7581 results about "Mobile device" patented technology

The present invention relates to an intelligent, context-aware battery management system embedded within a mobile device that dynamically allocates power resources based on real-time user behavior, system state, and environmental context. It incorporates a smart recognition engine that analyzes sensor-derived telemetry data to compute behavioral deviation scores, enabling the system to anticipate abnormal or emergency-prone conditions. A continuous activity classification module contextualizes user motion and geolocation to inform power policy decisions. Upon detecting significant behavioral anomalies or critically low battery conditions, an emergency mode subsystem is triggered, restricting device operations to essential functionalities while preserving energy for critical communication and navigation tasks. The system also establishes a secure, lightweight emergency communication tunnel for relaying essential metadata, including GPS and behavioral indicators, to predefined response servers.

The invention relates to a flow media bandwidth adapting system, which comprises flow server, media provider, and mobile device, wherein the flow server comprises server flow protocol module, bandwidth analyzing module, bandwidth selecting module, document analyzing module and media sending module; the mobile device comprises terminal flow protocol module, wireless module, bandwidth detecting module, buffer module and play module; the mobile device via wireless module and bandwidth detecting module timely reports received bandwidth state and media receiving state to the server flow protocol module; the server flow protocol module sends said information to the bandwidth analyzing module to find the media bandwidth and sending speed, to be sent by the media sending module. The invention can automatically adjust the sending speed and code bandwidth of media document via the network state and media receiving state, to improve relative play effect.

The invention relates to the technical field of atmospheric pollutant detection, and discloses a method and a system for detecting excessive emission of atmospheric pollutants. The method comprises the following steps: acquiring pollutant concentration data of multiple monitoring points in a target area to form an original data set; abnormal value detection and correction are carried out on the data set, sensor fault outliers are eliminated, and a preprocessed data set is obtained; extracting concentration change trend characteristics in a preset time window of each monitoring point, and constructing a spatial-temporal characteristic matrix; inputting the matrix into a pollutant diffusion model, calculating a transmission path and strength between monitoring points, and generating a regional transmission network; identifying a potential source region of abnormal fluctuation of pollutant concentration based on a network, and marking the potential source region as a candidate region to be checked; performing multi-scale concentration gradient analysis on the candidate area, and determining a key monitoring area; arranging mobile equipment in the key monitoring area, and collecting high-precision component data; and comparing the data with a standard emission source feature library, matching emission source types of which the similarity exceeds a threshold value, judging whether the emission exceeds the standard or not, and generating a detection report.

The invention discloses a VLM model intelligent decision-making-based driving method and device and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: extracting key visual features from continuous multi-frame driving scene images based on a preset visual feature extraction algorithm; inputting a user instruction and a time sequence visual Token corresponding to the key visual features into a preset VLM model for multi-modal alignment, and generating a target planning Token; inputting the target planning Token and the time sequence vision Token into a preset trajectory generation model to obtain a predicted trajectory; and converting the predicted trajectory into a control signal, and controlling the mobile device to complete a moving action based on the control signal. The problem of modal difference between a semantic space and an action space is solved.

A method for using a local large language model (LLM) within a user's secure computing environment is disclosed. The LLM operates behind a firewall to prevent transmission of sensitive data, and utilizes an encrypted vector database and artificial intelligence techniques for content retrieval, response generation, and task anticipation. This system can be used on mobile, wearable, vehicle, or IoT devices and offers various services such as health monitoring, financial advice, automated communications handling, and personalized daily activity optimization. It also has the ability to detect fraud, fine-tune responses using augmented user data, assist in negotiations, identify personal interests, and provide health recommendations based on dietary and physical activity data.

The invention discloses a mobile terminal streetscape image real-time segmentation method based on a lightweight neural network, and relates to the technical field of image segmentation. The method comprises the following steps: firstly, carrying out 320 * 320 adjustment, Z-score standardization, adaptive histogram equalization and 3 * 3 Gaussian filtering preprocessing on an input streetscape image; then, an improved MobileNetV3 backbone network is used, and a five-scale feature map is output in combination with DropBlock regularization through eight feature extraction stages including depth separable convolution and an SE attention module; multi-scale features are fused through a U-shaped structure, and a fusion feature map is generated through up-sampling, element-by-element addition of dimension reduction low-layer features and an attention gating module; and during reasoning, outputting a segmentation mask by using a convolutional layer, Softmax and a conditional random field, and finally performing knowledge distillation, weight pruning, 8-bit quantization and TensorRT optimization. According to the invention, high-precision real-time street view segmentation is realized, the robustness is high, and the method is suitable for different devices and scenes.

The invention provides a steel surface defect detection method and device, equipment and a storage medium. Relates to the technical field of image recognition. The method comprises the following steps: collecting steel surface defect images, and performing data enhancement processing on the steel surface defect images to obtain a data set after data enhancement; a backbone and neck network of a reference model YOLOv11s network is improved, an ECS-YOLOv11s model is constructed by adopting a multi-scale feature fusion mode, a data set after data enhancement is input into the ECS-YOLOv11s model to train and shoot and collect steel surface images in real time, the steel surface images are input into the trained ECS-YOLOv11s model, and a steel surface defect detection result is obtained. According to the method, the steel surface defects can be accurately and efficiently recognized, meanwhile, the needed calculation amount and parameters are reduced, and the requirement for deployment on mobile equipment can be met.

A system and method for extending mobile-optimized multi-stage language model processing with federated persistent cognitive architecture. The system processes prompts through a first large language model to generate “thoughts,” which are cached and processed with the original prompt through a smaller language model. Building upon the three-tier thought caching, the system implements a federated multi-tier hierarchy with local device, domain-specific branch, and global collective caches. A federated cognitive orchestrator coordinates operations across multiple domain-specialized instances, managing thought routing, state synchronization, and cross-domain knowledge sharing while maintaining domain boundaries. During user inactivity, autonomous reasoning continues in cloud environments, generating insights from existing thoughts and interaction history. The system performs memory consolidation, thought cache optimization, and cross-domain pattern recognition without consuming mobile device resources, while maintaining privacy boundaries. This persistent cognitive architecture functions as an evolving reasoning partner rather than merely a responsive tool.

A method performed by an apparatus for controlling autonomous driving of a vehicle is introduced. The method may comprise generating, based on a segmentation model processing point cloud data, a first semantic grid map, generating, based on an object detection model, a second semantic grid map, adjusting a probability regarding whether occupancy exists for an element included in each grid of the first semantic grid map and the second semantic grid map, and generating a fused grid map by determining, as a representative label, at least one label corresponding to a highest value among final probabilities of the at least one label, wherein the final probabilities are determined based on whether the at least one label matches the element, outputting, based on the fused grid map, a signal, and controlling, based on the signal, autonomous driving of the vehicle.

The invention provides a method and a system for actively monitoring, regulating and controlling a clean room, which are characterized in that environmental parameters in the clean room and spatial state information of a dynamic object are acquired through cooperation of a fixedly arranged sensor and a sensor carried by a mobile device, and the environmental parameters comprise airflow velocity, temperature and humidity, pressure difference, particulate matter concentration, illuminance and the like; the dynamic objects comprise positions of the personnel and the equipment and geometric models of the personnel and the equipment. And cleaning and fusing the collected data to generate a standardized parameter sequence with a time label, and constructing a three-dimensional dynamic environment model by combining a clean room structure and dynamic object information to realize grid mapping and visual management of environment parameters in the model. And on the basis of the model, an environment state change trend is predicted, risk grade evaluation is executed, a hierarchical regulation and control instruction is generated, closed-loop regulation and control and parameter adaptive adjustment of the clean room environment are finally realized, and the intelligent and refined level of clean room environment regulation and control is improved.

A magnetic component assembly for a mobile device provides an improved connection between a mobile device and other mobile accessories. The magnetic component assembly may comprise an array of magnetic attachment elements enclosed in a structure and configured to magnetically align and attach to a corresponding array of magnetic elements disposed in a mobile device, a mobile device accessory, or another assembly component. Additional attachment features and elements disposed in or attachable to the assembly may provide further engagement or attachment options. The assembly may incorporate different combinations of components to adapt the assembly for different use-cases and provide greater utility. Various magnetic component assemblies may be suitable for use with a variety of mobile devices and accessories such as covers, cases, wallets, chargers, mounts, grips, and supports.

The present invention belongs to the field of multi-equipment safety management and control for personnel and equipment clusters at an underground coal mine driving working face, and solves the problem of safety hazards caused by human-machine collaborative operations as the mechanization level of underground equipment increases. Provided are a system and method for safety monitoring and early warning of human-machine collaborative operation at a working face. The system comprises a safety management and control system for mobile equipment at a working face, which is used for performing in real time position, orientation and environmental sensing of individual equipment and behavior analysis of drivers; working-face collaborative intelligent wearable devices, which are used for environmental sensing of operating personnel and individual equipment and acquiring in real time the motion postures of the operating personnel; and a working face output control subsystem, which is used for identification and management of operating personnel entry and exit, position monitoring of personnel and individual equipment, operating personnel behavior identification and monitoring and working environment monitoring, and generating corresponding alarm instruction information. The present invention can realize human-equipment and equipment-equipment safety management and control during multi-equipment collaborative operation at a driving working face.

One or more computing devices, systems, and / or methods for mobile device security profiling are provided. A device connected to a communication network is detected. Device profile information associated with the device is used to select a device behavior security model from available device behavior security models. The device behavior security model is provided to the device. The device utilizes the device behavior security model to determine whether the device is exhibiting normal operating behavior or abnormal operating behavior (e.g., an application on the device performing a denial of service attack). If abnormal operating behavior is detected by the device, then the device can perform a remedial action.

Some embodiments provide a method for initiating a video conference using a first mobile device. The method presents, during an audio call through a wireless communication network with a second device, a selectable user-interface (UI) item on the first mobile device for switching from the audio call to the video conference. The method receives a selection of the selectable UI item. The method initiates the video conference without terminating the audio call. The method terminates the audio call before allowing the first and second devices to present audio and video data exchanged through the video conference.

The invention relates to a dynamic visual map matching autonomous optimization method based on IMU sensing, and belongs to the technical field of positioning and navigation of autonomous mobile equipment. The method comprises the steps of obtaining IMU high-frequency motion data and visual image data, performing noise reduction to obtain carrier short-time attitude change information, performing semantic segmentation on an image to recognize a dynamic target, extracting feature points and performing dynamic target weight evaluation; calculating confidence degree scores of the feature points, and mapping fusion weights of the IMU and the vision through a self-adaptive credibility distribution mechanism; s3, predicting a trajectory and a potential matching area based on carrier short-time attitude change information, incrementally updating a local map, and matching by taking an IMU trajectory as a constraint to obtain an initial result; and detecting the matching validity, reducing the re-matching range by using an IMU short-time track during mismatching, and correcting an initial value to obtain a final result. The map matching precision and stability in a complex dynamic scene are improved, the real-time performance and continuity are balanced, and the problems that a traditional scheme is redundant in calculation power and slow in mismatch recovery are solved.

Methods, apparatus, systems, and articles of manufacture are disclosed for device authentication in a dedicated private network. An example apparatus includes interface circuitry, machine readable instructions, and programmable circuitry to utilize the machine readable instructions to generate first credentials associated with a first network based on second credentials associated with a second network, the first credentials including first location data corresponding to a dedicated private network (DPN), cause a mobile device to program a programmable subscriber identity module (SIM) of the mobile device based on the first credentials, and permit the mobile device to access the DPN based on a determination that second location data corresponding to the mobile device and included with the programmable SIM corresponds to the first location data.

Systems and methods are disclosed herein for a user to use a mobile device with a camera and a terminal device with a camera to manage and use passwords via QR (Quick Response) codes. The terminal device may generate and display a QR code for a user account or data. The user running a password manager app on the mobile device may scan the QR code of the user account or the QR code of the data to generate, store, and retrieve a password, and to display a QR code for the password. The terminal device may scan the QR code of the password to receive and use the password in sign-up, sign-in, data encryption, and data decryption procedures.

The invention provides a multi-dimensional map generation method and device based on multi-sensor tight coupling SLAM. The method comprises the following steps: acquiring image data, point cloud data and inertial data acquired by using a predetermined sensor combination; state propagation is carried out based on the inertial data, and positioning output under a global coordinate system and an estimation result used for point cloud position correction are obtained; generating a three-dimensional map and a semantic map; geometric elements are extracted based on the three-dimensional map, and a geometric annotation map is formed by global coordinates according to the geometric elements; projecting the spatial information to a plane, and superposing ground color textures from the image data to generate a two-dimensional texture grid map; and associating the positioning output, the three-dimensional map, the semantic map, the geometric annotation map and the two-dimensional texture grid map, and providing an association result for a positioning and path planning module of the mobile equipment to call. The multi-dimensional map can be synchronously output through one-time mapping, the coordinates of the four layers are uniformly updated in real time, and the manual labeling cost is remarkably reduced.

In aspects of ending active noise cancellation based on a detected audio source, a mobile device implements an audio playback manager that detects a headset employing active noise cancellation (ANC) of audio in communication with a mobile device in an environment of the mobile device. The audio playback manager receives a selection of at least one audio source that triggers adjustment of the ANC and detects sound originating from the at least one audio source that triggers adjustment of the ANC. Based on detecting the sound originating from the at least one audio source, the audio playback manager adjusts the ANC.

The invention particularly relates to a mobile camera management system capable of adaptively adjusting video coding quality. According to the mobile camera management system capable of adaptively adjusting the video coding quality, a network condition monitoring and predicting module is used for monitoring the current network bandwidth and packet loss rate in real time and predicting the network state; the video coding control module is used for dynamically adjusting video coding parameters according to the current network bandwidth and the ROI; and the adaptive adjustment strategy module is responsible for issuing a video coding strategy to the video coding control module according to the data fed back by the network state monitoring and prediction module so as to realize dynamic adjustment of the video coding quality. The mobile camera management system capable of adaptively adjusting the video coding quality can avoid video lagging and frame loss when the network bandwidth is relatively low, is suitable for various mobile devices such as a vehicle-mounted device, an unmanned aerial vehicle and a wearable camera, effectively improves the continuity and availability of video transmission, and realizes stable application in an environment with unstable signals.

The invention discloses a data security transmission method based on an ML-KEM algorithm and a PUF, and the method comprises the steps: in a registration stage, mobile equipment generates an anti-quantum key through employing a PUF technology, and a CA issues an anti-quantum digital certificate based on a Falcon algorithm and a cryptographic accumulator; in an identity authentication stage, a mobile device and an edge gateway complete bidirectional identity authentication by exchanging identity labels, anti-quantum certificates and authentication key parameters in combination with a Falcon algorithm and PUF challenge-response, and negotiate to generate a shared key by using an ML-KEM algorithm, thereby effectively defending threats such as man-in-the-middle attack, replay attack and identity counterfeiting; in a data transmission stage, two communication parties realize data encryption transmission by adopting a symmetric encryption algorithm, and data integrity and source credibility are guaranteed in combination with a Falcon digital signature; the whole scheme has the advantages of quantum security resistance, efficient authentication, dynamic key updating, lightweight encryption and the like.

Systems and methods involving various registration and authentication workflows are disclosed herein. A user may be authenticated without the use of static usernames or passwords. In some embodiments, an authentication identifier may be generated that is associated with an authentication request for a user to access a protected resource (e.g., a web app). An authentication code may be generated based on the authentication identifier. The authentication code may be sent to a computing device to be provided to the user, who may provide the authentication code to an application on their mobile device. The mobile device may send a payload containing the authentication identifier, credentials saved on the user device from a previous registration step, and a digital signature. The digital signature may be authenticated using contents of the payload before validating the authentication identifier.

The invention belongs to the technical field of intelligent measurement, and discloses a mobile terminal automatic measurement method and system based on YOLO key point detection and an AR platform, and the method comprises the steps: obtaining multi-modal data, and carrying out the preprocessing; performing target detection and key point positioning based on the RGB image to obtain two-dimensional key point coordinates; based on the depth image and the pose information, a three-dimensional space coordinate system is established, the two-dimensional key point coordinates are converted into the three-dimensional space coordinate system, and in the conversion process, a self-adaptive weight fusion mechanism is adopted to perform fusion on the multi-modal data to obtain a fusion result; a nonlinear error propagation control model is adopted to suppress error accumulation in the process of converting the two-dimensional coordinates into the three-dimensional coordinates; and calculating morphological parameters of the target object based on the converted three-dimensional key point coordinates. According to the invention, the problems of low measurement efficiency, poor precision, high equipment cost, insufficient cross-platform adaptation and the like in the prior art are solved, and high-precision, real-time and low-cost automatic measurement of various types of target objects at the mobile terminal is realized.

The invention discloses a cloud edge collaborative task scheduling method based on a directed acyclic graph (DAG) and a near-end policy optimization (PPO) algorithm, and belongs to the technical field of deep reinforcement learning and mobile edge computing. The method comprises the following steps of: initializing a cloud edge environment containing mobile equipment, an edge server and a cloud server, and constructing a task dependency graph containing task calculation amount, dependency relationship and data transmission amount by using a DAG (Directed Acyclic Graph); establishing a function by taking minimization of the total response time of the application program as a target, and converting a scheduling problem into a Markov decision process; and inputting the current state to the trained intelligent agent based on the PPO algorithm, obtaining final action probability distribution through task dependence screening and legal action mask filtering, and sampling and executing scheduling. According to the method, the intelligent agent adopts a PPO algorithm and is trained based on DAG, the adaptive capacity to cloud edge collaborative scene resources and network changes is achieved, task accumulation delay is remarkably reduced, the resource utilization rate is remarkably increased, and the method has wide applicability.

Embodiments are provided wherein a mobile device that is associated with a cellular system is configured to communicate with a second device that is associated with the cellular system subject to a time-varying, dispersive, multipath fading environment. The mobile device comprises an antenna system comprising a plurality of polarizations and a processor that is configured to reduce a cross-polarization interference caused by said time-varying, dispersive, multipath fading environment while the mobile device uses a first polarization and a second polarization of the plurality of polarizations to increase a transmission throughput of information and / or a reception throughput of information. The mobile device is further configured to perform operations including processing first and second signals received respectively on the first and second polarizations and to use a plurality of receive channel coefficients to perform first and second mathematical operations on the first and second signal, respectively.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as physical intelligence, financial science and technology, medical health and the like, and discloses a motion control method, device and equipment of a mobile device and a medium. The method comprises the following steps: acquiring body state information of a mobile device and environment information of an external environment, performing feature fusion based on the body state information and the environment information to generate fusion perception features, generating a target movement track based on the fusion perception features, and adjusting the rigidity of leg joints in combination with the target movement track, a preset dynamic model and a movement stage. And predicting the power demand of each joint in the movement process, generating a motor control instruction, and driving each joint motor to execute the target movement track. The leg joint rigidity is dynamically adjusted by fusing multi-source sensing information, the motor control instruction is generated in combination with power prediction, and the movement stability and coordination of the moving device in a complex environment are improved.

In aspects of ending audio playback based on a trigger word, a mobile device implements an audio playback manager that detects a headset in communication with a mobile device, the headset causing active noise cancellation (ANC) and outputting audio playback communicated from the mobile device. The audio playback manager detects a trigger word that is audible in an environment of the mobile device. In response to detecting the trigger word, the audio playback manager ends the audio playback and adjusts the ANC of the headset.

The embodiment of the present application discloses a kind of control method of mobile device and related equipment, the method comprises: control the mobile device moves along preset path;When the mobile device moves to the position where satellite positioning signal does not satisfy preset condition, control the mobile device continues to move along the preset path, and in the process of continuing to move along the preset path, the distance between the position of the mobile device and the nearest one first position is determined;When the distance is equal to remaining mileage, if it is detected that the satellite positioning signal does not satisfy the preset condition, control the mobile device moves to the nearest one first position, so that the position of the mobile device after moving detects that satellite positioning signal satisfies the preset condition, and the remaining mileage is obtained based on preset mileage and the mileage of the mobile device continuing to move along the preset path.

Various systems and methods are presented regarding utilizing technology onboard a vehicle to mitigate the effects of communication signals being deleteriously affected / lost when operational surroundings cause occlusion / loss of receipt of positioning / location signals at the vehicle. The vehicle can be operating non-autonomously, partially autonomously, or autonomously. To supplement the lost / occluded signals position information of other systems proximate to the vehicle can be obtained / utilized. The other systems can include another vehicle, a mobile device, an internet, and suchlike. Also, onboard devices can be utilized to determine the location, such as an onboard camera system providing information regarding street signs, building facades, and suchlike.

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