1401 results about "Geographic area" patented technology

A system and method for AI-based dynamic pricing, mapping, and emissions control to optimize inner-city mobility. The system acquires real-time nitrogen dioxide data across a geographic area from sources including satellites, feeds this data into a decision support system along with road-specific weight matrices from authorities, and updates a dynamic penalty matrix for roads in the area. Automatic number plate recognition tracks vehicle movement, queries vehicle databases for emissions profiles, and updates the platform. Users input journey parameters and the system, using AI tools including a genetic algorithm economic and environmental dispatch (GA-EED) optimizer, generates an optimized route based on user-selected criteria such as time, emissions, penalty, and cost. The system enables dynamic, environmentally-aware route optimization for inner-city mobility.

The invention provides an emergency event visualization cooperation method and terminal equipment, and the method comprises the steps: obtaining a historical monitoring data set of an emergency event in a target region, carrying out the preprocessing, and generating a standardized event feature set; training a time sequence prediction model according to the dynamic environment parameters to obtain an event evolution prediction model; and constructing a geographic region matching model based on the static geographic parameters, and generating a visual layer template associated with the target region. And collecting a current environment data flow of the target area in real time, performing classification through the event evolution prediction model to obtain an event classification result, and calling a corresponding visual layer template from the geographic area matching model according to the event classification result. And fusing the diffusion path, the intensity level and the called visual layer template in the event classification result to generate a dynamic visual instruction set, and rendering and outputting an emergency event evolution situation map through an interactive interface. According to the invention, the timeliness of emergency response and decision reliability can be improved.

Systems and methods are disclosed for preserving patient privacy while allowing health data to be analyzed, managed, and stored in different geographical areas. One method for managing cross-border health data while preserving patient privacy includes: receiving a DICOM object from a hospital computing device for analysis; generating a unique case identifier for the DICOM object; validating the received DICOM object; if, based on the validation, the received DICOM object is valid, anonymizing the received DICOM object; updating the anonymous DICOM object to include the unique case identifier; compressing the updated DICOM object; and sending the compressed DICOM object to at least one data analysis web service(s).

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, are described for implementing a mission space platform. The platform is configured to identify radio frequency (RF) signals and analytics and generate a graphical interface with a map of a geographic area, where the map includes multiple grid points. For one or more RF signals: the platform determines a respective geolocation of an emitter that emits the RF signal and assigns the RF signal and its corresponding emitter to a grid point of the map based on the respective geolocation. Visual characteristics of grid points in the map are dynamically adjusted, in real time, base on new RF information about the area. The new RF information is provided as an output at the interface by displaying adjustments to the visual characteristics of the grid points.

The invention discloses an AI-based meter reading data management and resource scheduling optimization method and system, and relates to the technical field of intelligent management of meter reading data. The method comprises the steps that meter reading data of a meter is obtained, and the meter is provided with a corresponding two-dimensional code metal identification piece; meter reading data are managed according to geographic areas and user types, a multi-level data feature system is formed, and the user types comprise resident types and industrial types; carrying out trend modeling on the multi-level data characteristic system by adopting an AI model so as to determine an energy consumption trend in a future period; dynamically adjusting a meter reading task according to an energy consumption trend and a network load condition so as to dynamically schedule human resources, data resources, network resources and hardware resources; wherein the power grid topology position code is used for binding an association relationship between the meter reading task and the power grid physical conduction path. According to the invention, full-link optimization from meter reading data acquisition to resource scheduling is realized.

The invention discloses a multi-source remote sensing image zero sample change detection method, and relates to the technical field of remote sensing image processing, and the method comprises the following steps: obtaining remote sensing images collected by two or more remote sensing sensors at different time points in the same geographic area, the image types including optical images and radar images; preprocessing each source image, unifying the spatial resolution and the registration precision, and denoising and standardizing the image; according to the method, the cross-modal shared semantic embedding space is constructed and unsupervised comparative learning is introduced, so that the semantic consistency of the multi-source remote sensing image is effectively improved, and the change recognition capability of the model under the zero sample condition is enhanced; and meanwhile, a difference fusion calculation and structure consistency constraint module is adopted, so that the boundary judgment precision of a change region and the overall structure consistency are improved, and the accuracy and stability of a detection result are remarkably improved.

Systems and methods are disclosed for preserving patient privacy while allowing health data to be analyzed, managed, and stored in different geographical areas. One method for managing cross-border health data while preserving patient privacy includes: receiving a DICOM object from a hospital computing device for analysis; generating a unique case identifier for the DICOM object; validating the received DICOM object; if, based on the validation, the received DICOM object is valid, anonymizing the received DICOM object; updating the anonymous DICOM object to include the unique case identifier; compressing the updated DICOM object; and sending the compressed DICOM object to at least one data analysis web service(s).

The invention provides a smart city split emergency management method and system based on an Internet of Things large model, and the method is executed by an emergency supervision management platform of the system, and comprises the steps: determining at least one accident based on target data; determining a data criticality based on the target data, the data basic features and the at least one accident; determining a data emergency feature based on the target data, the data abnormal feature and the data criticality; determining at least one target sub-platform based on the target data, the data exception features and the division conditions; determining emergency parameters based on the emergency type, the emergency degree and the data emergency characteristics; determining working parameters of the emergency vehicle based on the emergency degree, the emergency parameters and the data emergency characteristics; and based on the emergency parameters and the working parameters, generating and sending a scheduling instruction, and controlling the emergency vehicle to drive to the geographic area to work. According to the method and the system, accurate determination and dynamic allocation of emergency resources can be realized, and the overall efficiency of urban emergency management is improved.

The invention relates to a spatio-temporal data prediction method based on space grid coding and a large language model, and belongs to the field of artificial intelligence and spatio-temporal data analysis. The method comprises the following steps: according to a spatial range of a geographic area, dividing the area into grid units, processing the grid units by adopting a coding method, and identifying each unit through a unique identifier; constructing a space-time dependency model based on the stay record of the user, representing each stay as a tuple, and predicting the next position of the user by analyzing a historical stay sequence and a context stay sequence; and designing a space-time instruction optimization prompt template in combination with a large language model, guiding the model to analyze historical data and context data by introducing grid coding and context perception reasoning, generating next position prediction, and providing explanation for each prediction. According to the invention, through grid coding and hierarchical modeling, the generalization ability of the model is enhanced, and accurate spatio-temporal behavior prediction is realized.

The invention relates to the technical field of building monitoring, and provides an early warning method and system for pile foundation health state analysis. The method comprises the steps that a monitoring platform receives and processes various monitoring data from a multi-source sensor in real time, and data fusion and dynamic trend analysis are carried out on the various monitoring data by combining a graph neural network and a lightweight multi-head attention sequential network with a building structure of a target building to obtain an initial pile foundation evaluation result; uploading the initial pile foundation evaluation result of the target building in each geographic area and various monitoring data to a cloud data processing center; the cloud data processing center stores the initial pile foundation evaluation results of the target buildings in the geographic areas, and comprehensively evaluates the correlation trend between the target buildings in the geographic areas to obtain correction parameters; and the correction parameters are issued to a monitoring platform, the monitoring platform dynamically combines the correction parameters to update the pile foundation health state of the target building in each geographic area, and a target pile foundation evaluation result of the target building is obtained.

Surveillance systems and methods for collecting electronic signatures and visual identifiers of targets to help create identifications or records of targets associated with one or more particular electronic signatures. The surveillance systems and methods can include an event analysis system and methodologies to facilitate classification and association of the collected visual identifiers of the targets with the collected electronic signatures of such targets, and can generate alarms or “hits” indicating presence of a known target across subsets of locations and times of occurrence of such hits or alarms for enhancing tracking and movement of targets throughout selected geographic areas or locations.

The invention relates to a method for the determination of the carbon balance in a predetermined geographic area, applicable to natural and / or human-managed systems, which integrates a series of known and validated technologies into a single information system on the carbon sequestered by natural and human-intervened systems. A system for determining the total carbon balance of a predetermined geographic area is also provided.

The invention relates to the technical field of unmanned aerial vehicle data processing, in particular to an unmanned aerial vehicle data processing method and system based on embedded combination with off-line map fusion, and the method comprises the following steps: before an unmanned aerial vehicle is started, pre-loading and dividing flight area map data, and classifying and storing the map data according to geographic areas and importance; and generating a plurality of region classification map data. According to the method and the device, the map data is preloaded and classified and stored before the unmanned aerial vehicle flies, so that the autonomous navigation capability of the unmanned aerial vehicle in a complex environment is improved, especially under the condition that a network is unavailable or signals are weak. The introduction of the quadtree spatial index optimizes the indexing and retrieval process of the map data, accelerates the response time and reduces the consumption of computing resources. The ant colony algorithm is used for path optimization, the data access mode and the access frequency of the current flight area are adjusted, and the efficiency and the economical efficiency of path planning are improved.

The invention relates to the technical field of satellite height measurement, and discloses a GNSS-R ocean plumb line deviation calculation method, device and equipment and a storage medium. The method comprises the following steps: acquiring a height measurement result, a geoid height and an average dynamic terrain of each GNSS-R mirror reflection point in an ocean area, and calculating a residual geoid height; dividing a global geographic area according to a longitude and latitude target interval to generate a target grid; for any lattice point in the target grid, screening a plurality of GNSS-R mirror reflection points around the lattice point as target points; and determining the weight of the residual geoid height of each target point based on the GNSS-R height measurement precision table, calculating the residual geoid height of the network point through weighted average, and further calculating the corresponding ocean plumb line deviation. By adopting the method, the global ocean plumb line deviation can be quickly calculated based on the GNSS-R sea surface height measurement result, and the accuracy of ocean plumb line deviation calculation is improved.

In various examples, systems and methods are described that may be used to generate a mask of a geographic area and corresponding vector representations of one or more environmental features included in the area. In some embodiments, the method and system may generate or obtain a first tile image representing a portion of a path surface corresponding to a geographic area. One or more features may be extracted from the data where the extracted features may indicate environmental characteristics associated with the path surface—e.g., lane boundaries, medians, traffic signs, signals, etc. Additionally, the method or system may generate a mask corresponding to the tile image and vector representations of the portion of the geographic area. In some embodiments, the locations of the environmental features associated with the mask may be reconciled with one or more previously generated masks that include some of the same environmental features.

The invention relates to the technical field of image detection, in particular to a satellite and unmanned aerial vehicle cooperative remote sensing image change detection system and method, and the method comprises the steps: obtaining a dual-time-phase satellite remote sensing image and an unmanned aerial vehicle remote sensing image of the same geographic region; the satellite branches are subjected to four-stage convolution-pooling operation, multi-stage wide-area features are output, and the unmanned aerial vehicle branches output high-resolution local features aligned with the satellite branches in space through the backbone network; performing channel interaction operation on each stage of double-time-phase features, and generating a spatial weight map to strengthen a change region; aligning adjacent level resolutions through transposition convolution, dynamically integrating multi-scale features, and outputting optimized fusion features in combination with residual connection; and performing convolution dichotomy on the fused features to generate a change detection result graph. According to the method, the problem of signal attenuation caused by heterogeneous data feature mismatch is effectively solved, the false alarm rate caused by environmental interference is remarkably reduced, and the complete detection capability of a micro-to-macro full-scale dynamic target is synchronously improved.

A system and method are disclosed for determining a classification and sub-classification of an aircraft. The system receives an aerial image of a geographic area that includes one or more aircrafts. The system inputs the aerial image into a machine learning model. The system receives an output from the machine learning model for each aircraft of the one or more aircrafts. Based on the output for each aircraft, the system determines a set of geometric measurements. The system compares the set of geometric measurements to a plurality of known sets of geometric measurements. Based on the comparison, the system identifies a known set of geometric measurements from the plurality of known sets of geometric measurements. The known set is mapped by a database to a sub-classification. The system outputs the sub-classification.

The invention discloses a multi-view-angle-based unmanned aerial vehicle visual positioning method and system, and relates to the field of unmanned aerial vehicle vision, and the method comprises the steps: obtaining a satellite map of a target region, and cutting the satellite map into overlapped blocks to construct a satellite library; acquiring images shot by the unmanned aerial vehicle from a plurality of visual angles in the target geographic area range, and constructing a multi-visual-angle unmanned aerial vehicle image based on the shot images; the images are processed through a multi-view-angle unmanned aerial vehicle visual positioning network, and the network comprises an embedded coding module, a view angle consistency feature learning module and a prototype construction and alignment module and is used for extracting single-view-angle and multi-view-angle unmanned aerial vehicle image features and satellite library features; and determining the current position of the unmanned aerial vehicle by calculating the cosine similarity between the multi-view unmanned aerial vehicle image features and the satellite library features. According to the method, DINOv2 feature extraction, adapter design and the view angle invariant attention network are fused, so that efficient information processing and feature extraction are ensured, and the positioning precision and reliability are improved.

The invention provides a small watershed non-point source pollution key source area determination method which can be applied to the technical field of pollutant analysis and the field of environmental science. The small watershed non-point source pollution key source area determination method comprises the following steps: acquiring multiple groups of rainfall runoff process information corresponding to a to-be-investigated geographic area; generating N groups of pollutant output quantity theoretical values based on the multiple groups of rainfall runoff process information and the N groups of land information; generating N groups of pollutant transmission resistance values based on pre-collected N groups of geographic information in one-to-one correspondence with the N geographic grid units; based on the N pollutant output quantity theoretical values and the N pollutant transmission resistance values, generating N pollutant output quantity actual values in one-to-one correspondence with the N geographic grid units; and on the basis of the N pollutant output quantity actual values, screening out at least one target geographic grid unit from the N geographic grid units to serve as a small watershed non-point source pollution key source area.

The embodiment of the invention provides a forest type remote sensing classification method and device, electronic equipment and a storage medium. The method comprises the following steps: determining a target geographic area and collecting multi-source remote sensing data; extracting canopy multi-dimensional space-time spectrum features based on multi-source remote sensing data, and screening geographical environment covariables capable of representing forest type differences; calculating the overall geographical environment similarity of the unknown point and the sample point by using a Gaussian similarity function; quantifying the individual representativeness of the sample points to the unknown point according to the overall geographical environment similarity, and selecting the forest type represented by the sample point with the highest individual representativeness as the forest type of the unknown point; drawing a forest type spatial distribution diagram and a classification uncertainty distribution diagram of the target geographic area based on classification results of forest types of all unknown points; and performing precision verification on the forest type spatial distribution map based on the classification uncertainty distribution map and a preset precision evaluation index.

A facility for estimating the value of a distinguished home is described. The facility trains a forest of decision trees to estimate valuations for homes within the geographic area where the distinguished home is located using data including both previous home sale transaction prices and synthetic sale transaction prices based on listing prices. The facility accesses information about the distinguished home's attributes and applies each decision tree in the forest to that information, generating a number of estimated valuations. The facility determines an overall valuation for the distinguished home based on the valuations generated by the decision trees.

A method and system for limiting mobile device functionality when the mobile device is located in a pre-defined fixed geographic area. The mobile device may receive a local disabling signal from a disabling device, which, when detected by a Device Owner Application resident on the mobile device, limits the mobile device functionality. Alternatively, the system may use GPS based geofencing to determine that the mobile device is in a predefined geographic area, and then transmit instructions to the mobile device, where a Device Owner Application operates to restrict the mobile device functionality. Mobile device functionality may be limited by restricting the mobile device's ability to send and receive text messages, email messages and phone calls; restricting the mobile device's ability to respond to user input; restricting the mobile device's ability to utilize a web browser; and restricting the mobile device's web browser from accessing predetermined web sites.

Methods for training a series of neural networks to output driving behavior control parameters is disclosed. The training dataset for the neural networks includes sensor-based vehicle driving recordings that may be categorized by geographical area, by qualitative driving behaviors, or by some combination, such that various training data subsets are used to train the series of neural networks. By learning either city-specific driving behavior control parameters, qualitative driving behavior specific driving behavior control parameters, or both, the resulting parameters may then be provided to a motion planning model for use in modeling predictive control for an autonomous vehicle. Rather than relying on XYZ trajectories of agent vehicles when planning future trajectories of the ego vehicle, the motion planning model is adaptive, due to the use of the learned driving behavior control parameters.

Implementations are described herein for obtaining a sequence of high-elevation images capturing a particular geographic area during a particular time period in a plurality of spectral bands; applying the sequence of high-elevation images as input to upstream machine learning model(s) to generate remote sensing embeddings indicating terrain feature(s) of the particular geographic area; applying agricultural data obtained from a local agricultural knowledge graph as input to additional upstream machine learning model(s) to generate agricultural knowledge embedding(s); inferring a natural-language description of a status of the particular geographic area based on generating: an aggregate representative embedding that semantically represents a plurality of agricultural conditions of the particular geographic area, and a natural-language description of one or more of the plurality of agricultural conditions of the particular area using a large language model; and causing a user device associated with an agricultural entity to present the natural-language description of the status.

Systems and methods are provided to select a set of candidate listings having geographic locations within a geographical area, fit a bound for a maps viewport to the set of candidate listings, generate a maximum score for the set of candidate listings based on a booking probability for each listing, a distance of the listing location from a center of the bound for the maps viewport, and visibility based on other listings. The systems and methods further optimize the listings shown in the maps viewport by removing and replacing farthest listings up to a predefined number of listings to be removed and computing a cumulative booking score for each set of listings to compare to the maximum score. The systems and methods cause display in a maps viewport in a user interface of a computing device of a set of listings that has a maximum score.

The invention provides a system and a method for target communication. A system for directional communication is disclosed. The system may include an ultrasound beamforming device, a sensor, and a processor. The ultrasound beamforming device may be configured to transmit an ultrasound carrier. The processor may be configured to obtain an input from a detection unit located in a geographic area, and to detect the presence of an object in the geographic area based on the input. The processor may also be configured to determine an object location in the geographic area based on the input. The processor may additionally determine an optimal sound frequency for modulating the ultrasonic carrier. Further, the processor may cause the ultrasound beamforming device to transmit the ultrasound carrier modulated at the optimal sound frequency toward the object location.

The invention relates to the field of computer technology application, and particularly provides a gate position association method and device based on hierarchical reinforcement learning and a medium, and the method comprises the steps: obtaining grid region information and association subject information corresponding to a target geographic region; the grid area is a gate position, and the associated subject is a flight; dividing all grid regions corresponding to the grid region information into a plurality of mutually exclusive region groups based on the grid region information; based on preset association constraint information, obtaining association subjects allowed to be associated with each mutual exclusion region group, and obtaining an initial association feasibility matrix of each mutual exclusion region group; based on the initial association feasibility matrix and preset mutual exclusion constraint information of each mutual exclusion region group, obtaining an association operation heterogeneous graph of each mutual exclusion region group; and obtaining an association result corresponding to each mutually exclusive region group by using the hierarchical reinforcement learning model. According to the invention, the distribution efficiency and the bridge approaching rate of the gate positions can be improved.

The invention relates to the technical field of data processing, can be applied to business scenes of medical health, financial science and technology and the like, and discloses a task merging and distributing method which comprises the following steps: creating and storing task information, acquiring a corresponding active task set, matching an object identifier, extracting a terminal equipment identifier, and extracting and sending the task information, and updating the task state after receiving the task confirmation information, screening and combining the tasks when the task confirmation information is not confirmed, generating a composite task unit, and issuing the composite task unit to a task execution end according to a preset strategy. According to the method, the tasks are screened and matched on the basis of the geographic region identifiers and the object identifiers, so that repeated pushing of the tasks in the same region and the same object is effectively reduced, and the task allocation accuracy is improved; in combination with the task state information and the terminal equipment identifier, the task receiving process is optimized, and the task execution efficiency is improved; through a task merging mechanism, the task execution cost is reduced, and in combination with a preset release strategy, task scheduling is more balanced, and the intelligent level of overall task management is improved.

The invention discloses a photovoltaic power station generating capacity calculation method and device, electronic equipment and a storage medium, and relates to the field of artificial intelligence and big data, and the method comprises the steps: obtaining the geographic position data and historical power generation data of a target power station; determining a geographic area to which the target power station belongs, iteratively selecting a reference power station in the geographic area, calculating a spatial correlation weight of the reference power station, and calculating a first theoretical power generation amount of the target power station in the target time period based on the spatial correlation weight of the reference power station and the real-time power generation data; inputting the historical power generation data into the exponential weighted moving average model, and outputting a second theoretical power generation amount of the target power station in the target time period; and calculating the theoretical generating capacity of the target power station in the target time period based on the first theoretical generating capacity and the second theoretical generating capacity. According to the invention, the technical problem of low calculation result accuracy of a mode of calculating the theoretical generating capacity of the photovoltaic power station according to meteorological data in the prior art is solved.

An improved manner of transmitting and receiving messages in V2X / V2V / D2D is presented in which a transmitting device determines a geographic location of the mobile transmitting device and generates a message for a service group having a group ID associated with the service group, the message comprising a first indication of a geographic area associated with the message, the geographic area based at least in part on the geographic location of the transmitting device. Then, the apparatus transmits the message to the service group, e.g., via V2X / V2V / D2D communication. A receiving device then determines its geographic location and determines whether to send a feedback for the message based on the first indication of the geographic area associated with the message and the geographic location of the receiving device.