1219 results about "Mobile app" patented technology

The invention discloses a hospital information intelligent analysis and decision-making system based on a multi-modal large model, and relates to the technical field of hospital information analysis and decision-making. The system comprises a data acquisition module, a preprocessing and fusion module, a large model construction and training module, an intelligent analysis module, a decision support module, a knowledge graph construction and application module, a data security and privacy protection module, a system evaluation and optimization module, a multi-hospital cooperation and data sharing module, a mobile application module and the like, and all the modules cooperate to realize hospital information intelligent processing and decision making. The system integrates multi-modal data, assists in precise diagnosis, recommends a treatment scheme, predicts resource demands, monitors medical quality, assists medical research, manages patient health and the like, comprehensively improves the intelligent level of hospitals, optimizes medical services and benefits doctors and patients.

A system for improving employee engagement and automating the integration of business processes. The system includes: a user interaction module configured to receive multimodal inputs, including natural language text and voice requests from employees via enterprise portals, mobile applications, voice-activated devices, and collaboration platforms, and to generate real-time responses via conversational output channels; a context processor that is operationally coupled with the user interaction module, wherein the context processor stores the interaction history, employee preferences, organizational role metadata, and task results in both short-term and long-term memory and dynamically derives context for controlling responses and initiating workflows; A natural language and intent processor that is communicatively linked to the context processor. The intent engine consists of large language models trained on company-specific lexicons to perform intent detection, entity extraction, ambiguity resolution, and sentiment or urgency classification from employee queries; a workflow orchestration layer in communication with the intent engine and the context processor, wherein the workflow orchestration layer includes a rule-based and AI-powered process execution engine configured to automatically initiate, route, and complete cross-functional business tasks, including approvals, escalations, and compliance checks, with workflows defined using modular templates that include conditional logic and time-based triggers; Webhooks and authentication protocols provide secure interoperability between the workflow orchestration layer and external enterprise platforms; a feedback and learning module that is operationally coupled with the workflow orchestration layer and the natural language understanding engine, wherein the feedback and learning module is configured to analyze task completion rates, response accuracy, latency metrics, and user feedback signals, and to retrain underlying language and workflow models for adaptive improvement in real time; and an administration console with role-based access controls, compliance dashboards, audit trails and interfaces for workflow configuration, whereby the administration console enables authorized personnel to monitor system operations, adjust interaction rules and enforce data protection restrictions across departments.

Presented herein are systems and methods for the employment of machine learning models for image processing. A mobile application for client-side image processing and validation, which interacts with and leverages native image processing software of the client device, where the image processing software and the mobile application include any number of machine-learning models for identifying a document and attributes of the document for recognition and validation. This mobile application uses the image processing software from a client operating system to control the camera. The image processing software generates various types of information about a video frame and the document, and the mobile application invokes APIs or software libraries of the image processing software to access the information and validate the frame and document.

Disclosed are a three-dimensional laser point cloud-based method and system for in-depth vegetation management in transmission corridors. The method comprises: collecting multi-source data by means of an unmanned aerial vehicle- and helicopter-mounted multi-sensor system, and preprocessing the multi-source data; using the processed multi-source data to create a digitalized power grid corridor and construct a vegetation management analysis model; on the basis of data analyzed by the vegetation management analysis model and geofencing technology, designing a hazard vegetation clearing-cost-compensation prediction model; and developing a mobile application for analyzing hazard vegetation data flows and the closed-loop management of vegetation management service flows. The described method achieves high-precision and high-coverage data collection, precisely identifies transmission line digital twins and hazard vegetation, standardizes and automates the management of hazard vegetation clearing and related compensation, and develops a mobile application for analyzing hazard vegetation data flows and the closed-loop management of vegetation management service flows, thereby achieving the end-to-end digital and mobile management of vegetation management. The organic combination of steps comprehensively improves the intelligence and efficiency of transmission line vegetation management.

The invention relates to the technical field of public transportation systems, and particularly discloses a bus departure scheduling method, which comprises the following steps of S1, integrating multi-dimensional data; s2, a dynamic prediction model containing machine learning parameters is adopted to calculate the passenger demand in the future period; s3, calculating the number of required vehicles according to the predicted demand, the vehicle capacity and the dynamic load coefficient; s4, constructing a multi-objective function including energy consumption optimization, and solving the optimal departure interval and route; and S5, according to the real-time data, correcting a scheduling scheme, collecting real-time feedback data through a passenger mobile application, analyzing the emotion and demand of the passenger by using a natural language processing technology, based on feedback intention recognition of an emotion analysis model, constructing a passenger demand knowledge base in combination with historical complaint data, and optimizing a dynamic prediction model and a scheduling strategy. Through technology integration and system innovation, the static and single bottleneck of traditional scheduling is broken through, and an intelligent solution considering efficiency, low carbon and user experience is provided for urban buses.

The invention provides a power cable comprehensive online monitoring system, and relates to the technical field of data processing, and the system comprises the steps: extracting a partial discharge distribution point set in a multi-dimensional feature fusion data set, and calculating the weight factor of each distribution point; based on the weight factors, a weighted point set concave packet generation algorithm is adopted to construct a partial discharge source probability distribution boundary, and a boundary feature point set is obtained; inputting the boundary feature point set and the multi-dimensional feature fusion data set into a convolution-long and short-term memory hybrid neural network to generate a diagnosis result; and a third-level early warning signal is generated based on a diagnosis result, early warning information is pushed to a remote operation and maintenance terminal and a mobile APP through an MQTT protocol, a digital work order service is automatically triggered to generate a maintenance task, and positioning verification is executed. According to the invention, the accuracy of monitoring and fault diagnosis is improved.

Presented herein are systems and methods for the employment of machine learning models for image processing. A mobile application for client-side image processing and validation, which interacts with and leverages native image processing software of the client device, where the image processing software and the mobile application include any number of machine-learning models for identifying a document and attributes of the document for recognition and validation. This mobile application uses the image processing software from a client operating system to control the camera. The image processing software generates various types of information about a video frame and the document, and the mobile application invokes APIs or software libraries of the image processing software to access the information and validate the frame and document.

Example aspects include techniques for creating an augmented reality filter on a mobile device. These techniques may include receiving, in response to a selection of a primary augment reality filter template (ARFT), a primary ARFT package corresponding to the primary ARFT, and receiving, in response to the selection of a secondary ARFT, a secondary ARFT package corresponding to the secondary ARFT. In addition, the techniques may include loading the primary ARFT package and the secondary ARFT package to form a combined ARFT, and modifying, based on user input received via a user interface, the combined ARFT to create a customized augmented reality filter (CARF). Further, the techniques may include generating, for the CARF via the development engine, a configuration file that causes the mobile application to add custom perceptive information to visual data.

This disclosure provides an improved universal interchangeable battery for electric vehicles forming part of a battery swapping ecosystem that includes electric vehicles, swappable batteries, a charging / swap station, a battery adaptor for reliable charging and communication, and a mobile application for managing battery swapping within a fleet and a network of charging stations, enabling efficient and user-friendly battery exchanges.

The present invention comprises a novel social media video debating web and mobile application. The platform will provide a space for users to debate uninterrupted by both the audience and the opponent whereby each participant is given a set time to express their thoughts on a subject matter. The online debate platform provides a controlled setting for the participants to have their debates viewed, voted on and subsequently ranked by the other users of the platform. The online debate platform is also monitored by a unique AI system that updates debate “winners,” flags offensive content, and moderates each debate on the platform in real time. The disclosed platform and following figures will provide a space for individuals to debate subjects in a uniformed structure and have real-time results from active user viewership. The online debate platform aims to provide an established place for constructive debating.

The invention presents an advanced soccer training system designed to revolutionize traditional practice methods through a synergy of technology and interactivity. It features an integration of sensors, Artificial Intelligence, and Augmented Reality technologies, providing real-time feedback, immersive simulations, and personalized training experiences. The system promotes skill development via data-driven insights and dynamic training environments, supported by mobile application connectivity for customized training regimens and performance analysis. Additional attributes include energy-efficient design, user-friendly transport mechanisms, and extensive multimedia capabilities like video recording and photo capture for skill review, establishing a novel paradigm in athletic training and development.

A system (100) for multi-channel purchase authorization with dynamic role validation, comprising: (a) a multi-channel request capture module configured to receive and standardise purchase requests initiated through a variety of communication channels, including corporate portals, mobile applications, emails and messaging platforms; (b) a role identification and contextual mapping module configured to dynamically retrieve user roles and contextual information based on real-time access management data and organizational hierarchy; c) a policy and rules module configured to evaluate purchase requests based on pre-configured and context-sensitive authorization policies, thresholds and compliance rules; (d) a dynamic role validation and escalation module configured to validate whether the requester has the authority to initiate or authorise a transaction and, if not, to automatically escalate the request to an appropriate authorised role; (e) an authorization workflow orchestration module configured to sequence approval steps, apply business logic, manage parallel or sequential workflows, and interface with external procurement systems; f) and an audit, logging and analytics module configured to record all request, validation and authorization actions in a tamper-proof log and generate real-time insights and compliance metrics, g) where the system enables real-time, role-based purchasing authorization across multiple channels with dynamic policy enforcement and escalation handling.

The invention discloses a power equipment temperature monitoring and early warning system and method based on wireless communication, and relates to the technical field of temperature monitoring, the system comprises a wireless temperature measurement terminal box and a mobile terminal APP, the wireless temperature measurement terminal box and the mobile terminal APP establish communication connection based on a wireless network, and the wireless temperature measurement terminal box is fixedly installed on power equipment; the wireless temperature measurement terminal box comprises an electromagnetic environment judgment module which monitors and judges whether interference exists in the environment where power equipment is located in real time based on an electromagnetic sensor and synchronizes a result into a temperature drift compensation analysis module; and the temperature monitoring module monitors temperature data in the power equipment in real time based on a temperature sensor. Through electromagnetic environment judgment and temperature drift compensation, historical data and a model are combined to dynamically correct interfered temperature data, the influence of electromagnetic interference is eliminated, real-time monitoring is matched with graded alarm, hidden dangers can be found in time, response can be made according to risk grades, accidents are avoided, and wireless connection adapts to complex scenes.

The invention discloses an intelligent early warning system for safety of buildings around foundation pit construction, and relates to the technical field of construction safety monitoring. The platform adopts a four-layer architecture of a sensing layer, a transmission layer, a platform layer and an application layer. The sensing layer collects data in real time through a multi-class sensor array; the transmission layer wirelessly transmits data by using the Internet of Things technology; the platform layer serves as a core, comprises a data management module, a digital twin modeling module and an intelligent analysis early warning engine, and is responsible for data preprocessing, three-dimensional model driving and intelligent risk study and judgment based on machine learning and a dynamic threshold value; and the application layer provides visual display and early warning push service through a Web terminal and a mobile APP. All-weather automatic monitoring, intelligent advanced early warning and accurate risk prevention and control of the surrounding environment of the foundation pit are achieved, a complete intelligent management closed loop is formed, and the construction safety level is effectively improved.

The invention discloses a driver side navigation switching management method and system. The invention relates to the field of intelligent traffic and mobile application development. Passenger order information (such as new order generation and order state change) from a scheduling system is continuously monitored; acquiring the current navigation state (destination, route planning, driving state and the like) of the driver in real time; switching condition judgment is carried out; if the driver is in common navigation and receives a passenger order, calling a preset judgment table based on the order emergency degree and the predicted arrival time of the driver, and if judging that a switching condition is met, triggering a navigation switching process; according to the system, the navigation switching response time is compressed from the second level to the millisecond level through an active mechanism of order triggering and state sensing, and a driver can complete switching without manual operation. A map SDK asynchronous calling technology is adopted, parameter transmission and state cleaning are completed in the background, and the switching success rate is increased.

The invention discloses a business travel user real-time feedback and suggestion system, which relates to the technical field of mobile application development and multi-terminal adaptation, and is characterized in that an edge layer guarantees the completeness of offline scene data through a dynamic load adapter, starting a structured compression protocol in a weak network, switching a multi-mode enhancement protocol in a strong network and matching with a priority cache queue; the decision-making layer adopts a parallel processing unit accelerated by an FPGA (Field Programmable Gate Array), and a real-time stream filtering unit adopts SimHash fingerprints to remove duplication; the scene understanding unit fuses the spatio-temporal data to generate event tags; the grading response unit automatically triggers AI compensation and manual work orders according to risk grades; and the collaboration layer verifies the responsible party of the travel system on the premise of hiding the user ID based on the zero-knowledge proof gateway so as to realize cross-platform secure data exchange. According to the system, a three-layer intelligent architecture is innovatively constructed, and full-link real-time response of travel service is realized.

Embodiments of a physical access control system may grant authorized portal entry upon receiving a physical access request by generating a temporal credential based on the elapsed time from a prior access request. The controller processes multiple physical access requests from various mobile application devices. For each mobile application device, embodiments may authenticate an initial (predecessor) access request. For subsequent (successor) access requests, embodiments may use monotonic nonces to advance the range of temporal code matches. Entry code generation is decentralized to distributed application devices and remains unpredictable until a subsequent (successor) access request is initiated by the same mobile application device.

Presented herein are systems and methods for the employment of machine learning models for image processing. A mobile application for client-side image processing and validation, which interacts with and leverages native image processing software of the client device, where the image processing software and the mobile application include any number of machine-learning models for identifying a document and attributes of the document for recognition and validation. This mobile application uses the image processing software from a client operating system to control the camera. The image processing software generates various types of information about a video frame and the document, and the mobile application invokes APIs or software libraries of the image processing software to access the information and validate the frame and document.

The present invention relates to a communication system and method designed for patients in clinical settings who face challenges using standard communication devices. This system includes a mobile application and associated devices that establish a secure, asynchronous communication channel between clinicians, patients, and their support networks. Authorized users can record and send voice messages and other media, which are automatically played on the patient's device without requiring active operation. The system is tailored for ease of use, accommodating patients with severe physical or cognitive limitations through hands-free operation and simple commands. It adapts to the patient's condition, pausing messages during rest or medical procedures and resuming when appropriate. The system also features cross-linguistic messaging, translating and synthesizing voice messages across languages while maintaining the speaker's voice. Additional features include support for rich media, automatic transcription, and AI-driven content analysis. Secure, encrypted channels ensure privacy, complying with healthcare regulations. This invention enhances emotional connection and support for isolated patients, acting as a virtual visitation tool.

A transaction card, a computing device, a computer program product, a computer-implemented system, and a computer-implemented method for delivering financial services and, more particularly, facilitating client device authentication via a two-dimensional, machine-readable barcode (e.g., a quick response (QR) code) containing a link to facilitate an automatic launch of a financial institution mobile application and client authentication credentials that facilitates authenticated client device access to one or more client financial accounts maintained by the financial institution.

Systems and methods for using device data to validate a mobile user are disclosed. In accordance with aspects, a method may include receiving, at a backend processing infrastructure of a third party and from a backend processing infrastructure of a mobile application provider, a first copy of location information and an IP address, wherein the location information and the IP address are associated with a mobile device; receiving, at the backend processing infrastructure of the third party and from a mobile application provided by the third party, a second copy of the location information and the IP address, wherein the mobile application provided by the third party is executed on the mobile device; and verifying, by the backend processing infrastructure of the third party, that the first copy of the location information and the IP address matches the second copy of the location information and the IP address.

The invention relates to the technical field of data security detection, in particular to a data security-oriented mobile application dynamic and static dual-combination detection method and system. The method comprises the following steps: collecting basic information of a target mobile application from a plurality of heterogeneous data sources, and constructing a basic data set of the mobile application information; performing decompilation and static analysis based on the installation file in the resource library, and outputting a static risk feature vector in combination with the sensitive data operation rule set; dynamically running a target application in the controlled sandbox environment, monitoring network traffic, system calling and file operation behavior sequences, and outputting a dynamic behavior risk feature vector; and fusing the two types of feature vectors, and inputting the fused feature vectors into a risk assessment model to generate a comprehensive data security risk assessment report. According to the method, a comprehensive evaluation system is constructed by fusing static and dynamic risk features, and full-dimension coverage of the security risk of the mobile application is realized.

The invention relates to the field of mobile applications, and particularly provides a cross-platform mobile application system and a task processing method thereof, a terminal and a medium, and the system comprises a cross-platform application framework layer which is used for constructing an interface and processing an interaction event; the core intelligent layer is constructed based on an AI agent development suite and is used for dynamically scheduling an AI agent according to a user intention and an application state; the AI agent pool comprises a plurality of agents with independent functions; the native function interface layer is used for bridging and calling native hardware functions of the equipment; and the large language model service interface is used for accessing large language model service. The method comprises the steps of receiving and standardizing a user event, analyzing a user intention, dynamically scheduling an agent to cooperatively execute a task, and finally updating a user interface by calling a native hardware function or accessing a large language model to enhance the capability. The intelligent level, the development efficiency and the user experience of the mobile application are improved.

The invention discloses a non-sensitive management control system and method for a shared office. The system comprises a mobile APP, a cloud management platform, an intelligent access control terminal, environment sensing equipment and an electrical control unit, through the management system integrating the mobile APP, the cloud management platform, the intelligent access control terminal, the environment sensing equipment and the electrical control unit, non-sensitive management of the shared office can be realized. According to the system, a tedious and low-efficiency application process is simplified, so that the employees can quickly complete office reservation, and the consumption of office time is remarkably reduced. Meanwhile, the system can dynamically adjust the electrical control unit according to real-time data provided by the environment sensing device, it is ensured that device operation is automatically closed or reduced in the unmanned period, energy waste is effectively avoided, and the operation cost is reduced. In addition, the resource utilization efficiency is improved through the fine management mode, administrative expenses caused by idle or overuse of resources are reduced, and therefore the operation efficiency of an enterprise is overall improved.

A lighted steering wheel device is provided. The device is comprised of a steering wheel that integrates customizable and functional lighting features to enhance both safety and aesthetics. The steering wheel comprises various materials and configurations, with embedded flexible LED strips encased in impact-resistant, UV-protected casings, capable of displaying a wide range of static or dynamic light patterns. These patterns can be synchronized with vehicle systems, such as flashing red for emergency braking or reacting to turn signals, and brightness can adjust based on vehicle speed. The device includes a control interface embedded in the wheel and offers further customization via a mobile app, which provides remote access to light settings and synchronization features. Additionally, the device can generate safety alerts, utilizing proximity sensors, GPS integration, and haptic feedback for a multisensory driver experience, with an illuminated emblem adding a complementary design element.

A wearable electroencephalography device includes an ear cuff around an auricle of an ear comprising a curved structure conforming to contours of the ear, an electroencephalography electrode positioned on the ear cuff and contacting skin for detecting brain activity signals, a wireless controller integrated with the ear cuff and processing the brain activity signals from the electroencephalography electrode, and a wireless communication module transmitting the processed brain activity signals to an external device. The wearable electroencephalography device includes a mobile application receiving the transmitted brain activity signals from the wireless communication module, analyzing the brain activity signals using machine learning algorithms to determine emotional states of a user, and providing real-time feedback regarding the emotional states through a user interface. The mobile application comprises a self-report interface allowing the user to input subjective state data and a live-feed interface displaying real-time subjective state data derived from the brain activity signals.

The invention provides a watershed flood early warning system and method based on hydrological model and mobile application coupling, and belongs to the field of watershed flood early warning. In the system, a communication and data transmission module collects data for hydrological model simulation in a watershed area; the model simulation module simulates hydrological data of rainfall runoff in a watershed area in real time by using a hydrological model based on the collected data, and transmits a simulation result to the flood risk forecasting module through the communication and data transmission module; the flood risk forecasting module generates a flood risk map based on the received simulation result and transmits the flood risk map to the communication and data transmission module; and the mobile application display module receives real-time early warning information generated by the communication and data transmission module based on the flood risk map, and displays the real-time early warning information to a user. The watershed flood is simulated in real time through the hydrological model, the flood forecasting and early warning information is sent to people in a watershed flood submerging range through the mobile application, and the accuracy and timeliness of watershed flood early warning can be improved.

The invention relates to the technical field of mobile application continuous integration automation, and discloses a multi-channel APP automatic packaging system which comprises the steps that byte code files in a released mobile terminal APP installation package are acquired, and an occupied symbol space set is generated; generating an available confusion namespace by using set complementary operation; extracting method-level code change by using an abstract syntax tree difference algorithm, and generating a change method set; generating a patch special confusion rule for the change method set by using a namespace allocation algorithm; compiling and obfuscating the change method set by applying a patch special obfuscating rule to generate a safe obfuscating patch byte code; performing packaging and signature operation on the safe obfuscation patch byte code, and outputting a minimized obfuscation safe hot repair patch pack; according to the method, the technical problems that class definition conflicts or method calling errors occur after the hot repair patch is loaded, and the downloading success rate of a user is affected due to the overlarge size of the hot repair patch are solved.

The invention provides a product advertisement putting method and system. Relates to the technical field of advertisement putting, and comprises the following steps: obtaining product advertisement putting data with a timestamp from an e-commerce platform, a mobile application and an advertisement media, and carrying out cross-terminal association on the product advertisement putting data and a user identifier to form a multi-source data set so as to optimize product promotion, advertisement putting and marketing strategies and improve commercial benefits. According to the product advertisement putting method and system, the interest, the purchase intention and the cross-channel activeness of the user can be reflected more accurately through cross-terminal association of the multi-source data and construction of the multi-dimensional audience portrait, so that the target audience can be matched more accurately during advertisement putting, the advertisement effect is improved, and meanwhile, the user experience is improved. The combination of the incremental transformation prediction model and the multi-target reinforcement learning decision engine enables the advertisement putting strategy to be adjusted in real time, and improves the putting real-time performance and the rate of return on investment.

The invention relates to the technical field of mobile application program performance analysis, and discloses an APP performance multi-dimensional analysis method and system based on machine learning, and the method comprises the steps: building a code semantic understanding model, analyzing an APP source code, and extracting the structural features and semantic information of a code; constructing a performance evolution analysis model, and identifying a long-term change mode of a performance index by collecting and analyzing performance data of the APP in different versions; constructing a code performance knowledge graph, taking code entities and performance indexes as nodes, and taking influence relationships between the code entities and the performance indexes as edges; constructing a dual-state mapping prediction model, and predicting the long-term and short-term influence of code change on the APP performance; according to the method, the influence of code change on performance can be accurately predicted by deeply understanding code semantics and a long-term performance evolution rule.