276 results about "Iot gateway" patented technology

The invention relates to the technical field of industrial Internet of Things, in particular to a predictive maintenance method for intelligent factory Internet of Things equipment, which comprises the following steps of: acquiring equipment operation parameters, environment monitoring data and historical maintenance records, constructing a multi-dimensional feature data set, extracting equipment degradation features by adopting a topological graph attention mechanism and a Bayesian network, and establishing a multi-dimensional feature data set; the method realizes equipment health state modeling and fault probability prediction, combines a dynamic adjacency matrix and a multi-objective optimization algorithm, comprehensively optimizes maintenance cost, equipment fault risk and associated equipment influence, dynamically generates an optimal maintenance plan, carries out constraint optimization based on a mixed integer programming method, automatically generates a maintenance instruction sequence, and achieves the optimal maintenance of the equipment. Tasks are issued through the computerized maintenance management system, the PLC control system and the industrial Internet of Things gateway, and the execution state is monitored and maintained in real time. The intelligent level of equipment maintenance is effectively improved, non-planned shutdown is reduced, and the equipment reliability and the production efficiency are improved.

The invention relates to the technical field of network management, in particular to an Internet of Things gateway control method and system based on AI computing power, and the method comprises the following steps: obtaining channel real-time signal intensity, noise level and occupancy proportion, monitoring protocol type and transmission condition, analyzing the relationship between retransmission times and interference, deducing protocol combination interference and throughput, and obtaining a real-time channel signal intensity, noise level and occupancy proportion. And configuring an optimal scheduling scheme, evaluating resource consumption and load states, packaging and requesting permission entrustment, and judging permission information in combination with an interaction record and an access control list. According to the method, different protocol distribution combinations are simulated and deduced, the data throughput of the whole network is further estimated and optimized, potential protocol conflicts are reduced, the use efficiency and the overall performance of network resources are effectively improved, consumption of a local computing unit and network bandwidth is comprehensively considered, packaging processing of request information is optimized, and the network performance is improved. And the real-time response capability and manageability of the network state are obviously improved.

The invention provides a heterogeneous network resource virtualization modeling and intelligent arrangement method and system based on a knowledge graph, and relates to unified modeling, dynamic retrieval and intelligent resource arrangement of heterogeneous network equipment. The method specifically comprises: 1, a unified modeling method based on a knowledge graph: integrating protocol attributes, dynamic states and topological relationships of heterogeneous devices such as a 5G base station, an SDN switch, a router, an Internet of Things gateway and the like into a structured knowledge graph, breaking the barrier of a manufacturer private data model, and realizing semantic-level collaborative scheduling of cross-domain resources; 2, designing a semantic retrieval engine: querying dynamic conditional reasoning through a natural language, replacing traditional manual rule definition, and improving retrieval response speed and accuracy; and 3, developing a graph-driven intelligent arrangement framework: combining a graph neural network (GNN) and reinforcement learning (RL), automatically generating a resource allocation strategy according to a real-time network state, reducing manual intervention and improving the resource utilization rate.

The invention belongs to the technical field of intelligent early warning, and discloses a water meter well remote ponding early warning method and system based on the Internet of Things. The method comprises the steps that collected water meter well measurement data are integrated through an Internet of Things gateway, comprehensive analysis is conducted on the measurement data, comprehensive characteristics are obtained, the measurement data and the comprehensive characteristics serve as input of an accumulated water analysis model, and an accumulated water characteristic mode is obtained; determining a leakage point coordinate through a fusion positioning algorithm in combination with sound wave positioning derivative features in the comprehensive features; performing dynamic analysis on the measurement data to obtain derivative dynamic characteristics, and taking the measurement data and the derivative dynamic characteristics as input of a dynamic characteristic model to obtain a dynamically adjusted graded ponding early warning threshold value; corresponding graded early warning is carried out according to the relation between the actual water accumulation amount and the graded water accumulation early warning threshold value; according to the invention, through multi-dimensional sensor data fusion and intelligent feature engineering, a closed-loop system integrating real-time monitoring, abnormity diagnosis, accurate positioning and grading early warning is constructed.

The invention relates to the technical field of data processing, and discloses an Internet of Things gateway data grading processing method and system based on edge computing, and the method comprises the steps: collecting original operation data and a data traffic value received by an Internet of Things gateway; performing feature extraction and clustering grouping according to the original operation data, calculating an average influence coefficient of samples in a group in combination with a preset service weight, and determining an importance level corresponding to the group; important data is screened out for distribution immediate evaluation; performing aging characteristic analysis according to the important data, and predicting a data processing priority; analyzing resource demand allocation according to the priority sequence and the data flow value, and constructing a resource allocation proportion; according to a resource allocation proportion and an allocation proportion lower limit, identifying nodes with insufficient proportions and optimizing the priority sequence to obtain a final scheduling scheme; according to the final scheduling scheme, the processing sequence is applied to the original operation data, and data grading output is obtained. According to the method, efficient and accurate data processing is realized.

The invention relates to the technical field of Internet of Things gateways, and discloses an Internet of Things gateway device and system based on edge computing, and the device comprises a hardware heterogeneous computing module and a multi-interface protocol adaptation module. The edge calculation local processing module is used for performing preprocessing, feature extraction and local decision on the acquired terminal data; the network redundancy and self-healing module is used for realizing accurate network disconnection detection, seamless switching of a main network and a standby network and equipment fault self-recovery through a multi-dimensional network health degree evaluation algorithm; the local autonomous storage module is used for realizing hierarchical storage of high-frequency data and network disconnection emergency data and seamless synchronization after network recovery through network disconnection data hierarchical caching and an incremental synchronization algorithm; and the cloud collaborative management module is used for realizing remote configuration, OTA upgrading and state monitoring. The method is high in integration, low in delay and fast in response, adapts to real-time scenes, saves bandwidth cost, improves cloud efficiency, is high in reliability, and realizes network disconnection and continuous operation.

The invention discloses an intelligent medical big data information management system, and the system comprises a data collection layer which serves as a sensing neural network, employs an Internet of Things gateway to be compatible with a medical equipment protocol, and deploys an edge calculation node for physiological signal preprocessing; the intelligent preprocessing layer is used for cleaning and standardizing the original data transmitted by the data acquisition layer; the informatization service layer is used for realizing fine-grained authority control based on an RBAC (Role Based Access Control) model, realizing inspection process automation by integrating an LIS (Line Information System) interface through a Hyperdger Fabric block chain evidence storage key operation hash, and constructing a zero-footprint DICOM (Digital Imaging and Communications in Medicine) viewer; the intelligent analysis layer is used for carrying out data life cycle management by adopting a mixed storage architecture, carrying out feature engineering on data, carrying out label matching and classified storage by using efficient neighbor search and similarity / distance measurement, quantifying contribution of each feature or feature combination to a single prediction result through an SHAP value, generating an interpretation result, and outputting the interpretation result; and presenting an interpretation result to a clinician or related personnel through a query interface.

Disclosed are methods, systems, and one or more computer-readable mediums for receiving, at an edge device from an external server, a rules database comprising a set of rules; receiving, by the edge device, first data from at least one device; processing, by the edge device, the received first data by comparing the received data to each rule among the set of rules; identifying a first triggering event in response to detecting a match between the received data and a rule of the rules database; and outputting an alert corresponding to the first triggering event.

The invention discloses a dual-channel adaptive network stability testing method and system, and belongs to the technical field of computer network testing. The system adopts a dual-channel asynchronous communication architecture in which a control channel and a data channel are physically separated, instructions and state information are transmitted through an independent TCP control channel, and high-speed test data streams are transmitted through a UDP or TCP data channel. The method comprises the following steps: dynamically and adaptively adjusting a timeout parameter based on real-time network delay detection; nanosecond constant interval packet sending control is realized by using a high-precision monotonic clock source and busy waiting compensation mechanism; a packet loss detection, positioning and ACK confirmation mechanism based on the serial number is realized in an application layer; and real-time statistical display and idle detection automatic termination are realized through multi-thread parallel processing. According to the invention, the precision, the stability and the adaptive capability of network testing are remarkably improved, and the method is suitable for long-time stability testing in various scenes such as a high-speed Ethernet, a satellite link, an industrial Internet of Things gateway and the like.

The invention relates to the technical field of intelligent monitoring, and discloses a cloud internet-of-things security monitoring method and system with a fault self-diagnosis function. The method comprises the following steps: an Internet of Things gateway pre-processes environmental data and then generates first processing data, an edge computing device performs real-time computing processing on the first processing data, generates second processing data, performs fusion analysis on all the second processing data, and outputs a first analysis result; the Internet of Things gateway transmits the first processing data, the second processing data and the first analysis result to a cloud server; the cloud server stores the received data, the abnormal state sensing model outputs a second analysis result, the second analysis result is displayed in a map level, and a real-time safety report is generated; the operation state of the monitoring system is monitored in real time, and a real-time fault report is output; and summarizing the real-time safety report and the real-time fault report and then transmitting the summarized report to a terminal. According to the invention, the efficiency and accuracy of cloud Internet of Things security monitoring are improved.

The invention relates to the technical field of Internet of Things data processing, in particular to a multi-modal data real-time processing method for an Internet of Things gateway, and the method comprises the steps: obtaining multi-source operation data, and packaging the multi-source operation data into a standard operation data set; obtaining high-bandwidth modal data in the standard operation data set; when the maximum link delay time is greater than a preset delay abnormal threshold value, obtaining a version effective fingerprint of the target model and a local model fingerprint; when a model version abnormity diagnosis result is obtained, calculating information redundancy; obtaining correction delay time, and comparing the correction delay time with a preset normal reference delay interval; and when the correction delay time is greater than or equal to the upper limit value of the normal reference delay interval, adjusting the current decision period. By monitoring delay in real time, diagnosing consistency of model versions, eliminating redundant information and executing link adjustment, accurate processing of high-bandwidth modal data is realized, and real-time performance and reliability of Internet of Things gateway data processing are improved.

The invention provides an intelligent production line management and control method and system for an automobile brushless motor, and relates to the technical field of motor vehicles, and the method comprises the steps: carrying out the comprehensive defect detection, and obtaining motor defect distribution; process failure mode backtracking is carried out, and P production line devices of P production process nodes are positioned; cross-process parameter coupling analysis is carried out, and M groups of parallel monitoring devices are recombined; m edge detection nodes are configured, the M edge detection nodes are in communication connection with a production line management and control middle table through an Internet of Things gateway protocol, and M multi-modal monitoring tasks are set; after the calibration state is calibrated, the M edge detection nodes dispatch M multi-modal monitoring tasks through dynamic computing power distribution, and dynamic calibration triggering driven by deviation diagnosis is executed. The technical problem that in the prior art, production of motor vehicles such as electric vehicles generally depends on manual inspection and experience judgment to conduct equipment calibration, an automatic real-time monitoring and calibration mechanism is lacked, and therefore the product quality is affected is solved.

The invention relates to the technical field of state monitoring, in particular to a state monitoring method and system based on a power grid intelligent Internet of Things gateway device, and the method comprises the following steps: based on the Internet of Things gateway device, collecting and analyzing multiple types of sensor signals, carrying out the unified arrangement to form a multi-parameter cooperative monitoring sequence, and comparing the changes of current and voltage signals; and extracting a synchronous response ratio feature group, calculating a thermoelectric trend consistency index in combination with the temperature change trend and the current amplitude, screening an interference level section, and judging abnormal linkage. According to the method, cross-parameter trend extraction, collaborative response, difference comparison and section identification are realized, correlation characteristics of multi-source signals in a continuous time period can be converted into identification basis, an abnormal forming process, a response link and state evolution are discriminated by combined characteristics, and abnormal section, sequence attributes and synchronization factors are jointly applied, so that the accuracy of the multi-source signal identification is improved, and the reliability of the multi-source signal identification is improved. And the identifiability and the classification capability of abnormal events under complex working conditions are improved.

The invention belongs to the technical field of data management, and discloses an inspection sample data tracking identification method and system based on the Internet of Things. The method comprises the following steps: a cloud data center constructs a sample tracking identification model and a sample data analysis model, and deploys a block chain network; the Internet of Things gateway is used for collecting real-time handover records and sending the real-time handover records to the cloud data center; the cloud data center performs tampering verification and generates real-time test sample data; the cloud data center is used for performing sample tracking and identification by using the sample tracking and identification model; the cloud data center is used for performing sample data analysis by using a sample data analysis model; and the cloud data center is used for storing the real-time test sample data, the real-time sample tracking identification result and the real-time sample data analysis result of the detection sample by using a block chain network. According to the invention, the problems of easy data tampering, difficult tracking, inaccurate analysis, low management efficiency and low storage reliability in the prior art are solved.

The invention discloses a communication method, system and device of Internet of Things equipment and a medium, and the method is applied to an Internet of Things gateway, carries out the communication strategy generation of configuration parameters and historical transmission data records according to an Internet of Things communication mode set, obtains a parallel communication strategy, and carries out the communication strategy generation of the configuration parameters and the historical transmission data records. The parallel communication strategy comprises a plurality of target communication modes; secret key generation is carried out on the parallel communication strategy to obtain a communication secret key group, the communication secret key group comprises a plurality of mode secret keys, and each mode secret key corresponds to one target communication mode; and transmitting the to-be-transmitted data of the Internet of Things equipment to the Internet of Things server side in parallel according to the communication key group and the parallel communication strategy. According to the method, the communication stability and reliability of the Internet of Things equipment can be effectively improved. The invention relates to the technical field of Internet of Things.

The invention provides an access method and device of Internet of Things equipment and an Internet of Things system, and relates to the technical field of Internet of Things. The method is applied to an Internet of Things gateway, and comprises the following steps: obtaining configuration data of an Internet of Things device to be accessed according to unique identification information of the Internet of Things device to be accessed; assembling function points of the object model according to the configuration data in combination with an equipment function model library so as to obtain a target object model of the to-be-accessed Internet of Things equipment; and sending the target object model to the terminal, so that the terminal controls the to-be-accessed Internet of Things device based on the target object model. According to the method and the device, the equipment function model library for unifying the abstract equipment capability is constructed, and the function point assembly of the unique identification information object model of the to-be-accessed Internet of Things equipment is combined, so that dynamic configuration is realized. The problems of low reusability, poor compatibility and high maintenance difficulty in a traditional equipment access mode can be effectively solved, the access period is greatly shortened, and the equipment access development workload and the maintenance cost are reduced.

The invention provides an oil depot state low-cost monitoring method and system based on the Internet of Things, and relates to the technical field of oil depot detection, and the method comprises the steps: deploying a sensor group at the position of an oil depot storage tank, and collecting original monitoring data; preprocessing the collected original monitoring data, and then uploading the data to a cloud server through an Internet of Things gateway; based on the received data, the cloud server performs inversion calculation on the real-time liquid level height of the storage tank through an intelligent algorithm, and performs calibration calculation on the volume of the special-shaped storage tank; state fusion analysis and abnormity diagnosis are carried out based on the real-time liquid level height, the volume data and the multi-source environment data; and triggering graded early warning according to a preset rule based on results of analysis and abnormality diagnosis. According to the method provided by the invention, hardware deployment cost is revolutionarily reduced, and all-around efficiency leap from manual regular inspection to unmanned real-time monitoring, from single parameter measurement to multi-source fusion diagnosis, and from passive reading to active early warning is realized.

The invention relates to the technical field of internet of things valve wireless monitoring, and particularly discloses an internet of things-based valve wireless monitoring and early warning system, which comprises a signal acquisition module for acquiring a valve position simulation position signal of a valve in real time through a position sensor; the wireless communication module is used for performing analog-to-digital conversion on the valve position analog position signal and transmitting a valve position digital signal generated after analog-to-digital conversion through a first wireless communication network and a second wireless communication network; the monitoring module is used for sequentially selecting each monitoring point position in the signal acquisition module and sending a monitoring command data packet to the wireless control terminal corresponding to each monitoring point position through the Internet of Things gateway; the control module is used for receiving a valve position control instruction fed back by the monitoring command data packet of each monitoring point position and generating early warning information; and the execution module is used for driving a valve to execute valve action operation according to the valve position control instruction.

The invention belongs to the technical field of edge computing, and discloses an Internet of Things gateway collaborative management system based on edge computing, which comprises a resource virtualization unit used for deploying a protocol independence abstract engine in a gateway cluster, analyzing and adapting various Internet of Things protocols, constructing a proprietary protocol conversion matrix, obtaining standardized equipment attribute data, and storing the standardized equipment attribute data in a server; establishing an equipment shadow model based on the standardized equipment attribute data; the edge collaborative scheduling unit is used for outputting panoramic state data through the equipment shadow model, abstracting the gateway cluster into a tough topology directed graph based on the panoramic state data by adopting an edge computing task scheduling algorithm, and coordinating the gateway cluster; the intelligent load balancing unit is used for monitoring the gateway cluster calculation load and the network transmission load at the same time, and predicting the load imbalance rate according to the gateway cluster calculation load and the network transmission load; the efficient, flexible and intelligent cooperative management of the Internet of Things gateway cluster is realized.

Disclosed is a system for providing dynamic spectrum access, the system comprising: one or more sensor nodes configured to collect environmental data; a plurality of Internet of things (IoT) gateways arranged in data or signal communication with the one or more sensor nodes via a network protocol, each IoT gateway comprising at least one spectrum channel; a distributed ledger configured for secure data processing between each of the plurality of IoT gateways and the one or more sensor nodes; and a dynamic spectrum access module arranged in data or signal communication with the plurality of IoT gateways, the dynamic spectrum access module configured to implement a deep learning algorithm, the deep learning algorithm configured to obtain the environmental data as input, parse the environmental data to obtain spectrum environment parameters, predict one or more use states of the at least one spectrum channel of each of the plurality of IoT gateways; and provide a spectrum access action based on the predicted one or more use states.

The invention belongs to the application category of the Internet of Things, and innovatively develops a multi-mode fusion building and industrial structure real-time sensing monitoring method with high cost. The technical innovation and breakthrough are realized by establishing a multi-physics field coupling model in order to solve the problems of high hardware layout overhead and data acquisition in a complex working condition scene in the existing monitoring system. Specifically, the research constructs a multi-physics coupling model with universality and an intelligent sensing framework based on relevance analysis of a building structure parameter transfer mechanism and in combination with heat conduction mode (such as convective heat transfer and radiative heat transfer) feature analysis in an industrial scene. According to the method, an exponential weighted moving average algorithm, a convolution enhancement algorithm, a time sequence weighting algorithm, a self-attention mechanism and a heat conduction sensing model are fused, and a data correction mechanism of multiple regression equations and regression coefficient estimation is combined, so that the hardware and operation and maintenance cost is remarkably reduced, and meanwhile, the monitoring coverage range and the prediction precision are improved. The method is suitable for Internet of Things gateway equipment with limited resources, virtual monitoring data is generated through sparsely deployed sensor nodes in building monitoring and industrial 4.0 environments, a high-real-time and intelligent manufacturing scene is provided, and a low-cost, high-precision and extensible solution is realized.

The embodiment of the invention discloses an Internet of Things multi-protocol adaptive access method and device and a medium, belongs to the technical field of Internet of Things communication, and solves the problems that an Internet of Things gateway protocol is insufficient in compatibility and insufficient in safety controllability in an industrial-grade high-reliability scene and a cross-platform collaborative scene. Comprising the following steps: loading a preset protocol plug-in, and carrying out initialization processing on a communication engine and a configuration management center so as to monitor a default port corresponding to each protocol; based on a feature code matching and AI protocol identification combined strategy, performing corresponding protocol matching identification on the monitored equipment connection request; verifying the current equipment based on preset authentication information, and establishing an encrypted data transmission channel under the condition that the verification is passed; receiving an original message sent by the equipment, and converting the original message into a uniform data format; and encrypting the data in the uniform format through the encrypted data transmission channel, calling the matched and identified protocol, and reporting the encrypted data to the Internet of Things platform through the communication engine.

The invention relates to the technical field of medical Internet of Things, and provides a ward patient sign information acquisition and intelligent Internet of Things control method, which comprises the following steps: acquiring patient multi-dimensional sign data by adopting a wearable sensor and sickbed peripheral monitoring equipment, and transmitting the data to a hospital data center through Internet of Things gateway hybrid networking after data processing; the data center analyzes the data by adopting a dynamic threshold model and generates early warning; and according to the early warning type and the emergency degree, intelligent equipment in the ward is controlled, and a control strategy is optimized according to equipment feedback. According to the invention, a traditional fixed threshold monitoring mode is changed, personalized accurate monitoring is realized, and misjudgment and missed judgment are avoided; multi-device cooperative collection and intelligent control linkage are achieved, and the ward environment and the device state are accurately adjusted; through data mining and prediction, the health risk of the patient is intervened in advance, a monitoring, control and optimized closed-loop system is formed, the medical monitoring accuracy and reliability and the ward intelligent management level are remarkably improved, and the personalized rehabilitation requirements of the patient are met.

The invention discloses a multi-communication interface Internet of Things gateway system and a resource dynamic allocation method thereof, and relates to the technical field of Internet of Things communication, the system comprises an RS232, an RS485, a CAN communication interface, an interface hardware detection circuit, a microcontroller unit, an external Flash chip, a 4G communication module and a cloud server; the method comprises the following steps of: dividing a plurality of independent firmware storage areas and differential packet storage areas in an external Flash; monitoring the physical connection state of the interface through a hardware detection circuit, and triggering the MCU to reset to a boot loader; the bootloader dynamically loads firmware, matched with the current interface combination, in the external Flash to an internal Flash running area of the MCU, and inactive interface resources are released; and firmware encryption verification and incremental updating are realized by combining a differential compression technology and a remote instruction. According to the invention, the problems of low resource utilization rate, high power consumption and low upgrading efficiency caused by resident memory of the traditional gateway firmware are solved through the strategies of partitioned hierarchical storage, loading as required and incremental upgrading, and the system performance and operation and maintenance reliability in a multi-protocol scene are remarkably improved.

The invention discloses a precise farmland irrigation system based on a block chain, and relates to the technical field of block chain technologies and water-saving irrigation systems. The system comprises a plurality of data acquisition sensors, a watering device, an Internet of Things gateway, a cloud computing platform and a mobile terminal device. The data acquisition sensor is used for monitoring environmental parameters and crop growth conditions in real time; the watering device automatically adjusts the irrigation amount according to data feedback; the Internet of Things gateway is used for data transmission, and the cloud computing platform is responsible for farmland data processing and analysis; a mobile application program is installed in the mobile terminal device, and irrigation state monitoring and auxiliary management decision making are provided for a user in real time. The system architecture takes a block chain as a bottom layer, all parties reach a consensus in advance, and intelligent provisions are automatically started when specified requirements are met. The system can realize accurate control of farmland irrigation, effectively save water resources, and ensure the safety and consistency of agricultural data sharing.

The invention discloses an Internet of Things gateway control method fusing local communication and AI computing power, and the method comprises the following steps: S1, constructing a multi-protocol adaptation layer for an Internet of Things gateway, recognizing the communication protocol type of access equipment, and building a unified data channel; relates to the technical field of Internet of Things gateway control, and provides an Internet of Things gateway multi-protocol adaptation layer based computing power resource distribution method, device and system, and the Internet of Things gateway multi-protocol adaptation layer based computing power resource distribution method and system improve device access compatibility by constructing a multi-protocol adaptation layer for an Internet of Things gateway, and generate computing power resource quantity distributed to an access device by obtaining the total residual computing power resource quantity of the Internet of Things gateway and based on QoS metadata of the access device. According to the invention, refined computing power resource allocation according to the task characteristics of the access device is realized, and the AI computing power unit is scheduled by creating the AI computing power unit, according to the QoS metadata of the access device and the computing power resource allocation strategy of the access device and through the container technology, so that the gateway of the Internet of Things can cope with different types of AI computing tasks, and the AI computing power unit scheduling efficiency is improved. And diversified processing requirements of the access equipment are met.

The invention relates to the technical field of Internet of Things communication fault positioning, and discloses an Internet of Things terminal equipment access transmission fault rapid positioning method and system, and the system comprises an Internet of Things terminal wireless connection diagnosis module, an Internet of Things terminal protocol interaction diagnosis module, and an Internet of Things terminal network configuration diagnosis and diagnosis result feedback module. Real-time network configuration log information of the Internet of Things terminal is accurately collected according to an Internet of Things gateway, and wireless network configuration fault diagnosis processing of the Internet of Things terminal accessing a network transmission layer is carried out by combining an intelligent search algorithm and scientifically stored network configuration abnormal log information of the Internet of Things terminal. The accurate diagnosis of the network communication fault of the access network transmission layer of the Internet of Things terminal is comprehensively diagnosed step by step based on the wireless connection fault, the protocol interaction fault and the network configuration, and the intelligence and the precision of the access transmission fault positioning result of the Internet of Things terminal are improved.

The application relates to the technical field of intelligent exhibition hall temperature control, and discloses an intelligent exhibition hall temperature central control system based on the Internet of Things, which comprises a data acquisition module, a feature extraction module, a trend prediction module and an optimization control module. The data acquisition module collects real-time temperature data through an Internet of Things temperature sensor node and generates temperature field data with time and space labels through time and space registration. The feature extraction module performs empirical mode decomposition on the temperature field data, extracts intrinsic mode function components and calculates temperature fluctuation feature vectors. The trend prediction module inputs the temperature fluctuation feature vectors into a long short-term memory network model to predict a predicted temperature sequence in a future preset time period. According to the difference between the predicted temperature sequence and a preset comfortable temperature threshold, the optimization control module adopts a multi-objective particle swarm optimization algorithm to iteratively optimize the valve opening degree of air conditioner terminal equipment, thereby generating a valve opening degree control instruction set. The instruction issuing module issues the valve opening degree control instruction set to corresponding actuators through an Internet of Things gateway.

The invention relates to the technical field of photovoltaic module string DC output current real-time monitoring and fault diagnosis, in particular to a photovoltaic string DC output real-time monitoring method and system and a computer readable storage medium. The method comprises the following steps: firstly, installing a group string level current monitoring unit at a direct current input port of a photovoltaic inverter, collecting direct current output current of a photovoltaic panel group string in real time through the monitoring unit, and then uploading collected group string current data to a monitoring platform through an Internet of Things gateway; and performing transverse comparative analysis on the group string current data based on the monitoring platform, identifying a complete disconnection or performance degradation fault, and when detecting that the group string current is abnormal, generating alarm information including a specific photovoltaic panel number and a physical position according to a preset group string topology database. According to the invention, the real-time and continuous monitoring of the DC output current of the photovoltaic panel group string and the accurate positioning of the panel level fault are realized, the fault response speed and the operation and maintenance efficiency are obviously improved, and the power generation loss and the operation and maintenance cost are reduced.

The invention relates to the technical field of Internet of Things and multimedia communication, in particular to a multimedia equipment centralized control method based on the Internet of Things, which comprises the following steps: realizing heterogeneous equipment access through a gateway dynamic analysis protocol of the Internet of Things; collecting multi-source data by utilizing an edge computing node, and detecting anomaly through Kalman filtering fusion and an isolated forest model; a dynamic control strategy is generated based on an LSTM neural network and a scene rule base, and synchronous switching of audio and video streams and self-adaptive adjustment of resolution are realized; control delay is guaranteed through hierarchical caching and a time-sensitive network protocol stack; and multi-terminal control is supported, and hierarchical authority management is implemented through a role authority matrix. According to the invention, the problems of difficult compatibility, insufficient control real-time performance and extensive safety management of heterogeneous equipment are solved, and the cooperation efficiency, response speed and use safety of multimedia equipment are effectively improved.