Method and device for calibrating device using machine learning in m2m system
AssigneesHyundai Motor Company, Kia Corporation, Industry Academy Cooperation Foundation of Sejong University
InventorJae Seung Song
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Abstract
In a machine-to-machine (M2M) system, a method for calibrating an Internet of Things (IoT) device may include steps of: receiving a measured value from at least one reference device, performing machine learning by using the measured value, storing an output value of the machine learning, and transmitting the output value to the IoT device for IoT device calibration. An apparatus for calibrating the IoT device in the M2M system includes a transceiver and a processor, where the processor is configured to perform the above steps.
Claims14
A method for calibrating an Internet of Things (IoT) device in a machine-to-machine (M2M) system, the method comprising:
- receiving a measured value from at least one reference device;
- performing machine learning by using the measured value;
- storing an output value of the machine learning;
- and
- transmitting the output value to an IoT device for IoT device calibration.
An apparatus for calibrating an Internet of Things (IoT) device in a machine-to-machine (M2M) system, the apparatus comprising:
- a transceiver;
- and
- a processor coupled with the transceiver,
- wherein the processor is configured to:
- receive a measured value from at least one reference device,
- perform machine learning by using the measured value,
- store an output value of the machine learning, and
- transmit the output value to an IoT device for IoT device calibration.
Dependencies are inferred from the claim text.