1222 results about "Text messaging" patented technology

The invention discloses an abnormal short message behavior detection method and system based on multi-dimensional feature fusion, and relates to the related technical field of short message security detection.The method comprises the steps that spatial and temporal distribution features, semantic association maps and equipment behavior fingerprints of short message interaction are collected, a dynamic feature pool is configured, and a cross-modal feature sequence is extracted; cascade identification is carried out; the feature fusion weight matrix is dynamically adjusted, an abnormal probability score is generated, and when the abnormal probability score exceeds a dynamic abnormal probability threshold, a multi-stage verification mechanism is triggered; and matching a time sequence mode at an edge computing node, dynamically generating a verification code triggering threshold value, performing interactive risk verification, and determining an abnormal short message behavior mark. The technical problems of insufficient detection timeliness and adaptability and high false alarm and missing report rate caused by single detection dimension and difficulty in identifying novel complex abnormal short message behaviors in the prior art are solved, and the technical effects of reducing the false alarm and missing report rate of short message anomaly detection and improving the detection timeliness and adaptability are achieved.

The invention provides an intelligent short message scheduling method and device based on multi-dimensional dynamic optimization, and the method comprises the steps: obtaining the performance data of a plurality of short message channels, and calculating a channel health score based on a weight dynamic adjustment model; determining a scheduling strategy according to the priority identifier of the to-be-sent message, and performing channel screening and optimal matching; executing message sending and monitoring a sending state; terminal state detection is carried out on the failure message through operator base station signaling, and a decision tree model is applied to determine a retry strategy; and performing Huffman coding compression processing on the P2-level marketing messages which fail in retry, and performing batch sending in an idle window. According to the method, a comprehensive performance evaluation index and reward function model is also constructed, and parameter optimization is performed by applying a reinforcement learning algorithm. According to the invention, multi-dimensional dynamic channel scoring, intelligent retry decision making based on terminal state perception, batch processing with balanced cost-time efficiency and a closed-loop self-optimization system are realized, the short message delivery rate is obviously improved, and the invalid retry rate and the sending cost are reduced.

The invention discloses an AI intelligent collaborative monitoring management system for a multi-index water volume system, and relates to the technical field of monitoring management, the collaborative monitoring management system comprises a data acquisition module, a water volume system analysis module, a collaborative monitoring module, an emergency early warning module, an early warning scheme module and a data visualization module, all the modules are connected through electric signals. According to the AI intelligent collaborative monitoring management system for the multi-index water volume system, abnormal changes in water quality, water volume and water ecological indexes are identified through anomaly detection, an early warning mechanism is triggered according to the detected anomaly, early warning information is sent to management personnel through various modes such as a visual interface, a short message and an email, and the management personnel can carry out early warning on the water quality, the water volume and the water ecological indexes. According to the invention, the time interval from the occurrence of the abnormity to the discovery of the abnormity is greatly shortened, and valuable response time is provided for managers, so that further deterioration of the abnormity is effectively restrained, and the safety and sustainable utilization of water resources are guaranteed.

The invention provides an intelligent short message link efficient detection method and system. According to the method, unmanned aerial vehicle cluster deployment is used for forming a dynamic communication topology, and the dynamic communication topology is used for monitoring the time delay mutation rate and the packet loss rate of a damaged short message link in real time and generating a state fluctuation sequence. When it is detected that the transmission time delay gradient exceeds an emergency communication threshold value, an abnormal marking mechanism is triggered, and abnormal association clusters and the space-time coupling relation of the abnormal association clusters are recognized by analyzing the data. Then, the information is bound with timestamps, and a block chain state change event is generated by using a multi-node parallel evidence storage technology; and adjusting the distribution density of the unmanned aerial vehicle according to a verification result, and generating a topology reconstruction factor so as to update a short message transmission path and optimize a communication network. According to the technical scheme provided by the invention, the stability and reliability of efficient detection of the short message link can be improved.

The invention discloses a property maintenance prediction system based on big data, and the system comprises the steps: monitoring equipment and environment in real time through an intelligent sensor, transmitting the data to a cloud or local storage through a wireless network, and carrying out the historical data processing and cleaning through a distributed architecture; predicting the equipment fault risk through machine learning, establishing a customized prediction model for different equipment, analyzing the life cycle and predicting the service life of the equipment; for old equipment, constructing a life extension model by using historical fault data; the system generates intelligent decision suggestions, pushes equipment health states to property management personnel, automatically formulates maintenance plans and priorities, and dispatches maintenance personnel; during fault prediction, early warning is given out in real time, related personnel are reminded through a short message or an APP, meanwhile, maintenance operation is recorded, historical data are analyzed, and future maintenance plans and budget are optimized; the system dynamically adjusts the life prediction model of the old equipment by accumulating historical data, and ensures the accuracy and efficiency of equipment health management.

The invention relates to an intelligent short message template generation method and system based on a large language AI model, and the method comprises the steps: extracting cross-cultural communication frequency, sentence pattern preference analysis results and screen size adaptation data from social media interaction data and equipment use logs of target audiences, and generating a cultural background distribution matrix; identifying regional culture features in the culture background distribution matrix to obtain a taboo matching result; generating an expression habit preference matrix according to the updated culture background distribution matrix; generating a preliminary short message template according to the expression habit preference matrix and the symbol semantic mapping table, and outputting an adjusted template set conforming to message length control; analyzing the acceptability of the adjusted template set on the language conciseness requirement and the interactive button layout, and generating a new template set; evaluating a text alignment mode of the new template set; and screening candidate short message templates according to the information definition score. According to the invention, the accuracy and acceptability of cross-culture short message communication can be effectively improved, and the participation degree of audiences is enhanced.

The invention discloses a sewage monitoring and early warning method and system, and aims to solve the problems of lagging and high misjudgment rate of traditional monitoring. The multi-modal acquisition module acquires water quality parameters, equipment states and pipe network data in real time through a distributed sensor network, a timestamp is calibrated through linear interpolation of a dynamic analysis engine, spatial features are extracted through concentration gradient calculation, and data are cleaned in combination with Kalman filtering and an isolated forest algorithm. And the intelligent analysis and decision module mines time sequence features based on the LSTM model and outputs pollution level indexes. And the grading response execution module triggers early warning according to three-level threshold values: a first-level APP pushes data, a second-level superposition short message and a third-level telephone alarm and links equipment, a standby purification device is started within 10 seconds, and a WebGL visual diffusion report is synchronously generated. The system constructs an acquisition-analysis-decision-response closed loop which is suitable for industrial and urban pipe network scenes.

The invention discloses a gas user intelligent safety inspection system based on the Internet of Things. According to the invention, through a multi-stage intelligent decision-making mechanism, the active protection capability of gas safety management is significantly improved. A traditional alarm system depends on single sensor threshold triggering, is susceptible to environmental interference and lags in response, while the system can accurately distinguish scenes such as real leakage and cooking interference by fusing multi-dimensional data such as gas concentration, temperature and flame and combining a user behavior mode to dynamically evaluate a risk level. For example, when it is detected that the gas concentration is abnormal but not accompanied by sudden temperature rise or a flame signal, the system automatically lowers the alarm level and only pushes prompt information; and when high-risk leakage is confirmed, the valve is immediately closed in a linkage mode, exhaust equipment is started, synchronous early warning is conducted through multiple channels such as telephones, short messages and a community platform, and it is ensured that the user and rescue strength respond in the golden time.

The invention relates to the technical field of short message auditing and intercepting, in particular to a short message auditing and intercepting system based on artificial intelligence, which performs multi-level semantic feature extraction on short message content by constructing a deep learning architecture mixed by a convolutional neural network and a recurrent neural network. And traditional keywords are effectively identified, and camouflage keywords, homophonic replacement and interference symbols which are easy to bypass are filtered. Furthermore, a short message semantic map is constructed through a multi-head self-attention mechanism, and weighted analysis and abnormal node recognition are carried out by taking sensitive words and key semantic units as map nodes and taking semantic association relationships among the nodes as edges, so that the abnormal short message recognition precision is improved. Besides, a multi-dimensional short message risk assessment mechanism is constructed by combining the historical behavior mode of the sending number, the number reputation score and the incidence relation between the numbers, and a hierarchical auditing strategy is implemented, so that the system processing efficiency and the interception accuracy are effectively improved.

The invention discloses a fraud phone recognition method and system based on multi-modal data fusion. The method comprises the following steps: acquiring multi-modal data of a plurality of fraud numbers from historical fraud data; constructing a multi-modal fraud data graph, taking each piece of multi-modal data of the fraud number as a node, and constructing a connection edge between the nodes according to an association relationship between every two pieces of multi-modal data; constructing and finely adjusting a large language model; multi-modal data of a to-be-recognized fraud number is obtained, a plurality of nodes are selected from the multi-modal fraud data graph, then the multi-modal data of the to-be-recognized fraud number and the multi-modal data of the selected nodes form cue words, the cue words are input into the large language model, and whether the obtained to-be-recognized fraud number relates to fraud or not and reason analysis for judging that the to-be-recognized fraud number is fraud are output. The invention relates to the field of communication, can improve the fraud recognition accuracy and system adaptability through deep fusion and calculation of multi-mode data such as call audio, short message text and call ticket data, and provides powerful technical support for fighting against novel telecommunication network fraud.

The invention provides a short message issuing processing method and system based on scene self-adaption. The method comprises the steps that a three-dimensional communication characteristic spectrum is constructed through a building information model and infrared thermal imaging data, short message request distribution is analyzed and predicted in combination with a signal attenuation field, cross-operator network quality data is integrated to form a converged communication quality field, and finally short message issuing is intelligently scheduled according to the network state and service requirements. According to the method, accurate short message routing optimization based on real-time communication quality and crowd distribution in a complex building environment is realized. According to the technical scheme provided by the invention, the short message delivery rate and timeliness in a complex building environment can be remarkably improved, and particularly, the communication reliability in a crowded area and a signal blind area is remarkably improved.

The invention discloses a light-weight government affair questionnaire intelligent touch and analysis system and method based on a fusion message, and the system comprises an integrated message application platform operation interface which is used for the submission, application, strategy definition and transmission of a customer message; the questionnaire engine is used for generating questionnaires, issuing strategies and performing multi-dimensional statistical analysis on questionnaire results; the intelligent message scheduling engine is used for realizing AI generation of rich media messages, multi-channel intelligent reach distribution, optimal reach mode selection and summary analysis of reach mode results; and the electronic fence data engine is used for processing operator real-time signaling big data and capturing operator numbers and accurate touch short messages in a specified range. An efficient and convenient short message creation and auditing mechanism, flexible and diversified questionnaire construction, intelligent rich media message generation, accurate regional orientation and audience access, intelligent distribution, high interactivity, comprehensive and deep data analysis and report generation can be realized.

The invention discloses a short message template intelligent identification method and system based on semantic similarity calculation, relates to the technical field of information and communication, and realizes automatic matching of a request short message and a template library through semantic vectorization and similarity calculation; semantic extension, structural constraint and a dynamic feedback mechanism are combined, so that the matching accuracy and robustness are improved; an optimization process driven by a multi-level model and category features is introduced, and an identification-feedback-optimization closed-loop system is formed; the system structurally comprises a semantic modeling module, a similarity calculation module, a dynamic feedback module and a template optimization module, automatic and efficient short message template recognition and updating can be achieved, and the requirements for real-time performance and accuracy in a large-scale application scene are met.

The invention relates to an AI intelligent short message content generation optimization method and system based on a user portrait, and the method comprises the steps: obtaining interaction record data, dominant feedback and implicit feedback of a user and a short message service, and constructing an initial interest association table of the user for the short message content; extracting high-frequency keyword theme clusters and time distribution of the reply text according to the initial interest association table; extracting semantic association and interaction frequency characteristics of the high-frequency keywords; calculating keyword emotion weight and unsubscribing keyword trigger scene distribution density according to the user enhanced behavior feature set; the appearing time point and the expression form of the unsubscribing keyword are combined; mapping explicit feedback correction semantics and implicit feedback emotion tendencies into interest nodes; triggering a scene distribution rule according to a confirmation willingness and an unsubscribing keyword in the historical reply; and generating a personalized short message matched with the dominant feedback questioning mode and the keyword emotion weight. According to the invention, the individuation degree and the user acceptability of the short message content can be effectively improved, and the unsubscribing rate is reduced.

The invention relates to the technical field of communication, and provides a short message content compliance generation method and system fusing a semantic large model. The method comprises the following steps: carrying out coarse identification on short message content to be processed by a service provider to obtain a short message type and a user demand; inputting the short message content into a semantic large model for deep semantic analysis, and outputting short message semantic analysis information; performing multi-dimensional compliance comparison on the semantic analysis information of the short message according to the type of the short message and a user demand, and identifying risk description content; and optimizing and adjusting the risk description content according to the short message type and the user demand and the semantic analysis information of the risk content, and generating target short message content. The technical problem that short message content generation in communication service depends on a template, and compliance risks cannot be dynamically identified and avoided according to user requirements is solved, and deep semantic analysis and multi-dimensional risk comparison through a semantic large model are realized; and the intelligent level and compliance guarantee capability of short message content generation in the communication service are improved.

A method and system for securely communicating with third parties who are authorized to control access to funds in a banking account held by a financial institution is disclosed. The method and system are particularly useful when the third party does not have direct access to account controls (for example, through a secure web portal or a secure banking application). While joint account holders, or other authorized users, of the banking account may communicate directly through an account management service, communication with the third party is mediated using a separate messaging service, such as a short messaging service (SMS). An authorization token may also be used as part of the approval process.

The invention relates to an AI intelligent short message pushing method and system based on user behaviors, and the method comprises the steps: obtaining the social relation and interaction frequency of short message pushing target group members from historical behavior data, and obtaining a classification result of an initial short message pushing target group; integrating the behavior data of the group members; determining adjacent groups by analyzing social relations and interaction frequencies of members among the groups to obtain a group feature set; identifying a first-time user according to the group feature set; obtaining a dynamic behavior change trend of the short message pushing target user from the real-time interaction data; if the matching degree of the real-time behavior preference distribution and the group feature set is lower than a preset matching degree threshold value, analyzing a social relation between the user and a new group member; and according to the mapping relationship and the real-time preference distribution, determining the priority and correlation of the push information items. According to the method, accurate description of user behaviors and adaptive optimization of a pushing strategy are realized through multi-level feature modeling, dynamic data updating and a cross-group cooperation mechanism.

The invention discloses a secure transmission system based on a multimedia short message, and relates to the technical field of communication and network security, and the system comprises a protocol stack security reinforcement module which carries out the hierarchical reconstruction of an MMS protocol stack, comprises a preprocessing layer, is used for intercepting and filtering illegal characters, and verifies the legality of a message structure through a finite-state machine; the analysis layer is used for pre-judging memory requirements based on message types and lengths by adopting a dynamic memory allocation strategy; the execution layer is integrated with a null pointer checking mechanism, and the validity of a pointer is forcibly verified before a protocol stack calls a function; the encryption and signature module is used for carrying out end-to-end encryption on a message body and metadata by adopting a hybrid encryption algorithm and carrying out message integrity verification through a lightweight hash tree; and the vulnerability real-time monitoring module is embedded into an abnormal behavior detection model based on machine learning and is used for dynamically identifying memory occupation abnormity and illegal instruction calling high-risk operation when the protocol stack runs.

The invention discloses a wireless heart rate monitoring and short message alarm method based on an Arduino single-chip microcomputer, and particularly relates to the technical field of heart rate monitoring, which comprises the following steps: acquiring environment and user activity information through a multi-source sensor, acquiring a heart rate data priority according to an environment risk score and user activity intensity, and sending the heart rate data priority to the Arduino single-chip microcomputer; future environment and activity conditions are predicted based on the long short-term memory network, sampling frequency and transmission strategies are adjusted in advance, prospective intervention on potential risks is achieved, practicability, accuracy and reliability of the heart rate monitoring system are improved, and the heart rate monitoring system is suitable for wide health monitoring scenes; when the heart rate abnormity is compared with the threshold value, multi-level alarm is triggered, the high-frequency sampling energy consumption of the sensor can be reduced, the data transmission path is evaluated and optimized in combination with the network reliability, the abnormity detection precision and stability are remarkably improved, and the problems that the abnormity is difficult to recognize in time and the power consumption is too high in a single heart rate sensor in a complex environment are solved.

The invention relates to the technical field of network security and data processing, and discloses a violation short message recognition method and system based on deep semantic understanding, and the method comprises the steps: firstly cleaning an original short message, generating a mixed embedding vector through characters, sub-words and pinyin, and carrying out the recognition of the violation short message; then processing through a double-layer detection engine, wherein the first layer utilizes rules and a lightweight model for rapid preliminary screening; in the second layer, for suspected samples, a double-tower fusion neural network architecture is adopted, local and global features are combined, fusion is carried out through a gating unit, and a large language model is input to carry out deep semantic reasoning. The system executes strategies such as interception or flow limiting according to the risk score, and realizes model iteration through a dynamic knowledge base and incremental learning. According to the method, the resource consumption and the detection precision are balanced through the layered architecture, the antagonistic variants are effectively identified by utilizing multi-dimensional feature fusion, and the method has the adaptive evolution capability for a novel violation mode.

The invention belongs to the technical field of intelligent short message service scheduling, and particularly relates to an intelligent short message scheduling system and method based on 5G network slices. According to the method, the short message service processing efficiency in the 5G network slice environment is effectively improved through accurate prediction and intelligent scheduling of the short message service traffic, the change trend of the short message service traffic can be accurately captured through smooth processing and exponentially weighted moving average processing of the traffic change rate time sequence, and the short message service processing efficiency is improved. Reliable data support is provided for subsequent scheduling decisions, meanwhile, through confidence evaluation and resource utilization evaluation, the predicted demand of short message service flow and the resource utilization condition can be comprehensively considered, the scheduling reasonability and effectiveness are ensured, in addition, the intelligent scheduling mechanism can automatically adjust resource allocation according to the scheduling priority, and the scheduling efficiency is improved. The sending requirement of the high-priority short message service is met, and the processing speed of the short message service and the user experience are further improved.

The invention discloses a multi-channel high-precision water level dynamic real-time monitoring system for a drilling water pumping test, and the system comprises a sensing layer which is used for deploying a multi-source sensor array, inhibiting interference through distributed layout and electromagnetic shielding, collecting multi-dimensional data in real time, and carrying out the preliminary filtering; according to the transmission layer, an optical fiber and twisted pair redundant network is constructed, an EtherCAT protocol is adopted for low-delay transmission, AES-128 encryption tampering prevention is integrated, and edge nodes compress data and verify integrity; the processing layer is used for carrying out real-time preprocessing on edge calculation and switching a standby sensor in abnormal detection; the cloud end predicts the water level trend through Spark Streaming analysis and an LSTM model, distinguishes interference through a random forest algorithm, and outputs calibration data and an analysis report; the application layer is used for constructing a three-dimensional drilling model based on Unity, dynamically displaying water level changes, synchronizing a multi-parameter curve and supporting historical backtracking; the early warning module notifies abnormity through sound and light and short messages, the decision module generates a report and supports multi-drill-hole comparison, and the test strategy is optimized.

Methods and systems for text messaging-based self-service authentication in absence of a physical authentication token. In some aspects, the system receives, from a mobile device, a first text message indicating a request for account access in absence of the physical authentication token, in which the mobile device is operating on a mobile network and associated with a user digital identifier relating to the mobile network. The system transmits, to the mobile device, a second text message including a link to a webpage for account access in absence of the physical authentication token; determines, based on mobile device information associated with the mobile device and the user digital identifier, whether to authenticate the request; and in response to authenticating the request, provides a temporary machine-readable code associated with the user account. The temporary machine-readable code may allow a third party to access the user account by scanning the temporary machine-readable code.

A processing system including at least one processor may obtain a text message content from a sender to a recipient, identify additional contextual content based upon a context associated with at least one of: the sender and the recipient, generate a revised text message content based upon the text message content in accordance with the additional contextual content, and transmitting a message to the recipient comprising the revised text message content.

The invention relates to the technical field of quantum computers, in particular to a short message secure transmission method and system based on a post-quantum algorithm and electronic equipment, and the method comprises the steps: obtaining short message data with a signature, and carrying out secret key packaging calculation through employing a first mixed public key provided by a second terminal, thereby obtaining a secret key packaging ciphertext and a symmetric secret key; encrypting the short message data with the signature by using the symmetric key to obtain a short message data ciphertext; the key packaging ciphertext and the short message data ciphertext are sent to a second terminal, and the second terminal decrypts the short message data ciphertext to obtain a short message data plaintext; according to the method and the device, a quantum security resisting key negotiation function is provided for the short message by adopting a mixed key encryption mode, quantum attack resisting protection is provided for the content of the short message, information is prevented from being intercepted or tampered in combination with a signature verification mode, and the security of short message transmission is further improved.

The invention discloses a multi-source environment monitoring and intelligent alarm system and method based on a Palladium platform. The method comprises the following steps: S1, obtaining preprocessed environment monitoring data; s2, forming transmission environment monitoring data; s3, carrying out distributed aggregation and fusion on the transmission environment monitoring data on the central Palladium platform; s4, identifying abnormal fluctuation in the data; s5, generating adjusted alarm threshold data by using a self-learning mechanism; s6, according to the adjusted alarm threshold data, carrying out grading evaluation on the detected environment abnormal events, forming multi-grade risk determination, and generating corresponding intelligent alarm signals; and S7, transmitting the intelligent alarm signal to each edge computing node and a related monitoring terminal, issuing alarm information in a short message, mail, voice broadcast or system interface display mode, and starting a corresponding emergency processing plan. According to the invention, the transmission efficiency of the alarm information can be effectively improved, and the emergency response system can make proper response according to different risk levels.

The invention discloses a multi-user multi-channel message scheduling method, system and device and a storage medium, and the method comprises the steps: creating a sending channel index structure and a message index structure, and creating a group of first-in first-out message cache queues of different channel types for each user; caching the obtained user message to the tail of a message cache queue, mapping the message ID to a message index structure, and mapping a sending channel ID to a sending channel index structure; according to the sending channel index structure, writing a to-be-sent message into a corresponding sending channel from a message cache queue of the user, and deleting a message ID of the to-be-sent message from the message index structure; performing flow velocity detection on each sending channel; and until the ID data in the message index structures of all the users are empty. The short messages submitted by different users have the same sending priority, so that the problem of poor experience such as user interface lagging or long-time non-response in a multi-user request scene in the prior art is solved.

Methods and systems for managing text messaging-based authentication in absence of a physical authentication token. In some embodiments, the system receives, from a mobile device, a first text message, in which the mobile device is operating on a mobile network and associated with a user digital identifier relating to the mobile network, and the first text message indicates a request for access in absence of the physical authentication token. The system performs an account search based on the user digital identifier. In response to locating a user account associated with the user digital identifier, the system performs an assessment based on mobile device information relating to the mobile network and associated with the user digital identifier; selects, from a plurality of candidate authentication protocols, an authentication protocol based on the assessment; and manages, based on the authentication protocol, the request for access in absence of the physical authentication token.

The invention relates to the field of variable replacement, and discloses a short message variable replacement method based on dynamic template editing, which comprises the following steps of: changing a region into an editable state by using a contentEdible attribute of an HTML (Hypertext Markup Language), and presetting a variable label style in an editing region; a configuration person inserts a variable by clicking a variable tag on an interface, dynamically creates a virtual node by using a creature DocumentFragment method of a DOM (Document Object Model), and inserts the corresponding variable tag into a position where a cursor is located in a special style; when a user clicks or inserts the variable label, using window.getSelection to obtain the position of a cursor in real time; after finishing editing, the configuration personnel click a saving button; the system replaces variable labels in a template with actual content according to a stored variable mapping relation through a template text extracted through code analysis in the background, and the replaced complete short message content is transmitted to a short message service module and is ready to be sent to a target user. The method has the advantage of improving the overall working efficiency and accuracy.

The invention discloses a slope early warning method and system based on a knowledge graph, and relates to the technical field of multi-source monitoring slope early warning, and the method comprises the steps: 1, unifying laser, radar, satellite remote sensing and underground water level monitoring flow into an index-structure-disaster situation graph containing traceability metadata; 2, generating an instability trigger coefficient by using a gradient lifting model driven by a coupling trend and credibility; step 3, automatically outputting short messages, broadcasts and social contact templates, and implanting abstract codes for publishing; 4, comparing the returned text in real time, marking deviation nodes according to graph consistency, and tracing a source link; and step 5, performing Hash solidification on the core early warning segment and spreading the performance to the alliance chain, and writing back the knowledge graph optimization template and channel. According to the scheme, multi-source data alignment is achieved, early warning is accurate and reliable, cross-medium semantic consistency and evidence chain traceability are achieved, and the requirement of the whole mountain disaster prevention process is met.