Abstract: Provided are a system and method for predicting time-series data. According to the system and method, first time-series data is externally input, and second time-series data which is time-series prediction data using an autoencoder-based time-series data prediction model (long-term time-series forecasting based on autoencoder (LTScoder)) is generated. The method includes an operation of receiving first time-series data, an encoding operation of inputting the first time-series data to an encoder of the model to generate a latent vector, a decoding operation of inputting the latent vector to a decoder of the model, and an operation of calculating a weighted sum of outputs of the decoder to generate second time-series data.

Abstract: Provided are an edge gateway system for providing device use and resource sharing suggestions and an operating method thereof. The edge gateway system includes at least one edge gateway and an edge gateway management server connected to the at least one edge gateway. The edge gateway is connected to one or more edge devices and transmits an operation status of the edge gateway and an operation status of the edge devices to the edge gateway management server, the edge gateway management server generates suggestion information to be delivered to a user of the edge gateway based on the operation status of the edge gateway and the operation status of the edge devices, and the suggestion information includes any one of an edge device use suggestion, an edge device sharing suggestion, and an edge gateway service resource sharing suggestion.

Abstract: Disclosed is an adaptive deep learning inference system that adapts to changing network latency and executes deep learning model inference to ensure end-to-end data processing service latency when providing a deep learning inference service in a mobile edge computing (MEC) environment. An apparatus and method for providing a deep learning inference service performed in an MEC environment including a terminal device, a wireless access network, and an edge computing server are provided. The apparatus and method provide deep learning inference data having deterministic latency, which is fixed service latency, by adjusting service latency required to provide a deep learning inference result according to a change in latency of the wireless access network when at least one terminal device senses data and requests a deep learning inference service.

Abstract: The present invention relates to an image collection sensor device, an unmanned counting edge computing system and method using the same, and more particularly, to an image collection sensor device capable of providing a high-precision unmanned counting service using a low-power wireless image collection sensor device operated by a battery by analyzing unmanned counting result data that counts the number of persons included in image data, determining image sensor parameters of the image data, and adjusting a collection cycle and collection image quality of image sensor data according to environmental changes in a sensing area.

Abstract: Disclosed are an anti-fingerprint film for automobile interiors and methods of producing the same. The anti-fingerprint film for automobile interior parts may include a base layer and an outermost layer located on the base layer including a fluorine-based compound, thus reducing the attachment area of the fingerprint composed of water and oil by virtue of the outermost layer having high water and oil repellency, ultimately removing fingerprint visibility.

Abstract: Disclosed are an anti-fingerprint film for automobile interiors and methods of producing the same. The anti-fingerprint film for automobile interior parts may include a base layer and an outermost layer located on the base layer including a fluorine-based compound, thus reducing the attachment area of the fingerprint composed of water and oil by virtue of the outermost layer having high water and oil repellency, ultimately removing fingerprint visibility.

Abstract: Disclosed is an adaptive deep learning inference system that adapts to changing network latency and executes deep learning model inference to ensure end-to-end data processing service latency when providing a deep learning inference service in a mobile edge computing (MEC) environment. An apparatus and method for providing a deep learning inference service performed in an MEC environment including a terminal device, a wireless access network, and an edge computing server are provided. The apparatus and method provide deep learning inference data having deterministic latency, which is fixed service latency, by adjusting service latency required to provide a deep learning inference result according to a change in latency of the wireless access network when at least one terminal device senses data and requests a deep learning inference service.

Abstract: Provided are a system and method for providing a microservice-based device control interface. The system for providing a microservice-based device control interface includes a Docker registry server in which resources required for providing a device control interface are located and a gateway which receives and installs resources and provides a device control interface using a Docker-based microservice structure.

Abstract: Provided are a system and method for providing a microservice-based device control interface. The system for providing a microservice-based device control interface includes a Docker registry server in which resources required for providing a device control interface are located and a gateway which receives and installs resources and provides a device control interface using a Docker-based microservice structure.

Abstract: In the present invention, by providing a device for determining a state of an optical network terminal line including: an optical signal transfer interface configured to transfer a downlink signal transmitted from an optical line terminal to an optical network terminal line and to transfer an uplink signal transmitted from an optical network terminal connected to the optical network terminal line to the optical line terminal; an optical signal transmitter configured to transmit an optical signal to the optical signal transfer interface; an optical signal receiver configured to receive the downlink signal through the optical signal transfer interface, to receive a reflected signal corresponding to the optical signal, and to detect intensity of the downlink signal and the reflected signal; a signal converter configured to convert the reflected signal from an analog form to a digital form; a signal processor configured to analyze the reflected signal of a digital form and to determine the state of the optical ne

Abstract: A terminal status monitoring apparatus connected to a terminal at an optical subscriber side in an optical network is provided. A signal transferring unit transfers a downlink optical signal to the terminal and receives, as a reflected optical signal, the downlink optical signal which is reflected at the terminal. A signal receiving unit measures an intensity of the reflected optical signal. A signal processing unit determines a connection status of a terminal device at the terminal by comparing an intensity of the downlink optical signal with the intensity of the reflected optical signal. A signal output unit outputs the connection status.

Abstract: A terminal status monitoring apparatus connected to a terminal at an optical subscriber side in an optical network is provided. A signal transferring unit transfers a downlink optical signal to the terminal and receives, as a reflected optical signal, the downlink optical signal which is reflected at the terminal. A signal receiving unit measures an intensity of the reflected optical signal. A signal processing unit determines a connection status of a terminal device at the terminal by comparing an intensity of the downlink optical signal with the intensity of the reflected optical signal. A signal output unit outputs the connection status.

Abstract: Provided is an optical distribution network (ODN) including an optical cable and an optical node, and more particularly, an optical distribution network including an optical cable and an optical node, wherein the optical node is implemented to acquire and analyze information regarding the optical cable through an optical connector included in the optical cable, and an operating method thereof. The ODN includes an optical cable and an optical node connectable to the optical cable, wherein the optical cable has an optical connector capable of being joined to the optical node, and the optical connector has an electronic tag configured to store identification information of the optical cable and a first connection pin configured to electrically connect the electronic tag and the optical node.

Abstract: Disclosed are a method and system for determining and controlling power of an optical transmitter of an optical network unit (ONU) for a time and wavelength division multiplexing passive optical network (TWDM-PON). The system includes an RSSI collector configured to collect received signal strength indication (RSSI) information from upstream optical signals received from the ONUs connected to optical line terminal (OLT) ports, an ONU power level determiner configured to gather the pieces of RSSI information about the ONUs from the RSSI collector, and to determine power of optical transmitters of the ONUs based on the gathered information, and a power mode controller configured to receive power mode setting information of the optical transmitters of the ONUs from the ONU power level determiner, and to generate a physical layer operation and maintenance (PLOAM) message to control power modes of the ONUs based on the received power mode setting information.

Abstract: Provided are an electronic device, a smart label, and an optical network management apparatus using the same. The optical network management apparatus includes one or more smart labels respectively equipped in ports and cables to work and a terminal device configured to transmit control signals, which control smart labels respectively equipped in a port and a cable to work among the one or more smart labels, to smart labels respectively equipped in the port and the cable to work.

Abstract: Disclosed are a method and system for determining and controlling power of an optical transmitter of an optical network unit (ONU) for a time and wavelength division multiplexing passive optical network (TWDM-PON). The system includes an RSSI collector configured to collect received signal strength indication (RSSI) information from upstream optical signals received from the ONUs connected to optical line terminal (OLT) ports, an ONU power level determiner configured to gather the pieces of RSSI information about the ONUs from the RSSI collector, and to determine power of optical transmitters of the ONUs based on the gathered information, and a power mode controller configured to receive power mode setting information of the optical transmitters of the ONUs from the ONU power level determiner, and to generate a physical layer operation and maintenance (PLOAM) message to control power modes of the ONUs based on the received power mode setting information.

Abstract: A fast protection switching method for a Passive Optical Network (PON). When performing protection switching from an operation link (an operation network) to a protection link (a protection network) in a PON, the fast protection switching method enables rapidly updating Equalization Delay (EqD) values, even if the EqD values are different for Optical Network Terminals (ONTs) of varying distances.

Abstract: Provided is a method of saving power in a passive optical network (PON) system including an optical line terminal (OLT) and a plurality of optical network units (ONUs), the OLT including an optical transceiver to communicate with at least one ONU through an optical line, and a controller to control the optical transceiver to transmit an upstream bandwidth map to the ONU at a predetermined transmission interval, wherein the transmission interval is determined based on a desired upstream data service delay time.

Abstract: Disclosed are a method and system for determining and controlling power of an optical transmitter of an optical network unit (ONU) for a time and wavelength division multiplexing passive optical network (TWDM-PON). The system includes an RSSI collector configured to collect received signal strength indication (RSSI) information from upstream optical signals received from the ONUs connected to optical line terminal (OLT) ports, an ONU power level determiner configured to gather the pieces of RSSI information about the ONUs from the RSSI collector, and to determine power of optical transmitters of the ONUs based on the gathered information, and a power mode controller configured to receive power mode setting information of the optical transmitters of the ONUs from the ONU power level determiner, and to generate a physical layer operation and maintenance (PLOAM) message to control power modes of the ONUs based on the received power mode setting information.

Abstract: Disclosed herein is an apparatus and method for detecting an optical line fault in a Passive Optical Network (PON). The apparatus includes an optical distribution unit configured to, when a multiplexed signal of a downstream light signal and a monitoring light signal is input, distribute the multiplexed signal to an Optical Network Unit (ONU) of a first optical path and to a second optical path. An optical layer management unit is installed in the second optical path and is configured to set a time at which the monitoring light signal of the multiplexed signal provided to the second optical path is received to a starting time of monitoring light measurement, compare a monitoring light signal reflected and returned from the ONU with a signal pattern obtained when no fault occurs, and then determine whether a fault has occurred in a distribution network.