Abstract: A system has a test apparatus comprising a test medium having a machine-readable identifier, the medium enabled to accept an analyte for a specific test, a smart telephone or a pad device having imaging apparatus, a digital memory, input apparatus providing recording of contextual information associated with a specific test, and first coded instructions providing integration of images and contextual information associated with a specific test into a specific data structure, a network-connected server having a processor and coupled to at least one server-side data repository, and second coded instructions executing on the processor of the server from a non-transitory medium. A user applies the analyte, allows the test to proceed to conclusion, and initiates at least one image capture by the imaging apparatus.

Abstract: The present invention is directed to methods and apparatus for predicting the quantum state, including the dynamics of such quantum state in so far as it represents a subject embedded in a community of community subjects. In the quantum representation adopted herein the internal states of all subjects are assigned to quantum subject states defined with respect to an underlying proposition about an item that can be instantiated by an object, a subject or by an experience. Contextualization of the proposition about the item is identified with a basis (eigenbasis of a spectral decomposition) referred to herein as the social value context. The dynamics are obtained from quantum interactions on a graph onto which the quantum states of all the subjects are mapped by a surjective mapping dictated by subject interconnections and subject-related data, including the social graph and information derived from “big data”.

Abstract: A system includes an apparatus having a test medium with a machine-readable identifier, the medium enabled to accept an analyte for a test, a network-connected communication device having imaging capability, enabled to record contextual information, and executing coded instructions, a server having coupled to at least one data repository, and coded instructions executing on a processor. A user applies the analyte to the test medium, allows time to complete, and initiates an image capture, wherein a data structure, including at least a resulting image, images or video stream, including one or more images of the test result, one or more images of the machine-readable identifier, contextual information captured at the time of the test and identify of the test subject providing the analyte, is transmitted on the network to the network-connected server, where the data structure is recorded.

Abstract: A semantic note taking system and method for collecting information, enriching the information, and binding the information to services is provided. User-created notes are enriched with labels, context traits, and relevant data to minimize friction in the note-taking process. In other words, the present invention is directed to collecting unscripted data, adding more meaning and use out of the data, and binding the data to services. Mutable and late-binding to services is also provided to allow private thoughts to be published to a myriad of different applications and services in a manner compatible with how thoughts are processed in the brain. User interfaces and semantic skins are also provided to derive meaning out of notes without requiring a great deal of user input.

Abstract: A vehicle comprising a power train, a drive train, a solar array, a sensor interface, a storage device and a processing device. The sensor interface may be configured to receive sensor data samples during operation of the 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 an amount of solar power converted using the solar array, (iii) determine an energy usage for traveling a route based on the pattern and (iv) adjust an amount of power applied to the power train in response to the energy usage for traveling the route. The amount of power applied to the power train may be adjusted in response to the amount of solar power.

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: 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 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: 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: 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: 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.