137 results about "Growth monitoring" patented technology

The invention relates to an IoT (Internet of things)-based sheep growth monitoring and information service cloud platform comprehensive system, which comprises an information service cloud platform, the internet, subscriber terminal equipment, an IoT intelligent control integrated machine and a sheep growth condition acquisition device; the sheep growth condition acquisition device is connected with the IoT intelligent control integrated machine; the IoT intelligent control integrated machine is respectively connected with the information service cloud platform and the subscriber terminal equipment through the internet. The IoT-based sheep growth monitoring and information service cloud platform comprehensive system disclosed by the invention has the beneficial effects that a growth archive of noncontact measurement (body length, body height, body temperature and weight) and automatic recording is established for sheep; suspected diseased sheep can be discovered in advance by body temperature measurement, and early discovery and early isolation are achieved, so that the infection and spread of an epidemic disease are reduced; arrangement is performed on growth information by the information service cloud platform, a data source can be provided for mutton tracing, and a basis is provided for a specialist and a manager to adjust sheep farming flows; the IoT-based sheep growth monitoring and information service cloud platform comprehensive system also has a remote sheep catching function and a weight estimation function.

The invention provides a lesion tissue growth monitoring method and system. The method includes the steps that inductive shear waves for deformation of a lesion tissue area are acquired, and an elastic image of lesion tissue is acquired according to the inductive shear waves; point-by-point matching is performed for an ROI area of the elastic image, pixel points in the area are tracked, and an elastic information image of the ROI area is constructed; the hardness attribute of the lesion tissue in the elastic information image is determined; the infiltration degree of the elastic information image is tracked, and the range of the infiltration tissue area is determined; the infiltration growth characteristic parameters of the lesion tissue are acquired according to the elastic information image, the hardness attribute and the infiltration tissue area range; the growth of the lesion tissue is monitored according to the infiltration growth characteristic parameters of the lesion tissue. Through the technical scheme, elastic information of the lesion tissue can be represented completely, the benign/malignance mass classification precision is high, the tumor growth monitoring accuracy is high, and an important basis is provided for pathological research on tumors and early diagnosis and treatment of tumors.

The invention discloses a dynamic visualization method and system based on big education data. The method comprises the steps that massive teaching process data is collected from an on-line teaching platform; the collected education data is transmitted to a server to be stored, and an education data base is formed; dimension reduction processing is conducted on high-dimensional data in the data base; according to a request of a visualized display terminal, the dimension needing to be presented is queried, and the corresponding data is mined out from a data storage layer, wherein the visualized display terminal is used for dividing the big education data into different dimensions according to the requirements of different users and conducting visualized displaying on a result fed back by the server. According to the method and system, massive complex big education data is displayed in a simple, efficient and visual mode, and the difficult problems such as teaching process quality management, student study and growth monitoring and intelligent education management decision making are assisted to be solved.

The invention relates to a method for obtaining a shrub branch length based on a digital image technology. A device capable of accurately obtaining plant fractal characteristics is designed through the method by using digital images obtained by a digital camera, a computer image processing method and a fractal characteristic method, and a method for obtaining a shrub branch length according to the dimensions of a plant fractal box is given out; and the plant branch length can be quickly, completely and accurately obtained through the analysis of the image fractal characteristics. The method provided by the invention provides a novel train of thought to quantitatively research the growth dynamic characteristics of an over-ground part of a desert shrub, has a great significance to the promotion of the development and completion for accurately and quickly obtaining the dynamic growth monitoring statuses of desert plants in the wild, and overcomes the shortcoming in a method for continuously measuring the growth of over-ground organs of plants.

The invention relates to the technical field of image processing and discloses a method for three-dimensionally reconstructing a tender shoot state of tea by combining an image and a computation model. The method comprises the following steps of: acquiring a tea digital image; after the spatial switching of color, segmenting the tender shoots of the tea image by an improved algorithm based on color and region growth; calculating three-dimensional coordinates of the tender shoots by the image of the segmented tender shoots of the tea and extracting all characteristic parameters; matching and calculating according to a data model base of the leaf shapes of the tea; and three-dimensionally reconstructing the tender shoots of the tea through VC++ by combining the image. Test results prove that the method avoids a large amount of calculation, visual effect is good, three-dimensional information of the tender shoots of the tea can be stored well, and the provided modeling method has variability, so the growing of the tender shoots of the tea can be simulated. A new method is proved for the growth monitoring and nondestructive testing of the tea.

Mold growth monitoring and prediction systems and methods for an environment are disclosed. The system includes a processing unit, a temperature sensor, and a humidity sensor. The processing unit obtains a temperature reading and a humidity reading of the environment from the sensors. The processing unit uses an algorithm to determine a probability of mold growth based on the temperature reading, the humidity reading, and a time reading. For example, the algorithm defines an envelope based on temperature, humidity, and one or more species of mold. The envelope substantially separates conditions detrimental to mold growth from conditions conducive to mold growth for the species of mold. The processing unit uses the algorithm to determine whether the temperature reading and the humidity reading fall within detrimental or conducive conditions to mold growth. Based on the conditions, the processing unit either increases or decreases the probability of mold growth.

The invention provides a big data fitting-based method and system for monitoring refractive growth of teenagers. The method comprises the steps of S1, building a big data model of a multi-factor dynamic refractive value; and S2, fitting out a dynamic refractive value of a tester by utilizing the big data model of the multi-factor dynamic refractive value in combination with basic information of the tester according to a naked eye vision detection value of the tester, obtaining reasons of poor vision of the tester, and if the tester needs to be subjected to deep refractive growth monitoring, fitting out a static refractive value of the tester by utilizing the big data model and performing long-term monitoring. By adopting the method and the system, the dynamic refractive value of the tester can be fitted out only by collecting the naked eye vision and the basic information of the tester, and the monitoring mode is simple; and for people needed to be subjected to refractive growth monitoring, the static refractive value of the tester can be fitted out only by detecting dynamic refraction, an adjustment range and various parameters of the biological structure of the eyes of the tester, without use of medicinal liquid for ophthalmoplegia, and the monitoring mode is simple.

The embodiment of the invention provides a crop canopy in-situ growth phenotype monitoring device and a three-dimensional reconstruction method. Through a data acquisition and collection module arranged on a canopy top, an image acquisition module arranged in a canopy, and a fisheye lens arranged on a canopy bottom, the morphological structure data of the top, the interior and the bottom of the canopy of the crop to be detected can be obtained, and the height and the angle of the image obtaining module in the canopy can be adjusted, so that the morphological structure data in the canopy are richer, and finally, the growth monitoring of the canopy of the crop to be monitored is more accurate and overall, and the universality is very good. The canopy growth monitoring device is used for obtaining the morphological structure data of the top, the interior and the bottom of the canopy, the morphological structure data are used for phenotypic analysis and three-dimensional reconstruction after certain pretreatment, the workload is small, the efficiency is high, and the obtained three-dimensional reconstruction model is high in precision.

The invention discloses an IoT based crops growth monitoring device and a monitoring method thereof. The monitoring device comprises monitoring mechanisms, each monitoring mechanism comprises a pedestal and a support bar fixed on the pedestal, the support bar is provided with an electric appliance installation box formed by buckling an upper tapered cover with a lower tapered cover, a part for driving a swing arm to rotate is arranged in the position, adjacent to the lowest side of the upper tapered cover, of the support bar, the swing arm is provided with laser range finders, a part for driving a ultrahigh-definition camera to rotate is arranged in a segment, where the upper tapered cover is positioned, of the support bar, leaf growth condition of crops can be obtained from an image collected by the ultrahigh-definition camera, and data collected by the laser range finders can be used to confirmed the plant height.

The invention adopts the computer vision technology to recognize characteristics of shapes and nodes of sugarcanes for achieving growth monitoring of the sugarcanes or intelligent segmentation of sugarcane varieties containing sugarcane shoots. Firstly, sugarcane images are obtained through a digital device, S components in a hue saturation value (HSV) color space of the sugarcane images are processed through threshold segmentation and mathematical morphology filter to be used as a template, reserve images of H components are segmented by threshold and calculation to obtain a composite image, the composite image is divided into 64 column areas, characteristic index of mass center ratio, roughness ratio, white spot ratio and the like is extracted, the nodes and internode columns are classified and recognized through a support vector machine so as to obtain the relation of the nodes and positions, and the average recognition rate is 93.71%.

The invention relates to the field of an imaging processing technology and discloses a tea image enhancement and division method based on a color characteristic. The tea image enhancement and division method comprises the following steps of: firstly, converting an original tea RGB (Red, Green and Blue) colored image into an HIS (Hue, Intensity and Saturation) color space; carrying out convergence calculation based on a characteristic hue on a hue H and carrying out adjustment and calculation based on an expected value on a saturation S; then, carrying out primary seed selection on hue and saturation parameters, and then carrying out regional growth on the seed region based on the similarity of colors and the connective characteristics of the region; combining a color distance and an edge distance to carry out the growth and the combination of the region; and finally, finishing the division of tea tender shoots. With the adoption of conversion, enhancement and division tests of a tea image color space, a result shows that the algorithm can better keep the color characteristic and can better divide the tea tender shoots from a tea image, so that a new method is provided for growth monitoring and nondestructive testing for teas.

The invention adopts the computer vision technology to recognize characteristics of shapes and nodes of sugarcanes for achieving growth monitoring of the sugarcanes or intelligent segmentation of sugarcane varieties containing sugarcane shoots. Firstly, sugarcane images are obtained through a digital device, hue saturation intensity (HSI) color space conversion is performed on the sugarcane images, color characteristics and threshold segmentation of an H component and an S component are combined, reverse images are segmented by threshold and calculation to obtain a composite image, the composite image is divided into 64 column areas, finally characteristic index of H parameters, S parameters, roughness ratio, white spot ratio and the like is extracted, the nodes and internode columns are classified and recognized through a support vector machine so as to complete recognition of the nodes and positions, and average recognition rate is 94.2%.

The present invention discloses a device and a method used for micro-organism culture and growth monitoring. The device comprises a bracket, a horizontal transmission mechanism, a plurality of dish trays, a mechanical grasping mechanism, a camera module, an upper computer and a controller. The horizontal transmission mechanism is arranged in an annular hollow area of the bracket, the dish trays are arranged on the horizontal transmission mechanism, the mechanical grasping mechanism is arranged on the bracket, and the camera module is arranged on the mechanical grasping mechanism. A micro-organism growth monitoring and processing system used for judging whether micro-organism growth in a culture dish is completed is built in the upper computer, and the controller is respectively electrically connected or communicably connected with the horizontal transmission mechanism, the mechanical grasping mechanism, the camera module and the upper computer. The controller controls movement of the horizontal transmission mechanism, the mechanical grasping mechanism and the camera module, and communicates with the upper computer to complete sorting of microorganisms in the culture dishes on all the dish trays according to growth conditions. The device is simple to control and high in automation program, can effectively improve monitoring efficiency, and greatly reduces economic costs and timecosts.

The invention, which relates to the agricultural growth monitoring system, discloses an intelligent greenhouse agricultural growth monitoring device comprising a plant ecological sensing system, a meteorological environment sensing system, and an equipment control system. The plant ecological sensing system and the meteorological environment sensing system transmit data collected respectively to an upper computer; and the upper computer controls turning on or off of the equipment control system. The plant ecological sensing system consists of a plant stem flow meter, a tree radial growth monitor, a chlorophyll content measuring sensor, a leaf thickness sensor, and a fruit expanding sensor; and the meteorological environment sensing system includes an air temperature sensor, an air humidity sensor, a soil temperature sensor, a soil humidity sensor, a carbon dioxide sensor, an in-greenhouse illumination sensor, an out-greenhouse illumination sensor, an out-greenhouse rain sensor, and an out-greenhouse wind direction and wind speed sensor. Therefore, the optimum growth environment and state of the plant can be guaranteed; the production cost can be saved; and the production energy consumption can be reduced.

The invention discloses a fruit growth monitoring sensor which comprises fixation clips, a force arm transmission fixing device and a displacement sensor. A pair of fixation clips are fixed on both ends of the diameter of a fruit to be measured, and are pivoted with the force arm transmission fixing device through a spindle respectively. The force arm transmission fixing device comprises a pair of first force arm rods connected with a pair of fixation clips, and a tension spring is connected between a pair of first force arm rods. Both ends of the displacement sensor are in lever connection with a pair of first force arm rods through a spindle fulcrum respectively. The sensor is arranged and positioned through the multi-point spindles, and has the advantages of simple structure and easy disassembly. A fixation clip is clamped on a plant fruit through a tension spring at the lower part of a force arm rod, which is fixed and firm, prevents the plant fruit from falling and can realize accurate measurement. The lever principle is used, and the force arms are used for data transmission and conversion. After the displacement sensor on the lower end of the force arms is combined for data conversion, the actual diameter value of the growth of the plant fruit is precisely measured.

The invention discloses an intelligent and efficient facility agriculture growth monitoring system and relates to an agriculture growth monitoring system. The system comprises a plant ecology sensing system, a meteorological environment sensing system and an equipment control system. The plant ecology sensing system and the meteorological environment sensing system transmit acquired data to a host computer. The host computer controls the on/off state of the equipment control system. The plant ecology sensing system comprises a plant sap-flow gauge, a tree radial growth monitoring instrument, a chlorophyll content determination sensor, a blade thickness sensor and a fruit swelling sensor. The meteorological environment sensing system comprises an air temperature and humidity sensor, a soil temperature and humidity sensor, a carbon dioxide sensor, a shed interior light intensity sensor, a shed exterior light intensity sensor, a shed exterior rainfall sensor, and a shed exterior wind-direction and wind-speed sensor. Based on the above system, the growing environment and the growing status of plants are ensured to be optimal. Meanwhile, the production cost is saved and the energy consumption during the production process is lowered.

The invention belongs to the technical field of field crop growth monitoring. The invention discloses a method and a system for identifying green plants in a field crop growth vigor monitoring image.An image monitor is used for monitoring the growth process of field crops, a monitoring image segmentation module is used for carrying out segmentation processing on collected field crop monitoring images through an image segmentation program, an identification program is used for identifying the growth vigor of the field crop images, and a classification program is used for carrying out classification operation on field crop type characteristics; constructing a field crop growth model by using the construction program, and analyzing the growth vigor of the field crops by using the analysis program. The crop growth model is established, the relevance among the natural environment variable, the artificial variable and the growth state in the crop growth process is analyzed, the problem of manual misoperation in the crop planting process is solved on the basis of facts, and agricultural production is guided more accurately.

The invention discloses a method for determining a summer maize canopy SPAD value estimation model based on hyperspectral technology. The method comprises the following steps: establishing a quantitative relationship model among the summer maize canopy SPAD values, a sensitive band and a spectral index by monitoring and analyzing data such as a plant canopy hyper-spectrum and plant canopy leaf SPAD values, analyzing change characteristics of the summer maize plant canopy spectral reflectivity under different SPAD values by the test of a small-scale lysimeter, determining a summer maize plant canopy original spectrum and a response relationship between a first-order differential and the canopy SPAD values, and screening sensitive bands and the optimal spectral index of the summer maize canopy SPAD values monitored during the whole growth period, thereby promoting the application of hyperspectral technology in accurate management and rapid and non-destructive growth monitoring of summermaize water and fertilizer.

The invention provides a method and system for identifying green plants in a field crop growth monitoring image. The method comprises the steps that firstly, color distribution analysis is conducted on image elements in the field crop growth monitoring image in an HSV color space so as to obtain the hue value range and the saturation value range, different from the ranges of other background image elements, of the green plants; secondly, a band-pass filter BPH (H) based on the hue H and a band-pass filter BPS (S) based on the saturation S are constructed so as to achieve the purpose that other background image elements, except the green plants, in the field crop growth monitoring image can be filtered away when the field crop growth monitoring image passes through the band-pass filter BPH (H) and the band-pass filter BPS (S) in sequence, and then the green plants in the field crop growth monitoring image can be identified through an excess green index and a threshold segmentation method. The method and system can correctly identify the green plants in the field crop growth monitoring images shot under the complex weather conditions and the complicated background.

The invention relates to the technical field of agricultural Internet of Things application, in particular to a tomato growth monitoring method and device, and the method comprises the steps: buildinga tomato growth analysis model in advance. The method comprises steps of acquiring environmental monitoring data of tomatoes and video and image information of current growth; when judging that the environment monitoring data exceeds a preset threshold value, sending an early warning prompt to the user terminal; according to the video and image information, sending an early warning prompt to theuser terminal when it is judged that the tomato plant change exceeds a preset change threshold value or the tomato plant has insect pests within a preset time; and importing the image information intoa tomato growth analysis model, and exporting a current growth index of the tomato through analysis and calculation. The method has the advantages that the growth condition of tomato plants is monitored through environment monitoring and video image monitoring to achieve the early warning effect, meanwhile, the growth indexes of tomatoes are analyzed through an algorithm model, and therefore realInternet of Things intelligent planting is achieved.

The invention discloses an escherichia coli dynamic growth monitoring method, and provides a method for realizing registration of an escherichia coli colony image and a previous moment image, which comprises the following steps: enabling the angles of the two images to be consistent, obtaining the centroid position of each colony, and further quickly obtaining the number of colonies in a culture dish; each bacterial colony can be positioned, the size and color information of each bacterial colony at the growth moment is counted, the growth speed is calculated according to the culture time, thegrowth stage of each bacterial colony at each time node is judged, and then a growth curve is obtained; according to the method, a regression model is used for predicting the bacterial liquid concentration according to two variable values of bacterial colony delay period time and growth rate in a logarithmic phase, the bacterial liquid concentration is compared with the concentration obtained bya traditional counting method, and error samples in the experiment process are screened out; based on the characteristics of bacterial colony growth, the regression model is established to accuratelypredict the concentration of the escherichia coli liquid, and compared with the traditional counting method which is easily interfered by the external environment, the method is more accurate, and thereliability of the obtained data is higher.

The invention discloses a ground-air tracking monitoring device for a pesticide spraying helicopter. A pesticide spraying monitoring device in the ground-air tracking monitoring device is used for monitoring the pesticide spraying flow rate, the pesticide concentration, the spraying direction and the residual dose; a pest monitoring device is used for monitoring pest and disease conditions of crops; a growth monitoring device is used for monitoring the type of vegetation and the growth conditions of crops; an environmental monitoring device is used for monitoring the surrounding environment information; a cell phone signal detector is used for monitoring the surrounding cell phone signal; an obstacle monitoring device is used for monitoring the obstacle situation in the front area; and a lower computer processes monitoring information obtained by the pesticide spraying monitoring device, the pest monitoring device, the growth monitoring device, the environmental monitoring device, thecell phone signal detector and the obstacle monitoring device and sends control instructions. The ground-air tracking monitoring device of the invention can realize ground-air tracking and monitoring,expand the monitoring range and realize comprehensive monitoring in the pesticide spraying process.

The invention relates to the technical field of farm irrigation, is used for solving the problem that an existing farm irrigation system cannot check abnormal reasons when crops grow abnormally, and particularly relates to an internet-based farm irrigation analysis control system, which comprises a control platform, the control platform is in communication connection with a spraying execution module, a growth monitoring module, an anomaly analysis module, a spraying analysis module and a storage module, the spraying execution module comprises an annular track water tank, a water inlet pipe is installed on the outer side wall of the annular track water tank, and a plurality of movable water pumps are arranged on the inner side wall of the annular track water tank; sprayers are arranged at the output end of the movable water pump, and the spraying distances of the multiple sprayers are different. According to the invention, through the growth monitoring module, the growth state of the crops can be detected and analyzed according to the growth characteristics of the crops, and the phenomenon that abnormal growth of the crops in individual growth areas is ignored due to the fact that overall growth is qualified is prevented.

The invention belongs to the field of thin film growth monitoring technologies and discloses a chemical vapor deposition monitoring system and method. According to the system, a thin film material isplaced in a chemical vapor deposition device; an optical imaging detection device comprises a femtosecond pulse laser device, a first cylindrical lens, a first virtual imaging phase array, a first diffraction grating, a first microscope objective, a second microscope objective, a second diffraction grating, a second virtual imaging phase array, a second cylindrical lens, a single-mode optical fiber, a photoelectric detector and a high-speed oscilloscope. According to the method, the growing process of the thin film material is monitored in real time through the optical imaging detection device, growing process information of the thin film material is obtained quickly in real time, and growing technological parameters are adjusted in real time to improve the growing quality of a thin film through comparison with data in a sample database. Therefore, the problem that in the prior art, chemical vapor deposition equipment cannot monitor the growing state of the thin film rapidly in real time is solved, and the technical effect that the growing information of the thin film material can be obtained rapidly in real time is achieved.