Abstract: Provided is a grease injection system including a plurality of grease injection devices and a host. The grease injection devices uses control information to output lubricating grease, and output a plurality of pieces of status information. The host receives the pieces of status information from the grease injection devices, and generates the control information based on the pieces of status information.

Abstract: The present disclosure provides an automatic berthing image ranging system for vessels and operation method thereof, the method comprising: obtaining a reference image around a position in which a vessel is located, the reference image comprises a first pattern and at least two second patterns; the reference image is projected to a reference plane to generate projection coordinates corresponding to the first pattern and the at least two patterns; determining a positional relationship between the vessel and a port by a predetermined distance, and the positional relationship is represented by an angle value.

Abstract: The present disclosure provides an automatic berthing image ranging system for vessels and operation method thereof, the method comprising: obtaining a reference image around a position in which a vessel is located, the reference image comprises a first pattern and at least two second patterns; the reference image is projected to a reference plane to generate projection coordinates corresponding to the first pattern and the at least two patterns; determining a positional relationship between the vessel and a port by a predetermined distance, and the positional relationship is represented by an angle value.

Abstract: A data processing method is proposed, including: sensing, via at least one sensing portion, target information of a target device; receiving and processing, via an electronic device, the target information of the sensing portion to form feature information; processing, via the electronic device, the feature information into a label matrix, and establishing, via an artificial intelligence training method, a target model based on the label matrix; and after the electronic device captures real-time information of the target device, predicting, via the target model, a life limit of the target device, wherein a content of the target information is corresponding to a content of the real-time information. Thus, a good target model is constituted and is advantageous in training artificial intelligence by processing the feature information into the label matrix.

Abstract: This invention discloses an inland river Lidar navigation system for vessels, comprising a receiver, a memory, a processor and a display. The processor coupled to the receiver and the memory, and the display coupled to the processor. Overall, the inland river navigation Lidar system based on Lidar is able to make use of the preset map data identification uncalculatable points of a point cloud of the predetermined procedure, thereby removing of the alignment step in traditional method can be omitted. Therefore, the processing speed can be improved.

Abstract: The present invention discloses an autonomous vessel simulation system, comprising an environment model building system, a vessel model building system and a central processing system. The environment model building system builds at least one environment model; the vessel model building system builds at least one vessel model and an operation module of the central processing system integrates the environment model and the vessel model. The vessel model is navigated in the environment model according to at least one navigational parameter, and a display module displays the navigation status of the vessel model. In addition, an operating method of the autonomous vessel simulation system is also provided.

Abstract: A data processing method is proposed, including: sensing, via at least one sensing portion, target information of a target device; receiving and processing, via an electronic device, the target information of the sensing portion to form feature information; processing, via the electronic device, the feature information into a label matrix, and establishing, via an artificial intelligence training method, a target model based on the label matrix; and after the electronic device captures real-time information of the target device, predicting, via the target model, a life limit of the target device, wherein a content of the target information is corresponding to a content of the real-time information. Thus, a good target model is constituted and is advantageous in training artificial intelligence by processing the feature information into the label matrix.