106 results about "Mobile context" patented technology

A modular system designed for privacy-preserving content recognition and supplemental content delivery across web and mobile environments. The system employs lightweight character sampling and vision-based recognition to generate unique content fingerprints without storing or replicating original data. It features a hybrid processing architecture, using local computing resources for intensive tasks while optimizing performance on resource-constrained devices. Core functionalities include multi-method content fingerprinting, real-time monitoring with adaptive sampling, and secure supplemental content association. Operating entirely on the client-side, it complies with website terms of service and privacy regulations. Advanced features include AI-driven content recognition, blockchain-based verification, and granular content targeting through resizable selection interfaces. This technology enables seamless delivery of supplemental content while preserving privacy, reducing resource usage, and ensuring scalability across browsers, mobile applications, and edge devices. It is particularly applicable in industries such as education, retail, and secure data sharing.

Detecting, locating, identifying, engaging, and / or shifting objects in automated or semi-automated fashion as well as methods, systems, apparatuses, and computer-program products therefor. Embodiments used for shifting objects in automated or semi-automated fashion may be implemented in stationary environments, and / or in moving, e.g., in-transit, environments, and may be used to transfer, route, and / or organize objects based on their designated destinations. The embodiments may further be implemented in a logistics network, thereby increasing the efficiency and capacity of the logistics network, among other benefits.

A method for detecting the sources of distributed denial of service attacks is disclosed. Control plane signaling data and user plane data is collected using network monitoring equipment connected to a communications network. The control plane signaling data and user plane data is correlated. Amounts of traffic are calculated for individual computing devices based on the correlated data. One or more computing devices are determined based on the amounts of traffic associated with the one or more computing devices satisfying a device anomaly criterion. A record including a list of the one or more computing devices is generated.

The invention discloses a communication and inductance integration method for a communication waveform in a high mobile environment. The method comprises the following steps: constructing a UAV-ISAC system based on AFDM; constructing a model of a communication signal sent by the UAV to the base station and a model of an echo signal received by the UAV and perceived by a ground user; determining the signal-to-noise ratio of each time slot communication part link and the signal-to-noise ratio of a sensing part echo based on a communication signal model and an echo signal model, thereby determining the capacity of each time slot communication link and the sensing mutual information amount of each user, and determining the total sensing mutual information amount, the total communication capacity of the UAV in the whole flight time, and the total consumed energy; constructing a total optimization problem by using the total communication capacity and the total consumed energy, and decomposing the optimization problem into three sub-problems of user scheduling optimization, transmitting power optimization and UAV trajectory optimization; and by constructing different constraint conditions and solving the three sub-problems, an optimization result is obtained. According to the invention, the energy efficiency of the UAV-ISAC system based on AFDM can be maximized.

The invention discloses a multi-unmanned aerial vehicle communication perception integration method based on adaptive reward weight adjustment. The method comprises the following steps: a plurality of unmanned aerial vehicles equipped with communication sensing integrated modules are matched to provide downlink communication service for large-scale mobile ground nodes under the condition of ensuring sensing fairness and information age; according to the method, multi-agent near-end strategy optimization is introduced to train trajectory planning in tasks of multiple unmanned aerial vehicles, collision, node association and resource allocation strategies are avoided, and the communication throughput of the system is maximized; for the problem of frequent and repeated training caused by ground node movement, an adaptive reward weight adjustment MAPPO method is introduced for dynamically guiding the decision process of each unmanned aerial vehicle, and compared with a reference scheme, the method can improve the communication throughput of edge ground nodes; experimental results prove that the method can enable multiple unmanned aerial vehicles to cooperate in a ground node mobile environment to obtain higher communication throughput.

According to the technical scheme, the invention discloses a non-invasive pulmonary arterial pressure and capillary wedge pressure continuous estimation device which comprises a three-axis inertial sensing module, an acoustic sensing module, an electrocardio electrode module, a feature extraction module, a calibration and estimation module and an edge calculation module. Single three-axis inertial sensing and acoustic signal fusion are utilized, and the PAP and the PCWP are continuously estimated in a non-intrusive mode through a calibration regression / deep learning algorithm. According to the invention, single inertia and acoustics are innovatively taken as a collection core, and a calibration-estimation closed loop is supplemented, so that the device has the advantages of long-term continuous monitoring and real-time output of hemodynamic parameters in low-trauma, wearable and mobile environments.

The invention relates to a wood counting method in a mobile scene based on DeblurGAN-v2 and YOLOv5, and belongs to the technical field of information. The problem that in the prior art, motion blurred images cannot be effectively processed, so that wood counting precision is low, and efficiency is low is solved. According to the method, an industrial camera is used for collecting a motion blurred image of wood in a moving scene, and a visual image calibration tool is used for marking the boundary of the wood in the image to construct an original data set; the method comprises the following steps: inputting an original data set into a DeblurGAN-v2 model for preprocessing operation, generating a clear image, and constructing a deblurring data set; and training the deblurred data set, establishing a wood detection model based on YOLOv5, and performing model evaluation. And inputting the images in the deblurring data set into the trained YOLOv5 model for prediction, and identifying and counting woods in the images. The accuracy and efficiency of wood counting in the mobile environment are remarkably improved.

The invention discloses a tracking motion analysis method and system based on a four-wheel drive wheel type ROS platform, and the method comprises the steps: obtaining an RGB image and depth information, carrying out the preprocessing, extracting two-dimensional coordinates of a joint key point, and mapping the two-dimensional coordinates into three-dimensional coordinates; calculating to obtain a target center point coordinate; the rotation angle and the movement distance are converted into movement instruction signals; constructing a skeleton edge set, extracting spatial features and dynamic features through calculation, and integrating the spatial features and the dynamic features to obtain a fusion feature vector; inputting the fusion feature vector into a preset action evaluation model, and outputting an evaluation result; and generating personalized action correction feedback according to an evaluation result. According to the method, target tracking, motion capture, dynamic evaluation and personalized feedback generation can be realized in a mobile environment, so that the scientificity, the real-time performance and the intelligent level of training are remarkably improved.

A mobile environmental sensor system includes a first mobile environmental sensor, a controller, and a network transmitter disposed on a transport unit. The controller is in electronic communication with the first mobile environmental sensor and the network transmitter. The controller includes a processor and a memory. The processor is configured to trigger a measurement from the first mobile environmental sensor. A sensed value is received from the first mobile environmental sensor. The processor compares the sensed value as received from the first mobile environmental sensor to a reference sensed value received by the controller via the network transmitter. The processor calibrates the first mobile environmental sensor based on the comparison of the sensed value as received and the reference sensed value as received. The calibration includes a normalization between the sensed value as received and the reference sensed value as received. The normalization includes a time dependent component.

A system and method are disclosed for touchless, gesture-based form validation using real-time input from a standard camera. Spatial hand gestures are interpreted as mouse-like actions—such as drag, click, scroll, and hold—to complete form tasks without physical input. The system includes a vision-based input module, an AI-powered gesture recognition engine using landmark extraction, an interaction handler that maps gestures to DOM-compliant events, and a validation controller that confirms field focus, checkbox toggling, and submission. A visual feedback renderer provides real-time cues indicating gesture success, failure, or activity. Navigation buttons enable directional control and element repositioning. The method supports secure CAPTCHA-style workflows via randomized tasks and gesture thresholds, executing natively in browsers using WebAssembly or TensorFlow.js. Applications include bot prevention, accessible interaction, and secure, device-free input for web and mobile environments.

The invention discloses a vehicle-mounted micrometeorological monitoring and camping site disaster early warning system and method, and belongs to the technical field of vehicle-mounted meteorological monitoring, and the system comprises a data collection and preprocessing module which is used for obtaining and calibrating multi-source meteorological and geographic data; the microclimate modeling module is used for generating a microclimate grid with a real-time weather predicted value by taking local microclimate data as a benchmark and fusing cloud and geographic data; the disaster risk assessment module performs quantitative risk assessment on camping disasters such as flood, tree smashing, landslide and thunderstorm based on the data of the microclimate grid; and the early warning generation module generates visual early warning information including a disaster icon, a risk level, time information and a risk avoiding instruction according to the quantitative risk assessment result. According to the invention, by optimizing the layout of the sensors and introducing a terrain correction interpolation algorithm and scene disaster assessment, the meteorological monitoring precision in a mobile environment is improved, and timely early warning of camping field micro-scale disasters is realized.

A computer-implemented method, system, and computer program product for reducing loads of edge servers in an autonomous mobility environment. The load of an edge server, which controls autonomous vehicles located within the edge server's coverage area, is estimated. In response to the estimated load of the edge server exceeding a threshold value, an action to reduce the load of the edge server is implemented by controlling one or more of the autonomous vehicles to operate in a certain manner so as to reduce the load of the edge server. Examples of controlling the autonomous vehicles to operate in a certain manner so as to reduce the load of the edge server include modifying a movement of the autonomous vehicle, modifying a frequency of sending vehicle data, offloading calculations to be performed in the autonomous vehicle that were previously being performed in the edge server, restricting lane changes, etc.

The invention discloses a method for carrying out link self-adaption in a retransmission system and a mobile environment, which is characterized by comprising the following steps of: constructing and initializing a reinforcement learning neural network; acquiring information, wherein the information comprises channel condition information and HARQ process information fed back by the current user; monitoring whether a channel environment is switched; constructing an observation state vector according to the information; inputting the observation state vector into a reinforcement learning neural network, and outputting an MCS corresponding to the current HARQ process; transmitting a data packet containing the MCS to the user and receiving feedback information of the user; judging whether the current HARQ process is ended or not according to the feedback information, if so, calculating a retransmission conversion throughput award of the current HARQ process, performing state, action and award alignment integration, storing the state, action and award into an experience pool, and then entering a subsequent step; and training the reinforcement learning neural network based on a gradient descent method according to the plurality of empirical data. The problem that a traditional algorithm cannot adapt to an actual 5G network and a complex and changeable environment is solved.

A computer-implemented method, system, and computer program product for reducing loads of edge servers in an autonomous mobility environment. The load of an edge server, which controls autonomous vehicles located within the edge server's coverage area, is estimated. In response to the estimated load of the edge server exceeding a threshold value, an action to reduce the load of the edge server is implemented by controlling one or more of the autonomous vehicles to operate in a certain manner so as to reduce the load of the edge server. Examples of controlling the autonomous vehicles to operate in a certain manner so as to reduce the load of the edge server include modifying a movement of the autonomous vehicle, modifying a frequency of sending vehicle data, offloading calculations to be performed in the autonomous vehicle that were previously being performed in the edge server, restricting lane changes, etc.

An antenna control device (10) according to the present invention includes: a mobile environment characteristic measurement unit (11) that measures a displacement amount in a three-dimensional direction of a first communication device (1) on which a first antenna (3) is mounted; a storage unit (14) that stores antenna characteristics of the first antenna (3); and a determination unit (12) that determines whether or not a gain of the first antenna (3) is equal to or greater than a threshold when the first communication device (1) communicates with a second communication device (2), and in a case where the gain of the first antenna (3) is less than the threshold value, receives as input the antenna characteristics of the first antenna (3) and the displacement amount in the three-dimensional direction of the first communication device (1) to determine orientations of the first antenna (3) and a second antenna (4) that is mounted on the second communication device (2) so that the gain of the first antenna (1) is equal to or greater than the threshold; and a first antenna orientation change unit (13) that receives a determination result from the determination unit (12) and changes the orientation of the first antenna (3).

To provide a highly versatile movement management system and movement management method that can flexibly adapt to an environment change in a range where a mobile body moves.SOLUTION: A movement environment management device (70) includes: a storage unit (74) that stores environment marker data (74b) in which identification information of a marker (40) provided in a movement range of a mobile body (10), which operates autonomously, and control required in accordance with surrounding environment of the marker are associated with each other; and a control unit (71) that receives the identification information of the marker from the mobile body, specifies corresponding control with reference to the environment marker data, and transmits information related to the control specified for the mobile body.SELECTED DRAWING: Figure 1

To predict quality of wireless communication.SOLUTION: An information processing device performs: acquiring first data related to quality of wireless communication from a first device; acquiring second data related to a mobile environment of the first device; and generating for each mobile environment, communication quality data being the data obtained by mapping the quality of wireless communication to a geographic area based on the plurality of first and second data.SELECTED DRAWING: Figure 1

The present invention relates to a personal awareness system that provides users physical health / wellness / welfare safety as well as online digital safety by blocking inappropriate digital content. The personal awareness system comprises a network protection appliance for use on a local area network (LAN), a software application that is used on a mobile computing device, a cloud-based remote data processing resource to administer the system, artificial intelligence (AI) information systems, and a monitor computing device that an observer can use to monitor, track, and receive alerts related to the user. The system can support many users individually as well as groups of users. In operation, sensors associated with the mobile computing device monitor the health, wellness, and location of users and digital filter rules suppress inappropriate digital content from user access providing digital safety. The mobile computing device seamlessly transitions between LAN environments and wireless mobile environments.

Techniques for equipping mobile devices with two different types of wireless communication devices, one of which is part of a mesh network that can serve as a backup path for transmitting data to the internet. The mobile devices, such as mobile carts, can dynamically switch to the mesh network if Wi-Fi connectivity fails or becomes weak. This dual-network approach improves data transmission reliability, reduces dependence on a single network type, and ensures continuous operation, which can be important in certain environments, such as healthcare settings.

The utility model discloses a novel cavity dual-local-oscillator dual-polarization dual-output frequency demultiplier, the novel cavity dual-local-oscillator dual-polarization dual-output frequency demultiplier comprises a dual-output frequency demultiplier, a wind direction deflection component and an auxiliary heat dissipation component, the novel cavity dual-local-oscillator dual-polarization dual-output frequency demultiplier is especially suitable for being used on mobile equipment, such as mobile satellite communication vehicles, unmanned aerial vehicles and other mobile platforms, and the frequency demultiplier is suitable for being applied to the mobile equipment. In order to solve the problem that in the prior art, a common frequency demultiplier is prone to electromagnetic interference due to the change of a mobile environment, an electromagnetic shielding part is designed, and the electromagnetic shielding part plays a role in protecting and preventing interference on the dual-output frequency demultiplier; in order to solve the problem that the dual-output frequency demultiplier is prone to overheating due to insufficient heat dissipation caused by the arrangement of an electromagnetic shielding part, an auxiliary heat dissipation part is further designed, and air cooling auxiliary heat dissipation can be automatically conducted on the dual-output frequency demultiplier through the auxiliary heat dissipation part in the equipment moving process.

The application discloses an anti-characteristic-unstable Tor App traffic analysis method and system, first extracts basic characteristics and bidirectional statistics of traffic generated by a mobile phone App running on Tor as a candidate characteristic set, then selects a subset from the candidate characteristic set as the representation of the traffic, filters out the traffic of N specific application types by solving an application type combination optimization problem, selects N characteristic subsets from the candidate characteristic set, and iteratively selects a machine learning model and a characteristic set suitable for the specific application type by solving an optimal combination problem, so that the Tor App can be accurately identified. The application solves the problem of characteristic instability in Tor App traffic analysis caused by the instability of the mobile environment, the diversity of app work content and the increasing number of new apps running on Tor.

This invention provides an information processing device, an information processing method, and an information processing program that can provide a diverse virtual space participation-based mobility environment that takes into account the prediction of human behavior in relationships with others, i.e., interactions. [Solution] The information processing device comprises a measurement unit that measures the movement simulations of multiple users in real space and reflects the measured movement simulation results in a virtual space; a storage unit that stores the movement status of multiple users; a model generation unit that generates simulation model data based on the movement status and stored data; and a simulation execution unit that executes a simulation based on the model data reflected in the virtual space when multiple users participate in the virtual space using different means of transportation.

Techniques for equipping mobile equipment with two different types of wireless communication devices, one of which is part of a mesh network that may serve as a backup pathway to route data to the internet. The mobile equipment, e.g., mobile carts, may dynamically switch to a mesh network when Wi-Fi connectivity fails or is weak. This dual-network approach enhances the reliability of data transmission, reduces the dependency on a single type of network, and ensures continuous operation, which may be important in certain environments, such as in a healthcare setting.

The invention discloses an autonomous mobile environment adjusting system and method based on layered multi-mode perception and dynamic comfort field coupling. The system adopts a unique layered architecture combining'global perception of a fixed layer 'and'precise perception of a follow-up layer', and the contradiction between global monitoring and local concentration of the service robot is solved. By fusing multi-modal data, the system initiatively generates a'dynamic comfort field 'for guiding actions, and decoupling precise movement and air supply control are achieved. The system can also intelligently cooperate with equipment such as an air conditioner, and the overall energy efficiency is optimized. According to the invention, the design of multi-stage active safety protection and privacy protection is integrated, and a complete, intelligent and reliable solution is provided for indoor personalized comfortable environment adjustment.

To update an environment map suitable for long-term implementation.SOLUTION: A method of updating an environment map M1 includes: the step of causing a moving device 1 to move a moving environment ME; the step of creating a local map M2 representing the presence or absence of an object around the moving device 1 for each of a plurality of passing points from start to end of movement; the step of creating a temporary environment map representing a region at this movement by use of a plurality of local maps M2 created from the start to end of the movement; the step of acquiring a plurality of temporary environment maps by causing the moving device 1 to move the moving environment ME a plurality of times; the step of, based on the plurality of temporary environment maps acquired, for each of a plurality of positions included in the moving environment ME, creating a frequency value map M3 by assigning a frequency value representing frequency in which the object is present at the position in the plurality of times of movement; and the step of updating the environment map M1 based on the frequency value map M3.SELECTED DRAWING: Figure 8

To provide a moving body capable of stably guiding a user even in a traveling environment having a step, and a control method of the moving body.SOLUTION: The moving body 100 includes a drive wheel 21 that comes into contact with a floor surface F, a drive motor capable of rotating the drive wheel 21 around a first rotation axis O1 as a rotation center, a main body part 10 supported by the drive wheel 21 and moving with respect to the floor surface F when the drive wheel 21 rotates around a second rotation axis O2 as a rotation center, a passive wheel 31 that comes into contact with the floor surface F and is provided on a front side F R in a traveling direction D of the main body part 10 to support the main body part 10, and a handle 40 that can be gripped by a user, a notification unit 44 capable of notifying the user of predetermined information, and a control unit capable of controlling the notification unit 44 and the drive motor based on a detection result of contact between the passive wheel 31 and the step S of the floor surface F.SELECTED DRAWING: Figure 4

Provided are a multi-view hyperspectral image matching method and system. The multi-view hyperspectral image matching method according to an embodiment of the present invention: acquires N channel multi-view hyperspectral images; generates D channel multi-view hyperspectral images from the acquired N channel multi-view hyperspectral images; extracts feature points from the generated D channel multi-view hyperspectral images and searches for matching points; and matches the N channel multi-view hyperspectral images on the basis of the feature point matching results. Accordingly, it is possible to reduce computational complexity during hyperspectral image matching, thereby enabling real-time processing and reducing power consumption consumed in a mobile environment.

The invention provides an Internet of Vehicles edge computing task on-demand unloading and priority decision-making method based on a double-depth Q network, and belongs to the field of Internet of Things edge computing. Comprising the steps that a user vehicle generates a calculation task, a communication and calculation module is constructed, an element extraction module is constructed, an unloading decision module is constructed, a priority evaluation module is constructed, and a task processing result is returned. According to the invention, edge computing and reinforcement learning are combined to enable a vehicle to cooperate with a roadside service unit to efficiently process a complex computing task in a mobile environment, so that the problem that a vehicle terminal cannot independently process a computing sensitive task in time due to limited computing resources is solved; according to the method, the vehicle calculation capability and the road side service unit calculation capability are dynamically coordinated in a vehicle edge calculation mode, and through an improved reinforcement learning method, the method can adapt to mobile scene task processing requirements through multiple iterative training.

This invention discloses a method for link adaptation in retransmission systems and mobile environments. The method includes: constructing and initializing a reinforcement learning neural network; acquiring information, including current user feedback on channel conditions and HARQ process information; monitoring whether the channel environment has switched; constructing an observation state vector based on the information; inputting the observation state vector into the reinforcement learning neural network and outputting the MCS corresponding to the current HARQ process; transmitting data packets containing the MCS to the user and receiving user feedback; determining whether the current HARQ process has ended based on the feedback information; if so, calculating the retransmission throughput reward of the current HARQ process, aligning and integrating the state, action, and reward, storing it in an experience pool, and then proceeding to subsequent steps; training the reinforcement learning neural network based on gradient descent using several empirical data points. This invention solves the problem that traditional algorithms cannot adapt to actual 5G networks and complex, ever-changing environments.