1841 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.

A geo-converged telemetry (GCT) system is described that provides an exchange of geographically-relevant telemetry data amongst various vehicles, devices, and systems for providing a holistic view of a geographic area. Telemetry data from various sources may be continually collected and transmitted to a nearby node of a GCT system, where the data may be converged based on geolocation and processed. The same and / or other vehicles, devices, and systems may operate as telemetry consumers that receive feeds of geo-converged telemetry data that may be tailored to functionalities of the consumer. As a vehicle moves, data that are determined to be geographically-relevant changes. The location of the processing may move from one processing node to another processing node in the edge network such that the processing is located proximate to the vehicle to minimize latency and provide real time or near-real time feedback based on a holistic view of the geographic area.

In some embodiments, a method and system for detecting surface changes in a geographical area over time is disclosed. The method includes encoding pre- and post-event images using frozen features of Segment Anything Model (SAM), processing encoded embeddings by a change modeler, processing change embeddings by a change prompter, decoding change embeddings and prompt embeddings using SAM to obtain change masks which include the detected changes.

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.

A computer-implemented method for artificial intelligence (AI) based risk / value assessment of a geographic area includes performing feature engineering to contextually enrich collected data. Three datasets are generated from the contextually enriched data, where a first dataset is generated by combining positive samples of the contextually enriched collected data with hard negative samples of the contextually enriched data, a second dataset is generated by combining the positive samples with soft negative samples of the contextually enriched data, and a third dataset is generated by combining the positive samples, hard negative samples, and soft negative samples. A machine learning model is trained to generate three different types of predictions for the risk / value assessment of the geographic area based on the three generated datasets.

The invention discloses a multi-platform store normalizing method, which relates to the technical field of computers, and comprises the following steps: extracting a standardized data set through a multi-modal feature extraction technology to generate a multi-platform feature vector; the feature vectors of the multiple platforms are input into a multi-algorithm fusion engine, parallel matching calculation is executed, meanwhile, a dynamic weight distribution mechanism is designed, normalized platform IDs and a cross-platform mapping relation table are output, and a matching confidence report is generated; a normalization result is stored in a distributed database based on a block chain, an incremental synchronization mechanism is designed, data are divided and stored according to geographic areas, node loads are dynamically distributed through a consistent Hash algorithm, and updated normalized platform data are obtained; through a multi-modal feature extraction technology and a multi-algorithm fusion engine, deep mining of a standardized data set is realized, an accurate feature vector set is generated, and the accuracy of cross-platform data matching is remarkably improved.

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).

A dense charging station for charging the battery may have lanes arranged in parallel, and each of the lanes may have sequential charging locations. A vehicle utilizing the charging station may position itself at the first available charging location, being receiving energy, and determine if a subsequent charging station becomes available in the lane, and then position itself at the subsequent charging location, once available. Multiple charging stations may be required to maintain a threshold power state for individual vehicles in a fleet of vehicles providing a service for a geographic region. A charging coordinator may determine when a battery of a vehicle does not satisfy a threshold power state and requires a recharge. Additionally, the charging coordinator may determine a candidate charging station from among multiple charging stations associated with the geographic region.

Method and system for the design, execution and monitoring of works, particularly in the construction field, through the modeling of projects by means of a BIM system integrated with the construction engineering necessary to configure all the systems and equipment required for construction, including automatic generation of smart contracts starting form a contract document. In a preferred embodiment of the present invention the automatic generation of a smart contract is performed by means of SysML (System Modeling Language) tool. IoT and / or Blockchain technologies are combined with conventional BIM systems for more precise monitoring and traceability of the stages in construction. The system and method according to a preferred embodiment of the present invention use the information collected by a plurality of detectors. The plurality of detectors preferably includes IoT devices. Detectors can be associated with any machinery used for the project and may include, for example, image acquisition devices such as cameras, remote cameras or web-cams fixed or mounted on drones; other possible detectors may be worn by construction staff. Detectors may also receive information from meteorological and / or seismographic services for a geographical area linked to at least one project.

The invention discloses an inland river water transportation facility monitoring data secure transmission method based on a block chain technology, and the method comprises the following steps: selecting an optimal sensor for data collection according to the geographic position and operation environment of a facility through a dynamic sensor switching mechanism, and eliminating errors caused by equipment faults and environment interference, after the collected data is subjected to time-space aggregation processing and classified according to geographic areas and time windows, based on a block chain node selection algorithm, an optimal node is selected for data transmission, the data is encrypted by adopting a hierarchical encryption strategy, the encrypted data is stored in a block chain network, and the data is transmitted to the block chain network through a threshold-triggered smart contract. And monitoring the stored data in real time, and automatically adjusting a monitoring scheme or starting an emergency mechanism when the stored data exceed a preset threshold value. The invention aims to improve the security and integrity of monitoring data transmission.

The invention discloses a dynamic low-altitude route planning method and system based on low-altitude meteorological data analysis, and relates to the technical field of route planning, and the method comprises the steps: carrying out the route pre-planning according to the information of a to-be-mapped region; in the flight process, the route is adjusted in real time according to the real-time weather information and the known obstacle area; and after surveying and mapping, re-planning a route to re-shoot the geographic area corresponding to the shooting data which does not meet the standard so as to obtain standard data. When the unmanned aerial vehicle flies according to the preset route, the real-time wind speed and wind direction information are considered to determine the safety boundary of the obstacle area, the route of the unmanned aerial vehicle is adjusted to bypass the obstacle area, and the safety risk of the unmanned aerial vehicle during surveying and mapping is reduced; after surveying and mapping are finished, secondary surveying and mapping are carried out on areas with unqualified data, factors such as real-time meteorological factors, distances of all the areas and the number of times of re-shooting of all the areas are considered during secondary surveying and mapping, and the operation cost and time are reduced while an air route meeting the surveying and mapping requirement is planned.

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.

A server-side management interface for a social media platform allows limiting a defined geographic area. Social media items originating from such restricted areas are automatically filtered or age-restricted for availability via a map-based graphical user interface of the social media platform.

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 collection, communication, storage, monitoring, and analysis of environmental, vehicle, charger, and charging session data over a single EV or over a fleet of EVs is used to enhance or optimize existing services as well as deliver new services based on analysis of the collected data. One such service is reduction in total cost of travel. The cost minimization is achieved with near-real-time data, models populated using past collected data, and knowledge of energy costs and of chargers located in different geographic areas with potentially limited power for charging available at each charger site or station. A fleet management application used for cost minimization optimizes cost of travel for a single EV or for an entire fleet. Using individual EVs cost optimization as a goal, each EV may be optimized for potential local minimum cost of travel based on predictions using data collected from the fleet or from multiple fleets.

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.

Systems and methods for heterogeneous slice deployment within a registration area are provided. In some embodiments, a method performed by a User Equipment (UE) for accessing a network slice includes: during registration with a network node, requesting network slice assistance; receiving network slice assistance from the network node indicating access to a first network slice in a first Tracking Area (TA) but not in an entire Registration Area (RA); and accessing the first network slice in the first TA. Some embodiments enable deploying slices in very small geographical areas to suit special use cases without necessarily having to deploy small RAs. Some of the potentially realizable use cases are in stadiums, factory slices, etc. The ability to deploy small slices within a large RA mitigates problems, such as high registration load, that one might deal with when the RA is too small.

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 can determine an overshooting cell of a base station in a mobile network. In some implementations, the system can determine a plurality of tiles to cover a geographic area. The system can determine, from a user device, a radio measurement associated with a tile of the plurality of tiles. The radio measurement may be determined based on a signal, associated with a cell of the base station, which is received by the user device when the user device is located in the tile. The system can generate a multidimensional matrix, e.g., a 2D or 3D matrix, from the plurality of tiles and the radio measurement. The multidimensional matrix may indicate a footprint of the cell. The system can invoke a machine learning model to determine, based on the footprint, an overshoot by the cell in the geographic area. Other aspects are also described and claimed.

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.