Alarm.com Incorporated

Farallon Computing Corporation

Netopia, Inc.

Marc Anthony Epard

Robert Leon Lutes

Ronald Byron Kabler

John Berns Lancaster

Jerald Frederic Johnson

Alain Charles Briancon

Curtis Scott Crawford

Christopher Allen Giacoponello

Victor Andres Jara-Olivares

Steven Jeffrey Goldberg

Alain Charles Briançon

David James Hutz

Robert Nathan Picardi

Daniel Marc Goodman

Craig Carl Heffernan

Harrison Wayne Donahue

Liam Shea Daly

Grant Rudd

Murali Pasupuleti

Michael Byron Price

Donald W Griffin

Neal E Trautman

He Ping

Paul F VanVleck

Eric Alexander Shumaker

Methods, systems, and apparatus for periodic water leak detection are disclosed. A method includes obtaining, using a water meter, water meter data representing the occurrence of water usage events at a property; determining, based on the water meter data, a periodicity of water usage events; determining that the periodicity of water usage events satisfies water leak criteria; and based on determining that the periodicity of water usage events satisfies water leak criteria, determining that a water leak exists at the property. Determining the periodicity of water usage events can include determining an average time between a start of sequential water usage events; and determining that the periodicity of water usage events satisfies water leak criteria can include determining that the average time between the start of sequential water usage events is less than a threshold time between the start of sequential water usage events.

Periodic water leak detection

A circuit for direct current (DC) offset estimation comprises a quantile value circuit and a signal processor. The quantile value circuit determines a plurality of quantile values of an input signal and includes a plurality of quantile filters. Each quantile filter includes a comparator, a level shifter, a monotonic transfer function component, and a latched integrator. The comparator compares the input signal and a quantile value. The level shifter shifts the output of the comparator. The monotonic transfer function component determines the magnitude of the shifted signal and provide a transfer function signal. The latched integrator suppresses transient characteristics of the transfer function signal and provide the quantile value. The signal processor is configured to calculate a weighted average of the quantile values to yield a DC offset estimate.

Density function centric signal processing

A monitoring system that is configured to monitor a property is disclosed. In one aspect, the monitoring system includes a sensor that is located at the property and that is configured to generate sensor data. The monitoring system further includes a voltage sensor that is configured to generate voltage data by measuring voltage at an electrical outlet located at the property. The monitoring system further includes a monitor control unit that is configured to receive the sensor data; receive the voltage data; determine an action of an electrical device that is located in the property or that is located at a neighboring property in a vicinity of the property; determine whether the electrical device is located at the property or at the neighboring property in the vicinity of the property; and perform a monitoring system action.

Voltage event tracking and classification

Scene and/or state information may be used to facilitate processing an input to separate one or more signals within the input, to shape the signal within the input, and/or for other processing of the input or signal(s) within the input. A scene determination may be made based upon location data, time data, data describing the received input, or other basis. A state determination may be made based upon the scene determination, properties of a signal itself, or other information such as location, time, etc. By determining an appropriate scene and/or state, processing of an input and/or a signal within an input may proceed in a fashion determined to provide the most valuable information for output. Systems and methods in accordance with the invention may be implemented in a wide variety of baseband processing systems, such as hearing aids and energy consumption monitoring systems.

Scene and state augmented signal shaping and separation

A system for classifying impulsive noise on a communications signal comprises an impulse signal generator, an integrator, a first comparator, and an impulse peak detector. The impulse signal generator receives a communications signal that includes impulsive noise and is configured to provide an impulse signal that includes just the impulsive noise. The integrator receives the impulse signal and integrates the impulse signal to determine the power of the impulse signal. The first comparator receives the impulse signal and is configured to compare the impulse signal to a first reference signal and indicate the time during which the value of the impulse signal is greater than the value of the first reference signal. The impulse peak detector receives the impulse signal and is configured to process the impulse signal, compare the processed signal to a second reference signal, and detect the peak value of the impulse signal.

Method and system for impulsive noise classification and mitigation

The operation of electrical appliances receiving electrical power from an electrical system may be indirectly monitored using monitoring units engaged with outlets on branch circuits of the electrical system. Electrical systems providing power to appliances to be monitored in accordance with the present invention may comprise split phase alternating current systems, tri-phase systems, or any other type of electrical system. Known loads may be applied to calibrate the monitoring system. The monitoring system may measure the power consumption of appliances operating on the electrical system and/or detect possible fault conditions. The monitoring system may be distributed across multiple monitoring units and other computing devices. Output devices may be used to output a summary of the power consumption or other operation of monitored electrical appliances.

Monitoring and fault detection of electrical appliances for ambient intelligence

The operation of electrical appliances receiving electrical power from an electrical system may be indirectly monitored using monitoring units engaged with outlets on branch circuits of the electrical system. Electrical systems providing power to appliances to be monitored in accordance with the present invention may comprise split phase alternating current systems, tri-phase systems, or any other type of electrical system. Known loads may be applied to calibrate the monitoring system. The monitoring system may measure the power consumption of appliances operating on the electrical system and/or detect possible fault conditions. The application of a known load to each phase of the electrical system for calibration permits different portions of the electrical system to be isolated and, therefor, provides improved accuracy in monitoring power consumption and detection of potential fault conditions.

Multi-node electrical power monitoring, analysis, and related services

The operation of electrical appliances receiving electrical power from an electrical system may be indirectly monitored using monitoring units engaged with outlets on branch circuits of the electrical system. Electrical systems providing power to appliances to be monitored in accordance with the present invention may comprise split phase alternating current systems, tri-phase systems, or any other type of electrical system. Known loads may be applied to calibrate the monitoring system. The monitoring system may measure the power consumption of appliances operating on the electrical system and/or detect possible fault conditions. Fault conditions may be detected by comparing obtained voltage or power signatures of appliances to expected voltage or power signatures. Expected voltage or power signatures may be obtained, for example, using historical data, a database providing typical voltage or power signatures, or through other means.

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Lawrence, KS, United States of America

Marc Anthony Epard