993 results about "Device type" patented technology

An AI-driven system for personalized advertising in real time, where: ◯ an analytics unit to monitor and analyze user behavior in real time across multiple digital platforms such as websites, mobile applications, social media, and smart devices; the unit collects data on user engagement, browsing patterns, time spent, and content preferences to enable targeted, personalized advertising; ◯ a prediction module that predicts preferences and interests of a user, operatively connected to the user interaction data collection unit, wherein the prediction module uses machine learning models such as deep learning, recurrent neural networks (RNNs) and transformer-based architectures to predict interests of users based on historical interactions and inferred preferences; ◯ an emotion and sentiment analysis unit that assesses the user's mood in real time through computer vision, natural language processing (NLP) and voice analysis, whereby the analysis of facial expressions, voice pitch and linguistic mood is used to determine emotional states and receptivity to advertising content; ◯ an embodiment of a context awareness component in operational communication with the emotion analysis and mood unit, in some cases further augmented by various environmental and situational data such as the device type and its physical location, date and time, and the content processed in the device, processing methods, etc., in establishing adaptability and automatic ad placement to be as relevant as possible to the user and their status as prescribed; ◯ Use reinforcement learning algorithms and generative AI models to drive advertising with personalization engines. Creative elements, messaging, and presentations are dynamically adjusted in real time based on user responses to ensure advertising is personalized and always optimized for best performance; o a privacy-focused AI system with federated learning, differential privacy methods, and on-device AI processing to reduce targeted advertising while complying with international data protection laws such as the General Data Protection Regulation (GDPR) and California consumer privacy laws; o an operationally adapted ad delivery mechanism to engage with real-time bidding (RTB) networks, programmatic advertising exchanges and demand-side platforms (DSPs) and place advertisements through digital advertising networks, which guarantees the delivery of tailored advertising to the most relevant audience in real time; and o a contextual feedback loop in which the machine learning models used in the preference and interest prediction module and in advertising personalization The engine is continuously updated to reflect the latest user engagement data, improving personalization over time and optimizing advertising performance.

The invention discloses an intelligent multi-dimensional automatic inspection operation and maintenance management method, device and equipment, relates to the technical field of network inspection, and aims to solve the problems that the inspection efficiency of network equipment is low and fault early warning is lagged. The method comprises the following steps: scanning equipment in a target machine room to establish an equipment registration file, wherein the registration file comprises an equipment type identifier and an associated inspection strategy template; collecting multi-dimensional data of each registered device according to the inspection strategy template, wherein the multi-dimensional data comprises a hardware operation state, a business middleware state and an environment monitoring parameter; determining abnormal data from the multi-dimensional data according to a preset dynamic threshold value, and generating and issuing graded alarm information according to the influence degree of the abnormal data; and creating a work order according to the abnormal data and automatically distributing the work order so as to process the abnormal data.

Techniques for processing with respect to a user input as contextual information is available are described. A system generates a first task prediction using first context data that is available when a user input is received. The system generates a second task prediction (e.g., updated first task prediction) when second context data is received, and then further generates a third task prediction when third context data is received. Example first context data may include device type information, time information, location, etc. Example second context data may include automatic speech recognition (ASR) data. Example third context data may include natural language understanding (NLU) data. Using the third task prediction, the system generates an output responsive to the user input.

Techniques for enforcing policies on Internet of Things (IoT) device communications are disclosed. Information associated with a network communication of an IoT device is received. The received information is used to determine a device profile, including a device type, to associate with the IoT device. A recommended security policy to be applied to the IoT device by a security appliance is generated.

The invention provides a production collaborative management method and system for a digital factory, and the method comprises the steps: calculating an affinity matrix between devices based on the physical positions, communication delays, device types and historical collaborative relationships of the devices, determining the collaborative weights of heterogeneous devices, and obtaining a device collaborative networking scheme; calculating a time sequence score according to the task completion quality, the energy consumption efficiency, the equipment stability and the collaborative adaptability of each equipment group, and performing dynamic weight adjustment in combination with environment monitoring data to obtain an equipment credit score; performing initial task allocation based on the equipment credit score, and performing continuous bias analysis and resource balancing by analyzing data in a task execution process to obtain a dynamic task allocation strategy; and finally, evaluating the collaborative effect of the equipment group according to the task allocation strategy, and dynamically optimizing the equipment group to obtain a collaborative evolution scheme. According to the method, the problem of unreasonable equipment resource allocation is effectively solved through a dynamic evaluation and balance mechanism.

The invention relates to the technical field of Bluetooth communication, and discloses an optimization method for secure communication of Bluetooth chip equipment. The method comprises the following steps: identifying a device type identifier and a protocol version feature, extracting a hardware capability parameter and generating an initial security policy set; collecting channel data, and calculating a stability index and a dynamic noise baseline; then, screening and sorting security policies to generate an execution queue, adjusting an encryption strength threshold according to a noise baseline to perform iterative optimization, and outputting final policy configuration; and when the target Bluetooth chip establishes the communication connection, loading the final security policy configuration and monitoring the channel state in real time, and triggering a policy dynamic switching mechanism when the channel state change exceeds the preset tolerance so as to optimize the security communication effect of the Bluetooth chip equipment. According to the method, the security policy can be accurately matched with the device and the channel state, the policy is dynamically adjusted, and the security and the stability of communication of the Bluetooth chip device are effectively improved.

The invention discloses an MQTT message transmission optimization method and system. The method comprises the steps of analyzing a theme, extracting a device type, a data feature and a geographic position triple, calculating a hash value, and mapping a device to a specified Broker fragment cluster node to generate a fragment mapping table; processing the equipment data in the edge domain in the fragment mapping table through an edge calculation layer, removing invalid data according to a preset rule, merging the equipment data in the same fragment node, and embedding a fragment node ID for an aggregation message generated after merging; identifying a fragment node ID and routing to a target fragment node, positioning a corresponding shared memory pool, and writing the message into the shared memory pool; and responding to a direct access request of the client, so that the client directly accesses the data from the shared memory pool through the user mode network stack. According to the method, the problem of uneven load is effectively solved, multiple times of state switching in the data transmission process is avoided, and the MQTT message transmission efficiency is improved while the transmission cost is reduced.

In some embodiments, the present disclosure provides an exemplary method that may include steps of obtaining data associated with a device within a network; determining a software being performed via type information of the device based on a scan of the network and data associated with the device; generating a type label for the device based on the software being performed; and generating, by the processor, a network security map that represents a topology of the network, wherein the network security map maps the device within the topology according to the type label so as to facilitate causing at least one security action with respect to the device within the network.

The invention relates to the technical field of data security, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a dynamic function menu generation method, device, equipment and medium, which comprises the following steps: acquiring an access request containing equipment type information sent by a user terminal, analyzing an authentication state of a user account and an associated license state, and sending the access request to the user terminal; and generating a dynamic session context defining function access qualification and an interface rendering strategy, loading a function menu strategy model containing function item set and permission mapping, determining a target permission level, matching a target function item subset with a rendering strategy, and generating and sending a function menu instance to the user terminal. The dynamic session context is generated in real time in combination with the user authentication state and the license state, linkage of permission judgment and interface rendering is driven, the function menu has the capacity of dynamic switching according to the session state, menu generation and accurate issuing based on actual authorization and the equipment environment are achieved, and unauthorized access is effectively avoided.

The invention relates to the field of industrial Internet of Things, in particular to an edge computing communication method and system for the industrial Internet of Things, and the method comprises the following steps: 1, a user issues a task to a service platform through a user platform, and after the service platform receives a task request, the service platform sends the task request to the user platform based on a device type and a task type associated with the task; classifying and marking the tasks, and determining real-time levels of the tasks and importance weights of associated production links; 2, the service platform transmits the classified tasks to a corresponding service sub-platform, the service sub-platform obtains historical operation data and edge node basic information of task associated equipment, generates a first calculation task carrying a task attribute tag according to a classification result, and sends the first calculation task to a management platform; and step 3, the management platform carries out unified management on the plurality of first computing tasks. By adopting the technical scheme of the invention, industrial scene characteristics can be fit, and task priority, resource dynamics and network adaptability are considered.

The invention discloses a multi-terminal collaborative modular power operation and maintenance method and system based on digital twinning, and the method comprises the following steps: constructing a global power topological graph of a power energy site, mapping power equipment, sensors and connecting lines into graph nodes and graph edges, and binding the static attributes of the equipment with the topological structure; and acquiring real-time operation data of the power equipment, and distributing a unified time label for the multi-source heterogeneous data. According to the method, a unified twinborn model of cross-voltage class, cross-region and cross-equipment type is established in a digital twinborn platform, and operation data of different equipment such as photovoltaic equipment, battery energy storage equipment, an inverter, a protection device, an electric energy meter and temperature control equipment are expressed in a unified data semantic mode; according to the invention, the system can still automatically establish a consistent device portrait under the conditions of a large number of multi-terminal devices and diversified communication protocols, and the multi-terminal cooperative computing capability is significantly improved.

A system and method for inferring device types. A method includes selecting a device type inference model from among a plurality of device type inference models based on a manufacturer of a device, wherein each device type inference model corresponds to a respective manufacturer and is trained using training data of devices manufactured by the respective manufacturer, wherein each device type inference model is trained to output a device type prediction; and determining an inferred device type for the device, wherein determining the inferred device type for the device further comprises applying the selected device type inference model to a plurality of features, wherein the plurality of features is extracted from device activity data indicating ports used by the device and at least one volume of traffic communicated via each port used by the device.

The invention provides a flow and form decoupling cooperative processing method, and relates to the technical field of business flow management, and the method comprises the steps: constructing a layered architecture, separating a flow control layer from a form service layer, defining a flow node jump rule by the flow control layer based on a BPMN standard, and dynamically defining a form structure by the form service layer through JSON Schema; a form identifier is declarated in the process definition file, a corresponding form template is matched through a dynamic mapping service according to context information, and the context information comprises a process instance state, a user role, a device type and a service type; establishing a data sandbox isolation mechanism, generating a unique data space identifier for each process instance, and managing data access authority through a multi-dimensional isolation strategy of a tenant level, a service level and a process instance level; deploying an event bus communication mechanism, triggering two-way communication between a process engine and a form engine through a predefined event type, and ensuring the consistency of cross-system operation by adopting a transaction compensation mechanism.

The invention discloses an Internet of Things equipment automatic identification method and device based on a cellular network environment and a storage medium, and the method comprises the following steps: S1, collecting IP flow information of Internet of Things equipment, exporting record data, and storing the record data to a flow data storage module; s2, extracting equipment traffic features, generating feature vectors, and storing the feature vectors in a feature database; s3, training an equipment identification model by using an improved structure sparse variational automatic encoder in combination with a space-time diagram convolutional network, and extracting an equipment traffic mode and behavior topological characteristics; s4, optimizing model training by adopting a category balance loss function; s5, collecting real-time flow data of to-be-identified equipment, converting the real-time flow data into feature vectors, inputting the feature vectors into the identification model, and calculating a matching result through cosine similarity; and S6, setting a similarity threshold value, outputting the type and the model of the equipment, or marking and storing unknown equipment. According to the method, the identification accuracy and the real-time performance are improved, and the identification capability of the shared IP equipment and the small sample equipment is enhanced.

The embodiment of the invention provides a memory resource allocation method and electronic equipment, and relates to the field of computers.The method comprises the steps that a first resource reference value corresponding to a slot position is determined from a plurality of memory resource reference values corresponding to a plurality of equipment types, the slot position supports equipment insertion of the multiple equipment types, and the first resource reference value corresponds to the slot position; one device type corresponds to one resource reference value; adjusting the first resource reference value based on the physical attribute of the slot position and the performance attribute of the slot position to obtain a second resource reference value corresponding to the slot position, and pre-allocating a reference memory resource of the second resource reference value to the slot position; when it is detected that the target device is effectively inserted into the slot position, determining a target resource demand value corresponding to the target device according to the register information of the target device; and allocating a target memory resource of the target resource demand value to the target device from the reference memory resources.

The invention provides a one-master multi-slave type high-speed serial communication and synchronous control method and system and a medium, and the method comprises the steps: firstly, resetting slave stations based on an initialization instruction, and sequentially transmitting equipment type query instructions based on a physical connection sequence, thereby completing the topology recognition of the slave stations; then, aggregated data frames are periodically constructed, a frame header is written into a master station status word, a frame body is formed by splicing slave station data packets according to a station number sequence, and a frame tail is a check code; and finally, the slave station analyzes the aggregated data frame based on the station number, executes the task, and feeds back a task execution result according to a physical inverted sequence. In addition, when a new slave station is accessed, the master station switches a status word and triggers the whole system to be reinitialized, and the new slave station is dynamically incorporated into the topology; according to the invention, the expansibility, the real-time performance and the reliability of multi-node synchronous control in an industrial scene are comprehensively improved.

The invention provides a Bluetooth equipment battery endurance test method, which is characterized in that a Bluetooth signal is sent and / or received through a Bluetooth adapter, a voltage value of a battery is acquired through a power supply monitoring module, and the method comprises the following steps: when a user tests Bluetooth equipment, the Bluetooth signal and the voltage value of the Bluetooth equipment are acquired; determining the device type of the Bluetooth device according to the Bluetooth signal, and determining an operation instruction through the Bluetooth device type; performing power consumption operation on the Bluetooth equipment according to the operation instruction; and determining the endurance of the battery of the Bluetooth equipment according to the Bluetooth signal and the change of the voltage value. The Bluetooth signal and the voltage value are acquired at the same time, so that the cruising ability of the Bluetooth equipment is measured, a real use scene is simulated, the Bluetooth equipment is fully automatically tested, manual operation is not needed in the process, and the test is efficient and accurate.

The present application relates to the technical field of computers. Provided are an automatic identification circuit for an external device to a Type-C interface, an electronic device, a server, and an identification method. A power mode judgment port and a power output control port of a Type-C interface are respectively connected to CC1 and CC2 pins of a logic judgment device, the level of the CC1 and CC2 pins being used for determining whether the interface is connected to a USB port and determining a device type corresponding to the USB port. An SCL pin is connected to a bus pin of a baseboard management controller. An SDA pin is connected to an interrupt pin of the baseboard management controller. An output end of a power management module is separately connected to power pins of the interface and the logic judgment device. An enabling end of the power management module is connected to a first GPIO pin of the baseboard management controller. The present application realizes direct connection between interfaces and external devices such as mobile terminals, thus reducing complex interface designs of servers and lowering the maintenance cost, and furthermore, can supply power to external devices by means of the power management module.

The invention discloses a hybrid advertisement carousel system based on dynamic optimization, and the system comprises the following modules: a data collection module which obtains user behavior data, an advertisement effect index and an environment variable in real time, the user behavior data comprises a click rate, a stay time length and an interaction frequency, and the environment variable comprises a time period, an equipment type and a network state; and the dynamic analysis module is used for analyzing the data acquired by the data acquisition module based on a machine learning model. When the method is implemented, the method has the following effects that the advertisement revenue is improved, the exposure ratio of the high-value advertisement is remarkably improved through dynamic optimization, and the rate of return on investment of the advertisement can also be improved; the resource utilization rate is high, traffic changes are responded in real time, the advertisement filling rate is remarkably improved, more advertisements can be played, and idle resources are reduced; the method is flexible and extensible, supports the quick adaptation of multiple advertisement forms and multiple terminal scenes, and puts advertisements according to the requirements of advertisers.

The invention relates to a hardware driving method supporting multiple operating systems, a driving program is divided into an equipment layer and a connection layer, the equipment layer comprises corresponding logic for operating hardware, and the connection layer comprises adaptive codes of the corresponding operating systems; the method specifically comprises the steps that 1, an equipment layer is constructed, same functions are sorted out for equipment of the same type, an equipment type model is abstracted, and a cross-platform unified interface specification is designed according to hardware functions, and the unified interface specification comprises multiple types of interfaces; 2, specific functions are achieved based on the cross-platform unified interface specification designed in the step 1; 3, creating a connection layer; and step 4, realizing the operation of the upper operating system on the equipment on the connection layer. According to the invention, for drive development, the processing modes of asynchronous and synchronous modes are unified, and the development cost is reduced. The hierarchical design function division of the equipment layer and the connection layer is clearer, and the code maintainability is improved.

The invention provides a self-adaptive PD charging control method and system based on a double Type-C circuit and a storage medium, and the method comprises the steps: monitoring an interface connection state in real time, collecting power-on current information when peripheral access is detected, and intelligently recognizing a device type in combination with a preset current threshold range and a PD protocol handshake process. The function change-over switch and the charging management module are dynamically configured; if the device is a data device, a data path is connected and power output is limited; if the device is a charging device, charging parameters are negotiated and high-power transmission is started; when the double charging devices are connected, intelligent power distribution and priority management are executed, electrical parameters such as voltage, current and temperature are continuously monitored, and self-adaptive adjustment is triggered when the voltage, the current, the temperature and the like exceed the limit. According to the invention, intelligent function switching and safe power management of double interfaces are realized, the risk of misplug damage is effectively avoided, and the equipment compatibility, the system energy efficiency and the user experience are improved.

The invention relates to an equipment monitoring graph generation method, device and equipment. The method comprises the following steps: acquiring a source equipment graphic file of the same equipment type as to-be-processed equipment; acquiring a plurality of first equipment measuring points from the source equipment graphic file, and acquiring first equipment information of the source equipment and first measuring point information of each first equipment measuring point from the centralized control system; acquiring second equipment information of the to-be-processed equipment and second measuring point information of each second equipment measuring point contained in the to-be-processed equipment from the centralized control system; based on the first equipment information and the second equipment information, acquiring target source equipment matched with the to-be-processed equipment from the source equipment, and based on each piece of first measuring point information and each piece of second measuring point information, acquiring an association relationship between each first equipment measuring point and each second equipment measuring point contained in the target source equipment; and processing the source device graphic file of the target source device according to the association relationship to obtain a graphic file of the to-be-processed device. The method can improve the graph generation efficiency.

The present application relates to the field of communication technology, and provides an application permission activation method, medium, and electronic device, which can activate the permissions of applications or in-application services in lightweight devices through full-scale devices, and promote the application ecology of smart wearable devices and the like to be more prosperous. The method includes: in response to the operation of opening a first application installed in a first device, the first device determines the permission activation status of the first application; when the permission activation status is not activated, the first device sends a first message to the second device, and the first message includes the device type of the first device and the permission activation status of the first application; when the second device determines that the device type is a preset type and the permission activation status is not activated, the second application in the second device is opened, and the second application has an associated relationship with the first application; the second device uses the second application to activate the permissions of the first application; the second device sends a second message to the first device, and the second message is used to indicate that the permissions of the first application have been activated.

The invention discloses an operation and maintenance management method for a DFMA assembly type machine room, and relates to the technical field of machine room management, and the method comprises the steps: obtaining the type, size, power consumption and environment requirement data of all equipment in the machine room, and building an equipment information database; according to the equipment information database, space utilization rates under different equipment combinations are calculated, and an equipment density distribution diagram is generated; a thermodynamic simulation model is adopted to simulate the heat dissipation performance under the density distribution diagram of the equipment, and temperature field distribution data are obtained; for different equipment types, dividing temperature and humidity control areas, establishing an environment control strategy, and generating an environment control scheme; a machine learning algorithm is adopted, the temperature and humidity change trend is predicted according to historical data, and a control strategy is automatically adjusted; maximization of the space utilization rate of the machine room is achieved, safe and stable operation of equipment is guaranteed, and a scientific basis is provided for future expansion of the machine room.

Provided in the embodiments of the present application are an interconnection link control method and apparatus, a nonvolatile readable storage medium and an electronic device. The method comprises: reading first device information of a target storage device from a specified configuration space of the target storage device, the target storage device being a storage device connected to a target processor on a server mainboard by means of a specified interconnection link, and the first device information being used for indicating the device type of the target storage device; when the target storage device being of a specified type is determined on the basis of the first device information, acquiring second device information of the target storage device, the second device information being used for indicating the specified interconnection link used for connecting the target storage device to the target processor; and enabling a volume management device (VMD) function of the target interconnection link indicated by the second device information, the VMD function being matched with the storage device of the specified type.

The embodiment of the invention discloses an artificial intelligence advertisement generation method and device based on a user portrait, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence advertisement generation, the method comprises the steps that user behavior information and equipment state information are acquired, and the user behavior information comprises historical behavior data and real-time behavior data; determining a device type and a network state according to the device state information; determining attention state information of the user according to the user behavior information; generating a multi-dimensional user portrait according to the equipment type, the network state and the attention state information; determining an advertisement length type according to the user portrait, wherein the advertisement length type comprises an ultra-short type, a relatively short type and a complete type; and generating an advertisement according to the advertisement length type and the user portrait by using the advertisement editing model. The problem that a traditional advertisement generation method is insufficient in flexibility and low in accuracy is solved.

The invention relates to the technical field of power bank control systems, in particular to an AI voice-based power bank control system, which comprises a voice interaction module, an equipment recognition module, an environment sensing module, a dynamic charging management module and a control center module, the voice interaction module is used for receiving a voice instruction of a user and analyzing the instruction content through a natural language processing technology; the device identification module is used for detecting the type of a connected device and a charging protocol, and obtaining the real-time charging demand of the device. The environment sensing module is used for acquiring an environment noise value # imgabs0 # and a temperature value # imgabs1 # of a charging environment; and the dynamic charging management module is used for dynamically adjusting the output power according to the equipment type, the environmental parameters and the historical charging data of the user. According to the invention, through environment perception and dynamic threshold determination, the voice interaction robustness is optimized, real-time adaptive adjustment of the charging strategy is realized, and the method is especially suitable for complex scenes such as travel, outdoor and the like.

The invention provides a high-performance virtual scrolling method and system supporting a large-scale tree structure, and the method comprises the steps: constructing a dual-mapping data table structure of the tree structure, which comprises a node mapping table and a sublevel relation mapping table; when it is detected that the node height changes, the virtual rolling rendering engine generates a flattened rendering list in real time based on the unfolding state of the corresponding node in the node mapping table; the virtual rolling rendering engine calculates rendering positions of nodes in the visual area through a dynamic position prediction algorithm; in response to the rendering location and the device type, the virtual scrolling rendering engine dynamically adjusts the virtual scrolling window and the tree structure node hierarchical indentation pitch, and renders in the virtual scrolling window according to the flattened rendering list. According to the application, the data relationship and the rendering position are decoupled through the double-mapping data table structure, the smooth rolling of ten thousand-level nodes can be realized, the memory occupancy rate is reduced, the interaction response speed and the rendering performance are improved, and the method has rolling stability, cross-device display consistency and deployment flexibility.

The invention discloses a distributed power distribution network terminal test method and system based on a cloud platform, terminal equipment and a computer readable storage medium. The method comprises the following steps: acquiring the equipment type of each to-be-tested power distribution network terminal; for each to-be-tested power distribution network terminal, generating a task set containing one or more test tasks and a corresponding task deadline according to the equipment type; determining a priority sequence of each test task according to the equipment type to which each test task belongs and the corresponding task deadline; obtaining a resource state of each test node in the cloud platform in real time; according to the resource state of each test node, distributing each test task to the test node according to a corresponding priority order, so that the test node obtains a test script and test data according to the received test task, tests the corresponding power distribution network terminal, and obtains operation data of the power distribution network terminal; and inputting the operation data into the analysis model to generate a test report. According to the invention, the test efficiency of the terminal is improved.

The invention discloses a method for heterogeneous scheduling of computing power under a large model training reasoning framework, relates to the technical field of computing power scheduling, and solves the technical problem that task interruption or resource waste is easily caused by incomplete task migration, splitting and recovery mechanisms when computing power is insufficient or equipment is abnormal. According to the method, parameters such as the load rate, the residual computing power and the temperature of the CPU, the GPU and the FPGA are dynamically collected, the calculation amount, the duration and the delay requirement of the task are combined, a quantitative model is established, the resource utilization rate is increased, a temperature prediction model is established in stages, a dynamic threshold value is set in combination with the equipment type, the environment temperature and the health degree, temperature early warning and migration in the task execution process are achieved, and the task execution efficiency is improved. The frequency reduction risk caused by overheating of equipment is reduced, the task interruption loss is ensured to be reduced by more than 50% through task splitting, intelligent migration and pause recovery mechanisms aiming at insufficient computing power or equipment abnormity, and the stability of the system during peak flow or hardware failure is improved.