2300 results about "Remote operation" patented technology

The invention relates to the technical field of operation and maintenance management and control, and discloses an intelligent building remote operation and maintenance management and control system based on a large model and a cloud edge collaborative architecture, and the system comprises a configuration subsystem which is used for carrying out the reverse proxy and persistent connection configuration of edge gateway equipment in an intelligent building, and obtaining a TLS encryption bidirectional communication channel; the construction subsystem is used for constructing a cloud-edge-end three-layer cooperative computing architecture; the conversion subsystem is used for performing unified semantic abstraction and conversion on the heterogeneous protocol data to obtain semantic data in a standard JSON (JavaScript Object Notation) format; the rule processing subsystem is used for performing rule processing through a near-end decision engine of the edge gateway to obtain a local intelligent response result; the multi-dimensional analysis subsystem is used for carrying out multi-dimensional analysis through a cloud large model engine to obtain an equipment health score, a fault prediction result and an energy optimization strategy, seamless fusion and interoperation of heterogeneous system data are achieved through the system, and then global optimization and linkage control of the intelligent building are achieved.

The invention relates to the technical field of industrial intelligent monitoring, in particular to a remote online monitoring method and system based on machine vision and artificial intelligence, and the method comprises the following steps: synchronously collecting a visible light video stream, infrared thermal imaging data and three-dimensional vibration spectrum data through an edge calculation node, and forming a multi-modal sensing data set; performing cross-domain feature alignment processing on the data set to generate a space-time synchronous composite feature matrix; inputting the composite feature matrix into a cascaded deep learning model, and outputting a three-dimensional diagnosis vector which comprises an equipment health state, an abnormal region and a fault probability; and matching the three-dimensional diagnosis vector with a historical reference vector through a DTW and cosine similarity combination algorithm to generate a deviation index, and outputting a self-adaptive alarm threshold and a maintenance suggestion scheme according to the deviation index. The method has the advantages of high multi-modal fusion degree, light diagnosis model and intelligent and adjustable alarm mechanism, and is suitable for real-time remote operation and maintenance in a high-risk industrial scene.

The invention discloses a central air conditioner load self-adaptive regulation and control method based on artificial intelligence, which relates to the technical field of heating ventilation air conditioner automatic regulation and control, and comprises the steps of edge end data preprocessing, deep learning load prediction and self-adaptive updating, intelligent control strategy, closed-loop feedback and continuous optimization and fault diagnosis and remote operation and maintenance. Through edge end denoising and feature labeling, the data transmission pressure is remarkably reduced, and the response speed is increased; the deep learning model is combined with online iteration and reinforcement learning, key parameters such as chilled water temperature and water pump frequency are accurately regulated and controlled, and energy consumption and comfort are considered; according to the method, prediction errors and equipment states are monitored, a model and a control strategy are synchronously updated when abnormity is detected, fault early warning is triggered in combination with health assessment, energy consumption is effectively reduced, the service life of equipment is prolonged, and finally an efficient and stable self-adaptive regulation and control system capable of being operated and maintained online in a long period is constructed.

The invention relates to the technical field of remote control, and discloses a remote control method and system based on gold wire bonding equipment, and the method comprises the steps: obtaining a high-precision multi-dimensional detection data set; processing the multi-modal original monitoring data to obtain a gold thread quality feature vector matrix; processing the multi-dimensional feature vector set to obtain unified quality index feature mapping; processing the uniform quality index feature mapping to obtain a multi-stage defect detection report; processing the historical quality data and the process parameters to obtain a parameter optimization suggestion report; processing the multi-source monitoring data to obtain an augmented reality interaction system; and the augmented reality interaction system receives an operation decision of a remote operator and remotely controls the gold wire processing equipment. By means of the remote control method and the high-precision remote control system based on the gold wire bonding equipment, millisecond-level response control over gold wire machining equipment is achieved, the instruction execution accuracy is improved, and operation delay is reduced; and potential quality problems are warned in advance.

The invention relates to the technical field of program control systems, in particular to an intelligent daily chemical production line online control system. The system comprises an equipment digital twin modeling module, a process parameter optimization module, a modular production unit adjustment module, an automatic scheduling and Internet of Things transmission module, an equipment monitoring and data analysis module and a fault prediction and remote operation and maintenance module. Acquiring equipment real-time operation state data of the intelligent daily chemical production line, and performing digital twinborn modeling based on the equipment real-time operation state data to obtain an equipment digital twinborn model; and performing simulation optimization calculation on each process parameter based on the digital twin model of the equipment to obtain stable-state process parameter set data of the equipment. Through technological parameter optimization, modular production unit adjustment, equipment monitoring and fault prediction, efficient dynamic optimization of the production process is realized, the flexibility, stability and fault prevention capability of the production line are improved, the production cost is reduced, and the production efficiency is ensured.

The invention discloses a photovoltaic power station intelligent remote operation and maintenance method and system based on relay protection, and the method comprises the steps: collecting the multi-mode characteristic quantity of a photovoltaic array region relay protection device in real time through a distributed optical fiber sensing network, so as to construct a dynamic protection characteristic matrix; performing feature decoupling on the dynamic protection feature matrix by adopting a space-time convolution adversarial encoder to generate a fault feature vector set; inputting the fault feature vector set into a physically constrained LSTM-GAN hybrid prediction model, and predicting a multi-dimensional failure probability tensor of the key relay protection node in a future preset duration; generating an optimal operation and maintenance strategy decision tree based on the multi-dimensional failure probability tensor; and analyzing the operation and maintenance strategy decision tree through a remote execution gateway driven by the digital twinborn, and synchronously updating the topological connection relationship of the digital twinborn bodies of the power station. According to the embodiment of the invention, the operation and maintenance efficiency and reliability of photovoltaic power station protection can be improved.

The invention discloses an intelligent substation real-time monitoring system and method based on big data, and particularly relates to the technical field of power equipment monitoring. Comprising a multi-source acquisition and processing module, a dynamic topology updating module, an equipment state monitoring module, a fault diagnosis and prediction module, an equipment life prediction module, an energy efficiency analysis and optimization module and a remote operation and maintenance scheduling module. According to the invention, high-precision fault detection and implicit association mining can be realized, the substation anomaly detection capability is improved, and the service life management of each power device of the substation is effectively optimized; reasonable distribution of maintenance resources can be ensured, equipment reliability is improved, comprehensive energy efficiency is improved, carbon emission is reduced, manual intervention is not needed to adjust an operation mode, optimization efficiency is improved, and intelligent operation of the transformer substation is realized.

The invention discloses a double-arm robot autonomous control system and method based on teleoperation and visual features. The system comprises a teleoperation acquisition module, a multi-view visual perception module, a data synchronization and demonstration acquisition module, a strategy model training module, an autonomous strategy execution module, a track deviation detection and takeover module and a hybrid control interface module. Human demonstration is completed through teleoperation, multi-modal information of images, tracks, clamping jaws and muscle activation is collected, perception features are fused by adopting multi-view space-time alignment and a cross-view attention mechanism, strategy learning is completed in combination with an end-to-end large model, and in the autonomous operation stage, the multi-view space-time alignment and the cross-view attention mechanism are combined with the end-to-end large model. The risk of current operation is predicted and evaluated through track deviation detection and collision probability, the autonomous control proportion is dynamically adjusted, manual intervention is allowed when necessary, the safety and stability of the whole system are improved, the robot control mode of seamless switching between man-machine cooperation and autonomous and teleoperation is achieved, and the method is suitable for object control tasks in complex and highly variable environments.

The invention discloses a multi-terminal mixed intelligent inspection and task scheduling method and system based on air-ground-person cooperation. The method comprises the following steps: constructing dynamic unknown environment active cognition; updating dynamic unknown environment active cognition; the candidate path segments are evaluated through a path cost evaluation function, path reachability judgment is performed based on a cost value, and an exploration guide item is introduced to actively guide an inspection carrier to enter an unknown area to realize synchronization of task execution and map expansion; in combination with semantic task description, real-time states of multiple inspection carriers and an updated global environment model, task dynamic allocation and path collaborative optimization are performed, and the emergency, execution efficiency and resource utilization rate of inspection tasks of multiple terminals are balanced; the operation state and environment cognitive quality of each inspection carrier are monitored in real time, and an MR teleoperation intervention mechanism is automatically triggered when it is detected that continuous planning fails, sensing confidence is lowered or a key unknown area is entered; projecting a global environment model, real-time sensing data and a planned path to an operator MR device in an immersive manner, guiding by an operator through gestures, gazing or voice, and finishing path correction or task redistribution by adopting a progressive sharing control strategy and fusing with a manual instruction and autonomous planning; a successful MR intervention process of an operator and a context environment thereof are recorded in a context memory library, and when a similar task or environment scene is encountered subsequently, a verified guide strategy or control parameter is actively recommended.

The invention relates to the technical field of the Internet of Things, and particularly discloses a machine room equipment remote operation and maintenance management method and system based on the Internet of Things technology, and the method specifically comprises the steps: collecting the operation state data of machine room equipment in real time through an Internet of Things sensor network, and obtaining the mean value and standard deviation of the historical operation data of the equipment; transmitting the data to a cloud server through a 5G network; the cloud server performs data cleaning, format conversion and storage, and establishes a unified equipment operation database; performing principal component analysis on the standardized data, extracting main feature vectors, and calculating the contribution rate of each operation parameter; calculating a total weight according to the contribution rate of each operation parameter, mapping the total weight to an original parameter, and respectively calculating a weight corresponding to each operation parameter; calculating a device health degree score based on the device operation data; selecting a logistic regression model, establishing a fault prediction model and calculating a fault probability; and comparing the fault probability with a preset threshold value, and determining whether fault early warning is triggered or not.

The embodiment of the invention provides an excavator handle control system for remote operation, a handle control method based on a Hall sensor is adopted, non-contact rocker data sensing is achieved, the influence of contact and movement abrasion on the service life of a handle is reduced, and the excavator handle control system has the advantages of being high in sensitivity and good in performance; the handle mechanism is more flexible to operate, and the service life of the handle is prolonged; a two-hand cooperative control mode is adopted, and two three-degree-of-freedom handles are used for simulating the driving environment of a real excavator, so that a good remote control effect is achieved, and the feeling of presence of an operator in the remote operation process is improved; the operation habits of a driver are fully considered, the walking and working of the excavator are respectively controlled through combination of different degrees of freedom of the left hand handle and the right hand handle, an operating lever of the real excavator is simulated in the aspects of structure, motion degree of freedom and working range, and the man-machine interaction environment of excavator driving is restored.

The invention discloses a hydraulic water quality monitoring control system for a drainage pipe network, which belongs to the field of data communication of a data center and comprises a rain gauge, a flow meter, a liquid level meter and a water quality monitor. The system also comprises an intelligent data analysis and diagnosis module, a remote control and automatic management module, an environment adaptability and safety protection design, a communication and data transmission optimization module, and an intelligent fault self-diagnosis and maintenance prompt module. A data analysis algorithm is adopted, data are transmitted to a central monitoring platform in real time through a wireless communication module, and centralized processing and analysis of the data are achieved. Meanwhile, the system has a remote control function and supports remote operation of drainage pipe network equipment through the intelligent tail end power supply controller. The environment adaptability design ensures that the equipment can stably operate in a severe environment, and the communication and data transmission optimization ensures the real-time performance and accuracy of data.

The invention belongs to the technical field of iron phosphate preparation, and discloses an energy-saving control system for iron phosphate preparation based on an energy consumption scheduling model. The system is composed of a data acquisition module, an energy consumption sensing module, a preparation process modeling module, an energy consumption prediction module, an energy-saving scheduling module, an intelligent execution module, a feedback correction module, a man-machine interaction module and a remote operation and maintenance module. The energy consumption sensing module intelligently senses an energy consumption state, the preparation process modeling and energy consumption prediction module accurately predicts energy consumption, the energy-saving scheduling module generates an optimal scheduling strategy, the intelligent execution module accurately executes an instruction, and the feedback correction module realizes closed-loop adaptive regulation and control; all the modules cooperatively operate, process parameters are adjusted in real time according to actual working conditions of iron phosphate preparation, energy consumption in the preparation process is remarkably reduced, the energy utilization rate is increased, and energy-saving optimization of iron phosphate preparation is achieved.

The invention discloses an electricity room environment regulation and control method and device based on an edge gateway. An intelligent sensing network is constructed by deploying at least one type of environment sensor in an electricity room; an edge intelligent fusion platform is constructed by customizing edge gateway hardware design and establishing a software platform; setting an environment parameter intelligent regulation and control strategy and a self-adaptive regulation and control strategy; and constructing a cloud-side collaborative architecture and augmented reality remote operation and maintenance system, and performing electricity room environment regulation and control in combination with the intelligent sensing network and the edge intelligent fusion platform. According to the technical scheme of the invention, through highly refined design, intelligence, precision and foresight of electricity room environment regulation and control are realized. By integrating the latest edge calculation, big data analysis, machine learning and Internet of Things technologies, an electricity room environment management mode capable of real-time sensing, intelligent analysis, autonomous regulation and control and continuous optimization is constructed.

The present invention discloses a remote operation and maintenance control method and system in a dual interactive mode, which relates to the field of remote operation and maintenance control technology, including: establishing a remote two-way communication connection, collecting substation data for pre-processing; judging the equipment status to determine the execution strategy; comparing the result with the preset standard configuration according to the result, triggering the corresponding rollback or repair operation; analyzing the abnormal state of the equipment, generating a fault diagnosis report; establishing an early warning mechanism based on the diagnosis report, and dynamically adjusting the early warning response by classification. The present invention adopts a multi-level control mechanism to dynamically adjust the execution strategy during the task execution process. When multiple tasks are concurrent, resources are automatically allocated through task scheduling and priority control. Effectively improve the response speed and processing efficiency of the operation and maintenance system. After each task or fault processing, the system automatically archives the operation results to the log database, and adjusts future strategies according to the task execution effect.

The invention discloses a charging pile remote operation and maintenance system based on the Internet of Things, and the system comprises a data collection and edge calculation module which is used for collecting multi-mode operation data of a charging pile, and generating standardized operation data; the health degree dynamic evaluation module is used for executing multi-modal feature coupling analysis on the standardized operation data; the fault root cause analysis module is used for starting a time-space coupled fault root cause analysis process to obtain a root cause confidence score and a high-risk component; the self-healing strategy execution module is used for generating a self-healing strategy of the charging pile; the resource dynamic scheduling module is used for realizing dynamic optimal distribution of operation and maintenance resources according to the health degree score and the geographic position; the intelligent operation and maintenance management module is used for updating the weight of the dynamic pruning random forest model and generating a hierarchical maintenance report; and the data full-process control module is used for completing automatic closed-loop management from data acquisition to operation and maintenance decision. According to the invention, remote intelligent diagnosis and self-healing operation and maintenance of the charging pile can be realized.

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.

The invention relates to the technical field of intelligent monitoring and operation and maintenance of power equipment, and discloses a remote operation and maintenance system and method for power equipment based on a digital twinborn technology, and the system comprises a data collection module, a digital twinborn modeling module, a state monitoring and diagnosis module, and an operation and maintenance decision module. The data acquisition module adopts a distributed grid architecture and optimizes sensor sampling by using a PPO algorithm; the digital twin modeling module fuses RLC voltage and a simplified heat dissipation equation, and model parameters are corrected through scaled Kalman filtering and aging factors; the state monitoring and diagnosis module realizes fault early warning based on multi-threshold detection and a Bayesian network; the operation and maintenance decision module adopts a genetic algorithm to generate an optimization operation and maintenance instruction; the method comprises the steps of adjusting parameters, updating a model, triggering calculation, sending a dimensional instruction and correcting model parameters. According to the invention, full-process intelligent management of power equipment is realized, the operation and maintenance cost is optimized, and stable operation of a power system is guaranteed.

The invention discloses a catenary part detection system comprising a data acquisition module used for acquiring multi-modal data of catenary parts in real time; the data preprocessing module is used for preprocessing the collected multi-modal data; the topological structure construction module is used for constructing a topological structure of the catenary part and generating a topological feature vector; the fault identification and prediction module is used for carrying out fault identification and predicting the healthy evolution trend of the parts; the alarm and response module is used for generating alarm scores and triggering corresponding response strategies according to different alarm grades; the intelligent decision support module is used for generating intelligent maintenance suggestions, providing maintenance decision support and helping make repair and maintenance plans; and the remote monitoring and feedback module is used for monitoring the state of the overhead line system in real time and feeding back the state to the monitoring platform to support remote operation and updating. According to the invention, through dynamic topology modeling and deep learning technologies, accurate fault identification and health monitoring of contact network parts are realized.

An automated storage and retrieval system includes an automated storage and retrieval grid and a delivery system. The automated storage and retrieval grid includes a container handling vehicle rail system and a delivery column. The container handling vehicle rail system is for guiding a plurality of container handling vehicles. The delivery column is adapted for transport of a storage container from a container handling vehicle to a delivery port situated at a lower end of the delivery column, and further adapted for transport of a storage container from the delivery port to the container handling vehicle. The storage container is configured to be stored in a stack of storage containers beneath the container handling vehicle rail system. The delivery system includes a remotely operated delivery vehicle, which includes a container carrier adapted to support the storage container. The delivery vehicle is further adapted to transport the storage container between a delivery port and a second location for handling of the storage container by at least one of a robotic operator and a human operator.

A personnel transportation pod for transporting, remote monitoring of, and / or providing medical support to at least one individual, the pod comprising: an airtight structure comprising walls forming an enclosed interior and an exposed exterior, wherein at least one of the walls comprise at least one opening for providing a passage for the individual from the exterior of the pod to the interior and vice versa, wherein the opening is sealable by a hatch; a connection means on the exterior of the pod, wherein the connection means enables the pod to be connected to a vehicle; a remote monitoring system comprising a monitoring means; a medical support system comprising life support equipment and at least one remotely operable robot capable of manipulating equipment and / or each individual; and a communication system, wherein in use, the communication system enables remote monitoring of each individual within the pod and remote utilisation of each robot to treat each individual.

The invention provides a robot teleoperation method and a robot. The robot teleoperation method comprises the steps that an acceleration command, an angular acceleration command and an expected attitude quaternion of an end effector are determined based on the current linear acceleration, the current angular acceleration and the current attitude quaternion of a control end; the current position and the current speed fed back by the end effector are obtained, a torque control signal for controlling the position of the end effector is determined based on the acceleration command, the current position and the current speed, and end acceleration feedforward is obtained; determining a torque control signal for controlling the attitude of the end effector based on the angular acceleration command and the expected attitude quaternion to obtain attitude feedforward; and a joint torque instruction of a mechanical arm joint corresponding to the end effector is determined based on the end acceleration feedforward and the posture feedforward, and the joint torque instruction is sent to a corresponding joint driver so that the end effector can synchronously act along with the control end. According to the invention, the problem of attitude lag of the end effector can be avoided, and the tracking error of the end effector is reduced.

The invention relates to the technical field related to intelligent production control, in particular to a coal mine production equipment control method and system based on remote body interaction, and the method comprises the steps: coal mine production equipment uploads parameters, analyzes the state, configures a twin architecture, and carries out local decision abnormity early warning. A remote end is communicated with an interaction device, biological characteristics are reflected as a pose instruction, time delay compensation and track deviation prediction are embedded, a multi-mode feedback unit triggers smooth control according to the pose instruction, and tactile feedback is enhanced in combination with a vibration spectrum. The technical problems that the network condition of the underground coal mine environment is poor, obvious communication delay exists in remote control, operation instruction lagging exists, and the response speed and operation safety of equipment are affected are solved, dynamic time delay is predicted through the LSTM network, track deviation is compensated, the real-time performance and stability of remote control are improved, accurate execution of instructions is ensured, and the service life of the equipment is prolonged. And the remote operation efficiency and reliability of the coal mine equipment are improved through high-precision pose control and real-time compensation.

The invention relates to the technical field of data center remote operation, and discloses a data center remote operation method and system based on collection gateway analysis, and the method comprises the steps: obtaining gateway resource data and data flow priority attributes; quantifying according to the resource data to obtain a cache length; when the cache length is greater than a length threshold value, processing by adopting a dynamic load balancing algorithm to obtain a migration data stream; analyzing according to the data stream to obtain a timestamp and a serial number; measuring according to the timestamp and the serial number to obtain transmission delay and packet loss rate; performing evaluation according to the transmission time delay and the packet loss rate, and performing link dynamic switching to obtain a backup transmission path when an evaluation result is a main link fault; according to the backup transmission path, adopting a distributed routing protocol to calculate and obtain a data transmission path; monitoring according to the data transmission path to obtain monitoring data; predicting according to the monitoring data to obtain an adjustment result; and performing optimization according to an adjustment result, and dynamically switching the main link and the standby link to perform data transmission. The method can solve the problem of low overall data transmission efficiency.

The invention relates to the technical field of power system automation, discloses a remote operation and maintenance method, system and equipment for wide-area substation automation equipment, and aims to solve the problems of data islanding, inaccurate diagnosis, strategy stiffness, low safety cooperation efficiency and the like in remote operation and maintenance of the wide-area substation automation equipment. According to the method and the system, a comprehensive platform is constructed, and multi-source heterogeneous data acquisition, intelligent fusion analysis, fault diagnosis and prediction, adaptive strategy generation, security remote control and block chain evidence storage and collaborative operation and maintenance are integrated. The method can solve the problem of data islands, improve the diagnosis and prediction precision and timeliness, optimize the operation and maintenance strategy, prolong the service life of equipment, and enhance the remote operation and maintenance safety and cooperation efficiency.

The invention discloses a multi-dimensional self-adaptive conductive connecting piece welding positioning system, and relates to the technical field of conductive connecting piece intelligent welding positioning, the system comprises a multi-dimensional data acquisition module, and a multi-modal sensor is used for acquiring contour, feature, current and other data; the data processing and analysis module processes data through deep learning and a physical model and predicts deformation; the self-adaptive positioning adjusting module controls the eight-axis linkage mechanical arm to compensate deformation through MPC; the welding process monitoring module fuses multi-source data monitoring and triggers adjustment when abnormity occurs; and the intelligent decision and feedback module realizes closed-loop control and optimization through knowledge graph and active learning decision feedback. Through multi-modal sensing and an intelligent algorithm, accurate positioning and dynamic compensation of welding deformation are achieved, welding parameters are adjusted in a self-adaptive mode, intelligent decision making and remote operation and maintenance are combined, the welding quality and stability are improved, errors and cost are reduced, and powerful support is provided for efficient welding production.

The invention relates to the technical field of intelligent power grid operation and maintenance, and discloses a power grid node health index assessment method suitable for remote operation and maintenance, and the method comprises the steps: S1, carrying out the fusion collection of multi-source data; s2, dynamic weight self-adaptive distribution is carried out; s3, dynamically correcting the life reference; step S4, layered health index calculation; s5, health state decision making and visualization are carried out; the data weight is automatically adjusted according to the timeliness difference of high and low frequency data through a dynamic weight adaptive distribution mechanism, so that the problem of health score long-term distortion possibly caused by low frequency data updating lag is solved, key parameters can be monitored in real time through a real-time anomaly detection and response mechanism, a parameter overrun early warning threshold value is set, and the early warning accuracy is improved. When the key parameters continuously exceed the limit, an online diagnosis mode is triggered, the data sampling frequency is increased, it is ensured that abnormal conditions can be quickly found and processed, the ability of the system to deal with sudden faults is improved, and the fault risk is reduced.

A system is disclosed. The system has an ultra-low latency data and video streaming module, comprising computer-executable code stored in non-volatile memory, a processor, a control center device, and a plurality of vehicle, robot or drone units that operate remotely from the control center device, each of the plurality of units including a control device. The control module, the processor, the control center device, and the control devices are configured to video stream using one or more camera modules disposed at each of the plurality of units, transfer the video streams from the control devices to the control center device.

The invention discloses an intelligent customer service method, device and system. The method comprises the following steps: S1, a service center accesses a first message; s2, the service center cleans the acquired first message; s3, performing semantic analysis; s4, when the first message is an after-sales message, the service center extracts an equipment identifier and an operation intention; and S5, executing feedback. According to the method, the multi-modal first message can be uniformly accessed, automatic analysis of a multi-language mixed instruction and equipment operation intention recognition are realized by utilizing a cloud AI large model, the multi-language mixed instruction is sent to a global equipment management platform to execute remote operation in combination with an automatic API workflow, and an intelligent reply is generated based on execution feedback; the problems that a traditional system is insufficient in cross-language analysis capacity, low in equipment operation efficiency and low in semantic recognition precision are solved, and the method has the advantages that the multi-language mixed instruction analysis capacity is improved, efficient integration of a customer service platform and an equipment management platform is achieved, and semantic analysis precision and an automatic closed-loop feedback mechanism are optimized.

A system provides for locking or unlocking a lock at a door of an intelligent door lock system at a dwelling by a designated dwelling user. An intelligent door lock system includes a remotely operable lock at a dwelling accessible by a user and a server in communication with the intelligent door lock system. A user mobile device is in communication with the server. The user mobile device includes an App that provides for locking and / or unlocking of the lock of the intelligent door lock system. The user communicates with the server using the user's mobile device, and the server is configured to process the user crossings one or more geo-locations relative to the dwelling and create a data set that is stored in a database.