1640results about "Indication/recording movement" patented technology

A system for receiving and temporarily maintaining a delivery item and dynamically initiating a dispatched logistics operation for a storage receptacle. The storage receptacle has an entrance opening for receiving the delivery item, a temporary storage area for temporarily maintaining the delivery item once deposited with the storage receptacle, and a retrieval door providing selective access to the temporary storage area. The system includes a backend server that maintains a management profile related to the storage receptacle, a bridge node mounted to the storage receptacle, and a wireless accessory sensor node having at least one sensor that monitors for a change in state of the storage receptacle. The wireless accessory sensor node broadcasts an updated advertising signal. The bridge node transmits retrieved event information to the backend server at a reporting time, and the backend server initiates the dispatched logistics operation from comparing the retrieved event information to location information.

An enhanced multi-compartment connected logistics receptacle system includes a storage receptacle, a bridge node, and wireless accessory sensor node with a plurality of sensors. A first subset of the sensors is disposed relative to a first monitored receptacle compartment and a second subset of the sensors is disposed relative to a second monitored receptacle compartment. The plurality of sensors monitor for a change in state of the storage receptacle. The wireless accessory sensor node detects the storage receptacle's state change based upon sensor data and broadcasts a signal with a flag set indicating there is event information available for upload. The bridge node detects the flag set, retrieves the event information available for upload from the wireless accessory sensor node, and transmits the retrieved event information to a backend server to cause the backend server to initiate a dispatched logistics operation related to the storage receptacle.

A centrally managed system for tuning a plurality of enhanced node-based logistics receptacles includes a backend server, a first enhanced node-based logistics receptacles, and a second node-based logistics receptacles. The backend server transmits a first setup message to a first bridge node, transmits a second setup message to a second bridge node, receives retrieved first event information from the first bridge node and retrieved second event information from the second bridge node, compares the retrieved first event information with a management profile and compares the retrieved second event information with the management profile, revises the management profile based upon the comparison of the retrieved first event information with the management profile and the comparison of the retrieved second event information with the management profile, and transmits an adjustment message that is based upon the revised management profile to the first bridge node.

An enhanced node-based connected logistics receptacle system includes a storage receptacle, a bridge node, and wireless accessory sensor node with at least one sensor monitoring for a change in state of the storage receptacle. The system's wireless accessory sensor node detects the storage receptacle's state change based upon sensor data, records timestamped information reflecting the detected change, and broadcasts a signal with a flag set indicating there is event information available for upload. The system's bridge node is operative to detect the flag set, retrieve the event information available for upload from the wireless accessory sensor node, and transmit a message related to the retrieved event information to a backend server to cause the backend server to initiate the dispatched logistics operation related to the storage receptacle.

An enhanced connected logistics receptacle system that selectively retrieves and reports event information to a backend server to initiate a dispatched logistics operation related to a delivery item. The system includes a storage receptacle for receiving the delivery item, a bridge node mounted to the storage receptacle, and a wireless accessory sensor node coupled to a plurality of sensors. The wireless accessory sensor node is operative to detect a change in state of the storage receptacle based upon sensor data, record timestamped information reflecting the detected change in state, and broadcast an updated advertising signal having a data available flag set within the updated advertising signal. The bridge node processor is operative to detect the data available flag, selectively retrieve event information from the wireless accessory sensor node, and transmit the retrieved event information to the backend server to cause the backend server to initiate the dispatched logistics operation.

The invention relates to the field of wind speed and wind direction prediction, and discloses a wind speed and wind direction prediction method based on an improved TCN-LSTM, and the method comprises the following steps: collecting real-time monitoring multi-dimensional meteorological data of an offshore wind station, and carrying out the preprocessing; performing feature fusion and feature enhancement processing on the preprocessed data, wherein the feature enhancement processing comprises spatial feature extraction, tensor reconstruction and time sequence modeling; inputting the data after feature fusion and feature enhancement processing into a wind speed and wind direction prediction model based on an improved TCN-LSTM hybrid neural network, and predicting the wind speed and wind direction at a future moment; the wind speed and direction prediction model comprises a time-space separation TCN network, a multi-head self-attention mechanism, an adaptive Dropblock mechanism, an LSTM network and a Bayesian optimization module; according to the method disclosed by the invention, the accuracy, robustness and calculation efficiency of wind power prediction in a complex marine environment can be improved.

The invention relates to the technical field of wind power plant wake flow testing, and discloses a 3D scanning type laser radar planning method suitable for wind power plant wake flow testing, and the method comprises the steps: determining a wind power plant wake flow wind measurement region according to a wind measurement demand; determining a mainstream wind direction and a wind speed interval of the wind power plant wake flow wind measurement area based on the wind power plant wind resource data, and obtaining unit coordinates and unit parameters of wind turbine units in the wind power plant wake flow wind measurement area; according to the mainstream wind direction, the wind speed interval, the unit coordinates and the unit parameters, performing simulation calculation on the wake flow field of the wind turbine generator in the wake flow wind measurement area of the wind power plant to generate a wake flow area cloud picture; according to the method, the arrangement position of the 3D scanning type laser radar is determined based on the wake flow area cloud picture and the actual landform of the site, the situation that the arrangement position of the 3D scanning type laser radar is repeatedly adjusted for multiple times due to arrangement errors possibly occurring during arrangement according to experience can be avoided, and the wake flow testing efficiency is improved.

An all-terrain vehicle may include a frame and a plurality of ground-engaging members supporting the frame. The all-terrain vehicle may further include a powertrain assembly supported by the frame and shiftable transmission supported by the frame and operably coupled to the powertrain assembly. The all-terrain vehicle may also include a display, a back-up camera, and a controller supported by the frame. The controller may be configured to receive a signal from the shiftable transmission corresponding to the shiftable transmission being in a gear of the plurality of gears other than a reverse gear. Further, the controller may be configured to determine the all-terrain vehicle is moving backwards and send an activation signal to the back-up camera to display images of the back-up camera on the display.

The invention relates to the technical field of unmanned aerial vehicles, and discloses an unmanned aerial vehicle power control system based on fault detection. The system collects state data of each component of the unmanned aerial vehicle in real time, the data calculation module accurately calculates key parameters such as battery remaining capacity and energy, fault states such as over-charging, over-discharging and temperature abnormity of the battery are rapidly judged, and meanwhile, the rotating speed and the load condition of the motor are monitored; the power management module dynamically calculates residual flight time and an optimal power distribution strategy according to data monitored in real time, power output can be rapidly adjusted when abnormal conditions are detected, and the feedback control module controls the power distribution strategy according to the flight attitude angle of the unmanned aerial vehicle. The power output of the motor is adjusted in real time, the power management and fault detection capability of the unmanned aerial vehicle in a complex environment is remarkably improved, the problems of over-charging, over-discharging and the like of the battery are effectively avoided, and the safety and reliability of the unmanned aerial vehicle are enhanced.

A system for self-executing enhanced interaction with a node-based logistics receptacle. The system includes a wireless accessory sensor node disposed on the node-based logistics receptacle to monitor storage receptacle components of the node-based logistics receptacle to generate sensor data. The system includes a bridge node disposed on the node-based logistics receptacle that uploads information related the sensor data, detects an external device separate from the node-based logistics receptacle, communicates with the external device to establish a smart contract based connection that provides an interaction privilege, interfaces with the external device according to the interaction privilege, and transmits an update message to the backend server that corresponds to at least a portion of the uploaded information related to the sensor data and information related to interfacing with the external device.

A dynamic learning server-based logistics system includes a node-based logistics receptacle operative to receive a delivery item as part of a logistics transaction and also includes a backend server maintaining a management profile related to operation of the node-based logistics receptacle. The node-based logistics receptacle includes a plurality of monitored receptacle components, a wireless accessory sensor node having a plurality of sensors, and a bridge node operative to retrieve event information from the wireless accessory sensor node. The backend server receives the retrieved event information, compares the retrieved event information with the management profile, identifies a threshold change condition from the comparison, dynamically revises the management profile when the threshold change condition is identified, and transmits an adjustment message to the bridge node. The adjustment message is based upon the revised management profile, and the adjustment message initiates a timing change to operation of the bridge node.

The invention provides a mobile base station and unmanned aerial vehicle cooperative monitoring system and method, relates to the technical field of unmanned aerial vehicles, and aims to solve the problems that an existing unmanned aerial vehicle monitoring system is low in single unmanned aerial vehicle operation efficiency and cannot meet the requirement for simultaneous execution of multiple tasks, and a traditional monitoring base station is limited in coverage range. And the method is difficult to adapt to complex construction environments or large-range monitoring scenes. The system comprises a moving and carrying module, a positioning detection module, a data acquisition module, a data processing module and the like, high-precision positioning, rotary multi-position parking apron and multi-task unmanned aerial vehicle cooperative work capability are integrated, the unmanned aerial vehicle has task synchronous execution capability, a base station has autonomous moving capability, and the system is suitable for complex terrains and high-precision unmanned aerial vehicles. And an environment monitoring module and a solar charging system are integrated, so that the long-term operation capability is enhanced. Through hardware integration innovation, the cooperative operation efficiency of the multiple unmanned aerial vehicles is improved, efficient linkage of the base station and the unmanned aerial vehicles is achieved, and the intelligent level of environment monitoring and construction management is improved.

A node-enabled logistics receptacle system with a deployable storage element for receiving and temporarily maintaining a delivery item. The system includes a storage receptacle with an entrance opening for receiving the delivery item and a deployable autonomous mobile container as the deployable storage element. A first node is mounted to the storage receptacle and includes a first node processor, a first node memory, a communication interface, and a plurality of sensors including an interaction sensor and a storage sensor. The first node detects a change in the state of the entrance opening, determines a current condition of what is presently maintained within the deployable autonomous mobile container, generates a deploy activation signal, and transmits the deploy activation signal to the deployable autonomous mobile container to initiate movement by the deployable autonomous mobile container from the host position within the storage receptacle to a position external to the storage receptacle.

The invention relates to the technical field of data processing, in particular to a building construction operation environment monitoring method and system based on the Internet of Things, and the method comprises the steps: collecting the particle concentration and wind direction data of a construction site area; according to the positions between different monitoring points and the particulate matter concentration, a flying dust influence area and a plurality of flying dust source points are obtained; further obtaining the influence degree of each monitoring point on each flying dust source point; based on the influence degree of the flying dust source points on the monitoring points, the particulate matter concentration of each flying dust source point is corrected, and then the flying dust contribution amount of each flying dust source point on each monitoring point is obtained; fitting weights of all the flying dust source points to all the monitoring points are obtained according to the flying dust contribution amount of the flying dust source points on the monitoring points, then data fitting is carried out, and the predicted particle concentration of each monitoring point is obtained; and monitoring the building construction pollution condition according to the predicted particle concentration. The influence caused by the external environment can be eliminated, and the environmental pollution caused by the construction site construction can be accurately monitored.

The invention relates to the technical field of laser radar meteorological detection, in particular to a wind field feature detection method and device based on a laser radar, and the method comprises the following steps: S1, controlling the laser radar to execute dynamic hierarchical scanning, and generating three-dimensional laser scanning data; s2, carrying out aerosol backscattering signal preprocessing on the three-dimensional laser scanning data; s3, extracting an aerosol motion vector of each range gate, and decomposing the aerosol motion vector into a horizontal wind field component and a vertical wind field component; s4, performing spatial gradient calculation to generate a spatial gradient distribution map; s5, respectively calculating a horizontal energy spectrum and a vertical energy spectrum; and S6, outputting wind field characteristic parameters. According to the invention, through fusion of the dynamic features of the laser radar point cloud, the wind shear space gradient and the energy spectrum analysis method, precise extraction of the turbulence intensity, the main energy scale and the three-dimensional vortex features is realized, and the accuracy and the spatial resolution of wind field structure identification are improved.

According to the method and device for determining the pose of the virtual object display unit and the electronic equipment, in the method for determining the pose of the virtual object display unit, the current pose of the virtual object display unit is determined according to the current pose of the vehicle body, and then the jitter parameter measured by the motion detection device is obtained; and according to the shaking parameter and the current pose of the virtual object display unit, determining the pose of the virtual object display unit at the display moment of the virtual object, thereby realizing that the virtual object displayed by the virtual object display unit can fit an actual scene and is not influenced by the bumping of a vehicle body to shake.

A wearable system for pedestrians / users is adapted to detect threats posed by, for example, approaching vehicles, bikers, and issue an alert. The wearable system may include an inertial measurement unit to measure the gait of the pedestrian and actively adjust alert generation thresholds to account for the noisy and large movements of the gait using present and past IMU data. The thresholds can be raised during active phases of the gait, and lowered in the quieter (i.e., less active) phases of the gait, keeping the range, and therefore time to react, relatively steady with respect to the pedestrian / user's motion. The alert generation threshold may be combined with the processed receiver data to determine threats and alert the pedestrian / user using any combination of haptic, audio, vibrational, or visual outputs.

The invention discloses a bridge vortex vibration early warning method and system based on vortex field monitoring. The system comprises a wind field acquisition subsystem, a vorticity calculation and prediction subsystem and a vortex field analysis and early warning subsystem. The wind field acquisition subsystem is used for monitoring wind speeds and wind directions of different space points around the main beam in real time. And the vorticity calculation and prediction subsystem calculates the wind speed and wind direction space point data acquired by the wind field acquisition subsystem in real time to obtain the vorticity value around the main beam, and predicts the vorticity value at the future moment. And the vortex field analysis and early warning subsystem performs frequency domain analysis on a vorticity time history, monitors and predicts vortex intensity and vortex shedding frequency in real time, and gives an early warning before vortex vibration possibly occurs. The system can give an alarm in real time according to a vortex vibration mechanism and can play a role in early warning in advance.

The invention discloses an integrated comprehensive actual measurement system for offshore platform floating support installation, and belongs to the technical field of offshore platform installation monitoring. The system at least comprises five subsystems including a marine environment monitoring system, a hull motion monitoring system, a fender load monitoring system, a DSU module separation monitoring system and an omnibearing video monitoring system, and an integrated comprehensive monitoring platform for managing the subsystems in a centralized manner. All the subsystems collect all-directional monitoring and module separation data in the floating support installation process through sensors and data transmission and transmit the data to the integrated comprehensive monitoring platform. The integrated comprehensive monitoring platform carries out unified coordination management to realize operation window decision, and a field surveying and mapping scheme is successfully guided to realize centimeter-level ship entry so as to complete offshore platform installation. According to the method, safe and reliable operation of the system in the floating support installation monitoring process is guaranteed, the floating support installation operation risk is greatly reduced, and successful installation of the offshore platform is powerfully guaranteed.

Various implementations include a low-drag smart tether system for measuring fluid speed and direction. The system includes a sleeve, a pressure sensor, and a tether. The sleeve has a longitudinal axis and an airfoil shaped cross-section as viewed in a plane perpendicular to the longitudinal axis. The sleeve has a leading edge. The sleeve defines a tether opening extending parallel to the longitudinal axis. The pressure sensor is disposed along a surface of the sleeve. The pressure sensor is configured to measure the pressure exerted on the pressure sensor by air moving over the surface of the sleeve. The tether extends through the tether opening defined by the sleeve. The tether has a tether longitudinal axis. The tether opening is positioned such that fluid flowing around the sleeve causes the sleeve to rotate about the tether longitudinal axis.

The invention discloses a PT symmetrical hot-pressing resistance MEMS wind speed and wind direction sensor. The sensor comprises four groups of PT symmetrical MEMS resonators which are orthogonally distributed and have hot-pressing resistance feedback; the PT symmetrical MEMS resonator comprises two cantilever beam resonators with completely same structures, a coupling spring beam connected with the two resonators, and a constant current source connected with one resonator, each cantilever resonator comprises two anchor areas, a wide beam connected with the anchor areas, a narrow beam with a piezoresistive effect, a warped thin plate structure and external electrodes located on the two sides of the thin plate structure. Wind speed and wind direction signals are converted into rigidity change of the resonator array through mechanical action by means of a warped thin plate structure, and the rigidity change enables the PT symmetrical MEMS system to deviate from an EP point, so that system frequency splitting is caused. As the frequency splitting quantity of the PT symmetric system is in direct proportion to the square root of the disturbance quantity, the wind speed and direction sensor can detect tiny wind speed signals, and has the advantages of very high sensitivity, simple process, high integration level and the like.

The invention provides an LSTM underwater robot modeling method based on TPE hyper-parameter optimization, and relates to the technical field of underwater robot modeling, and the method comprises the steps: carrying out the time sequence feature extraction through a memory unit comprising a forgetting gate, an input gate and an output gate, and predicting the state change amount delta Yt'at a t + 1 moment through an output layer; performing iterative optimization on the number of layers and the number of units of the LSTM network and training the model to obtain an optimized LSTM model; evaluating the optimized LSTM model through a multi-step cumulative prediction error, inputting an initial real state into the model to carry out T-step recursive prediction, updating a current state by utilizing a prediction state increment in each step, and finally calculating an average position error and an attitude error in a T-step window on a verification set; and selecting the hyper-parameter combination with the minimum comprehensive error of the verification set as a final model parameter, and completing the dynamic modeling of the underwater robot. According to the method, the problem that the model is inaccurate due to excessive parameterization in a nonlinear dynamic model can be solved.

The invention discloses a water environment pollution traceability system and method. The system comprises a multi-level monitoring module, a flow field reconstruction module, an inversion solving module, an intelligent identification module and a decision judgment module which are connected in sequence. The multi-level monitoring module acquires pollutant concentration and a three-dimensional flow field parameter time sequence in real time, and performs spatial interpolation and time filtering processing on flow field data; the flow field reconstruction module establishes a dynamic source-receptor response matrix according to the pollutant transmission track network; an inversion solving module calculates posterior probability distribution of the parameters; the intelligent identification module identifies the pollution source type through a pre-training classification model; and the decision judgment module comprehensively judges the effective pollution source according to the posterior probability confidence coefficient and the spatio-temporal evolution characteristics. According to the method, flow field reconstruction and probability inference technologies are fused, high-precision identification and parameter estimation of the dynamic pollution source of the water body are achieved, and the problems that in the prior art, mobile pollution sources cannot be effectively treated, and intermittent emission cannot be achieved are solved.

A computer-implemented method for assessing a fall risk of a user is provided. The computer-implemented method includes obtaining data indicative of the user engaging in a fall risk activity. The computer-implemented method includes adjusting a fall detection threshold of a wearable computing device worn by the user based, at least in part, on the data indicative of the user engaging in the fall risk activity. The method includes providing a notification indicative of the user being at risk of falling due, at least in part, to the user engaging in the fall risk activity.

The invention belongs to the technical field of ocean observation, and particularly relates to a GNSS buoy wind speed inversion method and system based on a physical information neural network, by introducing the physical information neural network, a physical equation and a neural network are effectively combined, the precision and efficiency of wind speed inversion are optimized, the generalization ability of a model is improved, and the wind speed inversion accuracy is improved. Therefore, a more accurate, rapid and widely applicable wind speed inversion solution is realized.

The invention relates to the technical field of breeding feed feeding, in particular to an intelligent feeding system and an intelligent control method. The intelligent feeding system comprises an aquaculture net cage module, a pneumatic feeding module, a bait conveying module and an intelligent control module. The culture net cage module comprises a culture net cage, and the shape of the culture net cage is a cube or a cuboid; the air-assisted feeding module comprises an air-assisted feeding machine; the air-assisted batch feeder is arranged above the culture net cage; the bait conveying module comprises a bait conveying pipe and a rotary controller; the bait conveying pipe and the rotary controller are arranged above the culture net cage; and the intelligent control module is used for measuring the wind direction and the water flow direction, and intelligently controlling the rotary controller through the measured wind direction and the measured water flow direction. According to the invention, the feeding efficiency and accuracy are improved, and the bait cost is saved.

The invention relates to the technical field of path planning, in particular to a water conservancy unmanned aerial vehicle inspection process control system and method based on big data analysis. Performing path risk assessment based on a water surface anomaly prediction result and a weather anomaly analysis result, performing unmanned aerial vehicle flight anomaly analysis based on unmanned aerial vehicle operation condition data and a historical path risk analysis result, and performing path planning selection. According to the method, the path danger is quantitatively evaluated based on the evolution condition of the weather and the wave condition on the path in the flight process of the unmanned aerial vehicle, the safety of path selection is improved, the influence of the future wind power condition on the wave danger is analyzed in the evaluation process of the wave condition, and the evaluation accuracy is improved. Therefore, the future wave danger is quantitatively predicted and evaluated, and the evaluation accuracy of the path danger is improved.

An on-line wind alignment angle calibration system of a wind direction instrument, comprising a wind direction instrument on-line calibration system, a cabin, a tower base, a monitoring room, and a server; the wind direction instrument on-line calibration system comprises: a wind direction instrument (1), a housing upper cover (2), a transmission gear (3), a transmission shaft (4), an integrated control module (5), a housing (6), a base (7), a speed reducer (8), a drive motor (9), and an angle encoder (10). Further provided is a calibration method based on the calibration system. The calibration method comprises: preprocessing wind power data; performing data processing by means of a DBSCAN clustering analysis method; performing data processing by means of a quartile algorithm, and determining a data interval; calculating a blade tip speed ratio interval; extracting wind direction interval power; and calculating a wind alignment angle. The wind alignment angle deviation of a wind turbine is obtained by means of calculation using an intelligent algorithm, then a reference zero position of the wind direction instrument is adjusted by means of an intelligent precise hollow drive module, thus on-line adjustment and calibration of the reference zero position of the wind direction instrument can be achieved, and safety hazards due to manual operation, frequent adjustment and calibration, high-altitude operation, and the like are reduced. Also provided are a computer-readable storage medium and a computer device for implementing the calibration method.

The invention discloses a low-power-consumption winch sensor based on a tunneling magnetoresistance effect. The low-power-consumption winch sensor comprises a measurement module, a signal conversion unit, a shell, a mandrel, a magnetic rotary disc and a detection assembly. The magnetic turntable and the mandrel are connected and rotate synchronously, the detection assembly comprises a TMR sensing element and N magnets, and the magnetic turntable is provided with mounting blind holes for embedding the magnets; the TMR sensing element is arranged on the shell and comprises a mounting plate and two sensing units, the magnetic domain directions of the two sensing units are perpendicular to the rotation axis, magnetic resistance signals of the two sensing units are converted through the signal conversion unit and input into the measuring module, the horizontal distance between the centers of the two sensing units and the magnet and the rotation axis is R, and the center distance L of the two sensing units is smaller than R * sin (180 degrees / N); the sensor is based on the TMR tunneling magnetoresistance effect, is high in detection sensitivity and low in energy consumption, outputs square wave signals with phase differences, can be used for a measurement module to accurately analyze and calculate the rotating speed and the rotating direction of a winch roller, is simple in overall structure, small in radial size and easy to install, and the installation precision is controlled.