Abstract: An acute kidney injury predicting system and a method thereof are proposed. A processor reads the data to be tested, the detection data, the machine learning algorithm and the risk probability comparison table from a main memory. The processor trains the detection data according to the machine learning algorithm to generate an acute kidney injury prediction model, and inputs the data to be tested into the acute kidney injury prediction model to generate an acute kidney injury characteristic risk probability and a data sequence table. The data sequence table lists the data to be tested in sequence according to a proportion of each of the data to be tested in the acute kidney injury characteristics. The processor selects one of the medical treatment data from the risk probability comparison table according to the acute kidney injury characteristic risk probability.

Abstract: A graded early warning system for pest quantity counting includes: at least one image capturing device used to capture images of at least one pest trapping device in an environment to generate at least one pest trapping image; at least one environment monitoring and sensing device used to detect the environment to generate at least one environment parameter; at least one pest detecting and identifying device used to detect quantities and species of multiple pests based on the at least one pest trapping image; and a cloud server used to receive the at least one pest trapping image, the at least one environment parameter, and the quantities and species of multiple pests; wherein the cloud server immediately establishes pest probability models, generates early warning signals, and prompts suppression decisions according to the at least one environment parameter and the quantities and species of multiple pests.

Abstract: A graded early warning system for pest quantity counting includes: at least one image capturing device used to capture images of at least one pest trapping device in an environment to generate at least one pest trapping image; at least one environment monitoring and sensing device used to detect the environment to generate at least one environment parameter; at least one pest detecting and identifying device used to detect quantities and species of multiple pests based on the at least one pest trapping image; and a cloud server used to receive the at least one pest trapping image, the at least one environment parameter, and the quantities and species of multiple pests; wherein the cloud server immediately establishes pest probability models, generates early warning signals, and prompts suppression decisions according to the at least one environment parameter and the quantities and species of multiple pests.

Abstract: A feeding analysis system of milk-production livestock includes a plurality of image analysis devices and a central server signally connected to each image analysis device. Each image analysis device is configured to capture a plurality of images of a feeding field, perform a clear processing on the images, identify a plurality of facial images of the plurality of milk-production livestock for feeding action from the cleared images and generate a plurality of capturing signals by capturing the plurality of facial images and a feeding duration corresponding to the facial images, and transmit the capturing signals to the central server. The central server is configured to receive the capturing signals, identify the milk-production livestock identities of the facial images of the corresponding capturing signal and generate a feeding record by integrating the identified milk-production livestock identity and the feeding duration of the capturing signal.

Abstract: A pest surveillance system comprising at least one pest monitoring apparatus and a main server is provided. The pest monitoring apparatus comprises an image capturing device, an environmental status sensing device, a controller and a network transmitter. The at least one pest monitoring apparatus is disposed in at least one space. The image capturing device is used for capturing an image of a pest catcher and generating an original image. The environmental status sensing device is used for detecting environmental status and generating an environmental parameter. The network transmitter is coupled to a network. The main server is connected to the network and receives the at least one original image and the at least one environmental parameter. An image processor of the main server calculates each original image according to each environmental parameter and generates a pest status data.

Abstract: A dairy cowshed monitoring system includes a cooling system having a plurality of operating modes, at least one image sensor, at least one temperature/humidity sensor, and a control circuit. The image sensor is for collecting image data in a dairy cowshed and obtaining a cow drinking water frequency in the dairy cowshed. The temperature/humidity sensor is for collecting a temperature and a humidity in the dairy cowshed and calculating a temperature/humidity index according to the temperature and the humidity. The control circuit is coupled to the cooling system, the image sensor and the temperature/humidity sensor and for receiving the image data, the cow drinking water frequency and the temperature/humidity index and determining whether to activate and control the cooling system in one of the operating modes to cool the dairy cowshed according to the cow drinking water frequency and the temperature/humidity index.

Abstract: A pest surveillance system comprising at least one pest monitoring apparatus and a main server is provided. The pest monitoring apparatus comprises an image capturing device, an environmental status sensing device, a controller and a network transmitter. The at least one pest monitoring apparatus is disposed in at least one space. The image capturing device is used for capturing an image of a pest catcher and generating an original image. The environmental status sensing device is used for detecting environmental status and generating an environmental parameter. The network transmitter is coupled to a network. The main server is connected to the network and receives the at least one original image and the at least one environmental parameter. An image processor of the main server calculates each original image according to each environmental parameter and generates a pest status data.

Abstract: The weight measurement instrument includes a support frame, a plant holder, and a load cell. The plant holder is assembled with the support frame and has an upper opening and a lower opening, a hydroponic plant can be planted in the plant holder and grow towards the upper opening and the lower opening; the load cell is fixed with the support frame and is used for measuring the total weight of the hydroponic plant automatically. A method for measuring the total weight of the hydroponic plant automatically is also provided.

Abstract: The weight measurement instrument comprises a support frame, a plant holder, and a load cell. The plant holder is assembled with the support frame and has an upper opening and a lower opening, a hydroponic plant can be planted in the plant holder and grow towards the upper opening and the lower opening; the load cell is fixed with the support frame and is used for measuring the total weight of the hydroponic plant automatically. A method for measuring the total weight of the hydroponic plant automatically is also provided.

Abstract: An image reconstruction method adapted to use with a planting bed is provided. The planting bed is constituted by a work platform disposed on a work plane and for supporting a plurality of plants thereon. The image reconstruction method includes steps of: capturing a plurality of images of the work platform from different positions on a monitoring plane to obtain a plurality of image data, wherein the monitoring plane is opposite to the work plane, the monitoring and work planes are parallel to each other in a visible range and have a predetermined distance therebetween; and performing an image stitching algorithm to stitch the image data into a two-dimensional image of the planting bed. A monitoring system of a planting bed is also provided.

Abstract: An exemplary locomotion analysis method includes steps of: acquiring a depth map including an image of a measured object, filtering out a background image of the depth map according to a depth threshold, finding out the image of the measured object from the residual image of the depth map, calculating three-dimensional (3D) coordinates of the measured object according to the image of the measured object has been found out, recording the 3D coordinates to reconstruct a 3D moving track of the measured object and performing a locomotion analysis of the measured object according to the 3D moving track. Moreover, an exemplary locomotion analysis apparatus applied to the above method also is provided.

Abstract: A bio-information monitoring system is provided. The bio-information monitoring system comprises a wireless sensor and a first wireless network node. The wireless sensor senses at least a bio-information. The first wireless network node collects the bio-information, wherein the bio-information is monitored in response to a command from a second wireless network node to the first wireless network node.

Abstract: The present invention provides a method for labeling a living organism by laser engraving, the method comprising fixing the living organism to a fixation device, coating whole or a part of body surface of the living organism with a paint operable to react with a laser; and reacting the paint with the laser to make a label by color alteration of the paint.

Abstract: A structure of a planting bed includes at least a work platform, a plurality of first and second supporting rods, a sliding track and an image capture apparatus. The first work platform is disposed on a work plane for supporting a plurality of plants. The first supporting rods each extend in a first direction. The second supporting rods are disposed on the work plane and around the work platform to support the work platform on the work plane, and each are connected to two adjacent first supporting rods. The sliding track is disposed on a monitoring plane and extends in a second direction. The sliding structure extends in a third direction and an end thereof is disposed on the sliding track. The image capture apparatus is installed to the sliding structure for capturing images at different positions on the work platform while the sliding structure is being driven to slide.

Abstract: An image reconstruction method adapted to use with a planting bed is provided. The planting bed is constituted by a work platform disposed on a work plane and for supporting a plurality of plants thereon. The image reconstruction method includes steps of: capturing a plurality of images of the work platform from different positions on a monitoring plane to obtain a plurality of image data, wherein the monitoring plane is opposite to the work plane, the monitoring and work planes are parallel to each other in a visible range and have a predetermined distance therebetween; and performing an image stitching algorithm to stitch the image data into a two-dimensional image of the planting bed. A monitoring system of a planting bed is also provided.

Abstract: An exemplary locomotion analysis method includes steps of: acquiring a depth map including an image of a measured object, filtering out a background image of the depth map according to a depth threshold, finding out the image of the measured object from the residual image of the depth map, calculating three-dimensional (3D) coordinates of the measured object according to the image of the measured object has been found out, recording the 3D coordinates to reconstruct a 3D moving track of the measured object and performing a locomotion analysis of the measured object according to the 3D moving track. Moreover, an exemplary locomotion analysis apparatus applied to the above method also is provided.

Abstract: A positioning method for a sensor node is provided, and the method includes steps of: providing a first antenna having a first omnidirectional radiation pattern on a first plane; rotating the first antenna about an axis substantially parallel to the first plane; transmitting a wireless signal while the first antenna rotates about the axis for every a predetermined central angle; receiving the wireless signal at the sensor node; obtaining Received Signal Strength Indications (RSSIs) of the respective wireless signals; and determining a location of the sensor node according to the RSSIs.

Abstract: An inspection apparatus for tomographing an object includes a moving unit and a rotating unit, which is disposed on the moving unit and rotates the object to be tomographed. A method for tomographing an object includes steps of disposing an object on an inspection apparatus; rotating the object by operating the inspection apparatus; and tomographing the object.

Abstract: A positioning method for a sensor node is provided, and the method includes steps of: providing a first antenna having a first omnidirectional radiation pattern on a first plane; rotating the first antenna about an axis substantially parallel to the first plane; transmitting a wireless signal while the first antenna rotates about the axis for every a predetermined central angle; receiving the wireless signal at the sensor node; obtaining Received Signal Strength Indications (RSSIs) of the respective wireless signals; and determining a location of the sensor node according to the RSSIs.

Abstract: A bio-information monitoring system is provided. The bio-information monitoring system comprises a wireless sensor and a first wireless network node. The wireless sensor senses at least a bio-information. The first wireless network node collects the bio-information, wherein the bio-information is monitored in response to a command from a second wireless network node to the first wireless network node.