10031 results about "Low power dissipation" patented technology

The invention discloses a data center intelligent operation and maintenance method and system based on an industrial internet of things, belongs to the field of image processing calculation, and aims to solve the problems of privacy protection deficiency, serious manual dependence and weak energy efficiency and safety. Full-link dynamic optimization is realized through an edge calculation layer and an adaptive clustering network, edge nodes are integrated with a wavelet transform noise filtering technology, dynamic denoising is performed on multi-band sensor signals of temperature, vibration, current and the like, heterogeneous device time sequence data are aligned in combination with a dynamic time warping algorithm, sampling frequency differences of multiple devices are eliminated, and the multi-band sensor signals are obtained. A weight formula is put forward, a cluster head is dynamically elected based on node residual energy, data similarity and a load coefficient, a transmission path of a high-delay area is optimized in combination with a multi-hop routing protocol, the packet loss rate and the signal strength are evaluated in real time, redundant coding is started for a high-packet-loss link or the high-packet-loss link is switched to a low-power-consumption mode. And synchronizing the dynamic topology state with the digital twin platform through an open platform communication unified architecture protocol.

Various embodiments herein provide techniques related to a main receiver of a user equipment (UE) and a wake-up receiver (WUR) of the UE. In the embodiments, the WUR receives a low-power wake-up signal (LP-WUS) from a base station. Based on the LP-WUS, the WUR may be configured to wake-up the main receiver of the UE, wherein the UE identifies received configuration information including duty cycle parameters and detects the LP-WUS based on the configuration information, and wherein the UE sets a state of the wake-up receiver based on an RRC state of the main receiver.

The invention relates to the technical field of Internet of Things management, in particular to a lightweight Internet of Things management system based on a star flash protocol stack, which comprises a plurality of modules such as a star flash protocol communication module, a dynamic topology management module and a resource virtualization module. The satellite flash protocol communication module realizes low-power-consumption efficient connection of equipment; the dynamic topology management module optimizes the network topology by using an improved multi-agent Q learning algorithm; the resource virtualization module realizes accurate resource allocation through a weighted bipartite graph matching model; the safety protection module adopts an attention mechanism to detect abnormities and guarantee data safety; the edge co-processing module realizes intelligent task unloading by means of deep reinforcement learning; all the modules cooperatively work under the overall planning of the cross-module coordination controller, and the information barrier is broken. According to the invention, the problems of high communication energy consumption, poor resource allocation, weak security protection, low task processing efficiency, insufficient module collaboration and the like of a traditional Internet of Things system are effectively solved, the system communication efficiency, the resource utilization rate and the security are remarkably improved, and the task processing capability is enhanced.

An object tracking device, such as may be attached to a trailer to track movements of the trailer, may have various communication capabilities, such as cellular / LTE, Wi-Fi and GPS, which each have varying power requirements. A power optimization routine determines which communications should be performed to conserve battery while also providing frequent location updates. The routine determines if another plugged in tracking device is within low power Bluetooth (BLE) range and, if so, communications location via that device. If not, a Wi-Fi scan is performed and a lookup table is consulted for the corresponding location of any identified Wi-Fi access points. If location data cannot be found for an identified Wi-Fi access point, GPS location of the device is determined and the lookup table is updated to include the GPS location of the Wi-Fi access point.

The invention relates to a dynamic adjustable multi-core cooperation mechanism and power consumption optimization method and system based on an RISC-V architecture. The method comprises the following steps: 1) initializing a dynamic adjustable multi-core cooperation system; comprising the steps that a hardware module is initialized, and the hardware module comprises a high-performance core P-core, a low-power-consumption core E-core, a hardware scheduling unit HSU and a power management unit PMU; loading a task queue, and marking task characteristics; 2) core state monitoring; comprising the following steps: an HSU monitors a core state; the power management unit PMU monitors voltage and frequency; 3) dynamic task scheduling; comprising the steps that task characteristics are allocated to a high-performance core P-core or a low-power-consumption core E-core; the idle core enters a low-power-consumption mode; and 4) self-adaptive energy saving is realized, and task migration is carried out. And through a dynamic task scheduling and energy-saving optimization algorithm, the flexibility and efficiency of the RISC-V multi-core processor are remarkably improved.

Systems and methods are described for transmitting broadcasts by Peripherals, receiving the broadcasts by Centrals, and communicating with a Backend by Centrals. Specifically, a Peripheral may generate and transmit an encrypted broadcast packet to a Central, the Central may transmit the encrypted observation information to the Backend, which may decrypt the broadcast packet. Additionally, a Central may transmit a request for authorization to connect to a Peripheral to the Backend. If authorized by the Backend, the Central may connect to the Peripheral. Further, a Central may receive a plurality of broadcasts over a period of time. The Central may store information about the broadcasts and, at the conclusion of the period of time, transmit the information about the broadcasts and the last-received broadcast to the Backend.

The invention relates to the technical field of unmanned aerial vehicles, in particular to a low-power-consumption star flash control module applied to an unmanned aerial vehicle and a dummy pilot control method. The method comprises the following steps: acquiring an original control instruction of a real flying hand, and converting the original control instruction into an encrypted pulse signal containing a dynamic key; fusing a frequency spectrum camouflage signal simulating the environment background of a dummy pilot into the encrypted pulse signal, and then transmitting the encrypted pulse signal to the dummy pilot in a self-adaptive frequency hopping mode; synchronously analyzing the dynamic key at a dummy flying hand end and stripping the frequency spectrum camouflage signal to generate a virtual control track matched with the real operation behavior characteristics; and reversely modulating an actual response signal of the unmanned aerial vehicle based on the virtual control track, so that the unmanned aerial vehicle executes an action and forms dynamic error compensation with the virtual control track. According to the invention, a real flying hand can be effectively protected from electronic reconnaissance positioning and attack of an enemy, and the concealment is improved.

Various embodiments herein provide techniques related to transmission of a wake-up signal (WUS) from a base station to a user equipment (UE). In embodiments, the WUS may be received by a wake-up receiver (WUR) of the UE. Based on reception of the WUS, a main receiver of the UE may exit from a deep-sleep state or an off state. Other embodiments may be described and / or claimed.

The invention relates to the technical field of electrical equipment analysis, and particularly discloses an electrical equipment operation state monitoring system and method, and the method comprises the steps: the system is deployed at an electrical equipment site, integrates a low-power-consumption processor and an FPGA acceleration module, and is used for collecting multi-source data in real time, and executing lightweight model calculation and local early warning; and storing full data and operating a global analysis model, and communicating with the edge computing node to realize data collaborative analysis. According to the electrical equipment operation state monitoring system and method provided by the embodiment of the invention, through edge computing lightweight deployment, data preprocessing and local early warning are completed on the equipment site, and high efficiency of monitoring response and low-power-consumption hardware adaptation are realized; by means of an electromagnetic interference dynamic evaluation module, an acquisition strategy is intelligently adjusted, noise is suppressed, the reliability of multi-source data is guaranteed, the efficiency, precision and intelligent capability of electrical equipment state monitoring are remarkably improved, and technical support is provided for reliable operation of power system equipment.

The invention discloses a clock tree synthesis method and related equipment, and the method comprises the steps: dividing a plurality of time sequence units which need to receive clock signals from a clock source into clustering clusters of different levels, and enabling the load capacitance of each clustering cluster of the same level to be balanced; according to a hierarchical sequence of clusters starting from the clock source, taking each cluster as a node of a clock tree, recursively constructing the clock tree, and inserting a target buffer at the position of each node for driving the corresponding node; analyzing the delay and offset of the constructed clock tree to obtain an analysis result; and if the analysis result indicates that the delay and offset of the clock tree do not meet the preset constraint condition, adjusting the clock tree until the adjusted delay and offset of the clock tree meet the preset constraint condition. According to the technical scheme, power consumption and offset can be effectively reduced, calculation efficiency and design reliability are improved, and the method is suitable for high-performance chip design under the advanced technology.

The invention discloses an electromagnetic ultrasonic thickness detection method and system based on a miniaturized low-power-consumption internet of things, and the method comprises the steps: carrying out the parameter optimization processing through a pulse coding excitation algorithm according to the electromagnetic characteristic parameters of a target material and a preset detection precision requirement, and outputting a low-power-consumption excitation parameter set; driving an electromagnetic ultrasonic transducer to generate a detection signal based on the low-power-consumption excitation parameter set, and outputting a compressed echo signal; performing multi-scale intrinsic mode decomposition on the compressed echo signal, and outputting a thickness correlation characteristic parameter set; inputting the thickness correlation characteristic parameter set into a depth residual error-attention network model, and outputting a thickness prediction result; and performing multi-node data fusion on the thickness prediction result based on an Internet of Things cloud platform to generate a final thickness detection report. According to the embodiment of the invention, high-precision and traceable thickness detection can be realized based on the miniaturized low-power-consumption Internet of Things.

The invention provides a low-power-consumption communication method and system based on a 5GRedCap portable WiFi network, and relates to the technical field of low-power-consumption communication, and the method comprises the steps: carrying out the adaptive control of a DRX period predicted according to WiFi access flow, setting the wake-up control of a RedCap communication terminal module, setting the adaptive switching of a bandwidth part, and setting the switching operation of a cellular communication system. By introducing a DRX cycle adaptive control mechanism based on WiFi access flow prediction and an intelligent wake-up strategy of uplink and downlink linkage into a 5G RedCap communication terminal module, the DRX sleep and wake-up cycle can be dynamically adjusted according to the actual service load state, the power consumption during the idle period of the terminal is effectively reduced, the energy waste caused by frequent wake-up is avoided, and the user experience is improved. And precise energy-saving management of the honeycomb side is realized.

The embodiment of the invention discloses an in-memory computing circuit based on a magnetic cache, and the circuit comprises at least one magnetic cache unit, at least one in-memory computing unit, and a timer. The magnetic cache unit in the at least one magnetic cache unit is used for caching data output by the corresponding in-memory computing unit as to-be-processed data within the corresponding data retention time; the timer is used for respectively setting data retention time for the at least one magnetic cache unit; and the in-memory computing unit in the at least one in-memory computing unit is used for extracting the data to be processed from the corresponding magnetic cache unit for calculation and outputting the computed data to other magnetic cache units. According to the embodiment of the invention, the invention achieves the flexible adjustment of the data retention time of the magnetic cache unit in various in-memory calculation scenes, and achieves the provision of a high-capacity cache for the data needed by in-memory computing under the lower power consumption.

The invention relates to the technical field of communication control, and discloses a self-adaptive frequency jump method, device and equipment for a low-power-consumption dual-mode Bluetooth chip, and the method comprises the steps: obtaining a current Bluetooth mode, detecting the channel quality of a communication environment, obtaining the basic characteristics of the channel quality, and constructing a channel decision management framework; the communication interference condition is detected in real time, the channel decision management framework is adjusted to avoid interference, and real-time channel quality monitoring and channel selection directivity analysis are carried out according to the adjusted channel decision management framework to obtain channel selection reference features. According to the method, channel selection and frequency hopping strategies are optimized through a self-adaptive frequency hopping mechanism, channel frequency hopping decision preprocessing of mode conversion is carried out on another Bluetooth mode on the basis of channel selection reference characteristics, collaborative decision of channel frequency hopping is carried out, and the dual-mode Bluetooth chip is driven to carry out channel frequency hopping processing. The problem that in the prior art, a fixed frequency hopping mechanism is difficult to adapt to the communication requirement of dual-mode Bluetooth is solved.

The invention relates to the field of energy-saving computing, and discloses a low-power-consumption control method and system of a controller, which are used for realizing prediction-sleep-wake-up-response full-link hardware in the controller. Time sequence state data of a controlled object is collected in real time, and a predictive sleep window value is dynamically generated by utilizing a predictive cooperative computing unit, so that intelligent scheduling of sleep and awakening is realized, and the power consumption of a controller is effectively reduced. Meanwhile, in combination with the technologies of threshold comparison, DMA data transmission optimization and the like, the data processing efficiency is improved, and invalid data transmission is reduced. And on the awakening mechanism, an asynchronous awakening circuit and an interrupt request mechanism are adopted to ensure that power supply is quickly recovered and control response is executed when an effective instruction is received, so that the real-time performance of the system is guaranteed. According to the invention, a prediction algorithm, hardware acceleration and an intelligent scheduling technology are fused, the performance of the controller is ensured, the power consumption is obviously reduced, and the endurance time of equipment is prolonged.

The invention provides a low-power-consumption self-repairing and energy self-supplying mine dust monitoring sensor network system, which comprises a plurality of sensor nodes and a central monitoring platform, and is characterized in that data of all the sensor nodes are transmitted to the central monitoring platform in real time; the sensor network synchronizes environmental parameters, and performs data analysis, processing and visual display on the central monitoring platform; a plurality of sensors are integrated in each sensor node, and the sensors are used for monitoring different environmental parameters in a mine environment; the types of the sensors comprise a dust concentration sensor and a temperature and humidity sensor, and the environmental parameters comprise dust concentration, temperature and humidity; the problems of long-time operation, insufficient energy supply, node failure, unstable data transmission and the like of a dust monitoring system in a complex mine environment are solved. The system integrates a multi-source environment energy collection module, and the technologies of mechanical vibration, airflow kinetic energy, thermoelectric power generation and the like are adopted, so that self-power supply of sensor nodes is realized, and the requirement of frequently replacing batteries or wiring is avoided.

The invention relates to the technical field of display screen driving, in particular to a low-power-consumption display screen driving method and system based on the OLED technology, and the method comprises the steps: S1, carrying out the image feature detection, collecting the inter-frame brightness change rate, the sub-pixel gray level distribution and the regional temperature gradient, and generating a dynamic driving signal parameter; s2, voltage compensation adjustment: dividing a power consumption area according to a brightness change rate, calculating a brightness compensation coefficient and correcting the voltage by combining gray level distribution and a temperature gradient, and realizing sub-pixel voltage dynamic adjustment; and S3, refresh frequency control: adjusting a local refresh rate according to the compensation coefficient and the correction voltage, executing a frequency reduction strategy on a high-power-consumption area, triggering ghosting suppression on a low-power-consumption area, and applying a temperature threshold to constrain a refresh upper limit. According to the invention, energy-saving driving, ghost suppression and brightness balance of the OLED display screen are realized, and the display performance and the system intelligence are effectively improved.

The invention relates to the technical field of network monitoring, in particular to a method for constructing a dynamic self-adaptive alarm monitoring network based on LoRa and Ad-hoc ad hoc network technology, which comprises the following steps: (1) integrating a dynamic Ad-hoc ad hoc network routing protocol on each LoRa node, so that each node can automatically discover neighbor nodes, establish and maintain a dynamic routing table, and automatically discover the neighbor nodes; a non-centralized network architecture is realized; (2) through a multi-hop communication mode, the alarm information can be flexibly transmitted among the nodes, the coverage range of the network is expanded, and the system adapts to a complex geographical environment; and (3) by utilizing the characteristics of low power consumption and long-distance transmission of the LoRa technology, stable communication between the nodes in a large range is ensured, meanwhile, the energy consumption is reduced, and the working life of the nodes is prolonged. Through the dynamic self-adaptive Ad-hoc routing protocol, the network can automatically adjust the routing according to the node state and the environment change, the dynamic change of the network topology is adapted, and the reliable transmission of the alarm information is ensured.

The invention relates to an ultra-low power consumption multichannel high-speed signal synchronous acquisition and emission system suitable for satellite communication. The system comprises an acquisition and emission board card which mainly comprises a plurality of radio frequency transceivers, an optical module, a clock unit, an FPGA (Field Programmable Gate Array) 1 processor and the like; the clock unit comprises a clock chip, a clock Buffer and the like; the optical module is used for receiving data, sending the data to an FPGA (Field Programmable Gate Array) 1 for processing, then sending the data to a transmitting channel of the radio frequency transceiver through a JESD204B interface for interpolation filtering, QEC (Quadrature Error Correction) calibration and refreshing, and then performing up-conversion to output an I / Q analog modulation signal; a receiving channel of the radio frequency transceiver receives an I / Q analog signal, the I / Q analog signal is sampled after low-pass filtering, the sampled data is sent to the FPGA1 for processing through the JESD204B interface after QEC calibration, and then the data is forwarded through the optical module. The system can realize ultra-low power consumption and reduce the weight of the whole machine.

The invention particularly relates to a lead-acid battery SOC accurate calculation and lead-acid battery polymorphic anomaly detection and protection method, which comprises the following steps: firstly, collecting and preprocessing multi-dimensional data information of a lead-acid battery, and then respectively calculating the preprocessed data based on a preset ampere-hour integral method and an improved extended Kalman filtering method; meanwhile, the battery operation condition is recognized through a preset condition recognition algorithm, and then dynamic weight fusion is conducted on calculation results of the two methods according to the condition to obtain a first fusion result; and then temperature compensation correction is performed on the result by using a preset temperature compensation model, and finally correction is performed in sequence by using a preset internal resistance-SOC relationship and an aging correction model to obtain a first SOC value. Through multi-dimensional data fusion, dynamic working condition weight distribution, temperature compensation and multi-mode cooperative protection, the SOC estimation error of the lead-acid battery is reduced, the safety and environmental adaptability under complex working conditions are improved, and meanwhile, intelligent interaction and low-power-consumption management are supported.

The invention provides an electric energy load real-time data acquisition and analysis method based on a low-cost scheme, and the method comprises the following steps: constructing a distributed data acquisition network, employing a combined hardware architecture of a current / voltage sensor and a low-power-consumption MCU, and achieving the data acquisition optimization through a dynamic sampling rate adjustment mechanism, when the load fluctuation exceeds a set threshold value, the sampling rate is automatically increased, when the load is stable, the sampling rate is reduced to a calibration sampling rate, and a Kalman filtering algorithm is adopted to carry out real-time data preprocessing; a three-level data transmission system is established, the three-level data transmission system comprises an edge acquisition node layer, a convergence gateway layer and a cloud processing layer, an optimized AODV routing protocol is adopted among nodes to construct a star-shaped and net-shaped hybrid network topology, and an optimal transmission path is dynamically selected according to the signal strength and the network congestion condition; a differentiated QoS transmission strategy is designed, and data is divided into three priorities of fault alarm data, real-time monitoring data and historical data.

The invention belongs to the technical field of intelligent hardware control methods, and discloses a low-power-consumption intelligent hardware control method which comprises the following steps: acquiring working state parameters and user interaction information of intelligent hardware, and generating an equipment state feature vector; judging whether a dormancy condition is met or not according to the equipment state feature vector; when the sleep condition is satisfied, sending a network communication agent instruction; the coprocessor configures an internal timer and awakens signal output after receiving the instruction; the master control stores a system operation state, configures a wake-up source and then enters a deep sleep state; the coprocessor cuts off the power supply of the inactive module; when a timer of the coprocessor reaches a preset network heartbeat cycle, a wake-up signal is sent to the master controller; and the master control recovers the system state, updates the feature vector and re-decides whether to sleep or not. And through multi-dimensional state perception and a master-slave cooperation architecture, and through refined power management and a dynamic reevaluation mechanism, the equipment power consumption is obviously reduced on the premise of ensuring the user experience.

The invention discloses an intelligent wake-up system and method for a mobile hard disk in a low-power-consumption mode, particularly relates to the technical field of wake-up control of the mobile hard disk, and is used for solving the problem that the mobile hard disk cannot accurately recognize a wake-up request in the low-power-consumption state. According to the method, the wakeup request in the low-power-consumption mode of the mobile hard disk is classified and identified, the operation type, the system running state and related behavior information are extracted, the multi-modal feature vector is constructed, and the request validity is intelligently predicted based on the integrated learning model, so that the wakeup judgment accuracy is improved, and the wakeup efficiency is improved. For the request with the prediction result in the uncertain interval, a short-time semi-activation window period is set, and secondary confirmation is performed by monitoring the host access behavior in real time, so that energy consumption waste and equipment loss caused by false wake-up are effectively avoided, self-adaptive response to the state change of the mobile hard disk is realized, and the service life of the mobile hard disk is prolonged. And the low-power-consumption intelligent control level and the energy-saving management capability are improved.

A voltage mode driver circuit has a first driver slice has a pullup structure that includes a first transistor and a second transistor and a pulldown structure that includes a third transistor and a fourth transistor. The first transistor has a gate that receives a first version of a first data signal. The second transistor has a gate that receives a first version of a second data signal. The third transistor has a gate that receives a second, complementary version of the first data signal. The fourth transistor has a gate that receives a second, complementary version of the second data signal. The first data signal encodes data in a first mode and enables the pullup and pulldown structures in a second mode of operation. The second data signal encodes data in the second mode of operation and enables the pullup and pulldown structures in the first mode of operation.

The invention discloses a single-chip microcomputer hierarchical dormancy control method based on dynamic power consumption prediction, and relates to the technical field of single-chip microcomputer low power consumption control, and the method specifically comprises the steps: building a mapping relation between a load current and a clock frequency; setting a dynamic dormancy threshold value; constructing a dynamic power consumption prediction model; a dormancy strategy is designed, module-level power consumption management and single-chip microcomputer function-based power consumption management are adopted, the callable frequency or the maximum operation duration of each function is distributed according to task priorities and battery residual energy consumption, and single-chip microcomputer peripherals are triggered through events and are independently awakened; and executing the sleep strategy, automatically awakening the single chip microcomputer according to a preset awakening condition, and realizing abnormity positioning and processing based on threshold comparison and power consumption monitoring in the process of executing the sleep strategy. According to the invention, module-level power consumption management and single-chip microcomputer function-based power consumption management are realized, the limitation of traditional global dormancy is broken, the need of overall reset during wakeup is avoided, and the response speed is improved while the energy consumption is reduced.

The invention discloses a multi-modal perception and optimization method and system for a low-power-consumption AR device, and the method comprises the steps: collecting multi-modal data, task demands, resource state data and environment data for the AR device; lightweight processing is carried out on the multi-modal neural network model through model pruning, parameter quantification and distillation technologies; inputting the collected data into a lightweight multi-modal neural network model for dynamic reasoning to obtain a multi-modal recognition result; comprising the steps of executing modal adaptive weight acquisition based on task requirements and environment data; executing energy consumption constraint scheduling according to the equipment resource state data, dynamically selecting a reasoning path strategy, and obtaining corresponding modal feature output; multi-modal feature fusion is carried out, task reasoning is completed, and a multi-modal recognition result is obtained; early-leaving control is executed based on a middle-layer confidence coefficient threshold value in the reasoning process; and interactively outputting a real-time multi-mode identification result. According to the invention, energy efficiency and precision balance and multi-mode fusion low-power-consumption optimization can be realized.

The invention discloses a cholesteric liquid crystal display driving method and a cholesteric liquid crystal display driving device for realizing dynamic video display, and belongs to the technical field of display. The method comprises the following steps: firstly, controlling a grid electrode and a source electrode driver to cooperatively work, and resetting a full-screen liquid crystal to a vertical arrangement state as a display reference; then applying a specific voltage signal to each pixel according to the current frame image data, so that the pixels are selectively kept in a vertical arrangement state or converted into a plane arrangement state to display a target image; then common electrode voltage polarity inversion is carried out, reverse voltage is applied for compensation, and finally the process is cycled to achieve image updating. The corresponding device comprises a display panel, a gate driver, a source driver and a time schedule controller for executing the method. According to the method and device, the refresh rate limitation of traditional cholesteric liquid crystal bistable switching is broken through, high-speed dynamic video display is achieved, meanwhile, the display reliability is effectively improved through polarity compensation, the service life is effectively prolonged through polarity compensation, and low power consumption and high compatibility are achieved.

The invention provides a kernel control method and device and electronic equipment. Relates to the technical field of inner cores. The method comprises the following steps: acquiring inner core state information of an inner core under the condition of processing a current thread; determining a target running state of the kernel in response to the condition that the kernel state information meets a set control condition or a running control instruction for the kernel is received; the target operation state comprises a target operation state of a power domain and / or a target operation state of a clock domain of the kernel; the power consumption corresponding to the target operation state is smaller than the power consumption of the kernel in a normal operation state; and determining an adjustment signal corresponding to the kernel based on the target operation state, and sending the adjustment signal to a power domain and / or a clock domain of the kernel so as to control the operation state of the kernel. According to the invention, the fineness of power consumption management can be improved, and the flexibility of kernel control in a low power consumption mode can be improved.

The invention relates to the technical field of prediction algorithms, and discloses a high-precision active power filtering and prediction algorithm for a three-phase ammeter, which comprises the following steps: acquiring original signals of three-phase voltage and current for baseline correction, performing time-frequency analysis on non-stationary harmonic waves and noise of the original signals, and dynamically adjusting filtering parameters; voltage and current phase alignment is carried out through FIR phase shift and zero crossing point detection, a phase-locked loop is constructed by using GRU to track the frequency of a power grid, the sampling frequency is dynamically adjusted, and frequency mutation is detected; iapFFT transformation is optimized to suppress spectrum leakage, a phase error is corrected through a deep learning network, and weak harmonic detection is enhanced by using an attention mechanism; classifying harmonic waves, and adaptively calculating total active power; dimensionality reduction is carried out on historical power and environmental parameters through an auto-encoder, and future active power is predicted; low-power-consumption hardware is adapted, and training efficiency and data security are optimized; three-phase signals are processed in parallel, and FPGA storage and FFT / FIR cores are optimized for filtering processing; and dynamically adjusting parameters of the phase-locked loop.

A wearable electronic device, a system and methods of monitoring with a wearable electronic device. The device includes a hybrid wireless communication module with wireless communication sub-modules to selectively acquire location data from both indoor and outdoor sources, as well as a wireless communication sub-module to selectively transmit an LPWAN signal to provide location information based on the acquired data. The device may also include one or more sensors to collect one or more of environmental data, activity data and physiological data. The device may transmit some or all of its acquired data to a larger system, including a cloud-based server to, in addition to providing location-based data, be used as a part of a predictive health care protocol to correlate changes in acquired data to salient indicators of the health of a wearer of the device. In one form, the predictive health care protocol uses a machine learning model.