59results about How to "Privacy protection" patented technology

This invention discloses a driver state monitoring and safety early warning method based on millimeter-wave radar, comprising: acquiring driver physiological micro-motion signals and driver macro-behavioral signals respectively through millimeter-wave radar to obtain driving environment information in real time; denoising the driver physiological micro-motion signals and extracting features to obtain driver physiological feature signals; constructing a time-frequency spectrum using driver macro-behavioral signals; determining the driver physiological arousal index and driver emotional state risk value based on the physiological feature signals; obtaining the driver dynamic behavior risk value based on the time-frequency spectrum; calculating an environmental complexity index based on driving environment information; constructing a driver state risk field model based on the driver physiological arousal index, driver emotional state risk value, and driver dynamic behavior risk value; calculating the driver state risk value using the driver state risk field model and environmental complexity index; and providing graded early warning based on the driver state risk value.

This invention discloses a method and system for managing chat logs based on a storage network, relating to the field of log management technology. The method includes the following steps: S1, constructing an interaction matrix; S2, constructing an association matrix; S3, calculating participation; S4, outputting summary text; and S5, assessing risk coefficients. This invention effectively divides different chat logs by constructing an interaction matrix and marks chat logs within the same conversation segment. After the initial construction of the interaction matrix, to further conserve storage resources, the position values ​​in the matrix are optimized: if the logical correlation between two chat logs is weak, the value at the corresponding matrix position is reset to zero, thus avoiding redundant storage; while for strongly correlated log pairs, their position value is retained as 1. This design quantifies the connection strength between chat logs, thereby reflecting the closeness of the relationship between users.

This invention discloses a fall detection method, apparatus, device, and medium. The method includes: determining target noise point detection information corresponding to the target radar detection information of a target person based on personnel radar detection information detected by millimeter-wave radar and noise point detection information detected by an acoustic detection device; determining the detection mode of the target person based on the target radar detection information, and determining target detection information from the target radar detection information and target noise point detection information based on the detection mode; wherein the detection mode includes an obstruction mode, a stationary mode, and a motion mode; and detecting the fall state of the target person based on the target detection information. This invention uses a combination of millimeter-wave radar and acoustic detection for fall detection, enabling continuous fall state detection even when the target person is obstructed by objects indoors, improving the accuracy and efficiency of fall detection; and since both millimeter waves and acoustic waves are invisible waves, user privacy can be effectively protected.

The present application relates to a kind of low-carbon park integrated energy system multi-agent collaborative carbon responsibility allocation method, steps include: the multi-source data of park is collected, with the minimum integrated energy system total operating cost as goal to carry out multi-energy flow optimization scheduling;With the dynamic correction model of two-way carbon flow considering the carbon flow transfer caused by energy storage charging and discharging process, dynamic carbon flow distribution matrix is constructed;Using load carbon responsibility decoupling allocation model, total load is decoupled into multiple sub-load categories, and different carbon responsibility allocation coefficients are given for each type of sub-load;With each interest party in park as the participant of game, Nash bargaining as collaborative optimization framework, maximum all participant utility gain as objective function, Shapley value as the basis for carbon responsibility allocation, multi-agent collaborative optimization is carried out, and the carbon responsibility allocation scheme of each subject is obtained in combination with user carbon responsibility allocation coefficient.Compared with prior art, the present application ensures the fairness, efficiency and operability of carbon responsibility allocation scheme.

This utility model discloses a privacy bed curtain device, relating to the field of medical supplies technology. It includes a support frame, with a first storage box and a second storage box fixedly mounted on the side and back of the support frame, respectively. A bed curtain assembly is installed inside both the first and second storage boxes. The bed curtain assembly is rotatably connected to a first support shaft on the inner wall of the first storage box, and a first extension frame is fixedly mounted on the surface of the first support shaft. This utility model, by setting the first and second storage boxes on the surface of the support frame, allows the bed curtain assembly to be stored away during normal use. In use, a drive motor can simultaneously extend the first and second extension frames to a horizontal angle, thus opening the bed curtain. Supports can be installed at all four corners of the bed simultaneously, thereby enclosing the bed with the curtain, improving patient privacy. Furthermore, the bed curtain device can move with the bed, effectively protecting patient privacy and reducing medical disputes.

The utility model discloses a kind of delivery clothes, it is related to obstetrical nursing technical field, including: coat and lower skirt, coat and lower skirt are separately set, coat includes front piece and back piece, front piece has front piece connecting edge along with the two sides of human body torso width direction, back piece has back piece connecting edge along with the two sides of human body torso width direction, two front piece connecting edges are respectively with two back piece connecting edges detachably connected, when front piece connecting edge and two back piece connecting edges are not connected, front piece and back piece can be opened towards the collar of coat, the side of back piece away from front piece is connected with first connecting structure and second connecting structure, first connecting structure is closer to the bottom of coat compared to second connecting structure, when back piece is opened towards the collar of coat, first connecting structure and second connecting structure can be detachably connected to fix back piece so that back piece keeps open state. Coat and lower skirt are not connected between each other, can better protect user privacy, convenient to use.

This invention provides a method for de-identifying fields on the RWA compliance audit log chain, comprising the following steps: preprocessing configuration; determination of fields to be de-identified; template adaptation and value generation; dual-mode storage; compliance verification and closed-loop optimization. The purpose of this invention is to provide unified and fixed de-identification templates for two core sensitive fields in the RWA on-chain audit log: "personal ID number" and "corporate tax number," ensuring privacy compliance while maintaining log traceability, and without affecting the normal display and use of other non-sensitive fields.

This invention discloses an emotion analysis and feedback device based on visual and audio recognition in the field of psychological instruments and equipment technology. The device includes: a mobile base; a functional panel, vertically fixed to the top of the mobile base; a positioning ring, vertically suspended to the side of the functional panel, with an internal opening larger than the frontal contour of the human body, used for centering the user and restricting their sitting posture; a connecting arm, one end connected to the lower end of the functional panel and the other end connected to the positioning ring, used to support the positioning ring in a suspended state; and a flexible covering assembly located above the connecting arm, its surface forming a sloped structure facing the functional panel, used to guide the user's gaze to focus on the functional panel. This device features a hollow, large-sized positioning ring, which can center and align the user's torso and correct their sitting posture, avoiding blind spots caused by posture deviation. Combined with multi-directionally deployed visual and audio acquisition components, it significantly improves the accuracy of emotion analysis.

This invention provides a training method, localization method, and system for an intelligent agent localization model based on dialogue and vision collaboration. The training method is applied to a federated learning system and includes: a server initializing a global model and distributing it to a client; the client receiving model parameters, training the model using local dialogue commands and visual data, generating multimodal representations, and then inputting them into two structurally identical but parameter-independent localization branches for parallel processing, outputting localization representations and prediction results, and executing navigation decisions based on the localization results; constructing a total loss function that includes a loss term constraining the consistency of the bi-branch representations and constraining the consistency of navigation state changes, and updating the local model; the client evaluating reliability based on representation consistency and navigation stability, uploading the model update and reliability to the server, and the server using this data to weighted aggregate and update the global model, iterating until convergence. This invention can suppress noisy dialogue interference and improve localization accuracy, navigation stability, and model generalization ability in federated learning scenarios.

The application discloses a data processing method for a trusted data space, comprising: analyzing a data collaboration request by a trusted scheduling gateway, determining a temporary access token and local task data of an edge device, a data provider for collaborative processing of a multi-party collaborative task, a dynamic access route of the data provider, and a target data dimension required to be provided by the data provider; checking the access legality of the edge device based on the temporary access token and the local task data of the edge device; if the checking is passed, requesting the data provider to feed back target task data corresponding to the target data dimension based on the dynamic access route; desensitizing the target task data based on a data desensitization rule corresponding to the data provider to obtain desensitized task data; and sending the desensitized task data and the local task data of the edge device to a task execution party, so that the task execution party processes the multi-party collaborative task. The application guarantees data privacy and access security, and realizes efficient and trusted collaboration of multi-party data.

This invention discloses a real-time dynamic relative positioning method, system, and device based on state domain correction information. The method involves: a server receiving real-time GNSS observation data streams from the entire network of reference stations and real-time precise orbit clock correction streams to perform real-time precise single-point positioning calculations, and broadcasting network-wide floating-point ambiguity information; then performing real-time phase deviation estimation and broadcasting it; further, combining the network-wide reference station observation data streams and real-time precise orbit clock errors to perform real-time precise single-point positioning fixed-solution calculations, and broadcasting network-wide atmospheric delay information; performing atmospheric modeling and broadcasting the model information; and a user terminal receiving the precise orbit clock correction information, phase deviation information, and model information broadcast by the server in real-time, generating virtual observation values ​​at its approximate coordinates, and performing real-time dynamic relative positioning calculations. This invention can significantly reduce the algorithm complexity of current precise positioning servers and is compatible with existing relative positioning user terminals while ensuring one-way communication and privacy protection.

This invention provides a method and system for determining emergency transport routes. The method includes: acquiring multi-source heterogeneous data of patients to be transported during emergency transport, including vital sign time-series data, transport node location data, and structured medical record data; inputting the multi-source heterogeneous data into a shared latent space projection network to obtain multi-source aligned data with data distribution alignment; inputting the vital sign aligned data from the multi-source aligned data into a reinforcement learning controller to obtain the dynamic weights of each vital sign component in the vital sign aligned data, and determining the disease risk level of the patient to be transported based on the dynamic weights; acquiring a global path planning model trained based on a federated learning framework, and inputting the disease risk level and the multi-source aligned data into the global path planning model to obtain the target transport route. This invention improves the safety and personalization of emergency transport.

This invention discloses a behavior-adaptive continuous identity authentication method and system. Through component attribution analysis, the basic continuous identity authentication model is deconstructed into multiple computational units. These computational units are used as components, and an ablation vector is designed to determine whether the component's parameters are set to zero during inference. Ablation experiments are conducted on the components based on a user behavior dataset to obtain a set of optimal-performing components. Through parameter search adaptation, scaling factors are applied to the parameters of key components based on the current user's behavior data. With the optimization objective of maximizing identity authentication accuracy, an optimization search is performed to obtain the optimal scaling factor. This optimal scaling factor is then applied to the key components of the basic continuous identity authentication model to generate an adaptive continuous identity authentication model for the current user's behavior, enabling continuous identity authentication for the current user. This invention improves the authentication accuracy and computational efficiency of continuous identity authentication, and is particularly suitable for mobile devices.

The utility model discloses a low power circuit integration junction box, including casing, modular interface array, embedded control module and safety protection module, wherein, the modular interface array contains at least three kinds of specifications test terminal, and each test terminal is connected with the measured circuit board through the elastic contact, embedded control module contains microprocessor, programmable signal generator and AD conversion unit. In addition, the low power circuit integration junction box still includes power module and wireless communication module. The utility model provides junction box through using S3C2451 embedded control processor to realize the automatic measurement and judgement of low power point fast, and can save the various measurement parameters of detected through programmable signal generator and AD conversion unit, then through wireless communication module carries out data transmission, and the convenient implementation detection result inquiry and transmission have improved the detection efficiency, and the detection result also has higher measurement accuracy and good repeatability.

The application discloses a non-contact cognitive load evaluation method based on infrared thermal imaging, which comprises the following steps: using an infrared thermal imager to shoot facial videos of a tester in a sitting state and when performing a cognitive task; positioning a nostril area in the facial images and extracting original breathing signals from temperature changes of the nostril area; after denoising the original signals, extracting breathing features in a time domain and a frequency domain; based on the extracted breathing features, performing feature selection, and selecting a random forest to construct a cognitive load level classification model; extracting breathing feature samples of the tester and inputting the breathing feature samples into the cognitive load level classification model to evaluate cognitive load levels of the tester. The application provides a non-contact cognitive load evaluation method which is objective, comfortable and robust.

The utility model relates to a gesture recognition light control system, which comprises a high-definition camera, an embedded artificial intelligence experiment box and a lamp panel suite, the high-definition camera and the lamp panel suite are respectively connected with the embedded artificial intelligence experiment box; the embedded artificial intelligence experiment box comprises a power supply, an MIPS processor, a neural network acceleration rod, a radiator, a mouse, a keyboard and a display, wherein the MIPS processor is electrically connected with the power supply, the neural network acceleration rod, the radiator, the mouse, the keyboard and the display. Gesture images are collected through a high-definition camera, gesture recognition is carried out through a trained neural network model in an embedded artificial intelligence experiment box, gestures can be accurately recognized, the lamp panel suite is controlled to be turned on, and real-time control is achieved. According to the utility model, image acquisition and image identification are completed through local equipment, calculation can be carried out without the help of a network or a cloud server, the privacy of a user can be better protected, and the intelligent use experience of the user is greatly improved.

Embodiments of the present application disclose a social information issuing method and device. A specific embodiment of the method comprises: receiving a social information obtaining request sent by a first user, determining a second user to which the social information obtaining request is directed; obtaining social information uploaded by the second user, wherein the social information at least comprises locked social information; in response to the target social information requested in the social information obtaining request being the locked social information, forwarding the social information obtaining request to the second user; and in response to receiving an authorization permission returned by the second user for the social information obtaining request, sending the target social information to the first user. The embodiment can provide the user with social information published and allowed to be viewed by other users based on the request of the user, protect the privacy of the publisher of the social information, avoid providing the user with too much social information with low value, and improve the quality of the obtained social information.

This application relates to the field of communication technology, providing a data transmission method, apparatus, electronic device, storage medium, and computer program product, applied to data source nodes of a data source organization in a blockchain network built on a consortium blockchain. The data transmission method includes: encrypting the data to be transmitted based on its data sensitivity type to obtain encrypted data; fragmenting the encrypted data to obtain fragmented data; and transmitting the fragmented data to at least one data processing node of the data processing organization in the blockchain network. This application improves data transmission security by utilizing the immutability of blockchain technology and encrypting the data; furthermore, by fragmenting the encrypted data before transmission, data privacy can be protected through multi-party computation, further enhancing data transmission security. Therefore, it can improve data processing efficiency and resource utilization while ensuring data transmission security.

This invention discloses an offline navigation method and system based on plain text and local AI. The method parses the user-input text start and end point information using a local offline AI model, combines it with a pre-stored local text-based geographic knowledge base to perform path reasoning, and generates plain text walking steps. The system does not rely on GPS, BeiDou, or other satellite positioning signals or external networks; all calculations and data storage are completed locally on the terminal, and it can generate simulated GPS coordinates and visually assisted navigation. This invention is applicable to scenarios such as signal-free spaces, indoor environments, and visually impaired assistance, and features high privacy, strong stability, and a wide range of applications.

This invention discloses a method, system, device, and medium for intelligent identification of malicious network traffic based on proprietary data fine-tuning. It belongs to the interdisciplinary field of network security and artificial intelligence. The technical problem this invention aims to solve is how to overcome the shortcomings of existing network security detection technologies when facing advanced, covert, and ever-changing network attacks, such as low detection accuracy, high false alarm rate, weak generalization ability, high rule maintenance costs, and difficulty in adapting to enterprise private business scenarios. The goal is to achieve efficient and accurate malicious traffic identification. The technical solution is as follows: Collect network traffic data from the target network environment, and perform session reconstruction and traffic standardization processing on the network traffic data to generate session-level traffic samples; preprocess and clean the session-level traffic samples, and extract features from the network traffic data to form a traffic feature vector; load a pre-trained basic malicious traffic identification model; and obtain proprietary traffic data corresponding to the target network environment.

This invention proposes a data fusion and intelligent recommendation method and system for digital economy empowerment in the cultural tourism industry. The method includes: performing distributed data collaborative modeling based on local differential privacy and federated learning to aggregate features from multiple sources of cultural tourism data while protecting privacy; constructing a dynamic knowledge graph that integrates visual semantics and spatiotemporal state, generating spatiotemporal evolution embedding vectors through cross-modal attention mechanisms and dynamic graph neural networks; constructing a twin simulation space mapping physical scenes, performing counterfactual inference based on sequence prediction models; generating a recommendation list using a deep reinforcement learning policy network, conducting virtual pre-runs in the simulation space, and iteratively optimizing the strategy based on feedback risk-reward indicators. This invention solves the problems of isolated cultural tourism data, semantic bias in recommendations, and lack of consequence pre-running, achieving intelligent decision-making that balances privacy security, recommendation accuracy, and overall operational efficiency.

This invention provides an AI-powered companion robot control system and method based on mobile communication devices, relating to the field of intelligent robot control technology. It collects multi-dimensional behavioral data of users using mobile communication devices and extracts behavioral feature vectors. Based on the behavioral feature vectors, it matches them with historical behavioral patterns to generate clone commands containing predicted actions and their confidence levels, emotional state values, and their confidence levels. The robot itself can execute the predicted actions based on these clone commands, providing proactive reminders and companionship to the user. Furthermore, by dynamically evaluating the computing power contribution level using the operating status parameters of the mobile communication device, it performs differentiated task scheduling, achieving the coordinated utilization of three levels of computing resources. This protects user privacy data, reduces the hardware cost of the robot itself, and organically unifies the high intelligence of cloud-based large-scale models with low-latency, secure local control, improving resource utilization, saving computing power, and achieving a three-in-one collaborative system.

The application belongs to the technical field of Internet, and particularly relates to an industrial Internet cross-domain metadata trusted fusion method and system, comprising the following steps: collecting structured metadata, time series metadata and relationship metadata of each industrial domain node, and constructing an intra-domain metadata graph based on field attributes and call relationships; performing semantic coding and time series coding on the intra-domain metadata graph, obtaining corresponding semantic representations and time series representations, and calculating inter-field consistency; identifying stable field clusters, drift field clusters and abnormal nodes according to the inter-field consistency in each industrial domain node; and performing segmented aggregation on the stable field clusters and the drift field clusters by each industrial domain node to generate anchor field summaries and drift trajectory summaries. The application combines metadata graph coding, field clustering and federal dynamic weighting, and realizes industrial cross-domain metadata private trusted fusion through abnormal compensation correction.

This invention discloses a multimodal spatial interaction head-mounted system and method for clinical nursing, comprising the following modules: A) a management platform; B) an indoor positioning and wireless communication base station, wherein the indoor positioning and wireless communication base station includes an ultra-wideband (UWB) positioning module and a positioning QR code; C) a nursing workstation, wherein the nursing workstation includes a data terminal, which includes an EHR / HIS integration module, a workflow configuration interface, and a device IoT gateway; and D) a head-mounted glasses terminal. This invention achieves high-precision spatial anchoring through hierarchical fusion positioning of UWB and visual SLAM, introduces multimodal aseptic interaction logic supporting emergency coverage commands to adapt to clinical practice, and innovatively adopts a dynamic privacy rendering and bystander detection mechanism based on the line-of-sight cone, effectively resolving the contradiction between information visualization, aseptic operation standards, and patient privacy protection in clinical nursing.

A blockchain-based group collaborative privacy game mechanism is proposed, applied to blockchain-assisted collaborative LBS query scenarios. In this scenario, all parties adhere to the same smart contract. Users, as entities on the blockchain, perform data storage and verification. Neighboring users spontaneously form collaborative groups to mutually assist in LBS queries; users are members of these groups. For any collaborative group, user profile information is stored on the blockchain. A mobile edge computing (MEC) server customizes a multi-user collaborative privacy game mechanism (CPGM) for each collaborative group based on member profile information. Group members, guided by the CPGM, perform collaborative forwarding and message obfuscation to defend against speculative attacks based on prior knowledge. The CPGM is updated in real-time when a user leaves or joins a collaborative group. This method satisfies users' privacy needs at an acceptable cost.

This invention discloses an adaptive distributed support vector regression method to combat Byzantine faults. First, the objective function of the SVR model is smoothed to construct an empirical risk minimization objective function. Then, with t=1, the master machine obtains initial parameter estimates on its local data. In the t-th iteration, a MOM-based aggregation method is used to obtain the MOM estimate, which is then used as the global gradient estimate. Subsequently, a robust global gradient is obtained based on the global gradient estimate. After obtaining the robust global gradient, the master machine updates the global parameters using gradient descent. Finally, it checks whether the convergence condition is met. If the convergence condition is not met, the above steps are repeated; otherwise, the globally optimal parameter estimate is obtained. By introducing a robust aggregation mechanism based on the MOM method, it can effectively suppress the influence of abnormal machines, significantly improving the stability and robustness of the system while ensuring prediction accuracy. It can be widely applied to various practical distributed systems.

The application discloses a blood pressure measuring system based on a FedABN algorithm, comprising a client and a server, wherein the client comprises a data acquisition module, a storage module, a signal quality evaluation module, a signal preprocessing module and a blood pressure estimation module; the data acquisition module extracts a vPPG signal by shooting a user's finger skin video through a mobile phone camera and sends the vPPG signal to the storage module and the signal quality evaluation module; the signal quality evaluation module sends the signal to the signal preprocessing module after quality evaluation; the signal preprocessing module sends the signal to the blood pressure estimation module after filtering out clutter; the blood pressure estimation module measures blood pressure by using a pre-trained model for the first 10 times, and sends updated model parameters to the server; the server calculates a client personalized blood pressure measuring model and sends parameters to the client; and the client starts to measure blood pressure by using the personalized blood pressure measuring model from the 11th time.