610 results about "Heartbeat" patented technology

The invention discloses a method for increasing and suppressing the number of alarms through an alarm source, and relates to the technical field of communication network operation and maintenance, and the method specifically comprises the steps: constructing a network real-time topology, building a set membership graph between a router and a downlink device, and when the heartbeat overtime alarm of the downlink device occurs in the network, starting the router according to the set membership graph. And counting the proportion of the lost equipment in a sliding time window taking the parent router as the dimension, when the proportion of the lost equipment exceeds a threshold value, judging that the router is a root cause, sending out an early warning of the router meeting the condition of a root cause determiner, and shielding the overtime alarm of the router. According to the method, the root cause event of'all the downlink devices of the same route are disconnected 'is dynamically identified in the real-time alarm flow, and a high-severity router fault alarm is used for replacing a plurality of device heartbeat overtime alarms, so that the alarm noise is remarkably reduced, and the operation and maintenance efficiency is improved.

The invention discloses a multi-device collaborative passenger flow statistical method and system, and the method comprises the following steps: presetting a unique identity label and a physical position index for devices, reading the unique identity label and the physical position index, and initializing the attribute information of the devices; a user datagram protocol broadcasting mechanism is started, and heartbeat information including the unique identity label, the physical position index and the online state is sent according to a preset period; monitoring the user datagram protocol broadcast message in the local area network, constructing and maintaining an online equipment list, and updating the online state of the equipment according to the heartbeat information receiving analysis condition; judging adjacent equipment based on a physical location index, and deciding whether to start a first boundary or a second boundary according to the online state of the adjacent equipment; and the decision result is transmitted to a passenger flow statistical algorithm to generate a shop-crossing detection line. According to the invention, multi-device collaborative passenger flow statistics dynamic boundary configuration is realized, the shop-crossing detection line is accurately generated, and the passenger flow statistics problems of fixed boundary configuration, easy missed counting and poor multi-device collaboration are solved.

The invention discloses a multi-modal interaction evaluation system and method based on synchronous data acquisition, and relates to the technical field of biomedical engineering and man-machine interaction, and the method comprises the steps: generating a synchronous pulse sequence through a synchronous signal generator according to the same coding time base, and outputting the synchronous pulse sequence to an optical path and an electrical path at the same time; pulse events are recognized in the video and the electrophysiological data respectively, and observation pairs of counting numbers and timestamps are obtained; time drift is continuously estimated and compensated through robust regression in a sliding window, and a unified time axis is generated; furthermore, a dynamic time window of heart beat anchoring is constructed according to an R peak event of the electrocardiosignal, and consistent segmentation and feature extraction of cross-modal data are achieved.

A method for agent failure detection including listening for an agent heartbeat signal from an agent, updating a most recent heartbeat timestamp for the agent upon receiving the agent heartbeat signal from the agent or, upon not receiving the agent heartbeat signal, probing the agent for a response. Upon receiving the response from the agent, the suspect agent designation is removed from the agent and the most recent heartbeat timestamp is updated. Upon not receiving the response, the method further includes designating the agent as a failed agent, sending a message to a service mesh and / or a message pool regarding the agent being designated a failed agent, activating a shadow agent associated with the agent, and resuming operation with the shadow agent replacing the agent.

The invention discloses a Raft consensus algorithm-based dynamic management method and a related device, and relates to the technical field of communication, when a slave node server does not receive a heartbeat packet of a master node server overtime, the slave node server is automatically converted into a candidate node server and broadcasts an election request; and if the number of the received feedback information for confirming that the candidate node server is changed into the master node server is greater than half of the total number of all the slave node servers, determining that the candidate node server is changed into the master node server. The delay risk that a master-slave centralized architecture depends on manual monitoring and manual switching is thoroughly eliminated, fault discovery and response are solidified on an algorithm level, and automatic disaster recovery without human intervention is achieved.

The present disclosure provides a system and method for managing an artificial intelligence (AI) agent within a secure cloud-based enclave. The system discloses consolidated training to optimize information retrieval by using a structured tree-like system, reducing redundancy in queries. The system provides heartbeat validation to evolve user preferences over time, ensuring accurate responses. Further, the system provides error minimization training to closely mimic user behavior, enhancing satisfaction. The system utilizes prompts and feedback to align responses with user intent. The system ensures that all involved agents are adequately trained, leading to more reliable outcomes. This integrated approach results in an efficient, adaptive, and reliable AI system, streamlining interactions and optimizing user experience.

The invention discloses a dynamic risk management and control method and system for an operation process and field interaction equipment, and relates to the technical field of industrial internet, machine vision and intrinsic safety control. The invention aims to solve the technical problems that the physical state and the digital approval in the existing job management are disjointed, the existing job management is easily attacked by multimedia data fraud (such as screen copying and historical photo forgery), and the control instruction is lagged in a dynamic environment. The method comprises the following steps: a system and a field controller establish bidirectional heartbeat monitoring based on a hardware watchdog, and equipment is set in a physical locking state by default; responding to the operation request, and acquiring multimedia evidence containing a bottom hardware level tamper-proof space-time fingerprint by utilizing a hardware security unit (SE) of the field interaction equipment; the authenticity and the space-time legality of hardware fingerprints are verified at first, and then moire detection, reflection analysis and semantic comparison are conducted through an AI algorithm; and only when the anti-counterfeiting and the content verification are both passed, generating an encryption driving signal to unlock. During operation, a state competition processing mechanism is introduced, if the environment is suddenly changed, the system preferentially suspends the authority through high-priority hardware interruption, and fault-oriented security (Fail-Safe) is achieved. According to the invention, through deep fusion of software and hardware, active defense and millisecond-level dynamic fusing of operation risks are realized.

The invention discloses a node health state determination method and apparatus, and an electronic device. The method comprises the following steps: acquiring a historical state vector of a point-to-point PCDN node in a historical time window; predicting the historical state vector by using a prediction model to obtain a predicted health factor sequence; comparing the predicted health factors in the predicted health factor sequence with a fluctuation sensing threshold to obtain a comparison result; and determining the health state of the PCDN node according to the comparison result. According to the method and the device, the technical problem that the prediction capability of the future trend of the PCDN state is limited when the state of the PCDN node is monitored by adopting a timing heartbeat mechanism or a static threshold judgment mode in the prior art is solved.

The invention discloses a privacy computing arrangement method, system and device based on dynamic trust and a medium, and relates to the technical field of data security. The method comprises the following steps: receiving a data processing request, and collecting context data including user trust, environmental risk and data sensitivity; calculating a dynamic trust score based on the context data, and dynamically selecting a target privacy calculation technology according to the score; scheduling tasks based on the selected technology and deploying a guard agent in the computing container; running state data is periodically collected through a guard agent to serve as heartbeat for verification, and if verification fails, key interruption and memory erasing and fusing tasks are triggered; after calculation is completed, packaging a result and an access control strategy into a security capsule; and in response to the capsule opening request, decrypting the rendering result in the memory after verifying that the terminal environment conforms to the strategy. According to the method, full-life-cycle dynamic control from calculation request to result use is realized, and the problem that authorization is out of control is solved.

The invention discloses a data retrieval method and system for a distributed database, and relates to the technical field of data storage and data retrieval, and the method comprises the steps: obtaining the operation state data periodically sent by each node through a heartbeat signal collection interface of the nodes of the distributed database, carrying out the time sequence analysis for the signal interval fluctuation, and obtaining the operation state data; if it is detected that the node signal interval exceeds a preset threshold value, marking the node as an abnormal node, determining an abnormal node list, and recording final task metadata analysis information of the abnormal node; according to the abnormal node list, screening out a node with the lowest current load from a standby node pool; according to the data retrieval method and system for the distributed database, quick self-healing, stable operation and continuous response of a distributed database retrieval service in a complex network environment are achieved, and the reliability of the system and the retrieval experience of a user are fundamentally improved.

The invention provides a WebSocket communication reconnection recovery method and related equipment. The method comprises the following steps: managing the life cycle of WebSocket connection through a finite-state machine; the method comprises the following steps: monitoring a WebSocket connection state by adopting a dual-channel heartbeat mechanism, configuring a client to send a PING frame of a current timestamp at a dynamic heartbeat interval for an uplink channel, and configuring a server to return a PONG frame of the current timestamp within a preset response time for a downlink channel; when the connection is interrupted, non-sent messages are cached through a non-standard LRU strategy combined with time sequence priorities, and reconnection interval time is calculated based on an exponential back-off algorithm; and finally, the WebSocket connection is reconnected based on the reconnection interval time, and the unsent message is retransmitted through a non-standard LRU strategy after the connection is recovered. According to the method, a finite-state machine is used for managing the WebSocket, a two-channel heartbeat mechanism and exponential backoff are used for rapid reconnection, a non-standard LRU strategy is used for guaranteeing that key information is not lost, and the defects that original WebSocket management is disordered, and connection is not reliable are overcome.

A method for assessing a state of stress of an individual when the individual is contacting a receiving surface of a device comprising a pressure sensor comprising a plurality of elemental gauges, each elemental gauge having a gauge factor of at least 10, the method comprising acquiring and digitizing each signal delivered by each elemental gauges of the pressure sensor each signal comprising a pseudo-periodic part, exploring the signal and detecting patterns corresponding to heartbeats, measuring an Inter-Beat interval and recording in a heartbeat timestamped file each Inter-Beat Interval, from the heartbeat timestamped file computing at least 3 stress indices and categorizing the state of stress of the individual based on the at least three indices and a stress assessment program implementing a trained algorithm, among an increasing stress, a decreasing stress and a neutral state.

The invention relates to a working method of a vehicle control system of a redundant electrical architecture, belongs to the technical field of redundant control systems, and solves the problem that an existing control system is poor in reliability. The method provided by the invention comprises the following steps: during starting, the main controller is defaulted to be an effective controller in the controller group with the backup, the hot backup controller monitors whether the main controller is in an abnormal state or not through a heartbeat signal, a fault signal and a first verification signal of the main controller, and if the main controller is in the abnormal state, the main controller is controlled to be powered off; the hot backup controller is switched to an effective controller; the cold backup controller monitors whether the hot backup controller is in an abnormal state or not through a fault signal, a heartbeat signal and a second verification signal of the hot backup controller; if the hot backup controller is in the abnormal state, the hot backup controller is controlled to be powered off, the control mode of the cold backup controller is activated, and the cold backup controller is switched to the effective controller. According to the invention, the reliability of the system is improved through effective arbitration of the effective controller.

The invention discloses an unmanned aerial vehicle multi-technology fusion intelligent control method. The method comprises the following steps: establishing serial port communication between an airborne terminal and an unmanned aerial vehicle; the airborne terminal acquires model information by receiving a heartbeat packet actively sent by the unmanned aerial vehicle, and switches to a corresponding control protocol according to the model information for controlling the unmanned aerial vehicle; and the airborne terminal is used for dynamically monitoring the signal quality of the communication link and adaptively switching the optimal communication link. According to the intelligent control system and method provided by the invention, intelligent switching can be performed according to indexes such as signal strength, delay and stability, and an early warning value is set to deal with a sudden communication loss problem, so that the communication continuity and the data transmission reliability of the unmanned aerial vehicle in a task execution process are ensured.

The invention discloses a main control election method for multiple micro-control units and a related device, and relates to the technical field of information analysis, and the method comprises the steps: calculating a priority value of each micro-control unit based on a starting timestamp, an internal temperature, a central processing unit utilization rate and voltage stability; each micro-control unit broadcasts a current voting round and proposes a master control identity identification number and a priority value so as to perform priority evaluation on each micro-control unit by utilizing a triple comparison rule; performing proposal updating based on a priority evaluation result to obtain proposal updating information; determining a main control unit and a plurality of standby control units by using a preset agreement mechanism based on the proposal update information; and the main control unit broadcasts a heartbeat frame, each standby control unit judges whether the main control unit has a fault based on the heartbeat frame, and if the main control unit is judged to have the fault, the main control election is performed again. According to the method, the consistency and reliability of the master control election process are guaranteed, and meanwhile self-judgment and self-recovery after the master control fails are achieved.

The invention relates to the technical field of physiological signal processing, and discloses a millimeter wave radar multi-dimensional physiological feature decoupling heart failure early warning system and method, and the method comprises the steps: configuring a millimeter wave radar to transmit a dual-beam frequency modulation continuous wave signal, collecting human body reflection echoes, and generating a multi-channel original digital signal matrix; generating a chest region and acra region phase signal, an overall reflection signal amplitude sequence and an overall phase drift signal after spatial isolation enhancement through distance-Doppler combined processing; decoupling to obtain a beat-by-beat heartbeat interval sequence, a pulse wave transmission time sequence and a daily net body fluid variation sequence; obtaining a rule engine risk level and a machine learning early warning sign, and determining a final risk assessment level through fusion decision; synchronous high-precision collection and decoupling of non-contact multi-dimensional physiological parameters are achieved, and accuracy and specificity of heart failure decompensation early warning are improved through double-layer model fusion.

The invention provides an equipment state detection method and device, electronic equipment and a storage medium, and relates to the technical field of smart home, and the method comprises the steps: obtaining the equipment activity of equipment and the current network quality, and then carrying out the dynamic adjustment of a sending period according to the equipment activity and the current network quality, the method comprises the following steps: acquiring a target sending period corresponding to equipment, sending heartbeat packets according to the target sending period, if monitoring that the number of times that the equipment continuously loses the heartbeat packets reaches a preset threshold value, acquiring multi-dimensional state data corresponding to the equipment, judging whether the equipment is offline or not according to the multi-dimensional state data, and sending the heartbeat packets to the equipment when the equipment is offline. According to the method and the device, the target offline reason corresponding to the device is determined, so that intelligent self-adaption of a detection strategy is realized, the detection efficiency and the resource utilization rate are improved, the offline state of the device is accurately identified, the accuracy and the reliability of state judgment are improved, accurate root cause positioning is realized, and the self-adaption capability of fault diagnosis is enhanced.

The invention discloses a weighing error compensation method for intelligent weighing integrated equipment, and particularly relates to the technical field of weighing measurement, and the method comprises the following steps: recognizing a weighing scene based on real-time working condition data, and starting a preset error compensation model; collecting sensor input data and a compensation value in real time and generating a system health state triple by embedding a meta-cognitive detection mechanism; a heartbeat timeout event is triggered by a triple exception, and a protection mechanism is started when a frequency threshold is exceeded; extracting a historical algorithm version and matching an optimal version for degraded operation; monitoring the state of the triple during the operation of the target historical version, and determining whether to recover the original model or send out early warning; according to the method, the weighing scene is recognized in real time, the preset error compensation model is started, the input data and the compensation value are monitored in combination with the meta-cognitive detection mechanism, the system health state triple is constructed, and the protection mechanism is triggered based on the heartbeat timeout frequency, so that self-adaptive, high-precision and high-safety control of error compensation is realized.

The invention provides a distributed system election method and device, electronic equipment and a storage medium, and relates to the technical field of servers, whether to re-elect or not is determined by monitoring the heartbeat of a leader node, and a broadcast message of a candidate node containing a tentative number, a transaction identifier, a load score and a node unique identifier is obtained; and evaluating the candidate nodes based on a preset weight and voting, determining a target leader node according to voting data, and determining the target leader node as a leader node after the target leader node sends a message and other nodes are converted into following nodes. Therefore, the problems of low fault recovery speed, low election efficiency, poor data consistency, network environment adaptability and the like during node election in the prior art can be solved, and the technical effects of improving the node fault recovery speed in the distributed system and improving the election efficiency are achieved.

The invention relates to a charging control method and device, a control unit, a vehicle and a storage medium. The method comprises the following steps: determining a main control unit and at least one preparation host from each inverter in an inverter cluster; determining the inverters except the main control unit and each standby host as slave units; on the basis of the target preparation host, if it is monitored that the heartbeat packet of the main control unit is lost and it is monitored that a response signal of the main control unit is not received within a preset time period, determining that the target preparation host is a new main control unit, and determining a new target preparation host; determining predicted load information corresponding to the slave unit according to the driving data of the vehicle in the current time period; generating a power distribution instruction of the slave unit according to the predicted load information corresponding to the slave unit; and based on the new main control unit, the power distribution instruction of the slave unit is sent to the slave unit. According to the invention, the battery charging power utilization rate can be improved, and the efficient operation of the vehicle-mounted parallel inverter system is ensured.

The invention provides a dual-redundancy control method, device and system for a gas turbine, electronic equipment and a medium, the position of a valve is monitored through a plurality of sensors, position signals are transmitted to two servo cards, and each servo card independently executes first-stage optimization, screens out the most reliable sensor feedback signal and sends the signal to a controller. And the controller further performs second-stage optimization, so that the accuracy of the valve position information finally fed back to the control system is ensured. The servo valve is provided with a redundant coil, the redundant coil and the two servo cards form a control loop respectively, and the states of the two servo cards are mutually monitored through analog quantity heartbeat signals. Only when it is confirmed that the servo card of the opposite side operates normally, the servo card enters the bypass mode, and meanwhile the fault state is fed back to the controller. And the controller immediately adjusts the parameters of the other servo card so as to ensure the stability of the position of the valve. According to the design, the reliability and the fault-tolerant capability of the control system are remarkably improved, and safe and efficient operation of the gas turbine is guaranteed.

This invention discloses a fire-fighting location and communication method and system that integrates multi-source sensing data, relating to the fields of fire-fighting location technology and communication technology. The invention significantly suppresses time drift at each node through a time calibration mechanism within the topological neighborhood. The corrected timestamp set generated by iterative correction ensures high consistency in cross-node timing, thereby improving the synchronization and reliability of multi-source data fusion. A dynamic generation strategy based on local gradients and communication status heartbeat signals enables the broadcast period to adapt to link fluctuations, improving network robustness in scenarios with thermal interference or smoke obstruction. Furthermore, the location and communication status table uniformly quantifies the location information interval, movement trend, and communication availability level, enabling synchronous optimization of location inference and communication routing selection, significantly improving the location accuracy and communication continuity for firefighters in complex environments.

The application discloses a kind of mobile equipment online examination methods, comprising: the behavior information of triggering at least two events in first event, second event, third event;According to two behavior information, output warning information;Examination program triggers pause event, and examination program is switched to background suspension operation;Heartbeat packet is sent to server;According to whether success of heartbeat packet reception, determine the data submission state of examination program;The data indicated by the input operation of user is sent to server and is stored in local answer database with encryption;When current examination program state is submission failure, supplement in local answer database is identified;Login current examination program, and the data in local answer database is uploaded according to version number.The application not only realizes full coverage monitoring to online examination cheating behavior, but also improves recovery success rate in abnormal submission scene.The application also discloses a system, electronic equipment and storage medium for implementing the above method.

The application discloses a kind of based on neural network's acoustic user identification and heartbeat monitoring earphone system and method, the system includes the earphone with microphone, acoustic analog-digital conversion equipment, the back-end service equipment at least includes: data acquisition module is used for acoustic signal transmission and reception;Data processing module is used to obtain preprocessed received signal;Human ear canal feature extraction module is used to extract MFCC feature and ear canal feature based on transfer function;User identity identification module is used to obtain trained neural network model;Heartbeat information extraction module is used to obtain processed phase information;Self-interference elimination module obtains phase signal not containing direct path interference;Heartbeat frequency calculation module is used to obtain heartbeat frequency.The application can reduce the cost of identity recognition and heartbeat monitoring, and robustness, high robustness.

The application discloses an improved method, system and medium for improving the reliability of wireless communication of a power distribution terminal. The method comprises: stopping the main station from sending services such as total calling, time, heartbeat, request link state and link test during remote control operation, and resuming the process after the remote control process is completed; adding remote control conditions for local discrimination by the power distribution terminal; extending the discrimination duration of communication timeout; and sending burst remote signaling and burst remote measurement messages occurring within a cycle time by separate packaging in units of cycle time, thereby improving information transmission efficiency. The application is dedicated to low signal areas and is compatible with IEC60870-101 protocol, and solves the low remote control success rate caused by hardware problems by using software modification; the terminal discriminates remote control conditions when the main station performs remote control operation, and effectively solves the remote control failure problem by adding a put-off constant value.

The invention belongs to the technical field of finite element analysis and reinforcement learning, and particularly relates to a distributed reinforcement learning and finite element simulation cooperative training system and method.The distributed reinforcement learning and finite element simulation cooperative training system comprises a center scheduler, M FEA servers, N RL computing servers and a high-speed network connecting the center scheduler, the FEA servers and the RL computing servers; the central scheduler is used for receiving heartbeat packets, hardware resource utilization rates and abnormal alarm data periodically sent by the FEA servers and the RL computing servers; according to the hardware resource utilization rate and the abnormal alarm data, based on a dynamic heterogeneous resource scheduling strategy, an FEA simulation result is sent to the selected RL calculation server, and simulation parameters are sent to the selected one or more FEA servers. Through hardware resource decoupling of the FEA server and the RL calculation server, the calculation time of collaborative optimization of the FEA and the RL is shortened, and the calculation efficiency of collaborative optimization of the FEA and the RL is improved. And hardware resources are optimally utilized.

This invention relates to a high-density sensory mattress, comprising a mattress body, flexible tactile sensors, and a circuit. The mattress body has recessed grooves in which multiple flexible tactile sensors are disposed. The flexible tactile sensors are characterized by comprising an upper insulating layer, an upper electrode layer, a middle pressure-sensitive layer, a lower electrode layer, and a lower insulating layer. The middle pressure-sensitive layer is located between the upper and lower electrode layers. Both the upper and lower electrode layers consist of several evenly spaced linear electrodes. The circuit comprises a signal acquisition unit and a host computer. The signal acquisition unit uploads the acquired signals to the host computer via Bluetooth communication. This high-density sensory mattress can not only analyze the user's sleeping posture but also obtain the user's breathing and heartbeat signals through changes in pressure values, providing data support for assessing the user's sleep quality.

The invention discloses a carbon integral management method and an air purification system, and relates to the technical field of air purification. The carbon point management method comprises the following steps: in response to a purification starting instruction, periodically sending an encrypted heartbeat packet to a circuit control board; wherein the circuit control board is used for accumulating the running time length of the air purifier when it is detected that the sending time interval of the encrypted heartbeat packet is not larger than a first preset time interval; the operation duration of the air purifier is obtained, and the carbon integral obtained by the user is dynamically calculated; the calculated carbon points are synchronized to a user account, and an interaction panel is controlled to display the carbon point balance of the user; and in response to the exchange request instruction, freezing and deducting a carbon point matched with a prize in the user account according to a carbon point and a prize exchange rule preset by the background server, generating a prize issuing instruction, and sending the prize issuing instruction to the background server to execute a prize exchange process. According to the invention, the accuracy and credibility of carbon integral calculation are improved, and the carbon integral participation enthusiasm of the user is improved.

The invention discloses an intelligent device positioning method and system, and relates to the technical field of intelligent device positioning, and the method comprises the following steps: S1, an equipment end and a server end establish a long connection; s2, the device side periodically collects light heartbeat data, packages the light heartbeat data, encrypts the light heartbeat data and sends the light heartbeat data to the server side; s3, the server receives and decrypts the lightweight heartbeat data; s4, the server side judges whether the equipment side moves or not based on the lightweight heartbeat data; s5, if the server side judges that the equipment side moves, the server side sends a real-time positioning request to the equipment side and stores real-time positioning data uploaded by the equipment side; and if the server side judges that the equipment side does not move, the server side reuses the latest positioning data. According to the positioning method and system of the intelligent device, the energy consumption of the device end is reduced, the waste of mobile network bandwidth is reduced, and the waste of storage resources of the server end is reduced.

The present disclosure relates to the technical field of automatic intelligent auxiliary detection of electrocardiogram, and proposes a self-supervised neural network learning heartbeat classification method and system based on pre-labeling, which comprises the following steps: preprocessing the acquired electrocardiogram data to obtain heartbeat data; performing time-frequency analysis on the acquired one-dimensional heartbeat data to convert it into a two-dimensional time-frequency graph; inputting the converted two-dimensional time-frequency graph into a trained self-supervised learning network model to classify the heartbeat data and obtain a classification result; the self-supervised learning network model is trained in combination with the SimCLR method and the clustering method, so that the loss function term changes from one item to two items, the learning effect is strengthened, and the classification accuracy of the heartbeat data can be improved.