Abstract: The present invention is a vehicle positioning system and a vehicle positioning method for a container yard. The system includes a cloud server and a gate checking device. The gate checking device is communicatively connected to the cloud server, and senses a first vehicle to generate a first gate sensing signal and a second gate sensing signal. The cloud server receives and fuses the first gate sensing signal and the second gate sensing signal to generate first vehicle identity information and first vehicle positioning information. Since the present invention generates the first vehicle identity information and the first vehicle positioning information by fusing at least two sensing signals, the present invention can improve positioning accuracy and reliability by adopting a positioning technology combining multiple factors. Further, there is no need to install a transmitter or a receiver on the vehicle, improving a success rate to install the present invention.

Abstract: A cargo container image capturing method and system applied to a bridge crane are provided. The cargo container image capturing method includes the following steps. A human-machine interface (HMI) image of an HMI of the bridge crane is captured. Several values are obtained from the HMI image using an image recognition algorithm. At least one camera is controlled to capture a cargo container image according to the values.

Abstract: An image analysis apparatus rectifies a first image and a second image to generate a first rectified image and a second rectified image respectively. A first container door in the first rectified image and a second container door in the second rectified image have the same sizes and the same pixel coordinates. The image analysis apparatus divides the first rectified image into a plurality of first blocks and divides the second rectified image into a plurality of second blocks in a same manner. The image analysis apparatus calculates respective correlations between every first block and its corresponding second block. Each of the correlations includes a grayscale correlation and at least one color correlation. The image analysis apparatus determines whether the first container door and the second container door represent the same container door based on the correlations.

Abstract: An image analysis apparatus rectifies a first image and a second image to generate a first rectified image and a second rectified image respectively. A first container door in the first rectified image and a second container door in the second rectified image have the same sizes and the same pixel coordinates. The image analysis apparatus divides the first rectified image into a plurality of first blocks and divides the second rectified image into a plurality of second blocks in a same manner. The image analysis apparatus calculates respective correlations between every first block and its corresponding second block. Each of the correlations includes a grayscale correlation and at least one color correlation. The image analysis apparatus determines whether the first container door and the second container door represent the same container door based on the correlations.

Abstract: Disclosed is a system for controlling terminal equipment comprising at least one terminal equipment, a gateway and a method for adding new terminal equipment. The terminal equipment uses a communication protocol. The gateway is coupled to the terminal equipment for generating a constructive command corresponding to at least one terminal equipment having a diversity of communication formats. The gateway has a read API, a write API, a command generating unit and a configuration file. The configuration file comprises read-write commands for the terminal equipment. The gateway generates the constructive command corresponding to the terminal equipment according to the configuration file. The communication generating unit of the gateway uses the constructive command to control or access the terminal equipment through the read API or the write API. Accordingly, terminal equipment can be easily added for being controlled by the gateway.

Abstract: A gateway, a power device controlling method and a power device information obtaining method are provided. A storage of the gateway includes at least one user queue and a power device queue. The gateway arranges at least one control command received from at least one user apparatus into the power device queue in a first-in-first-out manner so that a power device executes the at least one control command according to an order of the power device queue and transmits at least one result to the gateway. The gateway arranges the at least one result corresponding to the at least one control command into the at least one user queue and transmits the at least one result of the at least one user queue to the at least one user apparatus.

Abstract: A position estimation system is provided, including at least one measurement unit, a plurality of evaluation units and a particle filter. The at least one measurement unit obtains a first information, wherein the first information at least includes a motion information and a corresponding noise model of a traced object. Each of the evaluation units has a corresponding evaluation model, wherein each evaluation model generates a corresponding unit displacement estimation according to the first information. The particle filter samples and generates a plurality of displacement estimations according to the unit displacement estimations and the corresponding noise models respectively.

Abstract: A motion mode determination apparatus is disclosed, including an inertial device, a frequency decomposition module, a characteristic value generator, a training module and a determination module. The inertial device collects at least a first motion signal corresponding to a first motion mode and at least a second motion signal corresponding to a second motion mode, wherein each of the first and second motion signals includes a first signal, a second signal and a third signal. The frequency decomposition module decomposes the first signal into a first high-frequency signal and a first low-frequency signal. The characteristic value generator generates a plurality of characteristic values, wherein the characteristic values are the means and variances for each group of the first high-frequency signals, the first low-frequency signals, the second signals and the third signals respectively. The training module generates first and second data groups.