Disclosed are devices, systems and methods for a monitoring system for autonomous vehicle operation. In some embodiments, a vehicle may perform self-tests, generate a report based on the results, and transmit it to a remote monitor center over one or both of a high-speed channel for regular data transfers or a reliable channel for emergency situations. In other embodiments, the remote monitor center may determine that immediate intervention is required, and may transmit a control command with high priority, which when received by the vehicle, is implemented and overrides any local commands being processed. In yet other embodiments, the control command with high priority is selected from a small group of predetermined control commands the remote monitor center may issue.

Disclosed are devices, systems and methods for a monitoring system for autonomous vehicle operation. In some embodiments, a vehicle may perform self-tests, generate a report based on the results, and transmit it to a remote monitor center over one or both of a high-speed channel for regular data transfers or a reliable channel for emergency situations. In other embodiments, the remote monitor center may determine that immediate intervention is required, and may transmit a control command with high priority, which when received by the vehicle, is implemented and overrides any local commands being processed. In yet other embodiments, the control command with high priority is selected from a small group of predetermined control commands the remote monitor center may issue.

The data processing device includes: an extraction condition input unit receiving waveform data including a change point of a state of a device, parameter information about the waveform data, and transition information of the device; a similarity calculation unit calculating similarity between time-series data of the device and the waveform data; an operating mode determination unit setting the state of the device on the basis of the transition information of the device; a change point detection unit detecting the change point from the time-series data of the device on the basis of the calculated similarity and the determined state of the device, and setting a start time of a segment which is a subsequence of the time-series data and an end time of the segment; and an information output unit outputting, as segment information, the state of the device, the start time and the end time of the segment.

The data processing device includes: an extraction condition input unit receiving waveform data including a change point of a state of a device, parameter information about the waveform data, and transition information of the device; a similarity calculation unit calculating similarity between time-series data of the device and the waveform data; an operating mode determination unit setting the state of the device on the basis of the transition information of the device; a change point detection unit detecting the change point from the time-series data of the device on the basis of the calculated similarity and the determined state of the device, and setting a start time of a segment which is a subsequence of the time-series data and an end time of the segment; and an information output unit outputting, as segment information, the state of the device, the start time and the end time of the segment.

Techniques are described for keyless entry to a structure (e.g., hotel room) utilizing a set-back box. Registrants (e.g., hotel guest) may scan a barcode from their mobile device to check-in to the structure. Upon scanning the barcode or by other means, a mobile device identifier (e.g., a Bluetooth low-energy address (BLE)) is registered and associated with the checked-in structure. Receiving the registered mobile device identifier, the backend server pushes such to the set-back box associated with (e.g., resides in) the checked-in structure. The set-back box is enabled (e.g., BLE enabled) to actively scan addresses of nearby mobile devices. When the registered mobile device identifier is detected within a predetermined signal strength range (e.g., by using received signal strength indicator (RSSI) levels), the set-back box transmits a command to a smart lock (e.g., via BLE or Wifi or other radio) or to a lock controlling backend processor, to open the lock.

A method for detecting at least one machine defect provides defining from the machine kinematic data at least one condition indicator reflecting its condition, recording operating condition data of the machine and condition monitoring data of the machine during a predetermined period when the machine is operating normally, determining condition indicator values using condition monitoring data, and for determining current condition indicator values from the at least one condition indicator and the current condition monitoring data, a machine learning algorithm, predicting condition indicator values with respect to the current operating condition data, training the machine learning algorithm to establish a relation between the operating condition data and condition indicator values, and comparing the current condition indicator values and the predicted condition indicator values, and for determining if the machine is presumed to operate normally or not according to the result of the comparison.

A method for identifying underperforming agents in a multi-agent cooperative system includes receiving information relating to the performance of each agent in the multi-agent system, calculating an estimated extracted resource value of each agent based on the received information, comparing the estimated extracted resource value of each agent to a threshold value, calculating a performance index based on the comparison and identifying an agent as an under-performing agent based on the performance index. A system for identifying under-performing agents in a plurality of agents in a multi-agent cooperative system includes a performance analyzing processor, a communications port for receiving state information for each agent and control information for each agent, a classifier for identifying a subset of agents in the plurality of agents that are performance comparable and an optimizer configured to identify an under-performing agent of performance comparable agents and generate updated control information for the identified under-performing agent.

A method, system, and computer program product, include recording high-frequency wave data of local arid adjacent fault curves of a power grid to compare the high-frequency wave data with historical fault data to detect an actual fault region in the power grid, the power grid having a plurality of sensors distributed in the power grid, each sensor being upstream of one adjacent sensor and downstream of an other adjacent sensor.

Systems and methods for generating a facilities report for a property. A computer can receive survey data from the mobile device. A facilities report for the property can be generated based on the survey data.

Systems and methods for generating a facilities report for a property. A computer can receive survey data from the mobile device. A facilities report for the property can be generated based on the survey data.