68 results about "Smart internet" patented technology

The invention discloses a network attack AI detection analysis method and system based on the smart Internet, and belongs to the technical field of network security protection, and the method comprises the steps: building an attack feature library through distributed edge nodes in a cooperative manner, generating feature parameters of each node based on a local attack event, and transmitting the feature parameters to a central server for dynamic fusion through encryption; constructing a multi-modal interaction graph, identifying a potential attack link based on association strength among graph nodes, and deducing an attack intention to generate a defense strategy; deploying a virtualized network environment, dynamically injecting induction characteristics, and adjusting an induction strategy in real time according to the interaction behavior of an attacker; and monitoring an abnormal mode of the user behavior sequence, triggering an AI interaction verification process and storing a defense strategy. According to the method, rapid collection and fusion of network attack features are realized, the detection delay of network attacks is reduced, the accuracy of attack prediction is improved, the flexibility and effectiveness of network attack confrontation are enhanced, and the defense intelligence and adaptive ability of the whole network are improved.

The invention discloses a surface water river-entering sewage draining exit pollution abnormity tracing method and device based on intelligent Internet of Things. The method comprises the following steps: constructing a database according to surface water pollution basic data; all pollution sources in the database are divided into different levels of pipeline logic relations according to the upstream and downstream communication relation of the land parcel area, the pipe network and the water system, and a pollution source-land parcel-pipe network-monitoring station intelligent Internet of Things grid is constructed; carrying out preprocessing and feature analysis on all data in the intelligent Internet of Things grid to construct a model database; a traceability model and a pollution contribution model are built based on the model database, the traceability model is used for calculating the pollution contribution rate of each pollution source, and a target discharge port or a target pollution discharge node is determined according to the pollution contribution rate; the pollution contribution model is used for generating and displaying a pollution contribution value of the target discharge port or the target pollution discharge point in response to an input instruction. The problem that a pollution source cannot be quickly and accurately determined in surface water environment management is solved.

The invention provides a carbon emission monitoring method and system based on an intelligent Internet of Things, and belongs to the technical field of carbon emission monitoring, and the method comprises the steps: arranging an acquisition module, a screening module, a storage module, a prediction module, an early warning module and a self-regulation module in a park; the acquisition module is started to calculate an effective carbon emission index, the prediction module constructs a prediction model, future meteorological data is input, and the prediction model predicts the effective carbon emission index in a future time period; time data corresponding to the effective carbon emission indexes larger than the threshold value are input into the early warning module and the self-regulation module, the actual effective carbon emission indexes and meteorological data are fed back to the prediction model, and the self-regulation module sends out a new adjustment instruction. According to the carbon emission monitoring method based on the intelligent Internet of Things, carbon emission, energy consumption, environmental parameters and the like can be fused through screening, storage, prediction and other modes so as to effectively and reasonably calculate the effective carbon emission index, and then an adjustment instruction is sent out to monitor, regulate and control the carbon emission.

This application provides a channel measurement method and an apparatus, which may be used in a field such as vehicle-to-everything V2X, smart internet of vehicles, autonomous driving, or an unmanned driving. In a sidelink channel report procedure, a transmit end apparatus for sidelink communication indicates one or more candidate time intervals to a receive end apparatus. The receive end apparatus may attempt to obtain an available PSSCH for sending a channel measurement report on one or more time domain resources corresponding to the one or more candidate time intervals.

The invention relates to an intelligent internet bed reservation system, which comprises a diagnosis and treatment group intelligent management module for receiving disease characteristic data of a patient, generating a diagnosis and treatment group distribution scheme and outputting an operation schedule table to a dynamic scheduling engine; the dynamic scheduling engine module is used for generating time window prediction according to the operation scheduling table and starting a grading notification process; the notification and interaction module is used for generating patient customized notification content, feeding back a confirmation state to the patient management module and updating the hospitalization preparation progress; and the patient full-period management module is used for generating an electronic hospitalization certificate and optimizing a period prediction algorithm. According to the system, method and device for reserving the bed through the intelligent internet, the processor and the computer readable storage medium, the working efficiency of medical staff is improved, the patient receiving and treating plan is flexibly adjusted, and time is saved. The queuing condition can be checked at any time, and the patient can conveniently and reasonably arrange personal affairs.

The application discloses a kind of applied to the wisdom internet of things parking system and method of e-commerce shopping free parking, the parking system includes parking interaction component, user mobile terminal, e-commerce shopping parking platform, and remote server, and the e-commerce shopping parking platform is deployed in the remote server;The parking interaction component is set to roadside for user parking interaction;The user mobile terminal is used to login access deployed in remote server e-commerce shopping parking platform, and obtain the parking two-dimensional code information;The e-commerce shopping parking platform includes parking fee information generation module, payment module and e-commerce shopping information generation module;The remote server is used to deploy e-commerce shopping parking platform, and store user e-commerce shopping and parking information.The application is closely combined by setting parking interaction component and platform, and through platform shopping free parking reaches the dual purpose of booming economy and managing city.

The application discloses an intelligent internet unmanned aerial vehicle (UAV) box and an automatic docking and locking control system thereof, and belongs to the technical field of UAV cargo hoisting. The system comprises a suspension connection unit, an intelligent cargo box unit, a positioning unit, a mechanical lock unit and an intelligent control unit. When the suspension unit and the positioning unit are magnetically connected, the intelligent control unit determines the locking or releasing mode through the number of signal contact connections; in the locking mode, a power-on timing control module supplies a first direction current to an electromagnetic adsorption module, sequentially drives a lock mechanism to close, and realizes mechanical locking; in the releasing mode, a reverse current is supplied, the lock mechanism is sequentially driven to open, and automatic unloading is realized. The system realizes full-process automation of UAV hoisting, has a high-reliability double-locking mechanism, effectively prevents aerial misrelease, is integrated into a smart internet network, and significantly improves the safety, efficiency and informatization level of hoisting operation.

The invention relates to the technical field of electronic commerce, and discloses an artificial intelligence internet electronic commerce device which comprises a base, a fixing frame is fixedly connected to the side wall of the base, and a plurality of exhaust grooves are formed in the side wall of the fixing frame. The fan blades drive the sliding rails and the arc-shaped triangular plates to synchronously rotate through the rotating ring, along with increase of centrifugal force, the balancing weights slide outwards along the outer walls of the corresponding fan blades at the moment, inclined planes of the inclined planes are forced to make contact with the outer wall of the rotating column, the transversely-moved sliding baffles relieve limitation on the sliding blocks, the arc-shaped triangular plates all slide outwards, and the fan blades are driven to rotate. When the equipment begins to run, a gap is formed between the arc-shaped triangular plates; and when the equipment is not used, the air flow carries the impurities to flow along the semicircular inner wall, so that the impurities are finally discharged outwards from the inner wall of the exhaust groove along the inner wall of the arc-shaped triangular plate, and the situation that the impurities enter the case when the fan blades rotate in the early stage is avoided.

The invention discloses an intelligent Internet of Things system full-chain fault diagnosis method and system based on deep reinforcement learning, and belongs to the field of intelligent Internet of Things system fault diagnosis, and the method comprises the steps: constructing a DQN deep reinforcement learning model; obtaining historical fault data, and performing offline training on the DQN deep reinforcement learning model according to the historical fault data to obtain a fault diagnosis model; constructing a fault diagnosis system according to the fault diagnosis model; and obtaining a fault diagnosis result by using a fault diagnosis system. The method solves the problem that a traditional fault diagnosis method cannot be suitable for full-chain fault diagnosis of a complex electric power intelligent Internet of Things system with a large data size.

The present invention relates to the field of road traffic safety, and in particular to a secondary accident variable speed limit prevention and control method based on deep reinforcement learning, which is used to reduce the probability of secondary accidents. The secondary accident variable speed limit prevention and control method based on deep reinforcement learning uses a coil detector to collect information, which is the traffic status upstream and downstream of the accident; the central speed limit controller receives and executes the intelligent networked vehicle traffic flow with a variable speed limit strategy; the method is: the coil detectors are evenly arranged at certain intervals along each lane of the highway, and return the traffic status to the central speed limit controller at a measurement interval of 30 seconds; when a traffic accident occurs, the secondary accident variable speed limit prevention and control system is triggered to initialize; the central speed limit controller issues a speed limit command, and the speed limit command is updated every 2 minutes; based on the DQN algorithm, according to the current traffic status s at time t returned by the coil detector t , the evaluation network calculates the Q value of each action in the current speed limit control action space, that is, the current Q value, and selects the action with the largest current Q value as the optimal speed limit action a t ; The speed limit command is issued to the intelligent connected vehicle in the environment, and the reward value r is obtained after the speed limit command is executed t ; Update the traffic status to s t+1 ; Use the target network to calculate the next traffic state s t+1 The target Q value of all actions is calculated; the parameters of the evaluation network are updated to determine whether the variable speed limit control is ended according to the accident situation.

The invention discloses an intelligent Internet of Things access management method based on dynamic encryption, particularly relates to the field of Internet of Things access control, and is used for solving the problem that when existing Internet of Things equipment is accessed, validity is not dynamically judged based on interaction behaviors, and session keys are not updated in real time. The method comprises the following steps: firstly, constructing a communication chain group based on a communication topology of registered equipment, and establishing an upstream and downstream interaction role identification table; distributing a temporary key when an access request is initiated, and extracting a communication record of a current communication period to form a data collaboration window; extracting an input response from the window, outputting a numerical value, executing feedback and an echoing state to generate a collaborative residual parameter, and matching the collaborative residual parameter with a collaborative behavior model of the communication chain group; if matching succeeds, extracting communication abstract features and a time window identifier to generate a key disturbance factor, and generating a current session key; and if matching fails, communication is rejected and key synchronization is blocked, so that dynamic encryption access control based on interaction feature driving is realized.

This invention provides a multi-protocol smart IoT gateway device, solving the problems of traditional gateways such as limited functionality and protocol support. It utilizes a MIPS 1004Kc dual-core chip for computing and integrates WiFi 6E, LoRa, and 5G modules to achieve multi-protocol convergence. The software is based on OpenWRT, featuring intelligent adaptive protocol stack dynamic parameter adjustment, encryption and authentication for security, and intelligent channel and power adjustment to optimize communication and energy consumption. It is suitable for smart cities, industrial IoT, and smart homes, providing a stable and reliable communication solution.

The application discloses an old-age physical exercise health monitoring data processing method and system based on a smart Internet of Things, relates to the technical field of health monitoring data processing, and comprises the following steps: collecting light intensity data, surface reflectivity data and acceleration data in the health monitoring data processing link, performing time alignment processing on the collected light intensity data, surface reflectivity data and acceleration data, and generating exercise scene time sequence features. The application constructs exercise scene time sequence features through multi-source data synchronous collection and time alignment, realizes the differentiation of light and motion interference, and combines inverse sampling and position marking to maintain signal continuity. Through intermittent shading rhythm linkage sampling rhythm and brightness threshold dynamic regulation of light sources, blood flow signals are corrected in real time, and the health monitoring data is stable and reliable.

The present invention discloses a method and system for intelligent remote supervision and early warning based on the Internet of Things, and belongs to the field of intelligent Internet of Things technology. The present invention obtains the state information of the target special equipment system and its associated systems in different fault warning task processes, and performs correlation analysis and state attribute identification, thereby refining state attribute knowledge that is crucial to fault early warning. Furthermore, by combining this knowledge with the fault early warning algorithm, the present invention can accurately reveal the potential fault hidden danger state of the target system in a specific operating action link, and provide strong support for the preventive maintenance and safety management of the equipment. In this way, the problem of insufficient accuracy and timeliness of traditional fault early warning methods can be solved, providing new guarantees for the safe operation of special equipment systems.

1. The name of this design product: Smart Internet of Things Experimental Workbench. 2. Purpose of this design product: Used as practical training equipment for artificial intelligence and professional laboratories in universities. 3. The key design point of this product lies in the combination of shape and color. 4. The picture or photo that best illustrates the design points: three-dimensional picture. 5. The design for which protection is sought includes color.

The present invention discloses a multi-source water environment data processing method and system based on intelligent Internet of Things, which relates to the field of data processing technology, including: standardizing the acquired multi-source heterogeneous water environment monitoring data, obtaining the standardized data, performing multi-scale decomposition, and obtaining low-dimensional data; using a distributed storage architecture for low-dimensional data, dispersively storing the data on several nodes, establishing a data index and metadata management mechanism, and performing data retrieval and access; for the low-dimensional data, using a stream data processing method to clean, aggregate and analyze, extract key indicators and events, and construct water quality abnormality warning rules by setting water quality parameter thresholds and change rate thresholds in combination with a decision tree method to determine whether there is water quality abnormality; and constructing a water quality prediction model by a support vector machine and a random forest machine learning method to predict water quality trends. The present invention provides strong technical support for water environment monitoring and management.

The present invention discloses a method for predicting intelligent IoT terminal data based on a time-series graph network model. The method comprises the following steps: inputting raw, unbatched IoT terminal interaction data information, performing a dot product operation on the data with time constraints of different time periods, and obtaining IoT information time-series features with time constraints; constructing a time-series graph network model; batch-processing the IoT interaction features with time constraints, and then passing them through a graph attention network to capture the spatial correlation of the IoT interaction network; using a gated recursive network to capture the temporal correlation; and outputting a predicted value using a linear function; calculating a loss function between the predicted value and the true value, performing a dot product operation on the data with spatial constraints based on spatial architecture, and optimizing the parameters of the time-series graph network model; and inputting the historical data of the IoT terminal to be predicted into the optimized time-series graph network model to obtain the corresponding prediction results. This method can effectively capture the spatiotemporal correlation information in the data and improve the prediction effect by utilizing time and space constraints.

The invention provides an energy consumption monitoring method and system based on an intelligent Internet of Things, and belongs to the technical field of energy consumption monitoring, and the method comprises the steps: collecting multi-dimensional energy consumption data and environment data in a park in real time, and compensating the multi-dimensional energy consumption data and environment data at an edge position; removing abnormal data to form effective multi-dimensional energy consumption data, and constructing a real-time energy consumption analysis model and an energy consumption prediction model; comparing prediction data in the energy consumption prediction model according to the real-time energy consumption analysis model until the energy consumption prediction model and the real-time energy consumption analysis model have continuous consistency; a visual platform is connected with the real-time energy consumption analysis model and the energy consumption prediction model, and an early warning module and a report generation module are carried. According to the energy consumption monitoring method based on the intelligent Internet of Things, multi-dimensional energy consumption data and environmental data in the park are analyzed, energy consumption is calculated, it is ensured that the accuracy of an energy consumption monitoring result is high, and functionality is higher.

The invention relates to the technical field of electric power energy storage, and particularly discloses an electric power energy storage system based on an intelligent Internet of Things, and the system comprises an acoustic emission detection module which is used for obtaining stress wave information in an energy storage battery; the sensor group comprises a gas sensor, a temperature sensor and a pressure sensor and is used for respectively acquiring characteristic gas concentration information and temperature information of the energy storage power station and pressure information of the energy storage battery; the energy storage battery parameter docking end is used for acquiring operation information of the energy storage battery; the energy storage management system is used for carrying out safety threshold judgment according to the information acquired by the acoustic emission detection module, the sensor group and the energy storage battery parameter butt joint end, and carrying out correlation analysis according to the stress wave information, the characteristic gas concentration information, the pressure information, the temperature information and the operation information when the judgment does not exceed the threshold range; and predicting the out-of-control risk of the energy storage battery according to an analysis result.

The invention relates to the technical field of Internet of Things air switches, in particular to an intelligent Internet of Things air switch. The air switch comprises an air switch main body and a pre-mounting plate connected with the bottom of the air switch main body, a clamping groove is formed in one side of the bottom of the air switch body, a first spring is arranged on the inner side of the bottom of the air switch body, the other end of the first spring is connected with a lock rod, the outer ring face of one end of the lock rod is sleeved with a first auxiliary sliding plate, and a shifting block is fixedly arranged on the surface of one end of the first auxiliary sliding plate. A lock hole is formed in the surface of one end of the clamping block. Through the pre-installation plate, the lock rod, the shifting block, the spring and other structures, the air switch body can be conveniently and rapidly disassembled and assembled in the subsequent use process, no auxiliary tool is needed in the disassembling and assembling process, compared with installation through bolts, installation is convenient, the whole air switch is more convenient and rapid, and higher practicability is achieved.

The invention relates to the technical field of power grid electric power, in particular to a low-voltage power distribution intelligent Internet of Things system device circuit, which comprises a protocol converter unit and a low-voltage power distribution intelligent Internet of Things device unit, and is characterized in that the protocol converter unit comprises a power supply conversion module, a first communication module, a first power line carrier communication module and a first MCU circuit module; the low-voltage power distribution intelligent internet-of-things device unit comprises a current monitoring module, a voltage monitoring module, a smoke sensing module, a temperature and humidity detection circuit module, a power conversion circuit, a liquid crystal display module, a second communication module, a second power line carrier communication module, a 4G communication module, a remote signaling module, a FLASH external expansion circuit module and a second MCU circuit module. The problems that an existing low-voltage power distribution unit area device cannot monitor environment temperature and humidity changes in a transformer room, cannot monitor the smoke condition in the transformer room and cannot give an alarm on fire smoke are solved.

The invention provides an advertisement putting effect evaluation method and device, electronic equipment, a storage medium and a program product, and can be applied to the technical fields of big data, artificial intelligence, Internet, advertisement putting and the like. The method comprises the following steps: receiving an advertisement putting request sent by a multimedia platform; user attribute characteristics of the target user and an offline evaluation result of the putting effect of putting the advertisement to the target user on the multimedia webpage are obtained from an offline database, the user attribute characteristics are determined based on user attribute information of the target user, and the offline evaluation result is determined through offline effect evaluation analysis based on the user attribute information; feature fusion is carried out on the advertisement space attribute information, the user attribute features and the offline evaluation result to obtain online fusion features, and the advertisement space attribute information is determined based on the advertisement putting request; and on the basis of the online fusion features, performing online effect evaluation analysis on the putting effect of putting the advertisement to the target user to obtain a target evaluation result.

The invention relates to the technical field of commodity packaging, in particular to a pre-packaging method and device for scattered commodities and a flat bag, and synchronous execution of weighing, sealing and code spraying procedures is achieved through an electromechanical collaboration architecture. The device adopts a modular design, the intelligent weighing unit is integrated with an AI visual identification system, the synchronous error of the hot-press sealing module and the static code spraying module of the synchronous execution mechanism is less than or equal to 100ms, and the intelligent control unit supports a multi-mode operation interface. The industrial practicability is reflected as follows: the efficiency innovation single piece treatment time is less than or equal to 4.5 seconds, the intelligent internet of things supports remote monitoring and traceability, and the matched polymorphic application of a flat bag not only solves the garbage bag breaking problem, but also can reduce the plastic consumption by 30%. The technical scheme solves the industrial problems of low packaging efficiency of bulk commodities, high cost of label consumables, plastic pollution and the like, can be widely applied to the fields of foods, medicines, agricultural and sideline products and the like, and assists in intelligent upgrading of the retail industry.

1. Name of the product in this design: Intelligent Internet of Things Electrothermal Actuator. 2. Intended use of this design: as an intelligent IoT electrothermal actuator. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention relates to the technical field of intelligent Internet of Things supply chain management, in particular to an intelligent Internet of Things-based supply chain platform data management system, which comprises a data acquisition module, a contract execution module, a node control module, a credit evaluation module and a data asset module. The data acquisition module acquires material physical state information to generate a supply chain panoramic data stream; the contract execution module extracts key performance data and automatically verifies the key performance data according to intelligent contract logic, and generates a credible contract execution signal if a condition is met; the node control module triggers logistics and storage nodes to automatically control and synchronously update resource state records according to the signals; the credit evaluation module extracts features to generate a financial evaluation vector and calculates a dynamic credible score; and the data asset module is packaged into a standardized asset packet to synchronously authorize the alliance node. The system can realize the technical effects of contract automatic execution, node linkage control, credit dynamic evaluation and alliance collaborative decision.

The invention relates to the technical field of intelligent Internet of Things, and particularly provides a distributed credential equipment control docking method and device, and the method comprises the steps: enabling credential equipment to receive or transmit a control instruction through subscribing a specific theme or queue; internet of Things middleware is developed based on the go language, multi-architecture environment adaptation is achieved, and message transmission, routing and persistence are carried out; based on a standard Internet of Things protocol, data and a management instruction are transmitted through a message protocol, and Internet of Things equipment and intelligent agent equipment at an opposite end are managed, controlled and linked, so that message management and remote control of the equipment at the opposite end are realized. Compared with the prior art, data and management instructions can be transmitted through the message protocol, and the Internet of Things equipment and the intelligent agent equipment at the opposite end are managed, controlled and linked, so that message management and remote control of the equipment at the opposite end are realized.

A method for managing communication between Internet of Things (IoT) nodes in an IoT environment with an IoT hub involves using a high-power initiator node to request services and identify a candidate intelligent device among the nodes. Depending on a parameter of the initiator node, the intelligent device can flexibly operate as a low-power, high-power, or hybrid device. The method can include selectively assigning the intelligent device as a trusted designated node within the IoT environment. Furthermore, the method includes determining, based on the parameter, an optimal periodicity for communicating status messages from the trusted designated node to the IoT hub.The procedure then involves transmitting the status messages to the hub with the optimal periodicity via the trusted designated node, so that the trusted designated node acts as a proxy for the initiator node when it reports the status messages to the hub.

The present invention discloses a smart Internet of Things gateway management method, comprising the following steps: the gateway receives raw data, constructs data parsing rules, and sets various data parsing nodes required for use in the data parsing process, with each data parsing node being used for a step in the data parsing process; according to the sequence of the various steps in the data parsing process, determines the sequence of the various data parsing nodes and the correspondence between two adjacent data parsing nodes, and constructs the data parsing rules; for the raw data received by the gateway, edge computing runs the data parsing nodes one by one according to the sequence of the data parsing nodes determined by the data parsing rules to process the received data, thereby completing formatting of the raw data received by the gateway and obtaining data that meets the data format requirements of a destination platform; and pushing data: sending the data obtained by parsing the raw data received by the gateway to a server of the destination platform.

The application discloses a kind of multi-scene equipment communication methods and electric energy meter based on intelligent internet of things electric energy meter, it is related to electric energy meter communication technical field, comprising: obtaining voltage sampling sequence and current sampling sequence, according to signal zero crossing and disturbance event starting point determine phase anchor point, and combine event register and measurement state to determine scene number;With phase anchor point as center, extract integer fundamental period window, calculate voltage total harmonic distortion, current total harmonic distortion, harmonic amplitude and equivalent impedance amplitude, generate measurement fingerprint, and combine table in counter derived time slot seed;According to scene number configuration time slot length and maximum waiting time delay, based on measurement fingerprint and time slot seed, determine sending time slot and sending time, and after combining bearing state table selects main communication bearing and standby communication bearing, send message, and based on receipt check switch retransmission, to improve time slot determination accuracy, sending real-time and communication stability.