Robert Boschgmbh

Other

Burton Warren Andrews

Diego Benitez

Soundararajan Srinivasan

Badri Raghunathan

Juergen Heit

Marija Dragoljub Ilic

Aca Gacic

Rahul Kapoor

Mario E Berges Gonzalez

Ethan J Goldman

Jhi Young Joo

Felix Maus

Luciio Soibelman

Diego S Benitez Meijia

H Scott Matthews

Michael Hoynck

Akshay Rajhans

A method for determining an amount of electricity to purchase includes determining electrical power consumption characteristics of an electrical load at an end user of the electricity. A preference of the end user for an output of the electrical load is ascertained. The output varies with a rate of electrical power consumption by the load. A mathematical model is created of an amount of electrical power to be consumed by the load as a function of time and of monetary cost of the electricity. The model is dependent upon the electrical power consumption characteristics of the electrical load and the preference of the end user for an output of the electrical load. An amount of electricity is purchased based on the mathematical model of an amount of electrical power to be consumed by the load, and based on the monetary cost of the electricity.

Adaptive load management: a system for incorporating customer electrical demand information for demand and supply side energy management

Apparatus and method including acquiring a signal indicative of power consumption; detecting a transient in the signal; extracting a feature indicative of the transient, wherein extracting the feature includes: fitting a plurality of models to the transient, selecting one of the plurality of models as a model for the transient, and defining the feature indicative of the transient based on at least one parameter of the model for the transient; and classifying the transient based on the feature.

Methods and apparatuses for monitoring energy consumption and related operations

An exercise monitoring method and system in one embodiment includes a communications network, a wearable transducer configured to generate physiologic data associated with movement of a wearer, and to form a communication link with the communications network, a system memory in which command instructions are stored, a user interface operably connected to the computer, and a system processor configured to execute the command instructions to receive the generated physiologic data, analyze the received physiologic data with a multilayer perceptron/support vector machine/hidden Markov (MSH) model, model the analyzed physiologic data, and generate feedback based on a comparison of the model and a stored exercise object.

Wearable system for monitoring strength training

A medical sleep disorder arrangement integrates into current diagnosis and treatment procedures to enable a health care professional to diagnose and treat a plurality of subjects suffering from insomnia. The arrangement may include both environmental sensors and body-worn sensors that measure the environmental conditions and the condition of the individual patient. The data may be collected and processed to measure clinically relevant attributes of sleep quality automatically. These automatically determined measures, along with the original sensor data, may be aggregated and shared remotely with the health care professional. A communication apparatus enables the healthcare professional to remotely communicate with and further assess the patient and subsequently administer the treatment. Thus, a more accurate diagnosis and more effective treatment is provided while reducing the required clinician time per patient for treatment delivery.

Device and method to monitor, assess and improve quality of sleep

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 is predicted for each of the subsets of appliances. An output 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

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Pittsburgh, PA, United States of America

Burton Warren Andrews