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%.

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

A method and system for use in creating a profile of, managing and understanding power consumption in a premise of a user, wherein said premise comprises two or more power consuming devices comprises measuring, via at least one sensor, aggregate energy consumption at the premise, receiving at a mobile computing device comprising a data processor, said aggregated signal from the sensor, collecting and recording the aggregate signal over a plurality of time resolutions and frequencies, therein to create a predicted aggregate signal for each time x and frequency y, detecting changes in the predicted aggregate signal at time x an frequency y (detected consumption pattern changes) and conveying to at least one of the user, a utility company, and other third party a notification of detected consumption pattern changes.

System and method of compiling and organizing power consumption data and converting such data into one or more user actionable formats

A method of outputting to a user an indication of the usage of a utility, the method comprising: obtaining data indicating, for each of a plurality of appliances, a respective current level of usage of the utility by that appliance; for each of a plurality of appliance categories, using the obtained data to calculate a respective current total level of usage of the utility by appliances belonging to that appliance category; and outputting an indication of the calculated current total level of usage of the utility for at least one of the plurality of appliance categories.

Non-intrusive utility monitoring

Some embodiments teach an apparatus for determining a proximity of one or more first Bluetooth devices. The apparatus can include: (a) at least one Bluetooth base station with (1) a Bluetooth transmitter configured to transmit one or more service discovery requests to the one or more first Bluetooth devices; and (2) a Bluetooth receiver configured to receive one or more responses from the one or more first Bluetooth devices to the one or more service discovery requests; and (b) a computational module configured to run on one or more processors and further configured to determine one or more approximate distances between the at least one Bluetooth base station and the one or more first Bluetooth devices based on the one or more responses from the one or more first Bluetooth devices. Other embodiments are disclosed.

Bluetooth Proximity Detection System and Method of Interacting With One or More Bluetooth Devices

A method for non- intrusively monitoring a load including a plurality of appliances includes retrieving a plurality of mathematical models for modeling operation of a respective subset of the appliances. A value of a respective operational parameter (X) is predicted for each of the subsets of appliances. An output (Y) of the load is measured. A respective value of each of the operational parameters is calculated based on the mathematical models and the outputs of the load. The predicting, measuring and calculating steps are repeated until a metric pertaining to a difference error between the measured output and the predicted output calculated from the operational parameter and the mathematical models is equal to or below a threshold for one of the subsets of appliances. It is decided that the one subset of appliances is currently operating whose metric pertaining to a difference error is equal to or below the threshold.

Method for non-intrusive load monitoring using a hybrid systems state estimation approach

A method of inference of appliance usage from a point measurement on a supply line, said supply line being common to multiple appliances and/or components of appliances comprises the steps of: obtaining data from said measurement point; sampling power and reactive power at intervals substantially throughout periods of operation of said appliances or components of appliances corresponding to appliances or components of appliances being in ON and/or OFF modes of use; identifying characteristics of events by assessing power and reactive power change during an event; and by assessing one or more additional characteristics derivable from said power and reactive power to characterise an appliance; grouping events and/or cycles of events into clusters of similar characteristics; and inferring appliance usage based on said grouping.

A method of inference of appliance usage. data processing apparatus and/or computer software

L'invention concerne un procede de determination d'utilisation d'appareil a partir d’une mesure ponctuelle sur une ligne d'alimentation, ladite ligne d'alimentation etant commune a des appareils et/ou des composants d'appareils multiples. Le procede comprend les etapes suivantes : obtention de donnees depuis ledit point de mesure; echantillonnage de la puissance et de la puissance reactive a des intervalles pratiquement tout au long des periodes de fonctionnement desdits appareils ou desdits composants d'appareils correspondant aux appareils ou aux composants d'appareils etant dans des modes d'utilisation MARCHE et/ou ARRET; identification de caracteristiques des evenements par l'evaluation du changement de puissance et de puissance reactive pendant un evenement; et par l'evaluation d'une ou plusieurs caracteristiques additionnelles deductibles desdites puissance et puissance reactive pour caracteriser un appareil; groupage d'evenements et/ou de cycles d'evenements en groupes de caracteristiques similaires; et determination de l'utilisation d'un appareil en fonction dudit groupage.

Adam Laurence Camilletti

Papers

A method of inference of appliance usage. data processing apparatus and/or computer software

Procédé de détermination d'utilisation d'appareil, appareil de traitement de données et/ou logiciel informatique