Abstract: A method of communicating information, comprising modeling a stream of sensor data, to produce parameters of a predictive statistical model; communicating information defining the predictive statistical model from a transmitter to a receiver; and after communicating the information defining the predictive statistical model to the receiver, communicating information characterizing subsequent sensor data from the transmitter to the receiver, dependent on an error of the subsequent sensor data with respect to a prediction of the subsequent sensor data by the statistical model. A corresponding method is also encompassed.

Abstract: A facility creates a dynamic gauge for indicating the status of equipment. The facility causes a gauge to be displayed with an initial satisfactory range and an initial unsatisfactory range. The facility accesses historical data describing the status of a sensor attached to equipment. The facility determines a new satisfactory range and a new unsatisfactory range, and alters the gauge to visually indicate the new satisfactory range and the new unsatisfactory range.

Abstract: A method of communicating information, comprising modeling a stream of sensor data, to produce parameters of a predictive statistical model; communicating information defining the predictive statistical model from a transmitter to a receiver; and after communicating the information defining the predictive statistical model to the receiver, communicating information characterizing subsequent sensor data from the transmitter to the receiver, dependent on an error of the subsequent sensor data with respect to a prediction of the subsequent sensor data by the statistical model. A corresponding method is also encompassed.

Abstract: A vehicle monitoring system, comprising: an interface configured to at least communicate with a controller area network bus; a remote data telecommunication interface; a database; at least one automated processor, configured to: extract information from the controller area network bus; store records in the database representing the extracted information; process the database to determine operating statistics; selectively communicate at least a portion of the database over the remote data telecommunication interface; and determine at least one of an operating parameter for the vehicle and a predicted net fuel cost based on at least the operating statistics and a fuel unit cost.

Abstract: A method of communicating information, comprising modeling a stream of sensor data, to produce parameters of a predictive statistical model; communicating information defining the predictive statistical model from a transmitter to a receiver; and after communicating the information defining the predictive statistical model to the receiver, communicating information characterizing subsequent sensor data from the transmitter to the receiver, dependent on an error of the subsequent sensor data with respect to a prediction of the subsequent sensor data by the statistical model. A corresponding method is also encompassed.

Abstract: A method of predicting, in real-time, a relationship between a vehicle's engine speed, trip time, cost, and fuel consumption, comprising: monitoring vehicle operation over time to acquiring data representing at least a vehicle location, a fuel consumption rate, and operating conditions; generating a predictive model relating the vehicle's engine speed, trip time, and fuel consumption; and receiving at least one constraint on the vehicle's engine speed, trip time, and fuel consumption, and automatically producing from at least one automated processor, based on the predictive model, a constrained output.

Abstract: A facility creates a dynamic gauge for indicating the status of equipment. The facility causes a gauge to be displayed with an initial satisfactory range and an initial unsatisfactory range. The facility accesses historical data describing the status of a sensor attached to equipment. The facility determines a new satisfactory range and a new unsatisfactory range, and alters the gauge to visually indicate the new satisfactory range and the new unsatisfactory range.

Abstract: A facility creates a dynamic gauge for indicating the status of equipment. The facility causes a gauge to be displayed with an initial satisfactory range and an initial unsatisfactory range. The facility accesses historical data describing the status of a sensor attached to equipment. The facility determines a new satisfactory range and a new unsatisfactory range, and alters the gauge to visually indicate the new satisfactory range and the new unsatisfactory range.

Abstract: A method of predicting, in real-time, a relationship between a vehicle's engine speed, trip time, cost, and fuel consumption, comprising: monitoring vehicle operation over time to acquiring data representing at least a vehicle location, a fuel consumption rate, and operating conditions; generating a predictive model relating the vehicle's engine speed, trip time, and fuel consumption; and receiving at least one constraint on the vehicle's engine speed, trip time, and fuel consumption, and automatically producing from at least one automated processor, based on the predictive model, a constrained output.

Abstract: A method of predicting, in real-time, a relationship between a vehicle's engine speed, trip time, cost, and fuel consumption, comprising: monitoring vehicle operation over time to acquiring data representing at least a vehicle location, a fuel consumption rate, and operating conditions; generating a predictive model relating the vehicle's engine speed, trip time, and fuel consumption; and receiving at least one constraint on the vehicle's engine speed, trip time, and fuel consumption, and automatically producing from at least one automated processor, based on the predictive model, a constrained output.

Abstract: A method of communicating information, comprising modeling a stream of sensor data, to produce parameters of a predictive statistical model; communicating information defining the predictive statistical model from a transmitter to a receiver; and after communicating the information defining the predictive statistical model to the receiver, communicating information characterizing subsequent sensor data from the transmitter to the receiver, dependent on an error of the subsequent sensor data with respect to a prediction of the subsequent sensor data by the statistical model. A corresponding method is also encompassed.

Abstract: A method of determining anomalous operation of a system includes: capturing a stream of data representing sensed (or determined) operating parameters of the system over a range of operating states, with a stability indicator representing whether the system was operating in a stable state when the operating parameters were sensed; determining statistical properties of the stream of data, including an amplitude-dependent parameter and a variance thereof over time parameter for an operating regime representing stable operation; determining a statistical norm for the statistical properties that distinguish between normal operation and anomalous operation of the system; responsive to detecting that normal and anomalous operation of the system can no longer be reliably distinguished, determining new statistical properties to distinguish between normal and anomalous system operation; and outputting a signal based on whether a concurrent stream of data representing sensed operating parameters of the system represent

Abstract: A vehicle monitoring system, comprising: an interface configured to at least communicate with a controller area network bus; a remote data telecommunication interface; a database; at least one automated processor, configured to: extract information from the controller area network bus; store records in the database representing the extracted information; process the database to determine operating statistics; selectively communicate at least a portion of the database over the remote data telecommunication interface; and determine at least one of an operating parameter for the vehicle and a predicted net fuel cost based on at least the operating statistics and a fuel unit cost.

Abstract: A method of predicting, in real-time, a relationship between a vehicle's engine speed, trip time, cost, and fuel consumption, comprising: monitoring vehicle operation over time to acquiring data representing at least a vehicle location, a fuel consumption rate, and operating conditions; generating a predictive model relating the vehicle's engine speed, trip time, and fuel consumption; and receiving at least one constraint on the vehicle's engine speed, trip time, and fuel consumption, and automatically producing from at least one automated processor, based on the predictive model, a constrained output.

Abstract: A vehicle monitoring system, comprising: an interface configured to at least communicate with a controller area network bus; a remote data telecommunication interface; a database; at least one automated processor, configured to: extract information from the controller area network bus; store records in the database representing the extracted information; process the database to determine operating statistics; selectively communicate at least a portion of the database over the remote data telecommunication interface; and determine at least one of an operating parameter for the vehicle and a predicted net fuel cost based on at least the operating statistics and a fuel unit cost.

Abstract: Technologies are described herein for modeling business processes that facilitate the collaborative submission of data in a WFM system by modeling business processes in terms of cycles and assignments. A cycle defines a scenario for the business process along with a window of time in which the business process should be executed. Assignments are work activities that are defined within each cycle. A cycle definition is created for each business cycle within a business process. Each cycle definition includes data defining a recurrence pattern for the business cycle and data defining a time period in which one or more contributors to the business cycle may contribute data. Each cycle definition also includes one or more assignment definitions that define the scope, contributors, approvers, validation rules, deadlines, and data forms that should be used for the assignment.