1357 results about "Electronic map" patented technology

The invention provides an intelligent warehouse management system and method based on big data, and relates to the technical field of warehouse logistics, and the system comprises a data collection module which is used for collecting the electronic tag information, goods location coordinates and environment data of materials in a warehouse in real time through a radio frequency identification reader-writer and a wireless sensor network node, and uploading the information to a central server; the inventory early warning module is used for dynamically classifying the materials in the warehouse in the central server, calculating safety inventory intervals of various materials through historical turnover rate data, and correcting an inventory threshold value in combination with a real-time correction factor; and the positioning navigation module is used for acquiring the real-time positions of the materials according to the new safe inventory interval, and generating a goods allocation electronic map and final path navigation. According to the invention, the warehouse management efficiency and accuracy are effectively improved, the warehouse space utilization is optimized, the warehouse-in and warehouse-out operation level is improved, and visual and intelligent management is realized.

The invention belongs to the technical field of smart tourism management, and relates to an AI-based smart tourism recommendation method and system, and the method comprises the steps: obtaining instantaneous aggregation density data collected by a plurality of hidden monitoring nodes in a scenic spot in real time; generating a dynamic environment grade set according to the instantaneous aggregation density data, the real-time weather elements and the traffic control information; generating a user physical exhaustion level, and generating an interest preference label through an electronic map zooming operation track; identifying space-time synchronization features between the associated mobile terminals to generate a group type identifier, and binding the group type identifier with a strategy recommendation template; performing peak shifting recommendation sorting in combination with the dynamic environment level to form an initial recommendation scheme set; and comparing the matching degree between the initial recommendation scheme and the interest preference label, triggering the secondary optimization of the recommendation content based on the group type identifier when the matching degree is lower than a set range, and injecting an emergency risk avoiding path to complete a closed-loop recommendation decision chain. The problem that in the prior art, due to the fact that the data collection dimension is single, recommendation strategies lack group adaptability is solved.

The invention relates to the technical field of path planning, in particular to a path planning method and system for an inspection robot, and provides the following scheme: executing an inspection task through an initial electronic map, collecting first image data and pose information, recognizing an inspection target, completing image registration, and generating second image data; inverting and calibrating the optimal observation direction based on the structural sensitivity distribution of the local visual features and the illumination variation trend, and determining the shooting position and angle to form a path node; a multi-objective optimization model is adopted, the path length, the view angle continuity and the illumination interference are comprehensively considered, and an optimal inspection path is generated; the method is suitable for outdoor inspection scenes with complex structures and non-uniform target distribution.

The invention discloses a map navigation method and system based on integrated navigation, and particularly relates to the field of integrated navigation, comprising compass data acquisition, magnetic declination correction, map integration, navigation system data acquisition, navigation system data analysis and integrated navigation. According to the method, the precision and robustness of the navigation system are remarkably improved, different environments can be dynamically adapted, and the error influence is reduced; rich geographic information support is provided by presetting an electronic map and POI marks; the real-time navigation service provides visual road condition information and path planning, the user experience is enhanced, and on the whole, more accurate, reliable and convenient navigation service is provided for the user.

The invention discloses an airport unmanned luggage tractor path planning method and system, and belongs to the technical field of unmanned vehicle autonomous navigation, and the method comprises the steps: obtaining an initial path and a final path of an airport unmanned luggage tractor; matching the global electronic map of the airport and the path information of the final path with the actual environment information, and judging whether abnormity exists or not; a local environment in an airport is divided into a plurality of two-dimensional grid units, various obstacles are identified in the two-dimensional grid units, potential energy values are given to the grid units corresponding to the obstacles respectively, when the potential energy values are larger than a preset potential energy maximum value, it is judged that abnormity occurs, and a driving path of the unmanned luggage tractor is re-planned and serves as a final path. The operation of judging whether the abnormity exists or not is executed again, and when the abnormity does not exist, the driving path of the unmanned luggage tractor is generated. The method can avoid local path planning of sudden dynamic obstacles.

The invention discloses a land investigation quality monitoring system for remote sensing image intelligent segmentation and ground feature recognition, and relates to the technical field of remote sensing, and the system comprises an image recognition module, a label comparison module and a monitoring module, and specifically carries out the remote sensing image acquisition of a to-be-monitored land through a remote sensing sensor, and carries out the structural complexity analysis and image region division. The method comprises the steps of forming a non-uniform region set, analyzing and acquiring category probability vectors of pixel positions of all regions in the formed non-uniform region set to construct a tag map of a whole remote sensing image, comparing pixel-by-pixel categories on a current tag map and a reference tag map to form a change mask map, identifying a structural change region according to the change mask map, and identifying a structural change region through sequential analysis. And determining whether the corresponding candidate tag inconsistent region under different time phase conditions is still a structural change region, so as to obtain a judgment result, and updating the electronic map based on the judgment result.

The invention relates to the technical field of path planning, and discloses a path planning method and system of an AGV (Automatic Guided Vehicle) for a silver electrolysis process workshop. The method comprises the following steps: carrying out environment characteristic acquisition and electronic map construction on a silver electrolysis process workshop to obtain a silver electrolysis process workshop electronic map; calculating an initial optimal path of the AGV from the current position to the target workstation; detecting the actual driving resistance in the execution process of the initial optimal path to obtain a path correction parameter; performing local adjustment to obtain an energy-saving safe path; and in the process that the AGV executes the energy-saving safe path, the front moving obstacle and the electrolyte leakage area are monitored in real time, and a temporary detour path is generated. According to the application, the path planning is more suitable for the actual environment characteristics of the silver electrolysis workshop, the emergency situation of the silver electrolysis workshop can be timely handled, the equipment safety and the production continuity are guaranteed, the no-load rate of the AGV is reduced, and the overall logistics efficiency of the silver electrolysis workshop is improved.

The invention discloses an intelligent digital rail transit simulation test system based on a digital twinborn technology, which comprises a digital track simulation platform, a digital track internal test platform and a central digital track server, and a visual digital track 3D scene model is constructed by joint design based on the rubber wheel train dynamic model data and the digital track urban construction coordinate graph. The digital track internal test platform comprises a test navigation control unit, and a digital track mathematical model, an electronic map, magnetic coding data and environment perception simulation information are preset in the test navigation control unit. The train equipment state can be monitored, the train equipment state transition can be controlled in real time, the artificial intelligence machine learning technology is introduced, and the test effectiveness is improved; and a real vehicle and a simulation machine can be accessed at the same time to be converted into a test platform before internal product release. The invention further discloses an intelligent digital rail transit simulation test method based on the digital twinning technology.

The invention discloses a robot dog inspection path intelligent planning and dynamic adjustment method, system and device and a medium, and belongs to the technical field of robot path planning, and the method comprises the steps: calculating a task emergency degree index according to a weight coefficient of an inspection point and a time constraint, and determining a task priority; constructing a hierarchical electronic map containing the terrain difficulty coefficient and the moving cost; performing global path planning through a comprehensive cost function by adopting an A star algorithm; environment information is collected in real time through multiple sensors, and the dynamic obstacle layer is updated; performing real-time trajectory optimization by adopting a local path planning mode; selecting local path correction or global path re-planning according to the path execution state score; energy needed for completing the remaining tasks is predicted, and a charging path is planned when necessary. According to the invention, multi-target adaptive optimization of path planning is realized, a coordination mechanism of global planning and local adjustment is established, and the execution efficiency and reliability of inspection tasks are improved.

The invention provides a high-precision railway map generation method and system based on one-way trajectory correction, and relates to the technical field of heavy haul railway transportation, and the method comprises the steps: collecting a continuous image sequence and spatial attitude data of a current train in a driving process at the same time; determining pose change data of the current train based on visual feature points in the continuous image sequence; performing synchronous positioning and map construction based on the pose change data and the spatial pose data to generate an initial electronic map; and based on mileage information and image positions corresponding to preset markers in the continuous image sequence, the mileage and the track of the current train in the initial electronic map are corrected, and a corresponding electronic map of the current train in the driving process is generated. According to the method and system provided by the invention, the generation efficiency and accuracy of the railway electronic map are improved.

The invention discloses a base station coverage anomaly detection method based on big data analysis, and belongs to the technical field of base station coverage detection in the technical field of communication. Aiming at the problems that the existing base station coverage anomaly detection is insufficient in accuracy and cannot adapt to dynamic environment change, the method comprises the following steps of: acquiring operation data such as received signal strength indication values of all base stations in a target area for continuous 1-30 days and 10-60 minutes, performing dimension reduction processing, and calculating a coverage characteristic value obtained by multi-dimensional index linear weighting; the method comprises the following steps: acquiring a coverage anomaly probability value, inputting the coverage anomaly probability value into an isolated forest model which is trained by historical data and can be dynamically updated, outputting the coverage anomaly probability value, and when the coverage anomaly probability value is in an interval greater than 0.7 and less than or equal to 0.9, marking a corresponding base station position on an electronic map as a coverage anomaly area. The method can accurately position the abnormal coverage area of the base station, is suitable for real-time monitoring and abnormity identification of the coverage state of the base station in communication network maintenance, and improves the network optimization efficiency and the service quality.

The invention relates to the technical field of position tracking, in particular to an intelligent bracelet real-time position tracking visualization method and system. The method comprises the following steps: acquiring multi-dimensional sensing monitoring parameters of a user based on a smart bracelet, performing real-time motion state evaluation of the user, and performing adaptive adjustment of a position acquisition frequency to generate an adaptive position acquisition frequency; performing real-time position positioning acquisition based on the adaptive position acquisition frequency, and performing frequency-by-frequency spatial position positioning calculation to obtain a high-precision compensation reconstruction trajectory; the method comprises the following steps: acquiring public electronic map information, performing scene key element identification, and performing key attribute cognitive marking to obtain a plurality of scene attribute memory anchor points; and performing relative position distribution analysis on the high-precision compensation reconstruction trajectory based on a plurality of scene attribute memory anchor points, and constructing an anchor point space trajectory visual mapping graph. According to the invention, high-precision real-time position tracking of the user is realized, and clear and visual multi-level map information rendering is presented.

The invention relates to the technical field of signal monitoring, in particular to a GNSS interference monitoring method and system based on a navigation electronic map platform, and the method comprises the steps: obtaining corresponding GNSS signal data through a plurality of GNSS receivers distributed in a network, uploading the GNSS signal data, calling a pre-trained GNSS signal analysis model, and carrying out the calculation of the GNSS signal analysis model. Obtaining a corresponding GNSS signal analysis result; calling a corresponding GNSS signal type based on the GNSS signal analysis result, judging whether the GNSS signal type is in an abnormal mode, if so, determining the GNSS signal as a GNSS interference signal, and identifying a corresponding interference source position; and updating and displaying the detected interference source position and the corresponding interference influence range on the electronic map platform in real time, generating a corresponding suggested avoidance path on the electronic map platform based on the interference source position and the interference influence range, and sending the suggested avoidance path to a user on the electronic map platform. According to the invention, the accuracy of GNSS interference monitoring can be improved.

The invention provides a method for planning a target speed curve in a train pull-in parking stage. The method comprises the following steps: S1, reading speed limiting information in a train pull-in braking stage from a route electronic map; s2, according to the speed limiting information, a pre-braking rate sequence is obtained based on a segmented uniform deceleration motion model; s3, smoothing the pre-braking rate sequence to obtain a target braking rate sequence; s4, obtaining a target speed curve of each speed limiting section based on an acceleration and deceleration motion model according to the target speed and the target braking rate sequence at the starting point; and S5, performing interpolation processing on the target speed curve of each speed limiting section to obtain target speed curves at equal time intervals so as to complete the target speed curve planning in the train arrival parking stage. According to the method, the target speed curve in the train pull-in parking stage is smooth, the braking deceleration change in the whole deceleration stage is small, the situation of switching between deceleration and constant speed back and forth is avoided, the riding comfort of passengers is greatly improved, and the operation energy consumption is correspondingly reduced.

The invention relates to an active train obstacle detection method and apparatus based on a positioning technique. The active train obstacle detection method comprises the following steps: S1, acquiring an electronic map; S2, correcting initial parameters; S3, performing parameter calibration of a video camera; S4, detecting a train obstacle; and S5, outputting an obstacle recognition result. The apparatus comprises a positioning module, a laser radar detection module, a video recognition module, an operational host and an interface module, wherein the operational host is connected to the positioning module, the laser radar detection module, the video recognition module and the interface module respectively. Compared with the prior art, the invention can increase the obstacle detection rate and reduce report failures and errors.

Systems and methods for vehicle localization are provided for a robotic vehicle, such as an autonomous mobile robot. The vehicle can be configured with multiple localization modes used for localization and / or pose estimation of the vehicle. In some embodiments, the vehicle comprises a first set of exteroceptive sensors and a second set of exteroceptive sensors, each being used for a different localization modality. The vehicle is able to disregard at least one localization modality for a number of different reasons, e.g., the disregarded location modality is adversely affected by the environment, to use less than the full complement of localization modalities to continue to stably localize the vehicle within an electronic map. In some embodiments, a localization modality may be disregarded for pre-planned reasons.

The invention relates to the technical field of intelligent logistics, and discloses an intelligent logistics-oriented path planning method and system, and the method comprises the steps: determining a working area of a logistics vehicle, dividing the logistics vehicle into multiple paths according to traffic lights and guiding arrows, collecting the information of the paths and the vehicle through a detection unit, drawing an electronic map from an overlook angle, and carrying out the planning of the path. The processing unit calculates the vehicle density P of the obtained path; acquiring corresponding vehicle density according to corresponding parameter information, sequencing vehicle density data groups, planning a path by combining with an actual departure place and a destination, predicting a next time period by acquiring current vehicle speed and time period information, and performing combined analysis on three parameters including the vehicle density, an average vehicle speed and a vehicle speed fluctuation value to obtain a vehicle density prediction result. Therefore, the effect of improving the working efficiency is achieved.

The invention relates to the technical field of Internet of Things, and provides an obstacle avoidance method of an unmanned sweeper based on V2X communication and related equipment thereof. Space-time alignment and map initialization are carried out on satellite positioning information and real-time V2X communication data to obtain a reference electronic map, and rasterization fusion is carried out on the reference electronic map and laser radar point cloud data to obtain a dynamic obstacle probability map. Performing dynamic path planning on the dynamic obstacle probability map according to an A * algorithm to obtain an initial obstacle avoidance global path, and performing dynamic optimization on the initial obstacle avoidance global path according to real-time V2X communication data through a vehicle motion model to obtain a local optimization track; and performing motion analysis and instruction synthesis on the local optimization track through a differential driving model to obtain a driving control instruction. According to the invention, through multi-source information fusion, efficient probability mapping, double-layer path optimization and feedforward-feedback control compensation, the obstacle avoidance precision, the response speed and the driving smoothness in a complex dynamic environment are improved.

A navigation interface prompt method, performed by a terminal, includes: displaying a dynamic location identifier corresponding to a vehicle in an electronic map in a navigation interface, the dynamic location identifier being configured for indicating a real-time location of the vehicle on a navigation route, and the vehicle being in a first driving mode; and displaying, at a pre-prompt stage before the vehicle exits the first driving mode, a switch location identifier on the navigation route in the navigation interface, the switch location identifier being configured for indicating a predicted location at which the vehicle exits the first driving mode and switches to a second driving mode.

The invention relates to a dynamic optimization system and method for an intelligent operation and maintenance path of a photovoltaic base station. Real-time data are accessed and processed by using a data integration platform; the electronic map building module is used for calling the existing map service, marking on the map and dynamically updating the detailed information of the base station in real time to generate an electronic map; acquiring system work order data and work order task priority data in real time by using a work order acquisition module; selecting a corresponding path planning strategy by using a path planning optimization module, and for a single task, calculating an optimal path by using an A * algorithm; for multiple tasks, a priority weighted summation method is used for sorting, and then a path is planned; for new tasks, dynamically adjusting the task sequence and performing path fine adjustment; and finally, displaying the operation and maintenance path in real time by using a visual navigation module and navigating. Through multi-source data fusion and an intelligent algorithm, operation and maintenance path planning is optimized, task scheduling and path planning are dynamically adjusted according to real-time conditions, and it is ensured that tasks are efficiently completed.

The invention discloses an intelligent parking navigation system based on image recognition and the Internet of Things, and relates to the technical field of intelligent parking navigation, the system draws a three-dimensional electronic map of a parking lot, divides the parking lot into monitoring areas, deploys sensors and cameras to collect image data, and transmits the image data to a cloud through the Internet of Things. The intelligent regulation and control model module uses a convolutional neural network CNN to carry out parking space recommendation and path guidance. And the vehicle monitoring module monitors vehicles entering the parking lot in real time, calculates a geometric environment adaptation coefficient and evaluates a traffic risk. And the vehicle guiding analysis module calculates the traffic flow and the parking space idle index, and recommends a proper parking area for the vehicle. The parking space recommendation analysis module evaluates the comfort level of the parking space, ensures the safety of backing and parking, and avoids the risk of traffic jam or traffic accident through strategy adjustment. The system improves the parking efficiency and safety, and optimizes the parking experience.

According to the GIS fusion spatio-temporal data-based road traffic event-prone road section analysis method provided by the invention, the road traffic event information in the target area range is comprehensively acquired through different acquisition modes, and the comprehensiveness and diversity of the data are ensured. According to semantic description information for describing road traffic events based on natural languages, structured event occurrence time and position information are accurately extracted from gathered semantic description information by utilizing a semantic analysis technology and are converted into comprehensive information data fused with time information, so that the accuracy and efficiency of subsequent data processing are greatly improved. The converted space-time element fusion data of the road traffic event is associated and coupled with the vector electronic map road network data, so that deep fusion of the space-time data is realized; the fusion not only facilitates the unified management and efficient utilization of data, but also provides a solid foundation for the deepening application of the spatial position of the road traffic event.

The invention discloses an airport runway FOD inspection and operation safety guarantee system in the field of airport runway safety detection. A ground control platform receives three-mode image data of an unmanned aerial vehicle platform and sends flight control data; the unmanned aerial vehicle platform receives the flight control data, executes flight actions, collects three-mode image data and sends the three-mode image data to the ground control platform; the ground control platform comprises an FOD detection module, a map module and a task scheduling module; the FOD detection module receives the three-mode image data and performs video image recognition to generate image recognition data; a gridding electronic map is arranged in the map module, and the FOD detection module superposes the image recognition data on the gridding electronic map to generate map obstacle data; and the task scheduling module sends the flight control data to the unmanned aerial vehicle platform. According to the invention, three-mode image recognition is carried out on the airport scene through the unmanned aerial vehicle platform to enhance the FOD inspection detection accuracy, and the unmanned aerial vehicle platform is utilized to increase the monitoring range, so that emergencies can be found in time.

The invention discloses a path planning method and system based on Beidou satellite positioning, and relates to the technical field of Beidou satellite positioning, and the method comprises the steps: carrying out the high-precision positioning and error correction of Beidou satellite signals through employing a multi-source sensor fusion method, and obtaining the position information; matching the electronic map data with the position information by adopting an electronic map matching method to obtain electronic map data corresponding to the current position; constructing a traffic flow prediction model based on the position information and a machine learning algorithm, and inputting the position information into the traffic flow prediction model to obtain a traffic condition prediction result; based on the traffic condition prediction result, planning a path from the current position to the destination by adopting a path search algorithm to obtain a preliminary path; performing personalized adjustment on the initial path according to user preference setting to obtain a recommended path; and monitoring the final recommended path by adopting a real-time monitoring and feedback mechanism, evaluating the position change and traffic condition in the path, and obtaining a final path planning strategy.

The invention relates to the technical field of agricultural intelligent equipment, in particular to a field sowing grain distance detection system and method based on computer vision, and the method comprises the steps that an image collection module collects 4KRGB and near-infrared data of a sowing area; the image processing module is used for processing and correcting the acquired image in real time; the grain distance feature deep learning analyzer strengthens seed feature extraction through an attention mechanism based on an improved YOLOv5 algorithm, accurately distinguishes weeds from seeds, and calculates a center distance deviation value of adjacent seeds based on a preset target grain distance; the positioning fusion module fuses Beidou positioning data and a visual odometer track, generates seed longitude and latitude and burial depth coordinates by using a high-precision farmland surface elevation model, and maps the seed longitude and latitude and burial depth coordinates to a farmland electronic map; and the dynamic regulation and control execution mechanism adjusts the rotating speed of the seeder or the seeding gap according to the grain distance deviation value and a priority strategy, and dynamically corrects the grain distance. Therefore, the problems of high detection error rate, single detection algorithm, poor data relevance and the like in the prior art are solved.

The invention relates to the technical field of railway communication, and provides a train message information transmission method and system, and the method comprises the steps: constructing an electronic map, and storing the ID, type and position information of each transponder on a railway; when the train is powered on for the first time, the initial position of the train is obtained, transponder IDs on the two sides of the train are determined in the electronic map according to the initial position, the ID of the next transponder is selected according to the running direction of the train, and the type of the transponder is obtained; when the train runs, the ID of the passing transponder is recorded in real time, and the type of the next transponder is predicted according to the ID of the recently passing transponder; and adjusting a receiving mode of a train transponder receiving module according to the predicted transponder type, and adaptively receiving message information sent by the next transponder. According to the invention, the train control system does not need to add sidelobe management and transponder suppression functions, and can meet the communication requirements of two transponders.

The invention belongs to the technical field of rail transit automatic driving, and particularly relates to a shunting locomotive ATO high-precision alignment parking control system and method. The control system comprises a fusion positioning module, a laser ranging module, a speed control module and a distance compensation module. The fusion positioning module carries out high-precision fusion positioning according to the precise longitude and latitude, the line transponder position information, the real-time speed and the wheel cycle pulse number, and provides precise position information for the speed control module in combination with an electronic map; the laser ranging module receives a laser ranging distance on a coupled and propelled molten iron tank car or a railway wagon in real time through vehicle-to-vehicle communication; the speed control module calls a speed control algorithm to perform traction and brake control on the locomotive according to the accurate position information provided by the fusion positioning module and the distance information provided by the laser ranging module; and the distance compensation module realizes distance fine adjustment after accurate parking. The invention provides a shunting locomotive ATO high-precision alignment parking control system and method.

The invention provides a train positioning method and system based on Beidou navigation and inertial navigation, and the method comprises the steps: arranging a Beidou positioning terminal and inertial navigation equipment on a train, enabling the Beidou positioning terminal to operate independently of vehicle-mounted automatic protection equipment of the train, enabling the Beidou positioning terminal to be connected with the vehicle-mounted automatic protection equipment, and enabling the inertial navigation equipment to operate independently of the vehicle-mounted automatic protection equipment; the Beidou positioning terminal is used as an input source of the vehicle-mounted access unit; satellite positioning data of the Beidou positioning terminal are converted into signal electronic map position information through vehicle-mounted automatic protection equipment; when the train passes through an area in which the satellite signal is lower than a preset signal threshold value, performing auxiliary maintenance on the position information of the signal electronic map through inertial navigation equipment to obtain updated position information of the train; the updated position information is transmitted to the ground based on the vehicle-mounted access unit, so that the ground carries out movement authorization calculation on the train and a rear train of the train based on the updated position information; according to the invention, the train positioning precision can be improved.

The invention discloses a map moving track deviation correction method and system, belongs to the technical field of electronic maps, and aims to solve the technical problems that in the prior art, deviation exists in GPS track data, so that position information in map application is not accurate, and the map moving track deviation is not accurate. According to the technical scheme, the method comprises the following steps: data acquisition: receiving original latitude and longitude coordinate data and sensor data from a GPS satellite; data preprocessing: denoising and missing value processing are performed on the original GPS trajectory data, and the data quality is improved by using a Kalman filtering algorithm; feature extraction: extracting spatio-temporal features from the preprocessed data; constructing a deep learning model: constructing a deep neural network model for learning the spatial pattern and time sequence features of the trajectory data; the deep learning model inputs the spatial pattern and the time sequence characteristics of the trajectory data, and outputs the trajectory point coordinates after deviation correction; training and optimizing; correcting deviation in real time; and dynamically adapting.

The invention provides an intelligent marine emergency equipment automatic positioning method and system. Wherein multiple distress signals are received and fused, and optimal geographical location information and timestamps are generated; determining a distress area on a preset sea area electronic map, correcting a distress position, evaluating probability distribution of each potential distress area, and generating a primary search target with the highest probability; a thermal imaging and optical sensing system on the rescue unmanned aerial vehicle is started for scanning, and a high-accuracy potential survivor position is generated; the search and rescue path is dynamically adjusted and optimized, the search strategy is adjusted, the optimal flight path is updated in real time, and an economical and efficient search and rescue path plan is generated; and timely feeding back the accurate coordinates of the position of the potential survivor to the nearest rescue coordination center, and guiding first-aid equipment to go along the optimal path to implement rescue. According to the technical scheme provided by the invention, the search and rescue efficiency and accuracy are improved, and the position of a potential survivor can be quickly and accurately positioned.