378 results about "Behavioral analysis" patented technology

The invention discloses a petroleum drilling machine equipment intelligent alarm method based on video real-time display, and belongs to the technical field of petroleum exploitation equipment monitoring, and the method comprises the steps: obtaining the operation video of a key part of petroleum drilling machine equipment, and transmitting the operation video of the key part to a monitoring center; in the monitoring center, preprocessing the operation video of the key part to eliminate the influence of illumination disturbance, and carrying out key part identification and behavior analysis on the preprocessed operation video of the key part by using an equipment part detection and behavior analysis algorithm based on deep learning to obtain a detection result of the key part; and based on the detection result of the key part, the display alarm and the sound-light alarm of the abnormal type and the occurrence position are triggered in real time, and the alarm information is sent to the handheld terminal of the driller. According to the method, intelligent fault detection and alarm are realized, manual intervention is reduced, the comprehensiveness of equipment monitoring is improved, and the accuracy and timeliness of alarm are improved.

The invention discloses a pet behavior data management system and method based on big data, and relates to the technical field of pet behavior intelligent monitoring. Performing time synchronization and time sequence reconstruction; carrying out preprocessing, and carrying out key frame extraction and target detection on the video frame to obtain a pet posture track; on the basis of a state switching point of a hidden Markov model, dividing the data subjected to time sequence reconstruction into a plurality of behavior events, and combining adjacent related behavior events to form behavior blocks; extracting statistical characteristics, behavior frequency and context characteristics of each behavior block, and training an individual behavior baseline model by adopting a multi-scale sliding window and a weight attenuation strategy based on historical behavior data; and comparing the real-time behavior block with the individual behavior baseline, and carrying out anomaly monitoring and warning through an integrated classifier. According to the invention, cross-device pet behavior management and abnormal early warning can be realized, and the reliability and the intelligent level of pet health monitoring and behavior analysis are remarkably improved.

The invention provides a motion video key clip extraction method based on behavior analysis. The method comprises the following steps: firstly, performing decoding and frame standardization on a match video stream, detecting and positioning a coach target, and obtaining and expanding a bounding box; extracting a candidate skeleton key point set in the extended region, selecting the skeleton with the most key points as the skeleton of the coach, and performing cross-frame tracking; analyzing the skeleton in real time, triggering hand fine analysis and extracting hand key points when a scoring trend appears, comprehensively judging based on geometry, kinematics and time sequence rules, and generating a trigger signal when a specific scoring gesture is detected; and the background thread extracts fragments before and after the triggering moment from the video stream as key fragments, and stores the key fragments in association with metadata such as event types, coach identities and competition states.

The invention discloses a cross-scene user traffic monitoring behavior analysis method and system based on deep learning. The method comprises the following steps: collecting standard traffic data; establishing a multi-modal depth feature extraction network, extracting time sequence features of a statistical level from packet header information of standard traffic data by using a CNN convolutional neural network, obtaining semantic features from traffic payload by using a Bi-LSTM bidirectional long short-term memory network, and obtaining associated features of network resources based on a GNN graph neural network; fusing the time sequence features, the semantic features and the associated features by using a cross-modal attention mechanism to obtain fused features; and inputting the fusion feature into a behavior recognition model based on a multi-head self-attention mechanism, and outputting a user behavior tag which at least comprises application use, behavior intention and behavior abnormality score. The manual analysis cost is reduced, and the monitoring analysis efficiency and accuracy are improved.

The invention discloses a human resource production and teaching fusion supply and demand matching system based on a dynamic ability portrait, and relates to the field of human resource management. Comprising a capability analysis module, a structure modeling module, an occupational mapping module, a selection monitoring module, a path generation module, a behavior analysis module, a task matching module, a supply and demand evaluation module, a guide iteration module and a recruitment screening module. According to the method, capability portraits do not depend on subjective resumes any more, the accuracy and credibility are remarkably improved, the problem that a static label model cannot reflect a real growth track is solved, the competency and potential rising space of talents for posts can be more accurately judged, the problem that traditional HR cannot process cross-domain task matching is solved, and the method is suitable for popularization and application. And real-time closed-loop alignment of supply and demand of production and education is realized.

A method for enhancing security of data, code, and / or network components by introducing a layer of integrity management that adapts to changing conditions within a network. The method may include use of a processor to perform intrusion analysis using an intrusion detection system and / or prevention system, behavioral analysis by accessing user logs to see if behavior is within a normal range, and / or geolocation analysis to see if the piece of data, section of code, and / or network component are within their usual surroundings. When there is a concern of a data breach, leak, and / or hack, the processor may initiate a response that detects other pieces of data, sections of code, and / or network components in proximity, initiates a self-destruct mechanism, triggers hardware to perform outside of operational specifications, and contains the spread of the data breach, leak, and / or hack through shutdown procedures, isolating affected systems, and / or alerting security personnel.

The invention relates to the technical field of data security, in particular to an enterprise data leakage protection method and system based on behavior analysis. The method comprises the following steps: acquiring user keyboard dynamics data, terminal equipment micro-action data and data access flow data; according to the user keyboard dynamics data and the terminal equipment micro-action data, constructing a user biological behavior characteristic fingerprint, and obtaining user behavior characteristic baseline data; according to the data access flow direction data, establishing a data flow direction time sequence diagram to obtain user data access mode data; acquiring real-time user operation behavior data; and performing feature extraction processing on the real-time user operation behavior data to obtain real-time behavior feature data. According to the method, multi-dimensional user behavior characteristic fingerprints are established, more accurate identity confirmation is realized through biological behavior characteristics such as keyboard dynamics and terminal micro-actions, and the problem that the identity is reliable but the behavior is not reliable is effectively solved.

The invention discloses a cross-platform teaching tool data collaboration and personalized resource recommendation system based on an MCP protocol, and belongs to the technical field of education. According to the system, a multi-platform teaching tool is in unified butt joint through the MCP protocol adaptation layer, and the problem of data splitting is solved; the data co-processing layer cleans and fuses multi-tool data, generates a teacher / student / parent data view and stores an evidence through a block chain; the personalized recommendation engine generates role-based resource recommendation based on a teaching knowledge graph and multi-dimensional behavior analysis; the user interaction layer supports multi-terminal access, and the data security module guarantees compliance. According to the system, the cross-platform data collaboration efficiency is improved by 70% or above, the resource recommendation matching degree reaches 92%, the system is suitable for K12 education, higher education and vocational education scenes, teaching tool data barriers are effectively broken through, and the teaching data utilization rate and the resource recommendation accuracy are improved.

The invention discloses a network information security access control system based on dynamic trust evaluation, and the system comprises a behavior collection module which collects original behavior log data, and builds a behavior feature sequence reflecting an entity security state through a preset streaming processing engine; the behavior analysis module is used for carrying out long and short term behavior modeling analysis on the behavior feature sequence to obtain long and short term behavior pattern representation, outputting potential causal chain data based on the long and short term behavior pattern representation and an abnormal causal inference model combined with context perception, and constructing a dynamic trust portrait according to the potential causal chain data; the long and short-term behavior modeling analysis comprises long behavior modeling analysis and short behavior modeling analysis; and the strategy generation module is used for driving a strategy engine in real time based on the dynamic trust portrait, carrying out attribute extraction and dynamic attribute coding based on a behavior sequence in a software defined boundary frame, and dynamically generating and issuing an optimal dynamic access strategy with attributes according to a minimum permission principle.

The invention discloses an AI dialogue flow control method, system and device supporting real-time interruption of a user, a medium and a program product. The method comprises the steps that a user request is received, and a flow session is established; based on the stream session, requesting LLM increment generation, receiving fragments generated by increment, returning the fragments, and pushing the fragments to the client; when a click stop request of a user is received, an STOP signal is sent; when the STOP signal is monitored, sending a mark termination request; after a mark termination request is received, a subsequent generation termination request is sent to the LLM, a STREAMTERMINATED semantic event is published and broadcasted, and generated content and a termination mark are returned to the client; terminating subsequent generation comprises stopping untriggered subsequent reasoning and tool chain calling; discarding the tail cache which is not sent; and recording the output token count, and terminating the offset. The AI dialogue flow control method supports real-time interruption of the user, is low in delay, clear in semantics and recoverable, and further has the advantages of saving resources, being high in stability, capable of being universally expanded, gaining behavior analysis and the like.

The invention provides a malicious request interception system based on multi-dimensional behavior analysis and cloud-ground collaboration, relates to the technical field of network security, and analyzes normal equipment characteristics, a user behavior sequence and a cloud malicious equipment blacklist by collecting TCP / IP protocol stack characteristics and combining dynamic characteristics of the user behavior sequence. First interception is performed according to an analysis structure, deep identification is performed on a user behavior sequence after the first interception based on time sequence analysis and clustering analysis, and second interception is performed according to an identification result, so that the problems that a static rule cannot identify novel attacks and group attack features are difficult to capture are solved; and carrying out content verification on the user behavior sequence after the second interception, and carrying out third interception according to a verification result, thereby realizing dynamic adaptation of a service scene, solving the problem of poor static rule adaptability, carrying out whole system synchronization on all intercepted malicious logs, avoiding cross-node missed interception of malicious requests, and forming a defense iteration closed loop.

The present invention relates to the technical field of heating network regulation. Disclosed are an intelligent heating network operation and regulation system and method. A behavior collection module deploys several heating regulation detection points on a heating pipe network to collect heating-influencing behaviors at each heating regulation detection point; a behavior analysis module separately performs clustering on each heating-influencing behavior to determine behavior clusters, analyzes each behavior cluster, and obtains a target reference behavior cluster on the basis of the analysis results; a first calculation module collects real-time feature data of the heating pipe network, performs analysis, and calculates an initial heating load of the heating pipe network on the basis of the analysis result; and a second calculation module calculates a correction factor of the heating pipe network on the basis of the target reference behavior cluster, and corrects the initial heating load on the basis of the correction factor, so as to obtain a target heating load. The present invention can monitor the operation state of a heating pipe network in real time, automatically analyze heating variations, and quickly and accurately set a heating load, so as to achieve energy conservation and emission reduction, improve the user satisfaction, and reduce the operation and maintenance costs.

A system for quantum-enhanced behavioral analysis and secure database operations includes an ACAARY Database configured to store and process quantum-verified data under multi-tiered access control; an AR Quantum Cyber-Micro Expressions System configured to analyze involuntary behavioral patterns in digital communications via computational analysis of user interaction data; AR Quantum Sequence Triplications with Quantum Operations comprising three-qubit verification circuits implemented on superconducting quantum processors that perform parallel artificial-qubit processing to achieve unbiased quantum supremacy; an AR Quantum Parallel Data Algorithm Structure and Method Specialized Encrypted Algorithmic Quantum Procedures configured to execute simultaneous perpendicular encryption processing with real-time transaction verification across multiple channels; an AR Helmsmen Quantum Transportation Management System with integrated digital licensing and frequency-based quantum routing protocols; and an AR Thermodynamics Devices System configured to perform thermal bonding and division operations while maintaining different temperatures within defined containment areas for material modification.

The invention relates to the technical field of animal behavior analysis, and discloses an animal behavior accurate recording and analyzing system based on multi-mode keyboard coding. A data acquisition and synchronization module of the system acquires original key event data and generates a time sequence behavior data stream with millisecond-level precision; the coding logic engine module is used for converting the physical key sequence into a hierarchical behavior semantic coding sequence through a dynamic mode switching and key mapping technology; the behavior state modeling module is used for constructing an animal behavior state transition probability model, performing state decoding and estimation by adopting a hidden Markov model, and outputting a behavior state sequence with confidence; the behavior analysis and prediction module is used for predicting a behavior evolution trend and identifying an abnormal behavior event; and the threshold value dynamic adjustment module is used for dynamically adjusting an early warning threshold value through interaction between the normal behavior generator and the real-time discriminator aiming at an abnormal behavior event so as to finish accurate recording and risk analysis of animal behaviors.

The invention discloses a malicious interference detection device and method based on signal behavior analysis, and belongs to the field of wireless communication and network security. The device comprises a signal monitoring module, a behavior analysis module, a prediction and classification module and a self-adaptive updating module. The system further comprises an automatic parameter selection module. The signal monitoring module is used for acquiring transmission state, frequency band and time interval parameters in real time; the behavior analysis module is used for extracting time sequence features and frequency domain features and detecting malicious behaviors in combination with behavior analysis; the signal monitoring module is linked with the behavior analysis module, analyzes the high-speed data packet and extracts frequency domain features, and the prediction and classification module performs malicious judgment in combination with a neural network; and the adaptive updating module dynamically adjusts model parameters. According to the method, signal monitoring and behavior analysis are realized, malicious judgment and dynamic adjustment of model parameters are carried out in combination with the neural network, active identification and accurate detection of dynamic change malicious signals are realized, and the method has the advantages of improving detection accuracy and adaptively coping with threats.

The invention discloses a visual perception and trajectory restoration method, system and device for chicken motion analysis and anomaly detection in a large cage farm and a storage medium, and relates to the technical field of video monitoring and behavior analysis. Carrying out fine feature extraction by adopting a space and channel attention mechanism; fine features are combined with Kalman filtering and a Hungary algorithm, chicken individual identities are continuously tracked and adjusted through time sequence prediction and space matching, and a target bounding box is output; adjusting the individual identity of the chicken according to tracking, performing smooth repair on interrupted and shielded trajectory segments through spline interpolation and Kalman filtering, and performing reasonable trajectory recovery by adopting biological kinematics constraint; based on the target bounding box, a frequency domain feature analysis mechanism and a deep learning coding technology are introduced, a behavior feature vector is generated, and health early warning is triggered according to the abnormal confidence coefficient; according to the method, the chicken monitoring precision and the anomaly detection reliability are improved.

The invention discloses a communication monitoring method and a communication system. The system comprises a monitoring module, a feature extraction module, a dynamic identification module, a behavior analysis module, an adaptive optimization module and a visual interface module. The monitoring module collects communication data flow through a mirror image port, the feature extraction module extracts packet length, time interval, direction sequence and encryption features by using a multi-dimensional feature fusion algorithm, and the dynamic recognition module realizes multi-protocol type recognition based on an improved self-attention convolutional neural network. The behavior analysis module constructs a communication relation graph and performs abnormal communication tracing; and the adaptive optimization module realizes model self-learning and parameter optimization through reinforcement learning. According to the method, through sliding window sampling, self-correlation analysis, entropy detection and GNN map modeling, accurate identification and behavior restoration of implicit traffic in a complex network environment are realized. According to the method, high-precision identification can be kept under the conditions of multi-protocol mixing and encrypted communication, and the characteristics of intelligence, self-adaption and expandability are achieved.

The invention discloses a museum audience behavior analysis system integrating positioning and digital twinning. The system comprises an audience real-time positioning module, an exhibition hall collection digital twinning module, an audience behavior analysis module and a behavior feedback adaptation module. The audience real-time positioning module adopts a multi-source positioning data fusion algorithm to obtain audience three-dimensional position coordinates and motion parameters; the exhibition hall collection digital twinning module reconstructs an exhibition hall collection three-dimensional model based on multi-modal data, and an integrated positioning data interface maps the positions and tracks of audiences in the twinning model in real time; the audience behavior analysis module extracts audience behavior features, establishes association between the features and exhibit positions and exhibition area attributes in the twin model through a behavior-scene association algorithm, and outputs a behavior analysis result; and the behavior feedback adaptation module dynamically adjusts the display strategy according to the analysis result. According to the system, deep fusion of positioning and digital twinning is realized, the accuracy of audience behavior analysis is improved, and support is provided for exhibition hall operation optimization and visiting experience upgrading.

The invention discloses a pet motion state judgment method and system, and relates to the technical field of intelligent pet keeping. Comprising the following steps: continuously collecting original sensor data of a pet, wherein the original sensor data at least comprises three-axis acceleration and three-axis angular velocity; data preprocessing and motion parameter resolving are carried out on the original sensor data, multi-dimensional motion data used for motion state judgment are obtained, and the multi-dimensional motion data comprise at least one piece of continuous motion data in a time domain; acquiring a preset classification rule base corresponding to the body type category according to the body type category of the pet; and obtaining a target motion state based on the multi-dimensional motion data and the classification rule base. Through the multi-dimensional data and the targeted classification rule base, the technical problem that in the prior art, a unified model or a fixed threshold value cannot adapt to motion feature differences of pets with different body types is solved, and accurate judgment of various fine-grained motion states of the pets is achieved; and reliable technical support is provided for pet health monitoring and behavior analysis.

The invention discloses an AI vision intelligent inspection and foreign matter recognition emergency shutdown system for a belt conveyor. The system comprises data acquisition and sample construction; constructing a DETR foreign matter recognition model; images are collected in real time, and online recognition is conducted through a DETR foreign matter recognition model; carrying out target tracking and behavior analysis based on a multi-target tracking algorithm of ByteTrack; a distance threshold value, a speed threshold value and a score threshold value are set; graded alarming is carried out, and a shutdown signal is sent to the PLC control unit under the shutdown condition. The system comprises an alarm module, an edge calculation unit, a communication module and a PLC control unit. The AI inspection camera, the edge calculation unit, the communication module and the PLC control unit are connected in sequence; the edge calculation unit comprises an AI identification module and a tracking and behavior analysis module. According to the invention, real-time identification, behavior judgment and automatic safe shutdown linkage control of foreign matters or abnormal states on the conveying line can be realized.

The invention discloses a communication control method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of communication, and the method comprises the steps: receiving CEC communication data, and carrying out the non-standard type recognition of the CEC communication data through a type recognition model if a non-standard behavior of the CEC communication data is detected, thereby obtaining a target non-standard type, and determining a non-standard compensation strategy according to the target non-standard type, and responding to the CEC communication data according to the non-standard compensation strategy to obtain a communication result. The effective period of the non-standard behavior analysis and compensation strategy is shortened, the non-standard behavior response efficiency is improved, the recognition and compensation of the novel non-standard behaviors are improved, and the user experience is improved.

This invention relates to the field of equipment collaborative control technology and discloses a server-based equipment collaborative control method. The method involves a server continuously receiving multi-source sensor data and surrounding environmental information, performing consistency verification and data fusion on the data and information to generate a comprehensive feature dataset. This comprehensive feature dataset is then submitted to a collaborative requirement assessment module to calculate preliminary collaborative requirement parameters. Based on these parameters, the historical interaction records of the equipment group are accessed, and multiple parameter verification units process these records in parallel to obtain confirmed collaborative requirement parameters. Based on these confirmed collaborative requirement parameters, a behavior trend prediction module is activated to output behavior prediction parameters, while simultaneously acquiring a real-time operational snapshot of the equipment group. This snapshot is then analyzed by a behavior analysis unit to extract actual behavior parameters. Finally, the confirmed collaborative requirement parameters and the actual behavior parameters are logically integrated to output a collaborative control decision for the equipment group.

The invention discloses a land-based round pond culture tail water circulation system and method based on ecological comprehensive treatment, and belongs to the technical field of water treatment.The method comprises the steps that land-based round pond culture system tail water is obtained, and biological purification tail water is generated through solid-liquid separation, multi-stage sedimentation filtration and multi-nutrition-stage absorption and degradation treatment in sequence; carrying out fine filtration on the biological purification tail water to generate recyclable water; recycling the recyclable water to the land-based round pond culture system to obtain real-time water quality data; acquiring a fish activity image to obtain behavior analysis data; and performing comprehensive decision by combining the real-time water quality data and the behavior analysis data, and generating a collaborative regulation and control instruction. According to the technical scheme, multi-stage ecological purification treatment and intelligent cooperative regulation and control based on real-time water quality and fish behavior data are combined, efficient purification and resource utilization of aquaculture tail water can be achieved, the aquaculture environment is dynamically regulated and controlled, and therefore the stability and the intelligent level of the whole aquaculture system are improved.

A cable well lid intelligent monitoring method based on image processing belongs to the technical field of image processing, and comprises the following steps: step 1, constructing a hardware system for cable well lid intelligent monitoring; 2, when the well lid of the cable well is opened, the central processing module triggers monitoring; 3, after monitoring is triggered, the central processing module carries out operation target recognition and positioning; 4, after the operation target is recognized and positioned, the central processing module analyzes and records operation behaviors; 5, after the operation behaviors are analyzed and recorded, the central processing module executes operation planning judgment; and 6, after the operation planning judgment, the central processing module carries out data backtracking and analysis. According to the cable well operation and maintenance method, accurate recognition of underground operation personnel and operation tools is achieved through the image processing technology, operation key information is automatically recorded, the operation legality is judged in combination with a planned operation database, and then the safety, normalization and intelligent level of cable well operation and maintenance are improved.

The application relates to the field of computer-aided technology and specifically discloses a vision-impaired drawing assistance system based on physiological signals and behavior analysis, aiming to solve the problems of mechanical assistance process and poor interactive experience in the prior art. The system comprises a physiological signal acquisition module for acquiring user concentration and emotion, a drawing behavior perception module for capturing brush pressure and trajectory, a multi-modal data fusion and intention analysis module for fusing data and analyzing creation intention, an adaptive guidance strategy generation module for generating personalized guidance strategies, and a multi-channel feedback execution module for providing voice, tactile and sound feedback. Through the cooperative work of the above modules, the system can realize real-time perception of user state and intention, dynamically adjust multi-sensory assistance guidance, and thus improve the naturalness of interaction and the assistance effect.

This invention discloses a data security access control method based on an IoT platform, relating to the field of secure access technology. It includes a dynamic threat assessment step, which determines data risk by analyzing the behavioral sequence of the data parsing process. Specifically, for a specified data type, based on the parsing behavior of historical harmless data samples, a baseline of normal behavior sequence is constructed and its corresponding normal behavior ratio range is determined. Then, the current data to be assessed is parsed, and the real-time behavioral sequence generated during the parsing process is monitored and recorded. This invention overcomes the limitation of traditional access control that only manages who can access the data. By introducing a dynamic threat assessment engine into the access link, it performs in-depth behavioral analysis on the accessed data content itself, constructing a subject-object two-way security system that can effectively defend against data reverse intrusion attacks launched using legitimate data channels.

This invention discloses an individual motion behavior analysis system based on dynamic modal configuration and rule-guided fusion, belonging to the fields of intelligent perception, sports science, and human-computer interaction. It includes a data input module, a dynamic modal organization and configuration module, a multimodal feature modeling and fusion module, an indicator-level evaluation and behavior state prediction module, a statistical rule-guided analysis and result correction module, and a structured result generation and output module. These modules work together to form a complete closed loop for motion behavior analysis technology. This invention aims to address the problems in existing motion behavior analysis technologies, such as limited dimensionality of single-modal information, rigid multimodal fusion methods, insufficient stability and interpretability of analysis results, and strong dependence on large-scale manually labeled data.

The invention discloses a multi-modal psychological and behavioral analysis method. The method comprises the following steps: S1, acquiring multi-modal data; s2, performing time alignment processing on the multi-modal data, and calculating a quality vector; s3, performing feature extraction to obtain an initial feature vector of the multi-modal data; s4, introducing a quality vector to carry out time sequence coding processing on the initial feature vector of each mode to obtain a feature vector of each mode; s5, calculating the dynamic weight of each modal based on the quality vector, and carrying out dynamic weight fusion on the feature vector of each modal according to the dynamic weight to obtain a time sequence fusion feature vector; s6, performing pooling processing on the time sequence fusion feature vector to form a global feature vector with a fixed length; s7, realizing quantitative analysis of psychological and behavioral characteristics of the target object based on the global feature vector; and S8, outputting a feature importance analysis result and a compliance audit record, and generating a readable interpretation report. Correspondingly, the invention further discloses a multi-mode psychological and behavior analysis system.