176 results about "Command and control" patented technology

Disclosed in the present invention are an aviation equipment reliability evaluation method and system based on a knowledge graph and model inference. The method comprises: acquiring data of human factors, equipment systems, and a working environment of aviation equipment; carrying out preprocessing and text labeling on the acquired data; inputting the labeled text information into a constructed entity relationship joint extraction model to form a high-quality structured triple of the knowledge graph; constructing an elastic knowledge graph for the aviation equipment, wherein the elastic knowledge graph comprises an online knowledge graph and an offline knowledge graph which has aviation equipment reliability; and extracting semantic features, and analyzing the similarity between the extracted features to realize indirect inference of the aviation equipment reliability. The present invention fully fuses expert experience and knowledge data, and exerts respective advantages of a human brain and machine intelligence, so as to achieve accurate analysis and prediction of aviation equipment reliability, thereby providing intelligent risk analysis, early warning and optimization suggestions for command and control personnel, and reducing a fault occurrence rate.

The invention relates to the field of wireless communication and intelligent networks, in particular to a software defined radio-based ad hoc network dynamic slicing architecture and a management and control method, comprising a basic communication layer, an intelligent control layer and a service execution layer. The basic communication layer adopts a multi-distribution multi-center clustering architecture; the intelligent control layer is responsible for intelligent management and resource scheduling of the self-organizing network, and the intelligent control layer comprises a plurality of command and control nodes; and the service execution layer adopts a micro-service-based architecture, and encapsulates different network functions and service logics into independent micro-service modules. According to the method, the technical problems of high plane coupling, resource scheduling rigidness, insufficient survivability and high hardware dependency in the prior art are solved.

Various techniques for providing deep learning for inline detection of malicious command and control (C2) traffic from unstructured payloads are disclosed. In some embodiments, a system / process / computer program product for providing deep learning for inline detection of malicious C2 traffic from unstructured payloads includes monitoring a session at a security platform, wherein the session includes network traffic; executing a local deep learning model on the network traffic, wherein the local deep learning model is a machine learning implemented C2 (MLC2) model executed on the security platform; and performing an action in response to determining that the monitored session is associated with malware based at least in part on a verdict from the deep learning model.

The technology disclosed relates to a method, system, and non-transitory computer-readable media that detects malicious communication between a command and control (C2) cloud resource on a cloud application and malware on an infected host, using a network security system. The network security system reroutes the cloud traffic to the network security system. The incoming requests of the cloud traffic are directed to a cloud application in the plurality of cloud applications, and wherein the cloud application has a plurality of resources. The network security system analyzes the incoming requests, determines that the incoming requests are targeted at one or more malicious resources in the plurality of resources. Also, the network security system prevents transmission of the incoming requests to the malicious resources, by making the malicious resources unavailable for receiving future incoming requests, while keeping other resources in the plurality of resources available for receiving the future incoming requests.

The invention discloses a GIS-based artificial influence weather operation command method and device, and the method comprises the steps: obtaining meteorological data and geographic information data, and carrying out the spatial registration of the meteorological data and the geographic information data according to latitude and longitude coordinates, and obtaining the initial data after registration; determining a first target area according to the geographic information data; analyzing the weather data of the first target area based on the initial data, determining an operation mode according to an analysis result, and formulating an operation sowing amount based on the operation mode; and carrying out weather operation in the first target area by using the operation equipment according to the operation mode and the operation sowing amount. According to the invention, through integration of the GIS and the meteorological data, accurate command and control of artificial influence weather operation are realized, and the operation efficiency and effect are improved.

The invention discloses an environment perception and command control intelligent deduction platform based on bionic unmanned equipment, and relates to the field of intelligent deduction, and the platform comprises the steps: collecting environment data through a multi-mode sensor, encrypting the environment data through an anti-interference communication relay module, and transmitting the encrypted environment data to a central control platform; the data fusion preprocessing module is used for processing multi-source data and outputting a structured data stream, and the environment intelligent modeling module is combined with a geographic information system to construct a three-dimensional dynamic environment model; an intelligent deduction module carries out multi-scene deduction based on the model, and a self-adaptive control strategy generation module converts a decision tree into an anti-disturbance control sequence; and the man-machine collaborative decision-making module fuses operator intervention to generate a final instruction, and the instruction distribution and equipment collaborative control module issues the instruction to the bionic unmanned equipment to realize intelligent collaborative control. The method has the advantages that bionic perception, anti-interference communication and intelligent deduction are integrated, efficient cooperation and adaptive control of unmanned equipment in a complex environment are achieved, and the intelligence and robustness of task execution are remarkably improved.

The invention discloses a simulation platform for autonomous tracking of a subsea pipeline by a UUV. The simulation platform comprises a mother ship command and control node system used for issuing a task instruction to a UUV motion control and situation display system; the UUV motion control and situation display system is used for sending a course adjustment instruction to the UUV underwater unmanned vehicle and carrying out real-time graphical dynamic display on the navigation information of the UUV underwater unmanned vehicle; the UUV side-scan sonar model system is used for receiving the motion attitude information of the UUV underwater unmanned vehicle and carrying out detection result data production calculation on a target area in combination with the motion attitude information; the UUV subsea pipeline detection and identification system is used for carrying out pipeline identification according to side scanning detection result data and sending pipeline information to the UUV pipeline tracking strategy system; the UUV pipeline tracking strategy system is used for calculating the track information of the UUV underwater unmanned vehicle according to the pipeline information and the navigation information of the UUV underwater unmanned vehicle, and sending the track information to the mother ship command control node system.

The invention relates to the technical field of unmanned aerial vehicle radio detection, in particular to an unmanned aerial vehicle detection and judgment method based on cooperation of an air-ground system and radio detection, and the method comprises the steps: finding a suspected target through scanning of a multi-frequency-band radar, triggering an infrared thermal imager carried by an aerial unmanned aerial vehicle to approach an ultra-wide-frequency-band spectrum sensor for verification; accurate positioning is realized by combining ground photoelectric equipment multi-view triangulation positioning and a signal arrival time difference algorithm, a command and control center calculates threat levels through a multi-source data fusion engine, and navigation decoy of dynamically adjusting intensity is adopted for targets smaller than or equal to two levels. Hard killing of ground laser locking rotor center and air electromagnetic pulse synchronous coverage is executed on a target of more than or equal to three levels, the equipment state is synchronized in real time through an optical fiber link, high-energy-consumption equipment is intelligently closed after threat is relieved, a platform starting strategy is optimized, a detection closed loop of'three-dimensional perception-graded treatment-intelligent energy saving 'is constructed, and the intelligent energy saving effect is achieved. And an efficient and accurate low-altitude safety protection scheme is provided for a sensitive area.

The invention discloses a mooring type low-altitude monitoring countering unmanned system based on deep learning target recognition. The mooring type low-altitude monitoring countering unmanned system comprises a mooring unmanned aerial vehicle platform module, a multi-source sensing and data fusion module, a deep learning target recognition and classification module, a self-adaptive countering decision and execution module, a dynamic tracking and collaborative aiming module and a ground command and control module. The mooring unmanned aerial vehicle platform module forms a stable air monitoring and countering base point; the multi-source sensing and data fusion module provides high-quality input for system identification; the deep learning target recognition and classification module recognizes and predicts a target behavior through deep learning; the self-adaptive countering decision and execution module realizes precise countering; the dynamic tracking and collaborative aiming module applies counter energy to a dynamic target; the ground command and control module provides a human-computer interaction interface and displays global information. The low-altitude active defense system has the advantages that technologies such as multi-source fusion perception, deep learning AI recognition and self-adaptive precise countering are deeply fused, and the low-altitude active defense system is formed.

Method, apparatus and systems are disclosed that may be implemented in wireless transmit / receive unit (WTRU), an unmanned aerial vehicle (UAV) and / or a UAV-controller (UAV-C). In one representative method, the UAV may switch from a first Command and Control (C2) communication link between a UAV and a first UAV-C to a second C2 communication link for C2 communications. The method may include determining, by the WTRU, to switch C2 communications from the first C2 communication link to the second C2 communication link based on a C2 switching condition; sending, by the WTRU to a C2 control entity, a notification indicating link information used to determine switching from the first C2 communication link to the second C2 communication link; receiving, by the WTRU from the C2 control entity, information indicating a switch; and switching, by the WTRU, C2 communications from the first C2 communication link to the second C2 communication link.

The invention relates to the technical field of heat exchangers, in particular to a collaborative design and control method, device and equipment for a heat exchanger and a storage medium, and the method comprises the steps that operation data of a target heat exchanger under at least one working condition are collected, and performance coefficient data meeting preset performance conditions are output through a multi-target collaborative optimization model; after operation is conducted according to the performance coefficient data, the flow value, the pressure value and the temperature value of the target heat exchanger are collected, and a corresponding adjusting instruction is determined; and based on the digital twin body, determining performance attenuation data and / or a fault diagnosis result, further generating an optimization instruction, and controlling the target heat exchanger. Therefore, the problems that in the related technology, under the variable load working condition, when the load deviates from a design point, the heat transfer and efficiency become poor due to fluid flow and flow velocity changes, vibration is caused by uneven flow, the temperature control precision is poor, and physical property changes and temperature pinch points are prone to occurring in a supercritical working medium are solved; the post-adjustment adaptability is poor, the performance is difficult to optimize, the response is slow, and potential safety hazards exist.

A taskable aerial network includes a plurality of uncrewed vehicles, and a ground station executing a command and control subsystem in operable communication with the plurality of uncrewed vehicles and configured to receive a task input based on a timeline, a location, and / or a payload, receive a capacity input based on a location, a payload and an operational condition for an uncrewed vehicle, receive a traffic input based on a location of the uncrewed vehicles, receive a risk input and determine if the risk input passes a predetermined risk threshold, determine a flight plan based on at least one of the task input, the capacity input, the traffic input, and the risk input, and transmit the flight plan to the uncrewed vehicle to deploy the uncrewed vehicle to execute a task.

Exemplary systems and methods are directed to reducing processing complexity for command and control of a remote autonomous object in response to natural language commands. A processor receives a user command in a natural language format and extracts designated parameters for matching with a control prompt stored in a library of control prompts. The processor determines a confidence from a result of the operation. The confidence factor is used to selectively route the user command to a simple command processing path to generate a simple command message or a complex command processing path having one or more neural networks to generate a complex command message. The processor compares the simple command objective message, or the complex command objective message generated from the selective routing operation with known capabilities of the remote autonomous object to identify a remote autonomous object command, which is formatted and transmitted to the remote autonomous object.

The application discloses a city air traffic system control architecture switching method and device, relates to the technical field of system engineering and automatic control, and is based on an adaptive architecture switching control model constructed based on adaptive control theory and fuzzy logic control. Based on state variable values and performance index values of the system, the adaptive architecture switching control model is used to switch the type of the city air traffic control system architecture and the corresponding model structure in real time, so that the operation efficiency of the city air traffic system can be effectively improved, and the loss caused by the safety risk can be reduced. The application designs three types of city air traffic control system architectures for the city air traffic system, can meet the command and control requirements of different scenes, and provides a reference for the design of the city air traffic system control architecture.

The invention discloses a control method and system for sodium hydrosulfite synthesis and electronic equipment, and the control method comprises the following steps: a production starting instruction is obtained, and the production starting instruction comprises control configuration of a pretreatment stage, a feeding stage, an absorption liquid stage, a heat preservation stage, a large charging stage, a small charging stage, a cold charging stage and a discharging stage. By acquiring the production starting instruction and controlling the operation of each stage according to the preset configuration, the automation of the production process is realized, human errors are reduced, and the strict requirement on highly concentrated spirit of operators is lowered. Operating parameters of each stage can be accurately controlled according to a preset program, and product quality fluctuation caused by unstable operation in a traditional process is avoided. The operation parameters and the feeding sequence of each stage are automatically executed according to the preset configuration, the whole process is provided with safety alarm and termination and abnormity handling programs, the reaction process is continuous, smooth and safe, shutdown waiting or human errors are avoided, and the overall production efficiency and safety are improved.

The utility model discloses an unmanned aerial vehicle command and control seat rack, and relates to the technical field of unmanned aerial vehicle control equipment. The seat rack comprises a seat rack main body structure and a seat; the seat rack main body structure comprises a first rack, a second rack and a third rack which are sequentially connected from bottom to top; the bottom of the first rack is connected with a pedal, the second rack is connected with a host, an operating lever, a first touch display and an accelerator platform, the third rack is connected with two angle adjusting mechanisms, and the two angle adjusting mechanisms are connected with a second touch display and a third touch display respectively. The angle adjusting mechanism is used for adjusting the pitching angles of the second touch display and the third touch display according to different sitting postures of the operator on the seat, so that the operator in each sitting posture can see the display content of a screen; and a worker is in a relatively comfortable working state.

The invention provides a simulated training guidance control method and system based on artificial intelligence, and relates to the field of guidance, and the method comprises the steps: obtaining multi-source data and preset training scene state data, and carrying out the preprocessing of the multi-source data; identifying the preprocessed data through a pre-trained deep learning neural network model to obtain real-time initial training scene state data, and synchronizing the real-time initial training scene state data to perform data linkage to obtain real-time training scene state data; judging whether the real-time training scene state data conforms to preset training scene state data or not; and if not, updating preset training scene state data according to the real-time training scene state data, and predicting a battlefield situation according to the updated training scene state data to generate a new training action strategy to realize guidance control. According to the invention, the technical problems of poor flexibility, insufficient accuracy and low efficiency of simulation training guidance in the prior art are solved.

The utility model discloses a deep-sea operation and maintenance command and control integrated test platform, and the platform comprises a box body which is provided with a side door at one side and a cabin door at the end part; the cabin section storage rack is arranged on one side in the box body in a sliding manner; the lifting platform is arranged on the other side in the box body; and the hoisting system is arranged at the top in the box body. The cabin section storage rack is arranged to store the AUV cabin sections in order, so that the AUV cabin sections can be quickly assembled and debugged on site, the AUV cabin sections are also prevented from being in direct contact with the ground, and the equipment is prevented from being damaged; by arranging the hoisting system and arranging the track on the upper part of the box body, the AUV cabin section can conveniently operate inside and outside the box body, and the problems of high cost and low efficiency of a traditional carrying mode are effectively solved; rapid and stable transfer of the AUV cabin section can be ensured, manual intervention is reduced, and the operation risk is reduced; through the arrangement of the lifting platform and the function of freely adjusting the height, the height of the platform can be rapidly adjusted according to the size and debugging requirements of the AUV cabin section, and the debugging convenience of the AUV cabin section is improved.

A system, method, and device for detecting Command and Control (C2) traffic is disclosed. The method includes (i) converting, by one or more processors, a header for network traffic to a header representation having a smaller dimensionality than the header, (ii) querying a classifier based at least in part on the header representation to obtain a traffic classification, (iii) automatically detecting C2 traffic based at least in part on the traffic classification, and (iv) handling the network traffic based at least in part on the traffic classification.

Methods, systems, and devices for wireless communications are described. An application server may receive a remote pilot trigger message requesting establishment of a media connection and a command and control connection between a remote pilot station and an aerial mobile device. The application server may transmit an authorization message associated with confirming whether the remote pilot station is authorized to control the aerial mobile device, and the application server may receive a response message in response to the authorization message. The application server may communicate one or more control messages to initiate establishment of the media connection and the command and control connection between the remote pilot station and the aerial mobile device based at least in part on receiving the response message.

The application provides a UAV command information relay transmission method and system, and belongs to the technical field of UAV control. In the process of UAV command control, when a link fault occurs, the relay UAV is used to forward messages, the demand for measurement and control link resources is reduced, the global optimal allocation of link resources is realized, and when the measurement and control link of a UAV is interfered, the UAV can be adaptively adjusted to the command relay transmission mode, the anti-interference ability of the UAV communication link is greatly enhanced, and the survivability of the UAV is improved.

The invention discloses a civil air defense emergency command and dispatch method and system based on an unmanned aerial vehicle, and relates to the technical field of emergency command and control. According to the invention, data fusion is carried out through Kalman filtering to obtain a three-dimensional disaster situation entropy map; a disaster core area is identified based on an entropy threshold value, a dynamic weight centroid is calculated, and adaptive task partitioning is realized through a weighted Voronoi graph; a millimeter wave radar and binocular vision are fused to construct a three-dimensional grid map, a safe air route is generated through heuristic sampling and air route smoothing under flight constraints, and a collision avoidance mechanism is integrated to guarantee navigation safety; dynamically selecting a communication link, and matching the similarity of historical scheduling schemes or generating a scheduling scheme through a GRU model; optimizing the objective function, outputting an optimal scheduling instruction in combination with endurance and material matching constraints, and triggering closed-loop dynamic re-partitioning through periodic entropy re-evaluation until the disaster situation is relieved; a traditional one-way command mode is broken through, a perception-decision-execution full-chain closed loop is formed, and rescue timeliness and safety are remarkably improved.

The present invention provides a drone command and dispatch system, a drone joint inspection method, and a device, comprising: a monitoring module, a situation overview module, a command and dispatch module, a joint flight execution module, a task module, and an operation analysis module; the monitoring module is used to monitor the drone's external nest image and drone image; the situation overview module is used to browse the base station list, drone list, inspection statistics list, inspection record list, and operation analysis list to query corresponding information; the command and dispatch module is used to switch base stations and obtain real-time information corresponding to the base stations, and command and control the drone based on the real-time information and a predetermined command strategy; the joint flight execution module is used to perform joint inspections on multiple base stations via a joint inspection route; the task module is used to display the inspection record list and inspection plan list; and the operation analysis module is used to display the task list and achievement list. This method realizes the display and route planning of multi-base station drone joint inspections.

A method comprises a wireless device transmitting, to an access and mobility management function (AMF), a registration request message for the wireless device, receiving, from the AMF, a registration response message indicating an acceptance of a registration request of the wireless device, and transmitting, to the AMF, a protocol data unit (PDU) session establishment request for establishing a PDU session associated with an unmanned aerial system (UAS) service. The method further comprises receiving, from the AMF, a rejection of the PDU session establishment request, which comprises: a first parameter indicating that authentication and / or authorization for the UAS service is failed or revoked; and a second parameter indicating that authentication and / or authorization for a command and control (C2) communication is failed or revoked.

The invention discloses a space-air-ground cooperative low-altitude security command and control method, system and device and a medium, and relates to the technical field of unmanned aerial vehicles, and the method comprises the steps: generating a global dynamic situation map according to multi-source detection data; performing cognitive analysis on the global dynamic situation map to obtain a system configuration, a key unit and a current confrontation stage of the unmanned aerial vehicle swarm; based on the system configuration and the key unit, predicting a subsequent confrontation stage of the unmanned aerial vehicle swarm after the current confrontation stage and a corresponding swarm behavior characteristic; according to the current confrontation stage, the subsequent confrontation stages and the group behavior characteristics, a multi-stage induction signal sequence is generated, and induction signals differentially configured for the subsequent confrontation stages are set to trigger the unmanned aerial vehicle swarm to generate a preset state response by using the group behavior characteristics of the subsequent confrontation stages, the preset state response is planned as a favorable condition for executing the next-stage induction signal. The method has the effect of improving the concealment of confrontation.

The invention relates to a 5G private network base station based on liquid cooling and a cooperative command and dispatch system. According to the base station, the heat dissipation problem is specially considered in design, so that the cooling problem caused by space limitation in the operation process of the 5G private network base station is solved. In order to solve the problem, a liquid cooling technology is adopted, liquid cooling liquid with good heat conduction performance is injected into the 5G base station, the liquid cooling liquid makes full contact with a shell of the 5G base station, and efficient and uniform heat dispersion is achieved. In addition, in order to solve the problem that the transmitting power of the base station is reduced due to the cooling requirement, a collaborative command and dispatch system is designed. When a temperature sensor of a 5G base station detects too high temperature, the system can automatically reduce the transmitting power of the base station and coordinate other base stations through the command and control platform, so that a communication range coverage blind area caused by the base station with reduced transmitting power is filled. Once the temperature of the base station returns to a normal range, the system automatically recovers the transmitting power. According to the design, the cooling and stability problems of the 5G private network base station are effectively solved, and the operation efficiency and stability of the base station are greatly improved.

The system and method may look for bots using statistics. At a high level, bots communicate back and forth to a command and control computer. The communications are at somewhat random times by design to not be obvious. Using expected probability of a normal distribution rather than simply analyzing time of communications may result in better bot recognition.

The invention discloses a task management system and a task management method suitable for a swarm unmanned aerial vehicle system, and in the task management system, hardware cross-linking, remote control instruction transmission and remote measurement information transmission are carried out between a command control subsystem and a flight control subsystem; the flight control subsystem is connected with the task control subsystem, and task control and management information for the swarm unmanned aerial vehicle system is processed through the task control subsystem, so that modification of the unmanned aerial vehicle from a single unmanned aerial vehicle to multiple unmanned aerial vehicles is realized by additionally arranging the task control subsystem; the task control subsystem and the task load subsystem are crosslinked, and the task control subsystem is used for transmitting a remote control instruction and a telemetering return of the task load subsystem and receiving task image information from the task load subsystem; the command and control subsystem and the task load subsystem are crosslinked, and the task load subsystem transmits task image information to the command and control subsystem, so that the ground station can display the task image information in real time. According to the technical scheme provided by the invention, the problem that the existing flight management system of the unmanned aerial vehicle is difficult to realize information interaction, instruction control, cooperative task execution and autonomous task planning among multiple unmanned aerial vehicles in a swarm unmanned aerial vehicle system is solved.

A device for controlling a distance and / or a height of an attachment above the ground and / or above a plant surface. The attachment is attached to an agricultural vehicle. The device includes a scanner, an evaluation unit, and a control unit. The scanner detects a plurality of detections, detects a detection area, the detection area being is narrower in the direction of travel than transverse to the direction of travel, and detects objects via the plurality of detections and to record data on a detected angle, a detected distance to an object, and / or a density of the object or the objects. The evaluation unit reproduces a ground profile and / or the plant surface and / or a location-dependent plant density as evaluation data. The control unit processes the evaluation data into control commands and controls the distance and / or the height of the attachment to a target value.

The invention discloses a dynamic tactical knowledge graph construction and target attackable value analysis system and method based on an environment embedded graph neural network, and belongs to the technical field of military intelligent decision making and firepower command control. The system constructs a tactical knowledge graph fused with firepower application expert experience for tactical rule recessive and environmental constraint dynamic problems in target threat assessment. Based on an entity-relation-environment attribute triple structure, an ontology model covering a typical combat scene is established, and dynamic quantitative analysis of target attackable value is supported. An environment embedded graph neural network is innovatively designed, a battlefield environment is used as an internal structure variable of a graph, and deep coupling and self-adaptive reasoning of knowledge representation and a real-time situation are achieved. The system can comprehensively consider information such as enemy conditions, my conditions, typical scenes and the like, realizes accurate evaluation of multi-target threats and values, assists a commander in accurately capturing important high-threat high-value targets, and quickly forms a wave-order striking target list.