Abstract: A method, implemented by a computer, for constructing a 3D digital model of a building from a 2D plan of the building, the building having a geometry defined by at least one geometric parameter, the method comprising a plurality of steps, at least one of the steps requiring an input of at least one internal parameter, the method being wherein it comprises a step of selecting a set of parameter values without human intervention.

Abstract: A method, implemented by a computer, for constructing a 3D digital model of a building from a 2D plan of the building, the building having a geometry defined by at least one geometric parameter, the method comprising a plurality of steps, at least one of the steps requiring an input of at least one internal parameter, the method being wherein it comprises a step of selecting a set of parameter values without human intervention.

Abstract: Data processing method for analysis of the energy consumption of a site on the basis of measurements including: selection of data time series, segmentation of the time series into segments, projection of the segments, display of the projections of the data segments, e) selection of at least one first group of data segments, establishment of a digital model of classification characterising the first group of data segments, selected on the basis of calendar metadata establishment of a digital model of classification characterising the first group of data segments, selected on the basis of the segments' profiles (FIG. 5B).

Abstract: A method for estimating the charge of a battery comprises: acquiring at least one time series of measurements of voltage across the terminals of the battery, and at least one other time series of measurements of another physical parameter of the battery or of its environment; determining an operating regime of the battery; choosing a regression model from among a predefined set of such models; and estimating the charge of the battery by applying the regression model to the time series of voltage measurements and to at least one other time series of measurements. A device for estimating the charge of a battery and a device for training regression models of the charge of a battery, adapted for the implementation of the method are provided. A system for estimating the charge of a battery comprising a device for estimating the charge and a device for training regression models is provided.

Abstract: A method for estimating the state of health of a battery of an electric or hybrid vehicle in conditions of use, comprises the following steps: a) during the operation of the battery, acquiring a time series of measurements of speed or of acceleration of the vehicle and, simultaneously, at least one time series of measurements of a quantity chosen from: a current or a power delivered by the battery, and a voltage at its terminals; b) extracting segments of the time series corresponding to speed or acceleration patterns that satisfy at least one predefined condition; and c) determining estimations of the state of health of the battery by application of at least one continuous estimation or classification model to the segments of the time series. A device and system for implementing such a method and a method for constructing a continuous estimation or classification model are provided.

Abstract: Data processing method for analysis of the energy consumption of a site on the basis of measurements including: selection of data time series, segmentation of the time series into segments, projection of the segments, display of the projections of the data segments, e) selection of at least one first group of data segments, establishment of a digital model of classification characterising the first group of data segments, selected on the basis of calendar metadata establishment of a digital model of classification characterising the first group of data segments, selected on the basis of the segments' profiles (FIG. 5B).

Abstract: A method for estimating the charge of a battery comprises: acquiring at least one time series of measurements of voltage across the terminals of the battery, and at least one other time series of measurements of another physical parameter of the battery or of its environment; determining an operating regime of the battery; choosing a regression model from among a predefined set of such models; and estimating the charge of the battery by applying the regression model to the time series of voltage measurements and to at least one other time series of measurements. A device for estimating the charge of a battery and a device for training regression models of the charge of a battery, adapted for the implementation of the method are provided. A system for estimating the charge of a battery comprising a device for estimating the charge and a device for training regression models is provided.

Abstract: A system for real-time determination of a parameter of a movement having a repetitive form includes first estimating means for estimating an approximation of the period of the repetitive movement, before the end of the current movement, on the basis of representative signals indicative of the movement. A determining means determines a size of a sliding window on the basis of the period estimated by the first estimating means. Finally, a second estimating means precisely estimates, using the sliding window, the movement parameter, on the basis of the representative signals indicative of the movement and of the size of the sliding window delivered by the first estimating means.

Abstract: The invention pertains to a system for real-time determination of a parameter of a movement (PM, Tp) of repetitive form comprising: first means (EST1) for estimating an approximation (Tr) of the period of said movement of repetitive form, before the end of the current movement, on the basis of representative signals (S1, S2) indicative of said movement; means (DET) for determining a size (F) of sliding window on the basis of said period (Tr) estimated by said first estimating means (EST1); second means (EST2) for precisely estimating, by sliding window, said movement parameter, on the basis of representative signals (S1, S2) indicative of said movement and of said size (F) of sliding window delivered by said first estimating means (EST1).

Abstract: The invention includes a prediction method for the screening or diagnosis or therapeutic management or prognosis of prostate cancer, including collecting individual input data and providing predictive information on the risk linked to a type of disease. The input data includes at least one variable or a combination of variables of the genetic type such as the identification of markers of genetic polymorphisms considered as being linked to the development of the disease. The invention also provides an individual prediction device for the screening or diagnosis or therapeutic management or prognosis of prostate cancer including first means for acquiring individual information data by a user, and at least a first software interface on which the said first means operate. The invention additionally includes a computer program product having the method and providing predictive information on risk linked to a disease.