181 results about "Sleep waking" patented technology

The invention discloses an Internet of Things equipment power consumption management method and system based on big data, and relates to the technical field of equipment power consumption management. The Internet of Things equipment power consumption management method and system based on big data specifically comprises the following steps: S1, equipment classification; s2, power consumption evaluation and modeling; s3, implementing a dormancy awakening strategy; s4, strategy design and dynamic adjustment; through careful classification of the data center server and the Internet of Things equipment, power consumption characteristics of various types of equipment can be more accurately understood and managed. And secondly, through power consumption evaluation and modeling, an accurate power consumption model is established, and a power consumption threshold value is set, so that real-time monitoring and effective management of power consumption are realized. In addition, the implementation of the sleep wake-up strategy avoids invalid sleep of the Internet of Things equipment, and improves the energy utilization efficiency. The dynamic adjustment strategy not only realizes load balancing, but also dynamically adjusts the power consumption according to the task priority and the load condition, so that the overall power consumption is further reduced.

The invention relates to the technical field of SoC main control chips, and discloses a deep sleep wake-up control method and system for a multimode SoC main control chip. The method comprises the following steps: acquiring voltage and current data and temperature distribution data of each functional module of a multi-mode SoC main control chip under different environments and operation conditions EOC to obtain a chip monitoring data set; constructing a functional module topological graph and mapping the functional module topological graph into potential features to obtain deep sleep state criteria of each functional module; establishing a hierarchical Bayesian model, and identifying the state transition probability and EOC influence factors of each functional module to obtain a combination scheme of the deep sleep functional modules; determining a collaborative sleep control sequence; a hierarchical Bayesian model is input, a wake-up voltage and a clock sequence are generated, power consumption response of each function module is monitored in real time through a dynamic graph neural network, a safe wake-up control result is output, mutual interference among the function modules is reduced, and the overall power consumption management efficiency of a chip is improved.

The invention provides a sleep wake-up circuit. The circuit comprises a wake-up detection module, a trigger module, a power switch module and a micro control unit (MCU), the MCU comprises a system normal working module. The trigger module is used for outputting a first level or a second level through the second pin according to the state of the MCU; and outputting a trigger signal through a fifth pin according to the detection result of the wake-up event. And the power switch module is used for controlling whether the power supply can supply power to the system normal working module or not according to the level output by the second pin and the trigger signal. The embodiment of the invention can be applied to the electronic equipment of the vehicle, and the endurance time of the battery can be greatly prolonged.

According to the TENG-based self-powered sensing system and the sleep wake-up method thereof provided by the invention, through cooperation of the composite nano generator and the low-power-consumption Internet of Things technology, energy can be effectively collected in an all-weather manner, and acceleration data can be collected; the composite nanometer generator is formed by compactly combining a contact separation type friction nanometer generator and a solar cell, the space utilization rate is improved, and sunlight and mechanical vibration are used as energy sources. The friction nanometer generator is designed in a spring supporting mode, so that the durability is improved; the signal conditioning circuit is divided into two parts, one part is used for collecting and storing energy so as to realize self power supply; the other part is used for transmitting information carried by vibration so as to realize wake-up triggering of the low-power-consumption acceleration sensor; the system can realize self-powered and all-weather vibration monitoring, can be gradually applied to the fields of bridge health monitoring, air conditioner fan monitoring, iron tower monitoring and the like, and lays a solid foundation for realizing an IOT-based digital building technology in the future.

The invention discloses a sleep apnea two-stage detection method, and relates to the field of respiration detection, and the sleep apnea two-stage detection method comprises the following steps: collecting a trachea sound signal of sleep respiration of a user, and generating a Mel spectrum of the trachea sound signal; wherein the trachea sound signal comprises a breathing audio signal and a heart sound signal; constructing a sleep-awakening detection model based on a VGG16 network, and calculating the sleep duration of the user; performing sleep apnea section detection on the Mel spectrum by adopting a longitudinal box algorithm AV-Box; extracting S1 peaks and S2 peaks of the potential sleep apnea section, and calculating an RR interval according to the time interval of the adjacent S1 peaks; acquiring statistical characteristics of the RR interval, and performing apnea detection by using a support vector machine (SVM) according to the statistical characteristics; and calculating the sleep apnea hypopnea index AHI of the user according to the sleep apnea times and the sleep duration counted according to the apnea detection result. Aiming at low diagnosis precision in a sleep apnea detection method based on a sound signal in the prior art, the detection precision is improved.

The invention belongs to the technical field of crossing of artificial intelligence and computer system architecture, particularly relates to a computing power center equipment power supply intelligent system of a knowledge graph, and aims to solve the problem of low energy efficiency caused by extensive power supply management, unbalanced energy consumption and lagged load response. The system comprises a task analysis module, a dynamic load prediction module, a multi-source power supply scheduling module, an equipment-level power supply control module and a feedback optimization module, through load prediction and multi-source power supply cooperative scheduling driven by task semantics, voltage and current dynamic adjustment and sleep wake-up control are achieved, and a strategy is optimized online based on operation feedback. The scheme improves energy efficiency, equipment life and system stability.

The invention discloses a vehicle sleep wake-up automatic testing method, device and equipment and a storage medium, and relates to the technical field of vehicle-mounted testing, and the method comprises the steps: monitoring the communication state of a vehicle, judging whether a backbone network, a plurality of sub CAN network segments and a plurality of sub LIN network segments enter a sleep mode or not, and when the backbone network, the plurality of sub CAN network segments and the plurality of sub LIN network segments enter the sleep mode, starting the sleep mode; and sending a wake-up message, controlling a vehicle power supply to be powered on and starting the vehicle when the vehicle is waken up and preset operation time passes, obtaining wake-up data, and analyzing the wake-up data to obtain a test report. Through monitoring vehicle communication, each network segment is awakened and data is analyzed after entering a dormancy state, automatic testing of multi-subnet collaborative management under an SOA architecture is realized, and the testing efficiency and accuracy are improved.

This application discloses a BMS sleep wake-up circuit and method, a BMS, and an electric device. The BMS sleep wake-up circuit is provided with an enabling circuit. When a charging device is plugged in, the wake-up chip can be enabled through a first enabling signal to activate to wake up a BMS, and a control circuit outputs a self-locking signal, so that the wake-up chip keeps waking up the BMS. Additionally, after being activated, a mode in which the wake-up chip is enabled to activate is changed to a mode in which the wake-up chip is enabled through a second enabling signal to activate to wake up the BMS, so that when the charging device remains plugged in, after the self-locking signal is canceled, the wake-up chip is turned off, allowing the BMS to enter a sleeping state.

Embodiments of the present disclosure provide a secure channel sleep wake-up method, apparatus and device. The method comprises: when a node 1 is awakened from a sleep state, obtaining stored IP communication information communicating with a node 2, performing message encapsulation by using the IP communication information to obtain a first message, and sending the first message to the node 2; the node 2 obtaining the IP communication information and a key updating request message from the first message, and generating a second key according to information comprising a basic key corresponding to a basic key identifier in the key updating request message and a first random number generated by the node 1 and in combination with a second random number self-generated by the node 2; the node 1 obtaining the IP communication information and a key updating response message, and generating the second key and the second random number.

The embodiment of the invention discloses a sleep peptide and differential metabolite detection method for caenorhabditis elegans, belongs to the technical field of organism metabolism, and aims to research sleep-awakening key metabolite of caenorhabditis elegans and a regulation mechanism of the sleep-awakening key metabolite. According to the sleep peptide for caenorhabditis elegans, the sleep peptide is an F4 monomer as shown in SEQ ID NO: 1. Compared with the prior art, the sleep and awakening process of the caenorhabditis elegans under the intervention of the goat milk-derived sleep peptide is analyzed through a metabonomics technology, the key metabolite for regulating and controlling sleep and awakening is successfully screened out, and a core metabolic pathway related to the key metabolite is disclosed. The application also constructs a metabolite-pathway-target regulation framework, fills the blank of sleep research in the aspect of metabolic regulation, provides a scientific basis for a sleep intervention strategy based on metabolic regulation, and also lays a foundation for developing metabolic markers of sleep states in the future.

The invention discloses a sleep wake-up method and system for a multi-core heterogeneous product, and the method comprises the steps: enabling a main core to query the number of sleep locks recorded by all heterogeneous cores through inter-core communication after the sleep of the system is triggered, and judging whether to carry out the sleep operation or not according to the number of sleep locks; when the dormancy operation is carried out, the main core sends a dormancy starting notice to all heterogeneous cores; after the main core completes task freezing, the dormancy willingness of each sub-core is checked; the main core performs dormancy on the sub-core needing dormancy, takes over the wakeup interruption of the sub-core needing dormancy, records the wakeup interruption number, updates the clock and power supply resources of the sub-core needing dormancy, and cuts off the power supply of the sub-core needing dormancy; and the main core completes own dormancy action, determines final clock and power supply configuration of the system, provides basic working conditions for the wake-up source, and then the system enters dormancy. According to the method, a solution is provided for resource and event dispute processing and adaptive switching of a dormancy scene when the multi-core heterogeneous chip enters the dormancy state.

The invention discloses a dormancy awakening control device, a chip, a chip single board and a chip dormancy awakening method, and belongs to the technical field of chips. The sleep wake-up control device comprises an OR logic circuit and a latch. The output end of the OR logic circuit is connected with the first input end of the latch; the second input end of the latch is used for receiving a chip overall dormancy signal; the output end of the latch is connected with a first power supply; the first power supply is used for supplying power to the chip; under the condition that the second input end of the latch receives a chip overall dormancy signal, an output signal of the output end of the latch is in a first level state; the output signal in the first level state is used for triggering the first power supply to be powered down and switching to the second power supply to supply power to the sleep wake-up control device and the wake-up units of the physical layers of the ports included in the chip, so that the whole chip is sleep. According to the sleep wake-up control device disclosed by the invention, the overall power-off sleep of the chip can be realized, so that the power consumption of the chip is reduced.

The invention relates to the field of sleep medicine, in particular to a wearable monitoring system for sleep-awakening rhythm disorder and a method thereof. Comprising a monitoring module, a signal processing module, a signal analysis module and an intervention scheme execution module. The monitoring module is used for acquiring collective acceleration, PPG signals and emotional state data; the signal processing module is used for filtering and down-sampling; the signal analysis module extracts time-domain and non-time-domain features by using a pulse neural network; and the intervention scheme execution module selects a personalized phototherapy and vibration intervention scheme by adopting a Q-learning algorithm according to the feature data. According to the system, through technical innovation and ingenious design, high intelligence and individuation are achieved, the sleep quality and the daytime function of the user are effectively improved, and a new tool and method are provided for sleep medical research.

The invention discloses a heating energy consumption adjusting method and device, equipment and a storage medium, and the method comprises the steps: obtaining continuous multiple historical stroke data and current stroke data, and the historical stroke data is the stroke data of a sleep wake-up cycle; calculating a thermal management power limiting amplitude, a weighted temperature coverage coefficient and a battery heating coverage rate according to the multiple historical travel data and the current travel data, and obtaining a first initial threshold value and a second initial threshold value of thermal management; and then calculating a dynamic heating coefficient and a power limit value according to the current stroke data, the thermal management power amplitude limit, the weighted temperature coverage coefficient, the battery heating coverage rate, the first initial threshold value and the second initial threshold value, and then adjusting the heating energy consumption according to the dynamic heating coefficient and the power limit value. By dynamically adjusting the dynamic heating coefficient and the power limit value, the energy consumption of the whole vehicle at low temperature can be effectively reduced on the basis of ensuring the performance.

This application discloses a BMS sleep wake-up circuit and method, a BMS, and an electric device. The BMS sleep wake-up circuit is provided with an enabling circuit (120). When a charging device (10) is plugged in, the wake-up chip (200) can be enabled through a first enabling signal to activate to wake up a BMS, and a control circuit (130) outputs a self-locking signal, so that the wake-up chip (200) keeps waking up the BMS. Additionally, after being activated, a mode in which the wake-up chip (200) is enabled to activate is changed to a mode in which the wake-up chip (200) is enabled through a second enabling signal to activate to wake up the BMS, so that when the charging device (10) remains plugged in, after the self-locking signal is canceled, the wake-up chip (200) is turned off, allowing the BMS to enter a sleeping state, thereby solving the problem that a BMS cannot enter a sleeping state unless the charging device (10) is unplugged.

The utility model relates to turnout frame size and stock rail transverse displacement monitoring equipment, which comprises monitoring units arranged on the two sides of the bottom of a turnout stock rail in pairs and used for monitoring the frame size of a turnout and stock rail transverse displacement. Comprising a laser displacement sensor used for measuring transverse movement of the stock rail and a vibration sensor used for measuring vertical vibration of the stock rail. The reflecting surface is matched with the monitoring unit and is used for reflecting emitted light of the laser displacement sensor; and the monitoring host is in wireless communication connection with the monitoring unit. Compared with the prior art, the device can measure the size of the turnout frame and the transverse displacement of the stock rail in a static state and in the turnout vehicle passing process in real time, is high in measurement precision, and is not affected by severe weather. The equipment adopts a distributed mode, each monitoring unit works independently, each monitoring unit is powered by a battery, a sleep wake-up mechanism is adopted, and the equipment is in a sleep state when not collecting, so that the power consumption is reduced, and the working time is prolonged.

The objective of the present invention is to provide a brain water monitoring method and apparatus based on near-infrared spectroscopy, which can non-invasively and accurately measure the brain water activity of brain tissue according to sleep-wakefulness and a sleep structure on the basis of near-infrared spectroscopy without injecting a contrast agent, an aqueous solution, or the like to the human body (intravenously or intrathecally). To achieve the objective, the present invention comprises: a calculation step of calculating the fractions of oxidized hemoglobin, reduced hemoglobin, and water on the basis of signals measured by near-infrared spectroscopy; an extraction step of extracting a pure water fraction from the water fraction calculated in the calculation step; and an output step of outputting the water fraction extracted in the extraction step.

The invention relates to a low-power-consumption vibration signal collecting and processing system and method based on a heterogeneous multi-core system. The system comprises an MCU, an MPU, an SOC in-chip interconnection module, a trigger signal module and a data collecting controller module. The SOC in-chip interconnection module comprises a signal routing module, an interruption interconnection module, a shared data address bus and a shared RAM (Random Access Memory); the MCU comprises a first sleep wake-up module, a first data acquisition module, a first data storage module and an MPU wake-up synchronization module; the MPU comprises a second dormancy awakening module, a second data acquisition module, a second data storage module and an MCU acquisition data carrying module; the invention further provides an acquisition method based on the system, the vibration signal acquisition system can be quickly awakened, and loss of signal data in the whole awakening process can be avoided.

Embodiments described herein disclose a method comprising: determining a breathing waveform based on an image signal received from a camera focused on at least a portion of a patient; receiving an observed sleep signal of the patient corresponding to the breathing waveform in time, wherein the observed sleep signal comprises a sleep state tag; tagging each segment of the breathing waveform using a sleep-wake state tag to generate a tagged breathing waveform; generating an input feature matrix by processing the marked breathing waveform; and training a machine learning (ML) model using the input feature matrix.

The invention discloses a train sleep wake-up control method and system, electronic equipment and a storage medium, the train sleep wake-up control method is applied to an AOM, the AOM communicates with an ATP, and the method comprises the steps that a first instruction is received, when it is determined that the train meets preset conditions based on the first instruction, the train enters a target state and forwards the first instruction to an ATP, so that the ATP determines a feedback signal based on the first instruction, and the preset conditions are in one-to-one correspondence with the target states; and when it is determined that the train does not meet the preset condition corresponding to the target state, the target state is quitted, and dormancy awakening control is conducted on the train based on a feedback signal, received in the target state, of a train automatic protection system ATP. The sleep wake-up method is realized through target state conversion, each state function is independent, the structure is clear, and the later development cost is reduced.

The invention relates to the technical field of renewable energy sources, and discloses a renewable energy source-oriented water electrolysis hydrogen production control system and a power distribution method.The system comprises a monitoring unit, a hydrogen pressure monitor, a processing center, an execution terminal and a communication network; renewable energy consumption rate and electrolytic cell power change rate are improved, minute-level fluctuation is adapted, power distribution errors are stably controlled, hydrogen production efficiency loss is avoided, the utilization rate of the electrolytic cell is increased by improving a dynamic priority model, the overall energy efficiency of a cluster is improved, starting and stopping frequency of a basic load group is reduced by a grouping control strategy, and the service life of the electrolytic cell is prolonged. Standby energy consumption is reduced through a sleep wake-up mechanism, the standby power consumption of the system is reduced to rated power, the hydrogen pressure overrun accident rate is reduced through a safety constraint mechanism, and thermal stress damage of the electrolytic cell is reduced and the fault shutdown rate is reduced through temperature deviation protection.

The invention provides a vehicle sleep wake-up management method and device, a medium and electronic equipment. According to the method, the core controller is periodically triggered to enter the semi-dormant state through the external interrupt signal of any temporary wakeup object, and when the external interrupt information of the temporary wakeup object does not meet the preset wakeup condition, the core controller returns to the dormant state from the semi-dormant state. Therefore, the core controller enters the semi-dormant state regularly, and the situation that the core controller is in the dormant state for a long time, so that a battery is aged, damaged and reduced in performance is avoided.

The invention discloses a sleep wake-up method, system and device, a storage medium and a product, and relates to the technical field of computers, the sleep wake-up method comprises the following steps: monitoring the state of a power module, if it is monitored that the state of the power module is a sleep state, performing wake-up countdown based on a preset wake-up time to obtain a remaining wake-up time, wherein the preset wake-up time is sent by the sleep function module through the communication function module; and generating a wake-up signal based on the residual wake-up time, and sending the wake-up signal to a power supply control module, so that the power supply control module controls a power supply to be turned on based on the wake-up signal. According to the method and the device, the problem that wake-up modes in related technologies need to be triggered by external conditions, so that the sleep wake-up test efficiency is reduced can be avoided.

The invention discloses a sleep and wake-up method and device of a multi-core isomorphic chip system and a medium, the system comprises a main core and at least one sub-core, and the main core and the sub-core are provided with corresponding synchronous registers. The method comprises the steps that the main core sends a dormancy instruction, and the main core and the sub-core make dormancy preparation. When dormancy is prepared, if a task execution instruction is received, the main core configures a register of the main core into a parameter value representing dormancy stopping, sends an awakening instruction to the sub-core and makes awakening preparation. After the sub-core receives the wake-up instruction, dormancy is interrupted, wake-up preparation is made, and a register of the sub-core is configured to be a second parameter value representing non-dormancy. And after confirming that the sub-core register is the second parameter value, the main core assigns the own register to the second parameter value, and the system enters an awakening state. According to the embodiment of the invention, sleep wake-up state synchronization among multiple cores can be ensured, and abnormity caused by asynchronous states of the multiple cores is avoided.

The invention discloses a patient sleep awakening three-classification monitoring method and device based on a machine learning model, equipment and a medium, and the method comprises the steps: collecting acceleration data and activity counting and heart rate data of a subject, and carrying out the preprocessing of the collected data; extracting data features based on the preprocessed data, wherein the data features comprise a motion feature, a heart rate feature and a clock proxy feature; the extracted data features are input into a classification model, prediction state data of each Epoch are output, each row in the prediction state data comprises an Epoch starting timestamp, a real sleep staging label and a three-classification prediction result of the model, and therefore the prediction state data of each Epoch can be obtained. According to the method, the three-classification prediction accuracy of awakening, non-fast eye movement sleep and fast eye movement sleep can be effectively improved, and the method can be widely applied to sleep monitoring.

The invention provides a sleep awakening method and system for a mechanically marshaled train supporting multi-manufacturer vehicle-mounted equipment. The mechanically marshaled train is marshaled by a plurality of unit trains supporting the multi-manufacturer vehicle-mounted equipment. Each unit train is provided with a TCMS, and a first end and a second end are respectively provided with a VOBC and an AOM; the mechanical marshalling train is in a dormant state; the method comprises the steps that after a mechanically-grouped train receives an awakening command output by any AOM, the mechanically-grouped train is powered on; each VOBC and each TCMS finish self-inspection respectively; each VOBC is determined to be in a mechanical marshalling state according to the electric hook coupling state and the mechanical hook coupling state; each TCMS completes three-layer networking; the leading vehicle establishes cross-vehicle communication with the following vehicles; and if the mechanical marshalling train determines that the awakening state is successful awakening through the awakening test, the mechanical marshalling train confirms that the awakening is successful. By means of the method, the dormancy awakening problem of the train supporting mechanical marshalling of vehicle-mounted equipment of different manufacturers is solved.

Implementations described herein disclose a method including determining, based on an image signal received from a camera focused on at least a portion of a patient, a respiratory waveform, receiving an observed sleep signal of the patient temporally corresponding to the respiratory waveform, the observed sleep signal including sleep state labels, labeling various segments of the respiratory waveform using sleep-wake state labels to generate a labeled respiratory waveform, generating an input feature matrix by processing the labeled respiratory waveform, and training a machine learning (ML) model using the input feature matrix.

The invention discloses a battery management system, a battery system and electric equipment. When charging equipment is connected, the enabling circuit of the battery management system can generate a first enabling signal according to a first level signal provided by the charging equipment to enable the first chip to be started so as to supply power to the second chip, and when the second chip is started, the battery management system is awakened to enter a normal working state; the second chip outputs a self-locking signal after being started, so that the first chip keeps starting; the second chip can also stop outputting the self-locking signal to close the first chip when receiving a dormancy signal generated when the gun is pulled out or a dormancy signal generated by the system when the gun is not pulled out, so that the battery management system can enter a dormancy state, the problem that the battery management system cannot enter the dormancy state when the charging equipment is not pulled out is solved, and the charging efficiency is improved. And whether the edge-triggered first chip or the level-triggered first chip can meet the requirement that the battery management system can be dormant when the charging equipment is kept connected, so that the lead-acid consumption of the battery is reduced.

The invention discloses a vehicle-mounted intelligent cabin log system and a vehicle-mounted intelligent cabin log management method, and relates to the field of vehicle machine logs, and the vehicle-mounted cabin system comprises an MCU and an SOC; the MCU runs an AutoSAR real-time operating system and is responsible for CAN signal receiving and transmitting, communication diagnosis, sleep awakening and power management of the whole vehicle; the SOC runs dual systems through a Hypervisor virtual machine monitoring program, and the dual systems comprise an instrument system and a central control system; wherein the instrument system end runs a QNX / Linux system to realize quick response, and the central control system end runs an Android system to process intelligent interaction and cockpit entertainment functions; wherein the cabin log system is established based on the vehicle-mounted cabin system of the vehicle infotainment device 1 and the vehicle-mounted cabin system of the vehicle infotainment device 2; the cabin log system is used for log generation and storage of the vehicle-mounted cabin system of the vehicle infotainment device 1 and the vehicle-mounted cabin system of the vehicle infotainment device 2.

A vehicle communication system includes a gateway device. The gateway device is configured to receive electric power from a battery of a vehicle, relay communication among multiple communication lines coupled to respective electronic control units, perform, when receiving a signal through any of the communication lines, a sleep wake-up operation by transmitting a wake-up request signal to switch one or more of the electronic control units to be woken up from a sleep mode to a wake-up mode, and refrain from transmitting the wake-up request signal in a case where the gateway device determines in view of electric power consumption of the battery that transmission of the wake-up request signal is unacceptable.