Provided herein is a sensing management system capable of minimizing the amount of data transmission from sensors, the system including a plurality of sensors configured to sense information of surrounding environment, and, in response to a sensing value transmitted to a controller having a slope of a same directivity for twice or more times, to obtain a predicted slope using a current slope of the transmitted sensing values; and the controller configured to obtain the predicted slope using a same algorithm as the sensors, wherein, in response to a next sensing value being within an error range of the predicted slope, the sensors do not transmit the next sensing value to the controller.

A setpoint adjustment apparatus for a displacement meter (10) includes a determiner (343) to determine whether a measurement value acquired by an acquirer (341) in measurement of a reference workpiece using an applying setpoint, to be used in measurement of the reference workpiece, is within the range of a desired measurement value (352), and a changer (345) to change the applying setpoint. When the measurement value is within the range of the desired measurement value (352), the applying setpoint used in acquisition of the measurement value is employed as an applying setpoint for inspection of a measurement target (1). When the measurement value is out of this range, the applying setpoint used in acquisition of the measurement value is changed to a different applying setpoint, and whether the measurement value from the reference workpiece using this applying setpoint is within the range of the desired measurement value (352) is determined.

A computer-implemented method includes fetching, by a controller, data using a plurality of memory channels of a memory system. The method further includes detecting, by the controller, that a first memory channel of the plurality of memory channels has not returned data. The method further includes marking, by the controller, the first memory channel from the plurality of memory channels as unavailable. The method further includes, in response to a fetch, reconstructing, by the controller, fetch data based on data received from all memory channels other than the first memory channel.

An automobile includes an automotive lamp and an in-vehicle controller. A sensor generates image data. An encoder divides the image data into multiple data frames, and encodes the data frame thus divided. A scrambler scrambles the data frame thus encoded using a reproducible pseudo-random signal. A serializer converts the output of the scrambler into serial data. A transmitter transmits the serial data to the in-vehicle controller via a cable.

System and method for constantly monitoring the state of the oil of the wheels of heavy machinery, in particular mining trucks, while they are in motion. Comprising a server; a wireless sensor module attached to the rim of the wheel, obtaining oil measurements from an oil quality sensor, which sends the measurements to the server wirelessly; the sensor, located inside the sensor module; and a spoon-type mechanism which maintains the sensor in permanent contact with the oil inside the wheel, wherein said spoon-type mechanism rotates with the sensor module and the wheel. In addition, it may comprise a receiving antenna module which is located between the sensor module and the server. In addition, it may comprise a transmitter which is located between the receiving antenna module and the server.

A multiply redundant safety system that protects humans and assets while transfer(s)/fuelling of on road/off road, rail, marine, aircraft, spacecraft, rockets, and all other vehicles/vessels utilizing Compressed and or Liquefied Gas Fuels/compound(s). Utilizing Natural Gas Chemical Family of Hydrogen/Propane/ethane/ammonia/and any mixtures along with or with out oxidizer(s), such as Liquefied Oxygen, Oxygen Triplet (O3)/ozone/hydrogen peroxide/peroxide/solid oxidizer(s) one or more processors, utilizing Artificial Intelligence techniques/machine learning in combination with one or more sensors; in combination with one or more micro switches/actuator(s) combine to detect any leaks/fire(s)/or explosion hazards/vehicle motion/arc's, spark(s)/and other hazards for quickly mitigating/locking out/stopping fueling/gas/transfers/vehicle releasing system(s).

A multiply redundant safety system that protects humans and assets while transfer(s)/fuelling of on road/off road, rail, marine, aircraft, spacecraft, rockets, and all other vehicles/vessels utilizing Compressed and or Liquefied Gas Fuels/compound(s). Utilizing Natural Gas Chemical Family of Hydrogen/Propane/ethane/ammonia/and any mixtures along with or with out oxidizer(s), such as Liquefied Oxygen, Oxygen Triplet (O3)/ozone/hydrogen peroxide/peroxide/solid oxidizer(s) one or more processors, utilizing Artificial Intelligence techniques/machine learning in combination with one or more sensors; in combination with one or more micro switches/actuator(s) combine to detect any leaks/fire(s)/or explosion hazards/vehicle motion/arc's, spark(s)/and other hazards for quickly mitigating/locking out/stopping fueling/gas/transfers/vehicle releasing system(s).

This disclosure describes techniques for a consumer application that integrates a model-controller-view (MCV) design pattern with an event streaming platform such as an Apache Kafka™ in a network operation center (NOC) server to support NOC workspace interoperability. The MCV design pattern may include a pattern that divides an application into three main logical components (e.g., model component, controller component, and view component) to handle specific aspects of the application. In one example, the model component decouples the telemetry data streams from an event stream platform, and the controller component filters a queried set of decoupled telemetry data streams to dynamically control views to be rendered in the view component.

This disclosure describes techniques for a consumer application that integrates a model-controller-view (MCV) design pattern with an event streaming platform such as an Apache Kafka™ in a network operation center (NOC) server to support NOC workspace interoperability. The MCV design pattern may include a pattern that divides an application into three main logical components (e.g., model component, controller component, and view component) to handle specific aspects of the application. In one example, the model component decouples the telemetry data streams from an event stream platform, and the controller component filters a queried set of decoupled telemetry data streams to dynamically control views to be rendered in the view component.

A multiply redundant safety system that protects humans and assets while transfer(s)/fuelling of on road/off road, rail, marine, aircraft, spacecraft, rockets, and all other vehicles/vessels utilizing Compressed and or Liquefied Gas Fuels/compound(s). Utilizing Natural Gas Chemical Family of Hydrogen/Propane/ethane/ammonia/and any mixtures along with or with out oxidizer(s), such as Liquefied Oxygen, Oxygen Triplet (O3)/ozone/hydrogen peroxide/peroxide/solid oxidizer(s) one or more processors, utilizing Artificial Intelligence techniques/machine learning in combination with one or more sensors; in combination with one or more micro switches/actuator(s) combine to detect any leaks/fire(s)/or explosion hazards/vehicle motion/arc's, spark(s)/and other hazards for quickly mitigating/locking out/stopping fueling/gas/transfers/vehicle releasing system(s).