1529results about "Using reradiation" patented technology

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

The invention discloses a method for generating an autonomous inspection orthoimage of an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle surveying and mapping and autonomous navigation. Global optimization of an air route is realized through a path optimization strategy fused by a genetic algorithm in combination with grid characteristics of an inspection area and image parameter constraints, and candidate waypoints are used as nodes; redundant waypoints are screened through leg smoothness factors, route complexity is reduced, a genetic algorithm takes flight height and waypoint spacing as constraints, a fitness function containing flight distance, turning times and overlapping rate is constructed, a global optimal path is found through population iteration, multi-target requirements are optimized and balanced, and it is ensured that the route meets the image acquisition precision requirement and also meets the requirement of image acquisition. The flight distance can be shortened, the turning frequency is reduced, the cruising ability of the unmanned aerial vehicle is adapted, efficient propelling of the inspection task is guaranteed, meanwhile, waypoint coordinates output through simulation directly adapt to a flight control system, and it is guaranteed that actual flight parameters are consistent with planning parameters.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Access control system (1) for buildings (2) with a stationary unit (20) and a mobile unit (10), wherein the mobile unit (10) has a mobile transceiver (11) which is designed to transmit wirelessly and encrypted signals (S) for authentication and authorization of the mobile unit (10) with respect to the stationary unit (20) and for control of the stationary unit (20) by the mobile unit (10) to a stationary transceiver (21) of the stationary unit (20), wherein the stationary unit (20) comprises a control device (22) which is designed to determine a respective position (51 - 57) of the mobile unit (10) relative to the stationary unit (20) from the signals (S) transmitted from the mobile transceiver (11) to the stationary transceiver (21) at predetermined time intervals, to determine a movement path (50) of the mobile unit (10) from the chronologically successively determined positions (51 - 57) of the mobile unit (10) and to determine from the movement path (50) and a predetermined target position a probability with which a function is to be triggered when the mobile unit (10) approaches the target position, wherein the control device (22) is further configured to compare the probability with a predetermined threshold value and to trigger the function if the probability exceeds the threshold value.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Access control system (1) for buildings (2) with a stationary unit (20) and a mobile unit (10), wherein the mobile unit (10) has a mobile transceiver (11) which is designed to transmit wirelessly and encrypted signals (S) for authentication and authorization of the mobile unit (10) with respect to the stationary unit (20) and for control of the stationary unit (20) by the mobile unit (10) to a stationary transceiver (21) of the stationary unit (20), wherein the stationary unit (20) comprises a control device (22) which is designed to determine a position of the mobile unit (10) relative to the stationary unit (20) from the signals (S) transmitted from the mobile transceiver (11) to the stationary transceiver (21) and to control a function if a control command for triggering the function is transmitted to the stationary unit (20) by a mobile unit (10) authenticated and authorized by the stationary unit (20) and / or the position of the mobile unit (10) is within a predetermined access area (30), and wherein the control device (22) is designed to determine an angle (ϕ) from which the signals (S) were received from the signals (S) transmitted from the mobile transceiver (11) to the stationary transceiver (21), to determine a measured distance (rg) between the stationary transceiver (21) and the mobile transceiver (11) from a signal (S) received at the stationary transceiver (21) from the mobile transceiver (11) and from the measured distance (rg) and a vertical distance (rv) stored as a correction value in the control device (22) between the stationary transceiver (21) and the mobile transceiver (11), to determine a horizontal distance between the stationary transceiver (21) and the mobile transceiver (11) in the polar coordinate system lying in the horizontal plane as a distance (r) from which the signals (S) were received, so that the position of the mobile unit (10) can be specified as polar coordinates of a polar coordinate system lying in a horizontal plane, in whose coordinate origin the stationary transceiver (21) is arranged.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

The invention relates to the technical field of remote sensing surveying and mapping, in particular to a terrain recognition and three-dimensional reconstruction method based on a remote sensing surveying and mapping image, which comprises the following steps of: recognizing and selecting a key spectral band based on a remote sensing image, adjusting the configuration of a spectral filter, extracting key terrain data according to configuration data, and analyzing terrain change by utilizing terrain feature data. And recording related wave bands and positions, forming a comparison table, and combining natural colors and surface texture analysis to generate a three-dimensional model of the terrain. According to the method, the key spectrum sections are screened by adopting the preferable waveband index, the specificity and efficiency of data acquisition are improved, the spectral response section is accurately adjusted, it is ensured that a spectral region with remarkable earth surface reflection characteristics is focused on, and the practical value of spectral data is improved; the spectral configuration data optimizes the response performance of the sensor so that the data collected from the terrain is more sensitive and accurate.

The embodiment of the invention provides a multi-unmanned aerial vehicle cooperative surveying and mapping method and system for areas along a railway, and belongs to the technical field of railway surveying and mapping. The method comprises the steps that the unmanned aerial vehicle collects monitoring data in the flight process; the relative position and posture between the aircrafts are dynamically adjusted, and an observation configuration with variable baseline parameters is constructed; laser ranging modules carried by the unmanned aerial vehicles are controlled to execute synchronous ranging operation, and multiple sets of laser point cloud data covering the railway structure area are generated; performing coordinate registration and fusion on the collected laser point cloud data, and combining position information and attitude information of each unmanned aerial vehicle; and extracting geometric dimension parameters of the railway structure from the compensated three-dimensional model, and outputting the geometric dimension parameters as measurement results. According to the scheme, high-precision non-contact measurement of geometric dimension parameters such as the track gauge, the height difference and the roll angle of a railway track structure is achieved.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

The invention relates to the technical field of track foreign matter real-time detection, and particularly discloses a track foreign matter real-time detection method based on YOLOv5 improvement. Comprising the steps of video vibration synchronous acquisition, space offset compensation parameter generation, dynamic feature enhancement processing, feature weight thermodynamic diagram generation, hierarchical perception feature aggregation, cross-scale target verification, foreign matter positioning instruction packaging and multistage early warning execution control. Image distortion caused by mechanical vibration and illumination fluctuation is effectively overcome by synchronously acquiring track video and vibration time sequence signals, constructing a spatial offset compensation parameter set and combining with a dynamic feature enhancement template to correct video frames, a feature weight thermodynamic diagram is generated through visual saliency detection, features are aggregated through a layered perception model, and the visual saliency detection accuracy is improved. Early warning levels are dynamically matched according to the sizes and the positions of the foreign matters, and a sound-light alarm and braking system is linked; according to the invention, the reliability of data transmission is ensured, the operation and maintenance cost is greatly reduced, and the safety requirement of millisecond response of modern rail transit is met.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

The invention relates to the technical field of pavement disease automatic detection, and particularly discloses a pavement disease automatic detection method and system based on deep learning, and the system comprises a municipal pavement data collection module, a pavement image quality analysis module, a pavement image re-collection module, a pavement disease evaluation feedback module and a database. Flight parameters (speed and height) are dynamically adjusted through an environmental quality index (EQI), the image acquisition quality is ensured, the detection precision in a complex environment is improved, a multi-disease coupling risk model is constructed, region weight and traffic volume dynamic weight are integrated, a disease risk level is output, and finally a disease development trend is predicted through a one-time exponential smoothing method. The system achieves the dual functions of current situation evaluation and trend early warning, predicts the disease evolution trend based on historical data, remarkably improves the scientificity and timeliness of municipal road risk management, reduces the maintenance cost, and prevents safety accidents.

An autonomous vehicle system includes a vehicle including a base assembly having a front surface, a rear surface opposite the front surface, and side surfaces extending between the front surface and the rear surface. A sensor system is coupled to the base assembly and configured to detect one or more objects located in an area near the vehicle. The sensor system includes a first sensor oriented parallel with at least one of the front surface, the rear surface, or the side surfaces, and a second sensor oriented non-parallel with the front surface, the rear surface, and the side surfaces. A control system is configured to receive a communication regarding the detection of the one or more objects from the sensor system and generate one or more controls for at least one of the base assembly or one or more tractive elements.

The invention discloses a hydropower station diversion tunnel longitudinal crack depth detection method, which comprises the following steps: arranging ultrasonic measuring points above and below a diversion tunnel longitudinal crack to obtain a reinforced concrete sound velocity representative value; arranging ultrasonic measuring points within the length range of the crack; performing ultrasonic detection, and judging the depth of the crack through ultrasonic waves; adjusting the position of the ultrasonic measuring point according to the depth of the fracture until the ultrasonic shape is in a suitable state; and calculating the depth of each detection point of the longitudinal crack. According to the technical scheme, by means of the method for detecting the longitudinal crack depth of the reinforced concrete in the diversion tunnel of the hydropower station through the ultrasonic waves, crack depth detection and calculation of the circular tunnel are completed, and in order to judge the development condition and the stability state of the crack, the crack depth can be regularly detected in the overhaul period of a hydropower station generator set; therefore, monitoring of longitudinal crack expansion and extension is realized.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.

Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.