Georgia Tech Research Corporation

University of Washington

Belkin International, Inc.

Thomas M Robertson

Shwetak N Patel

Gregory D Abowd

Matthew Stephen Reynolds

Erich Peter Stuntebeck

Khai N Truong

Activity sensing in the home has a variety of important applications, including healthcare, entertainment, home automation, energy monitoring and post-occupancy research studies. Many existing systems for detecting occupant activity require large numbers of sensors, invasive vision systems, or extensive installation procedures. Disclosed is an approach that uses a single plug-in sensor to detect a variety of electrical events throughout the home. This sensor detects the electrical noise on residential power tines created by the abrupt switching of electrical devices and the noise created by certain devices while in operation. Machine learning techniques are used to recognize electrically noisy events such as turning on or off a particular light switch, a television set, or an electric stove. The system has been tested to evaluate system performance over time and in different types of houses. Results indicate that various electrical events can be learned and classified with accuracies ranging from 85-90%.

Detecting actuation of electrical devices using electrical noise over a power line

Disclosed is a system that uses existing power line infrastructure in a building as a distributed reception antenna capable of receiving signals from very low-power wireless sensors, thus allowing these sensors to be detected at ranges that are otherwise impractical with over-the-air reception. Also disclosed is a wireless sensor platform that is able to be sensed throughout a building with very low current draw. The disclosed technique may also be utilized to extend the range of mid-frequency consumer electronic devices by leveraging the power line as a reception antenna.

Method and apparatus for using in-home power lines to support low power wireless sensors and to extend the range of low-power wireless devices

Activity sensing in the home has a variety of important applications, including healthcare, entertainment, home automation, energy monitoring and post-occupancy research studies. Many existing systems for detecting occupant activity require large numbers of sensors, invasive vision systems, or extensive installation procedures. Disclosed is an approach that uses a single plug-in sensor to detect a variety of electrical events throughout the home. This sensor detects the electrical noise on residential power lines created by the abrupt switching of electrical devices and the noise created by certain devices while in operation. Machine learning techniques are used to recognize electrically noisy events such as turning on or off a particular light switch, a television set, or an electric stove. The system has been tested to evaluate system performance over time and in different types of houses. Results indicate that various electrical events can be learned and classified with accuracies ranging from 85-90%.

An indoor location system uses an electrical power line, power line signal injection devices, and portable position receivers (tags) to generate location data relating to positions of the tags in a structure such as a residence or business. The indoor location system fingerprinting of multiple signals transmitted along the power line to achieve sub-room-level localization of the positioning receivers. In one embodiment, the fingerprinting techniques utilizes wideband power line positioning (WPLP) that injects up to 44 different frequencies into the power line infrastructure of a structure. The WPLP technique improves upon overall positioning accuracy, improved temporal stability and may be implemented in commercial indoor spaces.

Sub room level indoor location system using wideband power line positioning

Disclosed is an indoor location system that uses an electrical power line, power line signal injection devices, and portable position receivers (tags) to generate location data relating to positions of the tags in a structure such as a residence or business. The indoor location system fingerprinting of multiple signals transmitted along the power line to achieve sub-room-level localization of the positioning receivers. Details regarding power line positioning are described along with how it compares favorably to other fingerprinting techniques.

Growing community of inventors

Atlanta, GA, United States of America

Thomas M Robertson