Methods and systems for repairing a malfunctioning autonomous vehicle (AV) or semi-autonomous vehicle (SAV) are described herein. The AV or SAV may determine that an autonomous feature or sensor is malfunctioning and the extent of the damage to the autonomous feature or sensor. Then the AV or SAV may compare the extent of the damage to a predetermined threshold to determine whether the AV or SAV remains serviceable or otherwise road worthy. If the AV or SAV remains serviceable, the AV or SAV may locate the nearest repair facility having the necessary electronic components in stock and technical expertise for repairing the AV or SAV. Then the AV or SAV may request the nearest repair facility to send an autonomous repair vehicle to the current location of the AV or SAV to facilitate repair.

Methods and systems for autonomous and semi-autonomous vehicle routing are disclosed. Roadway suitability for autonomous operation is scored to facilitate use in route determination. Maps of roadways suitable for various levels of autonomous operation may be generated. Such map data may be used by autonomous vehicles or other computer devices in determining routes based upon criteria for vehicle trips. Such routes may be automatically updated based upon changes in road conditions, vehicle conditions, operator conditions, or environmental conditions. Emergency routing using such map data is described, such as automatic routing and travel when a passenger is experiencing a medical emergency.

An actuating device for moving an actuator that features an actuating drive for generating an actuating movement for the actuator. The actuating device also includes a transmission device for transmitting the actuating movement from the actuating drive to the actuator. It also features a sensor device for detecting the actuating position of the actuator. The sensor device features a signal receiver and transducer. The signal receiver will be in the actuating drive and the transducer configured as part of the transmission device.

An automated system including a control target device and a control device which controls the control target device, in which it is possible to accurately estimate whether maintenance of the control target device is required and a portion requiring maintenance. The control device is an adaptive control device including a position control system, an adaptive identifier which estimates a parameter indicating a state of a control target device based on a control command and a control target output from the control target device, and an adaptive compensator which, based on the parameter which is estimated by the adaptive identifier, compensates the control command from the position control system to the control target device such that the control target device performs a planned operation regardless of a change in the parameter.

In an embodiment, a data processing method comprises storing one or more generic machine operating definitions, wherein each of the generic machine operating definitions describes expected operational behavior of one or more types of machines during one or more operating states; analyzing operating data that describes past operation of a plurality of machines of a plurality of types; based at least in part on the operating data and the one or more generic machine operating definitions, generating and storing one or more machine operating models that describe expected operational behavior corresponding to a plurality of operating states of the plurality of machines; wherein the one or more machine operating models comprise a plurality of data patterns, wherein each of the data patterns is associated with a different set of one or more operating states of one or more machines; wherein the method is performed by one or more computing devices.

The present invention relates to a power transformer asset management device and a method thereof, the device according to the present invention including: a full cycle database managing full cycle data of a power transformer; a physical performance evaluation unit performing physical performance evaluation that calculates a health index by analyzing and weighting life information, a failure ratio, operation history, and status information of a preventive diagnosis system from the full cycle data; a risk evaluation unit performing risk evaluation by generating a risk matrix using the physical performance evaluation result; an economic evaluation unit performing economic evaluation by evaluating costs over a full cycle of the power transformer; and an asset management unit establishing an investment plan for replacing the power transformer according to a maintenance priority of the power transformer determined using the physical performance evaluation result, the risk evaluation result, and the economic evaluation result.

A building management system (BMS) includes one or more memory devices having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform operations including using the operating data to evaluate one or more fault detection rules to determine whether at least one of the plurality of building devices is experiencing a fault condition, in response to determining that at least one of the plurality of building devices is experiencing the fault condition, determining an amount of carbon emissions generated due to the fault condition based on a fault emissions model associated with the fault condition and initiating an automated response based on the amount of carbon emissions associated with the fault condition.

Methods and systems for autonomous vehicle recharging or refueling are disclosed. Autonomous electric vehicles may be automatically recharged by routing the vehicles to available charging stations when not in operation, according to methods described herein. A charge level of the battery of an autonomous electric vehicle may be monitored until it reaches a recharging threshold, at which point an on-board computer may generate a predicted use profile for the vehicle. Based upon the predicted use profile, a time and location for the vehicle to recharge may be determined. In some embodiments, the vehicle may be controlled to automatically travel to a charging station, recharge the battery, and return to its starting location in order to recharge when not in use.

State-of-the-art approaches have concentrated on building solution(s) to match the amplitude of a time series with a user given one. However, these have failed to implement solution(s) which enables searching for pattern(s) that can depict human vision psychology. Embodiments of the present disclosure determine occurrence of pattern of interest in time series data for anomaly detection, wherein time series data is obtained, and first order derivative is computed. Further an angle of change in direction is derived based on a gradient of change in value of the time series data. This angle is further converted to a measurement unit. The time series data is quantized into bins and a weighted finite state transducers diagram (WFSTD) is obtained based on domain knowledge which is then converted to specific pattern. The specific pattern is searched in the bins to determine occurrence/count of the specific pattern for anomaly detection.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. To this end, a server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.