Abstract: A vehicle comprising a power train, a drive train, a sensor interface, a storage device and a processing device. The sensor interface may be configured to receive sensor data samples during operation of a vehicle. The storage device may be configured to store the sensor data samples over a number of points in time. The processing device may be configured to (i) analyze the sensor data samples stored in the storage device to detect a pattern, (ii) monitor operational parameters of the vehicle based on the pattern and (iii) determine an efficient speed to travel a route in response to the operational parameters. An amount of power corresponding to the efficient speed is applied to the power train.

Abstract: A vehicle comprising a drive train, an internal combustion engine, a sensor interface, a storage device and a processing device. The sensor interface may be configured to receive sensor data samples during operation of a vehicle. The storage device may be configured to store the sensor data samples over a number of points in time. The processing device may be configured to (i) analyze the sensor data samples stored in the storage device to detect a pattern and (ii) manage fuel supplied to the internal combustion engine in response to (a) current conditions and (b) operational parameters of the vehicle. The pattern is used to determine the current conditions. The fuel supplied to the internal combustion engine is managed to enable efficient fuel usage.

Abstract: A method for predicting energy consumption of a vehicle using a statistical model. The method includes (i) predicting a set of future input vectors for the vehicle at defined time intervals corresponding to a plurality of future points in time based on a subset of a plurality of reference input vectors previously generated at the defined time intervals at a plurality of previous points in time, (ii) predicting a change in the energy level of the vehicle at the future points in time using a processor and the statistical model, and (iii) providing results corresponding to the predicted change in the energy level to an output unit of the vehicle. The change in the energy level comprises a function of corresponding future input vectors and an associated weighting vector. The change in the energy level is predicted based on a regression analysis of the energy level associated with each of the reference input vectors.

Abstract: Described herein are devices, systems, and methods for managing the power consumption of an automotive vehicle, and thereby for optimizing the power consumption of the vehicle. The devices and systems for managing the power consumption of the vehicle typically include power management logic that can calculate an applied power for the vehicle engine based on information provided from the external environment of the vehicle, the operational status of the vehicle, one or more command inputs from a driver, and one or more operational parameters of the vehicle.

Abstract: A system comprising a plurality of self-powered devices and at least one remote device. The plurality of self-powered devices may be configured to (i) perform one or more tasks and (ii) select one of a plurality of modes of operation. The remote device may be configured to (a) determine scheduling data for one or more activities based on a resource capacity of the self-powered devices and (b) communicate with the self-powered devices. The activities may comprise one or more of the tasks. The self-powered devices may determine a computational cost of performing the tasks.

Abstract: A method for receiving an update from a remote source may comprise a step of connecting wirelessly to a transceiver. The method may comprise a step of communicating with a remote database via the transceiver. The method may comprise a step of providing operational parameter data to the remote database. The method may comprise a step of receiving updated operational parameters from the database based on a comparison of the operational parameter data to a latest version of the operational parameter data performed by the remote database. The method may comprise a step of updating one or more components of a vehicle using the updated operational parameters. The remote database may be configured to determine a status of the components of the vehicle and provide the updated operational parameters to keep software used by the vehicle to a latest version.

Abstract: An apparatus comprising an interface, a memory and a processor. The interface may be configured to receive sensor data samples during operation of a vehicle. The memory may be configured to store the sensor data samples over a number of points in time. The processor may be configured to analyze the sensor data samples stored in the memory to detect a pattern. The processor may be configured to manage an application of brakes of the vehicle in response to the pattern.

Abstract: A method for predicting energy consumption of a vehicle using a statistical model. The method includes (i) predicting a set of future input vectors for the vehicle at defined time intervals corresponding to a plurality of future points in time based on a subset of a plurality of reference input vectors previously generated at the defined time intervals at a plurality of previous points in time, (ii) predicting a change in the energy level of the vehicle using a processor and the statistical model, and (iii) providing results corresponding to the predicted change in the energy level to an output unit of the vehicle. Each reference input vector comprises a vehicle input vector and a database input vector associated with each point in time of the plurality of previous points in time. The database input vector for each defined time interval may be based on at least one of a plurality of environmental data and information about a road condition.

Abstract: A vehicle comprising a power train, a drive train, a sensor interface, a storage device and a processing device. The sensor interface may be configured to receive sensor data samples during operation of a vehicle. The storage device may be configured to store the sensor data samples over a number of points in time. The processing device may be configured to analyze the sensor data samples stored in the storage device to detect a pattern and adjust an amount of power applied to the power train of the vehicle in response to the pattern. The pattern may be used to determine current conditions for the vehicle. The amount of power may be adjusted to reduce energy loss.

Abstract: An apparatus comprising an interface, a memory and a processor. The interface may be configured to receive (i) sensor data samples during operation of a vehicle and (ii) data from a telemetry system. The memory may be configured to store the sensor data samples over a number of points in time. The processor may be configured to (i) analyze the sensor data samples stored in the memory to determine (a) operational parameters of the vehicle and (b) information associated with a second vehicle and (ii) adjust the operational parameters in response to the information associated with the second vehicle. The data from the telemetry system and the information associated with the second vehicle may be used to determine an amount of space between the vehicle and the second vehicle. The operational parameters may be adjusted to keep the amount of space within a pre-determined range.

Abstract: Described herein are devices, systems, and methods for managing the power consumption of an automotive vehicle, and thereby for optimizing the power consumption of the vehicle. The devices and systems for managing the power consumption of the vehicle typically include power management logic that can calculate an applied power for the vehicle engine based on information provided from the external environment of the vehicle, the operational status of the vehicle, one or more command inputs from a driver, and one or more operational parameters of the vehicle.

Abstract: Described herein are devices, systems, and methods for managing the power consumption of an automotive vehicle, and thereby for optimizing the power consumption of the vehicle. The devices and systems for managing the power consumption of the vehicle typically include power management logic that can calculate an applied power for the vehicle engine based on information provided from the external environment of the vehicle, the operational status of the vehicle, one or more command inputs from a driver, and one or more operational parameters of the vehicle.

Abstract: An apparatus comprising a sensor interface, a memory and a processor. The sensor interface may be configured to receive sensor data samples during operation of a vehicle. At least one of the sensor data samples may be driver-related. The memory may be configured to store the sensor data samples over a number of points in time. The processor may be configured to (i) analyze the sensor data samples stored in the memory to detect a pattern and (ii) generate a likelihood that a particular driver is operating the vehicle based on the pattern detected.

Abstract: Described herein are devices, systems, and methods for managing the power consumption of an automotive vehicle, and thereby for optimizing the power consumption of the vehicle. The devices and systems for managing the power consumption of the vehicle typically include power management logic that can calculate an applied power for the vehicle engine based on information provided from the external environment of the vehicle, the operational status of the vehicle, one or more command inputs from a driver, and one or more operational parameters of the vehicle.

Abstract: A device comprising a processor, an energy source, one or more sensors, a wireless transceiver and a memory. The memory may comprise instructions for selecting one of a plurality of modes of operation. The modes of operation may comprise (i) a low-power mode in which the device consumes less than a pre-determined or an adaptively-determined amount of power and the device has less than full functionality and (ii) a high-power mode in which the device consumes more than the pre-determined or the adaptively-determined amount of power and the device has more functionality than in the low-power mode. The instructions for selecting one of the modes of operation may comprise (i) instructions for conserving power by transitioning from the high-power mode to the low-power mode and (ii) instructions for activating the wireless transceiver to transmit a message with information from the sensors to a remote device.

Abstract: A device comprising a battery, a memory, a data acquisition circuit and a processor. The sensors may sample a current state of a dynamic process. The data acquisition circuit may have a first clock rate based on a sampling rate of the dynamic process. The data acquisition circuit may read sensor information from the sensors. The processor may have a second clock rate. The processor may process the sensor information and generate a monitoring signal based on at least one of the sensor information, a model of the dynamic process and a desired state of the dynamic process. The processor may schedule procedures for the device and determine computation times for the procedures based on context information. The second clock rate is faster than the first clock rate. The procedures are scheduled based on the sampling rate, the computation times for the procedures and opportunities to enter a standby mode to conserve power.

Abstract: Project-based interactive fundraising with funder rules is provided. A fundraising application is accessible by multiple online users for creating projects to be funded and for funding created projects. Projects can include project requirements, such as a target funding minimum. Online users can select created projects and establish funder rules to determine conditions to fund the selected projects. The project requirements and funder rules are processed to determine whether or not funds can be released to the projects or returned to the selecting users. The funder rules give funding users direct control over the project fundraising. The processed funder rules provide information on current and anticipated funding levels and can be used to find approximate optimal conditions to attain high funding levels and increase the likelihood of success to fund a project.

Abstract: Bookmarking content modules and tracking scores of user properties against the bookmarked content modules on a computer implemented social network are provided. Content modules containing text, audio, video, or audio-video content are accessible to users of a social network. User properties are associated with the users of the social network and the user properties are related to the content modules. Each user of the social network can bookmark a content module and score a user property against the bookmarked content module related with the same user property. Scores are tracked over a period of time to provide motivation and accountability to the user. Ad hoc online communities form around the bookmarked content modules; members of an online community all share at least one common bookmarked content module. A messaging function is provided for members of an online community to communicate with each other to foster support and accountability.

Abstract: A device comprising a processor, an energy source, one or more sensors, a wireless transceiver and a memory. The memory may comprise instructions for selecting one of a plurality of modes of operation. The modes of operation may comprise (i) a low-power mode in which the device consumes less than a pre-determined or an adaptively-determined amount of power and the device has less than full functionality and (ii) a high-power mode in which the device consumes more than the pre-determined or the adaptively-determined amount of power and the device has more functionality than in the low-power mode. The instructions for selecting one of the modes of operation may comprise (i) instructions for conserving power by transitioning from the high-power mode to the low-power mode and (ii) instructions for activating the wireless transceiver to transmit a message with information from the sensors to a remote device.

Abstract: A method and system includes predicting energy consumption of a vehicle using a statistical model. The method includes obtaining a plurality of input vectors for plurality of points in time, wherein each input vector includes a plurality of variables with a weight vector. Thereafter, the energy level for each input vector is captured for each point in time. Subsequent to capturing the energy level, the method includes predicting a change in energy level of the vehicle using the statistical model.