Abstract: A system and method are provided for associating location data from one or more unique sources. The place and time of a unique location enabled device are associated with stored demographic information relating to the particular place and particular time. The place and time of the unique location enabled device are associated with a historical record of past locations and time of locations that the device has been. Based on the association of demographical information and historical information, the unique location enable device is assigned to one or more groups or tribes. The location of all members of the group or tribe can be aggregated and exported for further analysis or display, thereby showing all group or tribe members at a particular time and place.

Abstract: A system and method are provided for associating location data from one or more unique sources. The place and time of a unique location enabled device are associated with stored demographic information relating to the particular place and particular time. The place and time of the unique location enabled device are associated with a historical record of past locations and time of locations that the device has been. Based on the association of demographical information and historical information, the unique location enable device is assigned to one or more groups or tribes. The location of all members of the group or tribe can be aggregated and exported for further analysis or display, thereby showing all group or tribe members at a particular time and place.

Abstract: A system and method are provided for associating location data from one or more unique sources. The place and time of a unique location enabled device are associated with stored demographic information relating to the particular place and particular time. The place and time of the unique location enabled device are associated with a historical record of past locations and time of locations that the device has been. Based on the association of demographical information and historical information, the unique location enabled device is assigned to one or more groups or tribes. The location of all members of the group or tribe can be aggregated and exported for further analysis or display, thereby showing all group or tribe members at a particular time and place.

Abstract: A method of detecting an event anomaly includes receiving one or more data points, in which each data point represents a spatial or temporal event; associating a unique identifier with each of the one or more data points to obtain one or more individualized data points; distributing the one or more individualized data points across a grid, in which the grid includes one or more cells; determining an event likelihood ratio for one or more of the grid cells; identifying one or more event clusters, in which each event cluster includes one or more of the grid cells; and storing in a data repository an event cluster having a significance level above a threshold significance level.

Abstract: Systems and computer-implemented methods are provided for comparing, associating and deriving associations between two or more spatial temporal data trails. One or more spatial-temporal data trails comprising one or more places are received at a processor. Each place is identified by a spatial temporal data point. And each spatial-temporal data trail is associated with an individual. The similarity between pairs of places is determined to establish one or more groups of places or one or more groups of individuals. Similarity and/groups can be determined based on demographics associated with the place or individual.

Abstract: A system and method are provided for associating location data from one or more unique sources. The place and time of a unique location enabled device are associated with stored demographic information relating to the particular place and particular time. The place and time of the unique location enabled device are associated with a historical record of past locations and time of locations that the device has been. Based on the association of demographical information and historical information, the unique location enable device is assigned to one or more groups or tribes. The location of all members of the group or tribe can be aggregated and exported for further analysis or display, thereby showing all group or tribe members at a particular time and place.

Abstract: A method of detecting an event anomaly includes receiving one or more data points, in which each data point represents a spatial or temporal event, associating a unique identifier with each of the one or more data points to obtain one or more individualized data points, distributing the one or more individualized data points across a grid, in which the grid includes one or more cells, determining an event likelihood ratio for one or more of the grid cells, identifying one or more event clusters, in which each event cluster includes one or more of the grid cells, and storing in a data repository an event cluster having a significance level above a threshold significance level.

Abstract: Systems and computer implemented methods are provided for comparing, associating and deriving associations between two or more spatial temporal data trails. One or more spatial-temporal data trails comprising one or more places are received at a processor. Each place is identified by a spatial temporal data point. And each spatial-temporal data trail is associated with an individual. The similarity between pairs of places is determined to establish one or more groups of places or one or more groups of individuals. Similarity and/groups can be determined based on demographics associated with the place or individual.

Abstract: A system and method are provided for associating location data from one or more unique sources. The place and time of a unique location enabled device are associated with stored demographic information relating to the particular place and particular time. The place and time of the unique location enabled device are associated with a historical record of past locations and time of locations that the device has been. Based on the association of demographical information and historical information, the unique location enable device is assigned to one or more groups or tribes. The location of all members of the group or tribe can be aggregated and exported for further analysis or display, thereby showing all group or tribe members at a particular time and place.

Abstract: A method for providing a virtual age estimation for predicting the remaining lifetime of a device of a given type, comprises the steps of monitoring a predetermined number of significant parameters of respective ones of a training set of devices of the given type, the parameters contributing respective wear increments, determining coefficients of a multivariate Hermite polynomial for modeling the wear increments determined from the training set operated to failure and whereof the respective virtual ages are normalized substantially to a desired norm value, deriving from the multivariate Hermite polynomial a formula for virtual age of a device of the given type, and applying the formula to the significant parameters from a further device of the given type for deriving wear increments for the further device.

Abstract: A method for providing a virtual age estimation for predicting the remaining lifetime of a device of a given type, comprises the steps of monitoring a predetermined number of significant parameters of respective ones of a training set of devices of the given type, the parameters contributing respective wear increments, determining coefficients of a radial basis function neural network for modeling the wear increments determined from the training set operated to failure and whereof the respective virtual ages are normalized substantially to a desired norm value, deriving from the radial basis function neural network a formula for virtual age of a device of the given type, and applying the formula to the significant parameters from a further device of the given type for deriving wear increments for the further device.

Abstract: A method for providing predictive maintenance of a device, comprises the steps of modeling as a time series of a discretely sampled signal representative of occurrences of a defined event in the operation of the device, the time series being modeled as two-state first order Markov processes with associated transition probabilities, wherein one state applies when the number of the occurrences exceeds a certain threshold, and the other state applies when the number of the occurrences falls below the certain threshold; computing the four transition probabilities the last N states Sn, where N is a predetermined number, conducting a supervised training session utilizing a set of J devices, which have failed due to known causes and considering the two independent probabilities and, the training session comprising computing the two-dimensional feature vectors for the initial M windows of N scans, computing the two-dimensional feature vectors for the final N number of scans, plotting a scatter-diagram of all 2D featu

Abstract: A method for providing a virtual age estimation for predicting the remaining lifetime of a device of a given type, comprises the steps of monitoring a predetermined number of significant parameters of respective ones of a training set of devices of the given type, the parameters contributing respective wear increments, determining coefficients of a radial basis function neural network for modeling the wear increments determined from the training set operated to failure and whereof the respective virtual ages are normalized substantially to a desired norm value, deriving from the radial basis function neural network a formula for virtual age of a device of the given type, and applying the formula to the significant parameters from a further device of the given type for deriving wear increments for the further device.

Abstract: This invention relates to the estimation of asset lifetimes. An embodiment of the invention includes a method for estimation of asset lifetimes, that has the steps of inputting historic asset data into a system, generating a wear index for an asset based on the historical asset data, computing an amount of wear of an asset based on the wear index, and generating a remaining life of the asset based on the amount of wear of the asset.

Abstract: A method for providing a virtual age estimation for predicting the remaining lifetime of a device of a given type, comprises the steps of monitoring a predetermined number of significant parameters of respective ones of a training set of devices of the given type, the parameters contributing respective wear increments, determining coefficients of a multivariate Hermite polynomial for modeling the wear increments determined from the training set operated to failure and whereof the respective virtual ages are normalized substantially to a desired norm value, deriving from the multivariate Hermite polynomial a formula for virtual age of a device of the given type, and applying the formula to the significant parameters from a further device of the given type for deriving wear increments for the further device.

Abstract: A method for providing predictive maintenance of a device, comprises the steps of modeling as a time series of a discretely sampled signal representative of occurrences of a defined event in the operation of the device, the time series being modeled as two-state first order Markov processes with associated transition probabilities, wherein one state applies when the number of the occurrences exceeds a certain threshold, and the other state applies when the number of the occurrences falls below the certain threshold; computing the four transition probabilities the last N states Sn, where N is a predetermined number, conducting a supervised training session utilizing a set of J devices, which have failed due to known causes and considering the two independent probabilities and, the training session comprising computing the two-dimensional feature vectors for the initial M windows of N scans, computing the two-dimensional feature vectors for the final N number of scans, plotting a scatter-diagram of all 2D featu

Abstract: A controlled stochastic resonance circuit applies stochastic resonance to bias a nonlinear device with a control signal having a selected amplitude, frequency, and phase to enhance or suppress the response of the device to a periodic signal embedded in noise.