135 results about "Smart system" patented technology

This invention provides an intelligent pipeline inspection and testing system, comprising a wirelessly connected surveying instrument and a mapping terminal. The surveying instrument includes a laser ranging module, an attitude sensor module, a GPS positioning module, and a processor. The output of the laser ranging module is connected to the first input of the processor to send the measured distance signal to the processor. The output of the attitude sensor module is connected to the second input of the processor to send the measured pitch angle signal and horizontal azimuth angle signal to the processor. The output of the GPS positioning module is connected to the third input of the processor to send the longitude, latitude, and altitude coordinates of the surveying instrument's location to the processor. This invention obtains the three-dimensional coordinates of the pipeline components (longitude, latitude, and altitude) through the GPS positioning module, and combines this with the infrared ranging function of the surveying instrument to obtain the vertical distance of the pipeline from the installation ground, thus achieving clear differentiation of different levels of pipelines in a three-dimensional intersecting pipeline system.

Provided are a method, device, equipment, storage medium and program product for document interaction. The method comprises: receiving an opening operation on a document; in response to the document meeting a preset condition, displaying a first identifier at a first content segment of the document, the first identifier representing a first comment of a smart system on the first content segment; and in response to a triggering operation on the first identifier, displaying a first interface element, the first interface element comprising at least part of the content of the first comment. In this way, the smart system can automatically add comments to the document, thereby simplifying the operation of the user.

A method, apparatus, device, storage medium, and program product for information presentation are provided. The proposed method includes: receiving a generation request, the generation request instructing an intelligent system to generate at least one visualization component corresponding to tabular data; and presenting analytical information, the analytical information instructing the intelligent system to create at least one visualization component in a component page, the analytical information including first information of the at least one visualization component, the first information indicating the layout attributes of the at least one visualization component in the component page.

This application discloses a multimodal cognitive trap accumulation assembly calculation method and system, applied to embodied intelligent robots. The specific method steps include: (1) learning, comparing, and embedding text corpora in the human language domain; (2) encoding trap perception data; (3) constructing a symbolic trap library SS; (4) collecting physical interaction data through a multimodal sensor array, compressing it through a spatiotemporal graph convolutional network and a variational autoencoder to generate an embodied trap library EE; (5) training a dual-tower contrastive learning model to establish a mapping relationship between symbolic traps and embodied traps, generating a cognitive anchor library AA. By constructing the cognitive anchor library AA, trap behavior and probability of the embodied intelligent system when performing tasks are avoided or reduced.

This invention relates to the field of facility durability assessment technology, and in particular to a life-cycle durability assessment system for cross-sea bridges in highly corrosive coastal environments. The system includes: a multi-source heterogeneous data acquisition module, used to acquire corrosive environment data, structural response data, component apparent damage data, and historical material performance data through a sensor network, image acquisition equipment, and database deployed on the bridge body and its environment; a data fusion and spatiotemporal registration module, connected to the multi-source heterogeneous data acquisition module, used to clean, align, and standardize the acquired heterogeneous data, and establish a mapping relationship between environmental exposure, material damage, and structural response; and a full-link intelligent system encompassing data perception, fusion analysis, AI prediction, dynamic calibration, and assessment decision-making. Through the fusion of physical mechanisms and data-driven approaches, this system achieves a fundamental shift in cross-sea bridge durability assessment from experience-based judgment to accurate prediction, and from passive maintenance to proactive operation and maintenance.

This invention discloses an AI intelligent system with multiple output data that can reduce erroneous selections, comprising: a registration module for inputting a device type or payment type registered by a user; an initialization module connected to the registration module, which configures multiple different artificial intelligence models according to the device type or payment type, wherein each artificial intelligence model is based on a large language model; an input module connected to the initialization module for inputting a user request; a processing module connected to the input module, which assigns the user request to the multiple different artificial intelligence models; a result generation module connected to the processing module, which generates multiple results from the user request using the multiple different artificial intelligence models; and a result display module connected to the result generation module, which displays the multiple results.

The application discloses a purpose factor driven layered long-term memory method and system, comprising: obtaining a task instruction of an embodied intelligent system; obtaining a semantic target vector of the task instruction; performing associated retrieval of the semantic target vector; screening a historical memory closest to the purpose factor; and performing a logical action in the historical memory. By introducing the system's own purpose as the core of filtering and coding, intelligent screening, layered storage and efficient calling of massive perception data are realized, and an implementable engineering implementation path is given.

Aspects of the disclosure relate to software systems of a tracking system (100) configured to process data from tracking tags ( 102, 104) affixed to assets to be tracked. The software systems may be used to process data such as payloads, interact with various systems including client facing systems, and make predictions regarding tracked assets. The predictions may provide information regarding the status of the tracked, assets during trips. Tire predictions regarding the trips may include destinations of the assets during the trips, events occurring during the trips, conditions of the assets during the trip, estimated, time of arrival at the one or more destinations. etc. The software systems may be robust such that these predictions may be made with minimal or no information pertaining to the trips beyond payloads from tracking tags (102, 104) affixed to the assets to be tracked.

This document provides a file interaction method, apparatus, device, medium, and product for one or more scenarios. The file interaction method includes: presenting a first interface associated with a first intelligent system; and, in response to a first operation triggered on the first interface, presenting a file set, the file set including multiple files, which are associated with multiple session tasks of the first intelligent system. Addressing the issue of poor file interaction experience during dialogue with the intelligent system, the document provides a file set to the user within the interface associated with the intelligent system. The user can view files associated with the intelligent system across multiple session tasks within the file set. This provides efficient and unified management of files associated with the intelligent system across multiple different session tasks, reduces the complexity of interaction between the user and files associated with the intelligent system, and improves the user experience of the intelligent system.

A system and method and for method for optimizing performance of a natural language processing (NLP) model includes clustering a validation dataset used in training the NLP model into a plurality of clusters; measuring a generalization in context parameter for one or more of the plurality of clusters; measuring an interference in context parameter for one or more of the plurality of clusters; and identifying a cluster, from among the plurality of clusters, for data augmentation, based on the measured generalization in context parameter and the measured interference in context parameter. Once a cluster is identified, a prompt is generated for submission as an input to a large language model (LLM) to prompt the LLM to automatically generate synthetic training data for the identified cluster, before the prompt is provided to the LLM and synthetic training data is received from the LLM. The synthetic training data is then labeled by a human before being used to further train the NLP model to improve the performance of the NLP model with respect to the identified cluster.

A computer implemented platform coordinates student participation in clinical shadowing and volunteering. An application server communicates with user devices to authenticate student and professional accounts, display filtered opportunity listings, and record attendance with timestamp and geolocation captured from a student device. The platform generates a session identifier, binds the captured fields to the identifier, and transmits a validation request to a verified professional or organization leader. Upon receiving validation, the system persists a tamper resistant log entry, updates cumulative progress against program specific hour goals, and triggers reminders generated by a requirements engine. Interfaces allow in app messaging for scheduling and confirmation. An export module formats validated histories for direct electronic submission to application portals or for download, enabling end to end discovery, recording, verification, tracking, and export.

We provide the system. [Solution] A means of receiving tasks entered by users, A means for analyzing the aforementioned problem and extracting requirements, A means for selecting the optimal combination from multiple artificial intelligence systems based on the aforementioned requirements, A means of integrating selected artificial intelligence systems to present solutions to users, A means of providing the aforementioned solution as information related to urban planning, A system that includes this.

This invention relates to the field of task modeling and scheduling technology for embodied intelligent systems, and discloses a method and system for structured modeling of task features for embodied tasks. The method includes: establishing a structured model containing six core dimensions: real-time level, action coupling relationship, perception dependency relationship, computational complexity level, accuracy requirement level, and execution stage identifier; mapping the original features of the embodied task to the model; pruning or expanding fields according to hardware capabilities to generate structured feature data with version numbers; and sending the data to the scheduling system through a standardized scheduling interface to achieve decoupling from the scheduling algorithm. This invention improves the standardization of embodied task access and the scalability of the scheduling system, and is applicable to complex embodied intelligent system architecture control scenarios.

A master control unit (MCU) is adapted to send wireless lighting fixture control signals to lighting fixtures using wired power line control (PLC) signals. The MCU has: an MCU power controller coupled through power lines for sending illumination power to the lighting fixtures; a command receiver for receiving from an input device, a modulated command signal having lighting fixture commands for the of lighting fixtures; a demodulator for demodulating the modulated command signal to obtain the lighting fixture commands; a wireless encoder for encoding the lighting fixture commands into wireless lighting fixture control signals for the lighting fixtures; a PLC modulator for converting the wireless lighting fixture control signals for the lighting fixtures into PLC lighting fixture control signals; and a power and PLC transmitter for sending the PLC lighting fixture control signals and the illumination power to each of the lighting fixtures using the wired power lines.

A method, apparatus, storage medium, and program product for use in conversations are provided. According to the proposed method, an input component is presented in a first interface, the first interface being used to display a conversation, the participants of which include at least two users; input content is received via the input component, the input content including a first element indicating a reference to a first resource; and during the conversation, a first message is sent, the first message being used to trigger an intelligent system to perform an action, the first message including the input content, the action being related to the first resource. This approach improves the convenience of conversations.

The present application relates to the field of building intelligence, in particular to a digital twin hybrid cloud edge collaborative intelligent real estate building group operation and maintenance system, the system collects building basic information, equipment operation data and environmental parameters, establishes a digital twin scene database, and synchronizes to edge devices, uses BIM, GIS, Internet of Things, 5G and AI technology to build a virtual and real digital intelligent building scene, realizes real-time synchronization of virtual scene and physical environment through AR / VR devices, the operation and maintenance module includes multi-source heterogeneous data fusion, edge intelligent analysis and decision-making, self-adaptive model training and iterative optimization, predictive maintenance algorithm of virtual-real mapping and multi-level collaborative decision-making and autonomous scheduling mechanism, realizes full digital management of building group, and the monitoring module monitors the state and operation of the edge device, provides data services, supports management decision visualization, and the system effectively improves the intelligent and digital level of building group operation and maintenance.

This disclosure provides an intelligent system and its antenna gain enhancement device. The antenna gain enhancement device includes several metal components and an insulating housing. Each metal component comprises an insulating main body and a metal layer and an insulating layer sequentially arranged from the inside out on the outer surface of the main body. Several independent metal components are arranged within the housing in a predetermined manner. The antenna gain enhancement device is matched with the antenna in the intelligent system. The metal components are used to generate polarization under the influence of an applied electromagnetic field to improve antenna gain. In this disclosure, by designing the antenna gain enhancement device to include several metal components and an insulating housing, these metal components do not require assembly and are directly installed into the housing in an ordered or disordered manner. This achieves polarization under the influence of an applied electromagnetic field, forming an enhanced electric field in the direction of electromagnetic wave propagation, thereby enhancing antenna gain and enabling wider communication range, smoother network speeds, and lower signal latency.

The application belongs to the technical field of communication automation, and discloses a communication automation link cooperative optimization regulation and control and self-recovery intelligent system and an application method. The application breaks through the technical bottleneck of traditional communication automation, i.e. "link isolated scheduling, time delay passive control and fault fuzzy disposal", and significantly improves the link cooperative efficiency, time delay prediction accuracy, fault tracing accuracy and self-recovery timeliness through modeling innovation and efficiency design, so as to adapt to the communication automation scenes such as industrial internet, smart grid, remote medical treatment and vehicle networking which have high requirements on link cooperation, time delay controllability and fault tracing capability. The application has clear innovation points and no repetition with the existing invention, and fills the gap of communication automation link cooperative optimization, time delay prediction regulation and control and fault tracing self-recovery.

This invention relates to a working method for an intelligent cleaning machine system, comprising: S1, acquiring the cleaning machine's start-up parameters; S2, determining whether the start-up parameters meet the cleaning machine's start-up conditions; if yes, proceeding to S3; if no, returning to S1; S3, acquiring current environmental state parameters; S4, determining whether starting the cleaning machine's cleaning operation will affect the user's life based on the current environmental state parameters; if yes, waiting for a preset time Tc before returning to S1; if no, controlling the cleaning to automatically start the cleaning operation. This intelligent cleaning machine system working method can autonomously determine the cleaning time to start the cleaning operation, avoiding disruption to the user's life and making it more user-friendly. This invention also relates to an intelligent cleaning machine system applying this intelligent cleaning machine system working method, and further relates to a storage medium storing computer instructions executable to implement the aforementioned intelligent cleaning machine system working method.

With the development of IoT, intelligent sensing, and artificial intelligence technologies, various intelligent systems collect massive amounts of multimodal data daily, including images, videos, audio, tactile signals, and sensor readings. This data contains rich environmental information, user behavior, and event records, forming a crucial foundation for systems to understand the world and make decisions. However, existing technologies suffer from modal silos, fragmented information, lack of proactive utilization, and privacy risks. Therefore, a method and system are needed to unify the internalization of multimodal data into searchable and associative semantic memories, supporting proactive cross-modal utilization. This application provides a multimodal data internalization method, system, and computer-readable storage medium, aiming to enable various intelligent systems to uniformly transform multimodal data such as images, sounds, and touch into timestamped semantic descriptions, forming searchable and associative memory timelines, and supporting memory-based proactive behavior.

A method, apparatus, device, medium, and program product for conversational interaction are provided. The proposed method includes: presenting first information on a conversational interface for a conversation between a first user and at least one second user, the first information including a first message; and presenting second information, the second information including a first instruction issued to an intelligent system, the first instruction being at least related to the first message.

The application belongs to the technical field of artificial intelligence and magnetic suspension transportation, and discloses a magnetic suspension transportation control intelligent system based on multi-modalities, which comprises a user subsystem, a user interface, an artificial intelligence subsystem, a ubiquitous perception subsystem, a magnetic suspension transportation physical subsystem and a communication subsystem; the user subsystem is used for submitting transportation demand, user demand and transportation objects; the artificial intelligence subsystem is used for completing system-level safety demanding tasks, vehicle-level safety demanding tasks and vehicle-level non-safety demanding tasks; the ubiquitous perception subsystem provides multi-modal perception information of the user subsystem and the artificial intelligence subsystem; the magnetic suspension transportation physical subsystem provides physical reality for completing the transportation demand; and the communication subsystem provides ubiquitous interconnection basis for other subsystems. The application effectively promotes the potential implementation of multi-modal artificial intelligence in the safety demanding field, accelerates the intelligent transformation of the magnetic suspension transportation system, and promotes the deep integration of computation, information and physics.

Described are an intelligence system and process for material blending in the gasification. The system includes a subsystem for material blending in the gasification, wherein the subsystem for material blending in the gasification includes a raw material property rapid analysis module, for obtaining raw material property parameters of raw materials according to characteristic spectral line intensities of in-furnace raw materials; a blended material property prediction module, for establishing a prediction model, and predicting blended material property parameters by means of the prediction model according to raw material property parameters and raw material proportions; a blending scheme optimization module, for establishing an optimization model, and obtaining an optimized blending scheme by means of the optimization model according to blended material property parameters; a blending scheme economy evaluation module, for outputting a blending scheme with the optimum technical economy.

A technology search and repurposing system comprising a query processing system, one or more intelligent systems, a response generator, machine learning (ML) powered navigator, and a curated database. Together these elements describe a system that doubles as a system to produce new technology-problem designs and as a system / method to curate a unique kind of data. The data itself may be used to build a new kind of AI that makes it possible to search technology by intent.

This invention discloses a method and apparatus for joint virtual-real simulation training of an unmanned intelligent system. The method includes: firstly, acquiring a set of physical entity equipment configuration data, training task configuration data, and training parameter configuration data; then, performing modeling and scene generation processing on the set of physical entity equipment configuration data, the training task configuration data, and the training parameter configuration data to obtain a set of digital equipment model data and virtual training scene data; next, performing joint virtual-real training processing on the set of digital equipment model data and the virtual training scene data to obtain a set of training process data; and finally, evaluating and performing closed-loop optimization processing on the set of training process data to obtain a target training evaluation report and optimized training parameter configuration data.

This invention belongs to the field of intelligent processing system technology, specifically relating to an AI intelligent processing system for personal data. It includes a data input module, an instruction parsing module, a CPU processor, a data encryption module, a memory, a backup device, an AI algorithm module, a data search module, an NPU processor, and a data output module. The CPU processor, NPU processor, and memory together constitute the core hardware of the system. Data interaction connections are established between the modules to collaboratively realize the functions of data input, parsing, processing, storage, backup, search, and output. Based on practical needs, this invention proposes an AI intelligent processing system for personal data that can meet the needs of individual users for storing large amounts of personal electronic data. Simultaneously, the embedded algorithms can also meet users' various needs for searching and editing data. The entire intelligent system is easy to operate, and user personal data can be easily accessed across all authorized devices, giving this invention high practical application value.

Systems and methods for intelligent machine learning model monitoring may include executing statistical test(s) for metric(s) to determine whether at least one of data used or an output in each machine learning model is statistically similar to expectations based on at least one of training data or test data for each model; when a first test failure of a tested model of a plurality of machine learning models occurs based on the statistical test(s) for the metric(s) exceeding a first test threshold, automatically executing an additional test based on the first test failure and additional historical data; and automatically generating an alert of test failure for the tested model based on the additional test exceeding an additional test threshold as a second test failure. The second test failure is representative of verification of the first test failure.