55results about How to "Reduce the amount of data collected" patented technology

The invention relates to map construction and application, and belongs to the technical field of map construction. The map construction method comprises the steps of successively collecting road image information on a road by multiple vehicles running on the road, and obtaining locating information at a position point where the road image information is collected; extracting road information from the road image information; uploading the road information and the corresponding locating information obtained by the vehicles through the vehicles; and generating or updating road map information on the road based on the road information and the corresponding locating information of the vehicles.

The invention belongs to the technical field of vehicle-mounted GPS (global position system) navigation and particularly relates to a self-adapting correction method for long sampling interval GPS data mileage calculation. The self-adapting correction method is generally applicable to a remote information management system of a vehicle. The self-adapting correction method comprises the following steps that 1), GPS sampling data is subjected to real-time processing; 2), a GPS dead signal zone is compensated; 3), the mileage calculation is subjected to self-adapting correction; and 4), a calculated mileage is output, wherein the real-time processing comprises the steps that 1-1), a calculation formula of a spherical distance between two points is corrected; 1-2), static shifting data is corrected; and 1-3), dynamic exceptional data is corrected. With the adoption of the self-adapting correction method for processing the GPS sampling data; the data quality is improved; dead zone compensation in a short time is realized; the precision of the mileage calculation is improved on the premise that the cost of a GPS navigation system is not increased; due to the self-adapting correction of the mileage, the precision of the mileage calculation is further improved. A model and an algorithm not only support on-line real-time operation, but also support off-line data processing.

The invention discloses a road-network traffic jam discrimination method based on a macroscopic fundamental diagram. The method comprises the steps that 1) the road network is divided into traffic cells; 2) the macroscopic fundamental diagram of the traffic cells is drafted; 3) critical points of jamming levels are defined in the macroscopic fundamental diagram, and a traffic jamming state is defined; 4) jamming levels of the traffic cells are determined; and 5) the jamming state is output. According to the method, the related data bulk is low, data processing is simple, the jamming state discrimination speed is high, the method can be used to discriminate the jamming state of areas of different ranges and sizes, and the traffic cells are merged and decomposed flexibly to change the jamming discrimination range rapidly.

The invention provides a human body three-dimensional data collecting system and method based on the light coding technology. The human body three-dimensional data collecting system comprises a rotary disc. Supports are arranged on the periphery of the rotary disc, a whole-body scanner, a half-body scanner and a face five-sense-organ scanner are installed on the three supports respectively, data lines at the tail ends of the three scanners are connected into a computer, and a matched software tool for model collecting, fusing, repairing and strengthening is arranged in the computer. The human body three-dimensional data collecting system is simple in structure, low in cost, high in accuracy and short in scanning time, the advantages of the scanners in different types are combined, division operation is adopted, the aim is explicit, and high-accuracy human body characteristic three-dimensional models of the five sense organs of the human body face, the head outline, hair details, the whole-body surface outline and the like can be obtained; a high-accuracy human body three-dimensional model can be obtained by fusing and splicing the characteristic three-dimensional models collected through the different scanners through software, and follow-up model processing is avoided; the multiple scanners work at the same time, and the scanning time is greatly shortened.

The invention relates to a double-focusing ultrasonic probe and sparse array photoacoustic tomography imaging system. Each probe comprises a concave detection face. The numerical value hole diameter of each concave detection face in the first direction is larger than that of the concave detection face in the second direction. A signal receiving angle of each concave detection face in the first direction is larger than that of the concave detection face in the second direction. The focused region length of each concave detection face in the second direction is larger than that of the concave detection face in the first direction. The first direction is perpendicular to the second direction. Each probe has a large signal receiving angle on an imaging fracture surface, and therefore the quality of an image reconstructed by a compressed sensing image reconstructing method under a low sampling rate can be improved. Meanwhile, an annular probe array can be formed in a sparse distribution mode, and cost of the imaging system can be reduced. Data acquisition amount needed by image reconstruction can be reduced, and therefore data acquisition speed and imaging speed are increased.

The invention discloses a multi-variety multi-objective passive locating method based on migration compression perception. The method specifically comprises the following steps: 1, deploying a sensor node; 2, collecting data to prepare for transfer function determination; 3, determining transfer functions of different varieties and objectives; 4, transferring a perception matrix by using the transfer function obtained in the step 3; 5, locating the objectives. The method disclosed by the invention can meet needs of sparse network deployment, low quantity of data acquisition and low energy consumption for wildlife conservation based on the migration compression perception. In comparison with the existing passive locating method, a locating model (perception matrix) is not required to be reconstructed for a newly emerged objective, and then high-precision locating can be finished. The locating method comprises the following outstanding advantages that reconstruction of the locating model, namely the perception matrix usually needs to cost a lot of manpower and material resources, however, the method disclosed by the invention can save the manpower and material resources, and meet the requirement for multi-variety multi-objective wildlife positioning.

The invention discloses a two-stage based automatic calibration and correction method and system for a repeater. The method comprises the following steps: firstly, fixing intermediate frequency; moving a local oscillator to obtain radio frequency gain modifying factors of different frequency points; then fixing the local oscillator; moving the intermediate frequency to obtain intermediate frequency modifying factors of different frequency points; and finally removing mutually-affecting components of the radio frequency gain modifying factors and the intermediate frequency modifying factors to obtain a total gain modifying factor corresponding to each frequency point. In the two-stage based automatic calibration and correction method and system for the repeater, a link gain control precision is high, the data amount which is collected in a calibration mode is reduced from N*N to 2*N, the data acquisition amount is greatly reduced, the production efficiency is improved, and the production cost is lowered.

The invention discloses a method for reducing a frequency aliasing effect of undersampled magnetic resonance imaging. The method comprises the following steps of (1) obtaining space K through a nuclear magnetic resonance spectrometer and performing undersampling on the original data of the space K by using a random oscillometric method to obtain undersampling data; (2) forming an over-complete dictionary by selecting a sparse method; and (3) performing recovery reestablishment on the undersampled data in the step (1) by using a recovery algorithm according to the over-complete dictionary to obtain original data, performing Fourier transform to obtain images and performing real-time imaging. The random oscillometric method comprises a variable-density oscillating spiral track and a variable-density oscillating radiation track.

The invention discloses an infrared wide-waveband hyperspectral calculation imaging device, which comprises a front-mounted infrared lens, a coding template generator and loader, a reflection-type spatial light modulator, an infrared relay lens set, a unit type spectrum radiometer, an infrared spectrum calculation imaging module and a hardware synchronous controller. The invention further discloses an infrared wide-waveband hyperspectral calculation imaging method. The unit type spectral radiometer has the advantages of being wide in spectral response range and low in system noise. The defectof mechanical scanning is avoided, and the data acquisition amount is reduced; the time needed by imaging is shortened, and the spectral resolution and the spatial resolution are improved. The devicehas the advantages of a fourier spectrum radiometer of being real-time, fast, accurate and highly sensitive, and overcome the defect that a traditional unit non-imaging type infrared imaging spectrummeter is low in mechanical scanning speed and large in data redundancy.

The invention discloses a power station equipment data acquisition method and system. The method comprises the following steps: creating at least one SQLite thread according to equipment information;storing the configuration information of the equipment and the measurement points into an SQLite database; querying equipment information in the SQLite, and classifying the equipment information according to the IP and port information, wherein each type creates a thread; acquiring measurement point configuration information in a single thread according to details of each device; acquiring measurement point data, comparing the acquired measurement point data with a Redis database, and selecting whether to store the measurement point data and report the measurement point data according to a comparison result. According to the method and the system, the timeliness of data transmission of the power station equipment can be effectively improved, the total amount of data transmission can be reduced by collecting the equipment measuring point data in a grading manner, and the network pressure during data transmission is reduced.

The invention belongs to the technical field of optical microscopy imaging, provides a wide-field color light slice microscopy imaging method based on deep learning, and solves the problems that defocusing information is complex, the resolution ratio is poor, SIM-OS imaging needs large-data-volume acquisition and the like in wide-field microscopy imaging. Unique high resolution and panchromatic property of full-color structured light illumination are fully utilized, and a single-width wide-field microscopic imaging result can be used for training. The method is popularized to a wide-field microscopic imaging experiment; according to the method, a light slice component with a wide scene depth and a full-color high-quality image can be directly obtained from a wide-field image, and meanwhile, the method has three-dimensional reconstruction and data analysis capabilities equivalent to those of full-color structured light illumination imaging in spatial resolution and dimension; in addition, the required data volume is sharply reduced compared with that of full-color structured light illumination; according to the method, under the condition that details are not lost, the imaging throughput of an imaging system is remarkably improved by extracting a wide-scene-depth optical slice result and reducing data acquisition, and meanwhile, the phototoxicity pollution risk of the system isreduced.

The embodiment of the invention discloses a vehicle ADAS driving data acquisition method and device, a man-machine interaction device and a vehicle, relates to the technical field of auxiliary driving, and solves the problem that the data volume of ADAS driving data acquired at present is large in the prior art. The method disclosed by the embodiment of the invention mainly comprises the following steps: monitoring real-time driving data of the vehicle advanced auxiliary driving system; judging whether the driving data exceed a preset safety threshold value or not; and if the preset safety threshold value is exceeded, collecting the current driving data of the vehicle. In the driving process of the vehicle, the real-time driving data of the vehicle can be monitored, when the real-time driving data exceed the preset safety threshold value, the current driving data of the vehicle is collected, and compared with a mode of collecting all the driving data, the data collection amount of the driving data of the ADAS can be greatly reduced, the driving data of the ADAS can be conveniently uploaded to a server, and the ADAS data analysis cost is reduced.

The invention discloses a soybean plant rapid three-dimensional reconstruction method based on phenotype-oriented accurate identification, and the method comprises the steps of enabling a user to useKinect to scan a soybean plant, i.e., a soybean plant, at intervals of a set angle, and obtaining a plurality of frames of point cloud scenes where the soybean plant is placed on an automatic rotatingdisc; after removing a point cloud background through straight-through filtering, calculating a rough registration matrix by using a Rodrigs formula according to a rotation angle provided by a user,performing fine registration by using an ICP algorithm, performing hierarchical clustering on plant point clouds to obtain skeleton points, setting each point to be adjacent to nearest K points for the skeleton points to obtain a plurality of connected components, performing trunk Dijkstra path growth, branch growth point selection and branch communication component Dijkstra path growth on trunk communication components where root nodes are located, and finally performing three-dimensional visualization of a plant skeleton through a pyvista visualization library. According to the invention, the plant point cloud does not need to be processed in advance through software to obtain the parameters, the purchase expenditure of modeling software and the learning and using time cost of the modeling software are saved, and the invention is more efficient.

The invention relates to the technical field of intelligent equipment, in particular to monitoring equipment and a vibration abnormality judgment method. The monitoring equipment comprises a vibrationsensor, a processor, a data communication assembly and a power supply assembly. The vibration sensor, the data communication assembly and the power supply assembly are connected with the processor. The vibration sensor is used for collecting vibration information in real time, and the vibration information comprises vibration speed and/or acceleration. The processor is used for calculating the vibration amplitude according to the vibration information collected by the vibration sensor. The data communication assembly sends the vibration amplitude to the server, and the server judges whether the monitoring equipment is abnormal or not according to the received vibration amplitude. The problems that in the prior art, vibration waveforms need to be transmitted to a server, the data collection amount is large, power consumption is large, and resources consumed for transmission are large are solved, and the effects that the data collection amount and the power consumption of monitoring equipment and the resources consumed for transmission can be reduced are achieved.

The invention relates to the technical field of medical apparatuses and instruments and discloses a data collection method for a syringe. The method includes the following steps of providing a first component and a second component which can move relative to each other and generate scale information in the syringe; arranging multiple permanent magnets on the first component at intervals, and arranging at least one Hall sensor on the second component; driving the first component and the second component to move relative to each other, and using the permanent magnets for triggering the Hall sensors to calculate triggering frequency; adopting a microprocessor for generating the scale data according to the triggering frequency. By adopting the triggering frequency of the Hall sensors as recognition information for obtaining the scale data of the dosage of the syringe and forming electronic data information, more convenience is provided for users to store and track the data. The invention also provides the syringe capable of achieving automatic collection and electronization of the scale data of the dosage and providing convenience for the users to store and track the data.