period of time, the signal having values that exhibit a change in the detected levels, extracting a local feature from a sample of the signal, wherein the local feature indicates a probability that a human in the FOV caused the change in the detected levels, extracting a global feature from the sample of the signal, wherein the global feature indicates a probability that an environmental radiation source caused the change in the detected levels, determining a score based on the local feature and the global feature, and determining that a human motion has been detected in the FOV based on the score.

Abstract: A method for guiding installation of smart-home devices may include capturing, by a camera of a mobile computing device, a view of an installation location for a smart-home device; identifying a wire in the view of the installation location for the smart-home device; determining an instruction for connecting the wire to the smart-home device; and displaying the view of the installation location for a smart-home device with the instruction for connecting the wire to the smart-home device.

Abstract: An image of at least a portion of a room may be received, the image of the room comprising an image of a sensor mounted in the room. At least one optical parameter related to the image of the room may also be received. A distance may be determined between the sensor and a camera that captured the image of the room, wherein the determination of the distance is based at least in part on the optical parameters and on known physical dimensions of the sensor. A sensitivity requirement of the sensor may be determined, based on the distance. The determined sensitivity may be sent to control logic of the sensor.

Abstract: Systems and techniques are provided for sensor bypass. Activation may be received at a bypass input of an entry point sensor of a security system while the entry point sensor is in an armed mode. The entry point sensor may detect that the entry point monitored by the entry point sensor is closed. The entry point sensor may enter into a bypass mode. Detection by the entry point sensor of an opening of the entry point while the entry point sensor is in the bypass mode may not result in the generation of an alarm by the security system.

Abstract: A method for guiding installation of smart-home devices may include capturing, by a camera of a mobile computing device, a view of an installation location for a smart-home device; identifying a wire in the view of the installation location for the smart-home device; determining an instruction for connecting the wire to the smart-home device; and displaying the view of the installation location for a smart-home device with the instruction for connecting the wire to the smart-home device.

Abstract: Systems and methods of detecting human movement with a sensor are provided, including generating a motion event signal in response to movement detected by the sensor, and generating a parameterized curve to represent the detected motion. The parameterized curve is fit to a predetermined window of sensor data captured by the sensor to filter the motion event signal. A noise magnitude estimate and a curve fit error is determined based on the fitted parameterized curve to the predetermined window. A detection threshold value is determined based on the curve fit error, a noise source signal estimate of known noise, and zero or more noise magnitudes from other sources. Human motion is determined by correlating a true motion event signal with human motion based on a comparison between a value of a point on the parameterized curve and the detection threshold value.

Abstract: A method for optimizing the placement of smart-home devices may include receiving, by a mobile computing device, a location for a smart-home device, where the mobile computing device comprises a display and a camera; rendering a view of a virtual object that represents a field-of-view of the smart-home device, where the view of the virtual object is rendered based on a position corresponding to a position of the mobile computing device; and displaying, by the mobile computing device, the view of a virtual object that represents a field-of-view of the smart-home device on the display of the mobile computing device.

Abstract: Systems and methods of using active infrared (AIR) sensors to map a room of a home or building and determine whether an external portal (e.g., window and/or door) of the room is open or closed are provided. In particular, the systems and methods include outputting infrared (IR) light from an IR light source of an active infrared (AIR) sensor, receiving reflected IR light with a light sensor, and determining, with a processor coupled to the light sensor, whether a window of a room is open according to the received reflected IR light.

Abstract: A method includes detecting, with a passive infrared sensor (PIR), a level of infrared radiation in a field of view (FOV) of the PIR, generating a signal based on detected levels over a period of time, the signal having values that exhibit a change in the detected levels, extracting a local feature from a sample of the signal, wherein the local feature indicates a probability that a human in the FOV caused the change in the detected levels, extracting a global feature from the sample of the signal, wherein the global feature indicates a probability that an environmental radiation source caused the change in the detected levels, determining a score based on the local feature and the global feature, and determining that a human motion has been detected in the FOV based on the score.

Abstract: A method includes detecting, with a passive infrared sensor (PIR), a level of infrared radiation in a field of view (FOV) of the PIR, generating a signal based on detected levels over a period of time, the signal having values that exhibit a change in the detected levels, extracting a local feature from a sample of the signal, wherein the local feature indicates a probability that a human in the FOV caused the change in the detected levels, extracting a global feature from the sample of the signal, wherein the global feature indicates a probability that an environmental radiation source caused the change in the detected levels, determining a score based on the local feature and the global feature, and determining that a human motion has been detected in the FOV based on the score.

Abstract: In an implementation of the disclosed subject matter, a device may emit a first emission sequence of infrared radiation at a subject, and capture a first reflected sequence of infrared radiation reflected from the subject. The first emission sequence may be compared to the first reflected sequence, and, based on the comparison, a sequence of variations may be determined. The sequence of variations may be compared to signal pattern stored in a sleep profile for the subject. The subject may be determined to have exhibited sleep behavior based on the comparison of the sequence of variations to the signal pattern stored in the sleep profile. In response to determining the subject has exhibited sleep behavior, the device may capture a second reflected sequence of radiation reflected from the subject. A breathing rate of the subject and/or a heart rate of the subject may be determined based on the second reflected sequence.

Abstract: A device may emit a first emission sequence of infrared radiation at a subject, and capture a first reflected sequence of infrared radiation reflected from the subject. The first emission sequence may be compared to the first reflected sequence, and, based on the comparison, a sequence of variations may be determined. The sequence of variations may be compared to a signal pattern stored in a sleep profile for the subject. The subject may be determined to have exhibited a sleep behavior based on the comparison of the sequence of variations to the signal pattern stored in the sleep profile. In response to determining that the subject has exhibited the sleep behavior, the device may capture a second reflected sequence of radiation reflected from the subject. A breathing rate of the subject and/or a heart rate of the subject may be determined based on the second reflected sequence.

Abstract: A method for optimizing the placement of smart-home devices may include receiving, by a mobile computing device, a location for a smart-home device, where the mobile computing device comprises a display and a camera; rendering a view of a virtual object that represents a field-of-view of the smart-home device, where the view of the virtual object is rendered based on a position corresponding to a position of the mobile computing device; and displaying, by the mobile computing device, the view of a virtual object that represents a field-of-view of the smart-home device on the display of the mobile computing device.

Abstract: A system and method for detecting human intruders while rejecting/ignoring an occupant's registered pet. An object detection system is configured to detect an object that is present in a monitored area and generate a signal output relative to the type of object. A signature processor is configured to receive the generated signal output and produce an object signature, and compare a threshold signature to the object signature, wherein the threshold signature is generated using a photograph of a reserved object, and wherein the object detection system rejects the detected object when the object signature is determined to be similar to the threshold signatures.

Abstract: Systems and techniques are provided for guided installation feedback for an opening sensor. Detected magnetic field strengths of a magnetic field created by a magnet of an opening sensor as detected by a magnetometer sensor of the opening sensor may be received over a time period. It may be determined that there has been a change in the strength of the magnetic field created by the magnet as detected by the magnetometer sensor based on the received detected magnetic field strengths. Accelerometer data from an accelerometer disposed in the magnetometer sensor may be received. It may be determined from the accelerometer data that the magnetometer sensor was not moving and positive feedback may be provided to an installer of the opening sensor, or it may be determined from the accelerometer data that the magnetometer sensor was moving and negative feedback may be provided to the installer of the opening sensor.