Abstract:
A smart-home device may include a plurality of temperature sensors, and a processing system that may be configured to operate a first operating state characterized by relatively low power consumption and a corresponding relatively low associated heat generation, and a second operating state characterized by relatively high power consumption and a corresponding relatively high associated heat generation. During time intervals in which the processing system is operating in the first operating state, the processing system may process the temperature sensor measurements according to a first ambient temperature determination algorithm to compute the determined ambient temperature. During time intervals in which the processing system is operating in the second operating state, the processing system may process the temperature sensor measurements according to a second ambient temperature determination algorithm to compute the determined ambient temperature.
Abstract:
A path light that utilizes an ambient light sensor to determine the lighting conditions may experience feedback from its light source if it determines that the lighting conditions are appropriate to illuminate the path light's light source. The path light, as disclosed herein, may compute an offset value to ascertain the amount of feedback from the light source. Upon learning the offset value, the path light may subtract the offset value from a detected amount of light to determine whether the lighting conditions of its surroundings still meet a threshold level of darkness for the path light to illuminate.
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 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 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:
Systems and techniques are provided for motion sensor adjustment. A signal indicating that motion was detected by a motion sensor may be received. A status of an HVAC system may be received from a computing device that controls the operation of vents of the HVAC system. The status of the HVAC system may include times vents of the HVAC system are operating. Using the status of the HVAC system, it may be determined that a vent of the HVAC system located in an area visible to the motion sensor was operating during the time period in which the motion sensor detected motion by correlating the time period in which the motion sensor detected motion with the times the vent was operating as indicated by the status of the HVAC system. The signal indicating that motion was detected may be ignored as a false alert and no alert may be generated.
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 system and method is provided for the control of a network of devices wherein each device of the networked devices provides for the operation of a sensor such as an accelerometer, processor and communication element within each device, and network and/or cloud based processing and storage, to process collected data to permit detection and predictive analysis of traffic patterns, weather patterns and other forces of nature. The system and method can analyze duration and magnitude of vibration signals, and considering maps and known locations of devices, tracks and highways and historical data regarding each, use machine learning techniques to accurately classify the motion and provide real-time and predictive analysis.
Abstract:
A system includes a plurality of sensing devices disposed at a premises, the sensing devices being configured to generate data based on activity detected at one or more openings in the premises and to transmit the data, a plurality of speakers dispersed at the premises, a memory configured to store output profiles corresponding to a plurality of respective events and to store a plurality of respective sounds, and a processor configured to identify an event based on the transmitted data and to execute a stored output profile assigned to the event, the execution including automatically playing a stored sound through one or more of the speakers in accordance with the selected output profile.
Abstract:
A method may receive, in response to a first event, a first sensor data from a first sensor, and receive, in response to the first event, a second sensor data from a second sensor. The method may select, from among a plurality of event profiles, a first event profile. The first event profile may comprise a first condition matching the first sensor data, a second condition matching the second sensor data, and a plurality of conditions which, when met, indicate the occurrence of the first event. Conditions may include a sensor data, a time period, a user data, a sequence of conditions, or a combination of such data. The first event profile may comprise a first event notice to be provided in response to the occurrence of the first event. The method may provide the first event notice to a recipient indicated by the event profile.