248 results about "Adaptive communications" patented technology

The invention relates to the technical field of ship communication, in particular to a multi-link converged communication method and system for a ship. The method comprises the following steps: receiving navigation information broadcasted by other ships in a preset range, evaluating the availability of a communication frequency band, and generating sea area communication channel state data; acquiring geographic position data of each ship; space communication link potential analysis is carried out according to the geographic position data of each ship and the sea area communication channel state data, and cross-chain space communication potential data is generated; constructing a multi-link ad hoc network topological structure according to the cross-chain space communication potential data; and task adaptation communication link allocation is carried out based on a multi-link ad hoc network topological structure, and a multi-link fusion transmission strategy is constructed, so that real-time communication link safe switching management is realized. According to the invention, on the basis of communication service adaptation and a multi-link fusion transmission strategy, real-time communication safe switching and high-reliability transmission of the marine formation are realized.

The invention discloses a forestry ecological environment real-time monitoring and management method based on big data, and belongs to the technical field of forestry ecological environment management, and the method comprises the following steps: S1, multi-source heterogeneous data collection and sensor network deployment; s2, multi-modal data fusion and intelligent transmission: developing an adaptive communication protocol dynamic switching module, and automatically switching to a satellite communication link in a 4G / 5G network blind area; s3, mass data storage and distributed calculation: constructing a hybrid cloud storage architecture, and storing real-time monitoring data into a Redis cache queue; s4, intelligently extracting ecological environment indexes; s5, dynamically evaluating the ecological bearing capacity; s6, performing multi-level early warning and emergency response; s7, making a precise forestry management decision; and S8, carrying out system self-optimization and closed-loop management. According to the method, the air-space-ground integrated monitoring network is constructed, so that the comprehensiveness and the real-time performance of forestry ecological environment perception are remarkably improved; multi-source data of the unmanned aerial vehicle, the satellite remote sensing and the ground sensor are complementary.

The invention relates to the technical field of multi-agent cooperative control, and discloses a multi-agent reinforcement learning formation adaptive method fusing a graph attention mechanism. According to the method, a dynamic graph state space is constructed, and a speed self-adaptive communication mechanism and a multi-target return function are combined, so that the problem of insufficient generalization ability during intelligent agent number change or topological structure dynamic adjustment is solved. The scheme comprises the following steps: establishing a virtual leader-following formation model and a motion dynamics model; designing an adaptive communication radius formula based on speed change; constructing a graph state space, and dynamically aggregating neighbor information by using a multi-head attention mechanism; designing a strategy network and a value evaluation network with residual connection; and a centralized training distributed execution framework is adopted to update model parameters. Adaptive extraction of key neighbor information is realized through a graph attention mechanism, and adaptability and stability of a formation system in a complex environment are improved by combining dynamic communication range adjustment. The method is suitable for unmanned aerial vehicle group control, robot cooperation and other scenes.

The invention discloses a hydraulic power plant automatic debugging system with a self-adaptive communication function. The system comprises a processing unit, a storage unit, a communication module, an input / output interface, a task classification module, a model architecture configuration module and other functional modules. The use method comprises the following steps: analyzing task complexity and high-dimensional features of input data through a task classification module, and grading by adopting algorithms such as principal component analysis and a support vector machine; the model architecture configuration module is used for matching a model architecture according to the complexity level and determining an initial calculation path; the dynamic path adjustment module optimizes a calculation path in combination with real-time data, and the resource distribution module redistributes resources when the calculation power exceeds the limit; the model compression module generates a compression model adaptive to the edge device through pruning and quantization algorithms; the parameter fine tuning module is used for jointly optimizing model parameters for a multi-task scene; according to the method, the adaptability and efficiency bottleneck of an existing debugging tool in a complex scene is effectively solved, and the intelligent debugging level of an automatic system of a hydraulic power plant is improved.

The invention discloses a wireless transmission anchor rod multipoint stress sensor system, which relates to the technical field of intelligent monitoring of geotechnical engineering and comprises a data sensing and acquisition module, a data processing and transmission module, a data receiving and storage module, a data analysis and decision module and a user interaction and management module. The technical key points are as follows: multi-protocol adaptive communication and quantum encryption are carried out, a multi-protocol adaptive communication stack is based on an improved near-end strategy optimization algorithm, intelligent switching of communication protocols can be completed in an extremely short time according to an actual environment, and the intelligent switching of the communication protocols can be completed in scenes such as mountainous area tunnels with complex and changeable signals. The problem that transmission of a traditional single protocol is prone to being interrupted is effectively avoided, continuity of data transmission is guaranteed, meanwhile, the integrated quantum key distribution unit adopts a BB84 protocol and is combined with a two-factor encryption system, data transmission safety is remarkably improved, quantum attacks can be effectively resisted in a monitoring scene with the extremely high requirement for data safety in confidential work, and the security of data transmission is improved. And the data leakage risk is avoided.

The invention discloses an area terminal adaptive communication method and system based on link quality perception, and relates to the technical field of power area terminal communication by predicting link quality, comprising the following steps: predicting link quality according to multi-dimensional perception data to obtain link quality prediction data; determining a candidate link based on the service-link adaptation rule base, determining a target link according to the link quality prediction data of the candidate link, and performing data transmission through the target link; according to the real-time link quality data of the target link, whether switching is needed or not is judged in combination with the power grid operation state, and if switching is needed, the link priority is calculated to obtain an optimal link, and link switching is carried out; the method can adapt to a complex operation scene of a power grid, improves the link switching efficiency, improves the communication efficiency and communication reliability between the station area terminals, and solves the problem of low communication efficiency caused by poor environmental adaptability and relatively high switching time delay between a communication protocol and a module in an existing station area terminal communication technology.

The invention relates to the technical field of old people health management, and discloses a personalized health auxiliary management system based on artificial intelligence, which comprises a multi-mode sensing module, an intelligent preprocessing module, a dynamic knowledge graph module, a personalized inference engine module and a self-adaptive communication and interaction module. The multi-mode sensing module is used for acquiring physiological, environmental and behavioral data; the intelligent preprocessing module desensitizes and cleans data through federal learning, and extracts core features; the dynamic knowledge graph module constructs and updates an exclusive graph containing basic and dynamic nodes and associated edges; the personalized inference engine module generates a layered intervention scheme; and the adaptive interaction module adapts to the cognitive ability and synchronizes the scheme. According to the invention, health information integration and dynamic intervention are realized, the management accuracy and compliance are improved, and the method is suitable for home non-clinical scenes.

The invention relates to the field of computer big data, and discloses a self-adaptive parallel computing high-dimensional data dimension reduction and classification optimization system which comprises a quantum tensor decomposition module, a dynamic routing module, a heterogeneous computing classification module and a feedback regulation and control module. The quantum tensor decomposition module realizes nonlinear feature extraction of high-dimensional data through super-adjacency tensor modeling and entanglement entropy constraint; the dynamic routing module generates an adaptive communication path based on pulse time sequence weight optimization and quantum key verification; the heterogeneous calculation classification module dynamically schedules a quantum processor according to data characteristics, and FPGA and GPU resources execute mixed gradient aggregation; and the feedback regulation and control module guarantees the robustness of the system through multi-dimensional parameter closed-loop correction and a multi-stage fault-tolerant mechanism. All the modules cooperate to form a closed loop of dimension reduction, transmission, classification and regulation, the problems of feature extraction distortion, low resource utilization rate and poor dynamic environment adaptability in the prior art are solved, and the real-time performance and reliability of high-dimensional data processing are remarkably improved.

The invention relates to the technical field of address allocation, in particular to an automatic discovery and dynamic address allocation method for 485 bus equipment, which comprises the following steps: a host verifies a broadcast address and transmits an instruction to a bus, captures a delay response of a slave to establish a response queue, analyzes dense signals and peels off conflict fragments, dynamically adjusts sampling to generate rhythm mapping, and sends the rhythm mapping to the slave; address instructions are issued according to the sequence, the slave machines check, update and return receipts, the host machine collects and generates an allocation table, monitors signal drift, adjusts time sequence parameters, reconfigures response time periods, updates a synchronization state and completes recording. According to the method, a mapping mechanism based on a broadcast response time sequence is established, stable node distinguishing is obtained through signal multi-dimensional analysis, independent extraction and sequence self-correction are achieved through differential allocation and dynamic sampling, a self-adaptive communication structure is constructed, unified recognition pairing and rhythm coordination are achieved in address allocation, and the self-organization capacity is remarkably improved; concurrency conflicts are reduced, precision is improved, and communication consistency and efficient automatic addressing in a dynamic environment are ensured.

The invention provides a theoretical modeling method and system for describing the relationship between the gradient entropy and the compression rank, and provides a theoretical basis for gradient compression strategy design and adaptive communication optimization. According to the method, modeling is carried out on gradient matrix eigenvalue distribution, internal relation between eigenvalues and compression errors is revealed by applying a random matrix theory and characteristic spectrum analysis, and a function relation between a compression rank and a reconstruction error is constructed. On the basis, a constraint condition that a compression error absolute value is kept constant is introduced, the standard deviation of the gradient matrix is incorporated into error estimation, a corresponding relation between the standard deviation and a compression rank is derived, and the effect of the standard deviation serving as a compression error intermediate variable is clarified from the statistical angle. According to the method, the minimum compressible rank under specific precision can be estimated, a unified analysis framework is provided for analyzing compressibility differences of different training stages or network layer gradients, and the method has good theoretical universality and engineering practicability.

The invention discloses a help-calling emergency response system based on an intelligent communication network, particularly relates to the field of intelligent communication, and comprises a multi-source data acquisition layer, a preprocessing and feature extraction layer, a progressive analysis engine, a decision fusion center and an execution control layer. According to the method, the data integrity and the anti-interference capability are remarkably improved, the time-space reference unification module adopts a PTP protocol and a coordinate system conversion technology, accurate alignment of multi-source data is achieved, a multi-dimensional feature matrix is generated through time-frequency conjoint analysis, and the problem that the feature extraction dimension of a traditional system is single is solved; the progressive analysis engine triggers a hierarchical response strategy based on dynamic fusion of a transmission robustness index, a space confidence coefficient and an environmental risk value, combines terrain refraction compensation and a timeliness attenuation mechanism to optimize decision logic, breaks through the limitation of a fixed threshold response mode, adapts to communication quality fluctuation and environmental sudden change, reduces rescue delay risk, and improves rescue efficiency. And the resource scheduling accuracy and the system intelligence level are improved.

The invention discloses a multifunctional remote monitoring system for safe operation of chemical plant electrical equipment, which relates to the technical field of remote monitoring of chemical plant electrical equipment and comprises a data acquisition unit, an edge calculation unit, a self-adaptive communication unit, an intelligent diagnosis unit and a remote monitoring unit. The data acquisition unit is used for acquiring valve state, liquid level, temperature and pressure signals in real time; the edge computing unit is integrated in a programmable logic controller (PLC) and is used for data preprocessing and local analysis; the adaptive communication unit is used for optimizing the data transmission priority based on the existing industrial Ethernet protocol Profinet / EtherNet / IP; the intelligent diagnosis unit is used for equipment health state evaluation and fault prediction; the remote monitoring unit realizes visualization and remote control through an upper computer; the programmable logic controller PLC is AB 1756-L71 and is used for integrating an edge computing unit to complete tasks of data preprocessing and local analysis.

The invention discloses an AI development optimization system based on dynamic learning and an adaptive algorithm, and relates to the technical field of artificial intelligence, and the system comprises a collection module which collects GPU occupation data and transmission channel state data, and generates a separation operation signal; the identification module is used for triggering operation task analysis according to the separation operation signal and distributing a transmission channel identifier for the subtask; the path module queries the idle state of each computing unit of the GPU and generates an exclusive communication path; the detection module is used for running the subtasks in the exclusive communication path and outputting channel signal mixing degree; the triggering module is used for setting a mixing degree threshold value and triggering a path replacement signal and a merging operation signal; and the merging module suspends the sub-task processing process based on the merging operation signal, performs merging according to the operation sequence of the sub-tasks, and outputs a complete task. According to the method, efficient resource scheduling and task optimization of AI development are realized through coordination of dynamic task topology analysis and self-adaptive communication path binding.

The invention discloses a multi-serial-port peripheral automatic identification and protocol adaptive communication method in an embedded system. The method comprises the following steps: monitoring physical connection states of a plurality of serial ports in the embedded system; performing communication parameter self-learning on the target serial port, and determining a baud rate and a data format matched with the access equipment; automatically matching the features of the initial data frame with a plurality of protocol feature templates stored in a protocol feature library preset in the embedded system to obtain one or more candidate communication protocols; constructing a verification instruction by using a frame format of the candidate communication protocol, sending the verification instruction to the access equipment, performing interactive verification, and confirming a final target communication protocol according to a response result of the access equipment; and the self-adaptive communication link establishment aiming at the access equipment is completed. The method has the advantages that the problems that manual configuration is needed, deployment is tedious and errors are prone to occurring during mixed connection of multi-protocol equipment are solved, and the flexibility, expandability and deployment efficiency of an embedded system are remarkably improved.

The invention relates to the technical field of communication, in particular to a time sequence adaptive communication experiment automatic evaluation and verification method and system, and the method comprises the steps: S1, dynamically generating multi-scene channel parameters, including high-speed movement, dense multipath and burst interference scenes, and driving channel simulation through a predefined time-frequency domain parameter model; s2, monitoring key performance parameters of the communication system in real time, including bit error rate, synchronization error, delay jitter and spectral efficiency, and performing data acquisition at a sampling frequency not lower than 1kHz; s3, testing the adaptive algorithm through a dual-mode verification engine; s4, automatically calculating a synchronization retention rate, a spectrum efficiency improvement rate and a dynamic adjustment effectiveness index; and S5, generating a three-dimensional visualization report including a time domain performance curved surface, frequency domain feature distribution and an energy consumption analysis result. The invention discloses an automatic evaluation and verification method and system for a time sequence adaptive communication experiment. The test efficiency is remarkably improved, and the one-sidedness problem of traditional single-index evaluation is solved.

The invention discloses a self-adaptive communication protocol switching method and device. The method comprises the following steps: acquiring network environment data corresponding to a target network environment, terminal equipment data corresponding to terminal equipment in the target network environment and service demand data; fusing the three kinds of data to obtain fused feature data; inputting the fused feature data into a network environment prediction model, and processing the fused feature data by using the network environment prediction model to obtain performance prediction data of each candidate network in the target network environment on a future preset time window; according to the adaptation capability value of each communication protocol in the protocol library under the performance prediction data; and after a target communication protocol is selected according to the adaptation capability value and the service demand data, switching to the target communication protocol. According to the invention, the technical problem that a conventional communication system adopts a fixed communication protocol and cannot be dynamically adjusted according to a network environment and service requirements in the prior art, which has great limitation, is solved.

According to the multi-unmanned helicopter hoisting system based on cooperative control, the safety, the stability and the operation efficiency of multi-helicopter cooperative hoisting are improved. Firstly, dynamics and kinematics constraints are fused, and a distributed control strategy is adopted, so that multiple unmanned helicopters can realize accurate cooperation according to a real-time state; thirdly, arranging an attitude sensor and an acceleration sensor on the suspended object, and combining a feedback control algorithm to effectively inhibit swinging of the object; and finally, the system adopts a self-adaptive communication protocol, a redundant link and a hierarchical fault-tolerant mechanism, so that the reliability of information transmission and the self-adaptive capability after a fault are enhanced. According to the invention, through multi-source environment perception and adaptive flight adjustment, efficient and safe operation of a suspended load task under a complex environment condition is realized, and the environment adaptability and robustness of an unmanned helicopter cooperative suspended load system are significantly improved.

The invention discloses an electric power marketing metering equipment abnormity early warning method and system based on edge computing, and relates to the technical field of electric power system monitoring, and the method comprises the steps: collecting the original multi-mode operation data flow of target electric power marketing metering equipment in real time during the operation of the system; performing sliding window segmentation and parallel feature extraction on the data stream to obtain a mixed feature vector; inputting the mixed feature vector into an isolated forest model and a gradient boosting decision tree model in an integrated anomaly detection engine, and calculating a comprehensive anomaly confidence score; generating a local early warning event or cache feature data according to the confidence score, and triggering an adaptive communication scheduling process; on the collaborative decision-making platform side, receiving and aggregating reported information, carrying out Bayesian network reasoning by combining the multi-source data of the power grid, and completing global anomaly verification and final decision-making; and starting a model evolution process according to a global verification result, executing incremental learning and generating a parameter updating package.

The invention discloses a multilayer space dynamic topology adaptive communication network construction method, and belongs to the technical field of communication networks. The method is realized through five steps of constructing a multi-layer fusion architecture of space-based, air-based and ground-based networks, instantiating network slices of power service perception, performing dynamic topology abstraction and resource pre-mapping based on virtual cell division, performing power and bandwidth collaborative allocation based on reinforcement learning, and deploying multi-domain fault diagnosis and predicting a closed loop. According to the invention, power and bandwidth collaborative allocation based on deep reinforcement learning not only can optimize the total capacity of the system, but also can realize dynamic balance of the network load. The system can automatically adjust the power and bandwidth distribution according to the real-time network state in the operation process, and the self-adaptive mechanism enables the network to efficiently cope with the demand changes of different power businesses.

The invention relates to the technical field of rail transit, and discloses a wire harness detection system for a rail vehicle, which comprises a master control unit, a first detection unit, a second detection unit and a self-adaptive communication module, and is characterized in that the master control unit is used for storing a topological information database of a to-be-detected wire harness; the database comprises wire harness numbers, terminal position codes and rated test parameters; the first detection unit and the second detection unit are respectively provided with an anti-misplug structure, and the anti-misplug structure comprises a magnetic code positioning interface which identifies terminal magnetic pole codes through a Hall sensor; the multi-channel parallel detection circuit realizes parallel testing of multiple wire harnesses by adopting a time division multiplexing technology. According to the invention, the system can effectively prevent the problems of wrong insertion and missing insertion of the terminal, the magnetic coding positioning interface accurately identifies the magnetic pole code of the terminal through the Hall sensor, it is ensured that only the matched terminal is allowed to be inserted, and manual operation errors are fundamentally eradicated.

The invention belongs to the technical field of battery abnormity identification, and provides a vehicle battery abnormal behavior identification method and application based on an adaptive communication gateway, and the method comprises the steps: collecting battery and vehicle data in real time, and integrating the data into a unified time sequence; calculating a dynamic working condition factor to generate a working condition label; constructing a space-time tensor in the space-time coding of the battery state; defining each battery monomer as a node, dynamically generating a connection weight between the nodes, and constructing a dynamic probability graph; the time anomaly and the space anomaly are fused, and a space-time joint anomaly energy value is obtained through weighted combination calculation; generating a dynamic abnormal threshold value, and performing abnormal judgment by combining the dynamic abnormal threshold value with a space-time combined abnormal energy value and gradient change thereof so as to trigger an alarm; and abnormal battery monomers are positioned, a space-time thermodynamic diagram is generated, and a diagnosis result is uploaded to a cloud platform through a communication gateway. According to the method, the working condition characteristics of the vehicle are analyzed in real time, and the space-time probability graph model of the battery system is dynamically reconstructed, so that working condition driven normal parameter fluctuation and potential fault signals can be distinguished.

A computer-implemented sustainable communications management system for monitoring, analyzing, and optimizing institutional communication practices with regard to sustainability goals. The system includes: a communication interface configured to receive communication-related data from a variety of digital and physical communication channels assigned to an institution; a processing unit that is operationally coupled with the communication interface and configured to process communication-related data with reference to a variety of sustainability parameters, including ecological, social and ethical dimensions; a storage system that is operationally linked to the processing unit and stores the following: predefined sustainability targets aligned with institutional goals; thresholds corresponding to key performance indicators (KPIs); and historical records of previous communication activities; a controller configured to coordinate the data flow between the communication interface, the processing unit and the storage, thus ensuring real-time updates of performance data; a sustainability assessment server configured to calculate sustainability impact assessments based on the correlation between the processed data and the predefined sustainability parameters; and a display interface configured to present the calculated impact assessments, performance analyses, and adaptive communication recommendations via a graphical dashboard accessible to authorized users.

The invention relates to a Manchester coded signal decoding method and a Manchester coded signal decoding system, and belongs to the field of electronic information, communication and power system automation. A plurality of clocks with the same frequency and different phases are generated according to Manchester encoding signals, the clocks are used for sampling the signals, a phase-shifting clock sampling method is used, dependence on a high-frequency clock is reduced, most interference in communication signals is determined to be eliminated according to a majority voting strategy for sampling results, and the accuracy of the signals is improved. And the seriously distorted signals are corrected according to special value enumeration, so that the interference of signal duty ratio distortion and burrs is reduced, and the decoding reliability is further improved. And finally, determining an original data stream of the signal according to the two level states of each code element. The method is used for decoding high-speed and ultra-high-speed Manchester encoding signals under the conditions of no high-frequency clock, poor data signal quality or unstable clock, and simultaneously realizing self-adaptive communication of different encoding formats.

The invention discloses a multi-band adaptive communication method, device and equipment based on a power line carrier, and belongs to the technical field of power line carrier communication, and the method comprises the following steps: in the receiving process of a power line carrier signal, under the condition that a leading signal is detected to arrive, receiving the power line carrier signal; filtering the received signal in parallel through a plurality of bandwidth-configurable filters, and determining a plurality of cross-correlation values of a plurality of parallel filtered signals of the received signal and the same local sequence, the local sequence being set according to the overall detection frequency band; determining a sending frequency band of the received signal according to the cross-correlation value; the received signal is processed according to the sending frequency band, so that parallel detection of a plurality of frequency bands can be realized, detection of the frequency bands one by one is not needed, equipment can quickly and accurately determine a proper working frequency band for network access, the network access efficiency and the communication rate are improved, and different services are supported to select different frequency band communication and multi-frequency-band parallel communication.

The invention discloses a modular sensor adaptive integration and data processing method and system in a complex terrain environment, and the method comprises the steps: constructing an extensible sensor sensing layer through a standardized interface module, and achieving the plug and play of various environment monitoring sensors; performing an inspection task in a complex terrain area based on a mobile device, and performing fusion processing on real-time data acquired by multiple sensors through an edge calculation layer; according to the environment data characteristics, the terrain complexity and the running state of the mobile device, the inspection behavior strategy of the mobile device is dynamically adjusted, and follow-up data monitoring and processing are carried out; the processed real-time data is uploaded to a cloud collaboration layer for collaborative analysis in a self-adaptive selection communication mode, and fundamental conversion from a static and fixed monitoring mode to a dynamic and adaptive mode is realized through modular sensor integration, mobile inspection, edge intelligent processing and self-adaptive communication; and the coverage rate, the efficiency and the intelligent level of environment monitoring are remarkably improved.

The invention discloses an agent collaborative awareness and resource scheduling method, and belongs to the technical field of resource collaborative scheduling, and the method comprises the following steps: S1, initialization and architecture construction, S2, edge awareness and data processing, S3, local collaboration and strategy generation, S4, global scheduling and collaborative execution, and S5, feedback optimization and model updating. The bottom layer carries out data preprocessing by utilizing edge calculation to reduce the transmission quantity, the middle layer realizes safe and efficient data fusion and model updating by virtue of federated learning, and the high layer optimizes global resource scheduling based on a Lagrange dual decomposition method and a genetic algorithm, so that the purposes of reducing system complexity and balancing resource allocation are achieved; meanwhile, an adaptive communication mechanism is introduced, a communication strategy is dynamically adjusted according to channel quality and the like, data interaction energy consumption is reduced, and communication reliability is improved.

The invention relates to the technical field of simulation, and particularly discloses a self-adaptive communication method and a heterogeneous interconnection multi-core distributed simulation experiment system node communication architecture, and the method comprises the steps: S1, detecting the state of a simulation entity, and judging the event triggering opportunity; the simulation entity comprises a semi-physical simulation entity and a parallel simulation entity; s2, when event communication is triggered, determining simulation entities which communicate with each other; and S3, performing data transmission between the simulation entities which are determined to communicate with each other, and encoding and decoding the data. According to the method, the distributed simulation requirement of the large-scale simulation entity is met, an optimal communication mechanism and a semi-physical model distributed simulation strategy oriented to large-scale simulation entity scheduling management are constructed, and the virtual-real interconnection and cluster control semi-physical simulation capability of a simulation experiment platform is further improved.

The invention relates to the field of seawater detection, and particularly discloses a seawater detection system based on a wireless disposable temperature-salinity-depth sensor, which comprises an underwater sensor unit, a water surface relay unit and a data analysis terminal, and realizes accurate adjustment of the movement speed of the sensor through closed-loop feedback control. Wherein the underwater sensor unit comprises a pressure self-adaptive buoyancy system, a multi-parameter sensing array and an anti-interference communication module; the closed-loop feedback control takes real-time speed deviation as input; according to the invention, by adopting a dynamic buoyancy adjustment and self-adaptive communication strategy, stable motion control precision and data transmission reliability can be maintained under complex hydrological conditions. The pressure self-adaptive buoyancy system realizes quick response through linkage of a micro air pump and a compressed air cylinder, and can automatically adapt to different ocean scenes by combining three intelligent working modes, so that high-precision data acquisition can still be completed under a five-level sea condition, and the operation robustness in a severe environment is greatly improved.

The invention discloses an intelligent help-seeking ring system based on low-power-consumption Bluetooth, and the system comprises a multi-mode sensor combination which comprises a motion sensor, a physiological sensor, and an environment sensor; the multi-level triggering module is configured to judge a user state through a preset multi-level early warning algorithm based on the fusion data acquired by the multi-mode sensor, and trigger corresponding distress signals according to different risk levels; the self-adaptive communication module is configured to carry out distress signal transmission through low-power-consumption Bluetooth; the self-organizing network system comprises a plurality of Bluetooth receiving nodes, and mesh networks are formed among the Bluetooth receiving nodes to relay and forward distress signals; and the monitoring processing system is configured to receive and process the distress signal from the self-organizing network system and execute a corresponding rescue response. By constructing the combination of the multi-level triggering module and the multi-mode sensor, the accuracy and the intelligent level of triggering the distress signal are improved.

The invention discloses an intelligent mine disaster early warning device and system, and the device comprises a multi-mode sensing array which comprises a bionic mine pressure sensor group, a gas spectrum fingerprint recognition module, and a micro-seismic beam forming array; the adaptive communication network comprises an edge preprocessing unit and a dual-mode communication module; and the dynamic risk assessment server is configured with a spatial-temporal feature fusion neural network and a threshold evolution engine. According to the invention, three-dimensional reconstruction of a stress field is realized through a tree-shaped groove substrate of the bionic mine pressure sensor group and a three-dimensional piezoelectric network, and a multi-mode sensing system covering stress, gas and slight shock is formed in combination with wide-spectrum gas fingerprint identification of the micro Fourier infrared spectrometer and the electrochemical sensor group. The spatial resolution and the gas type recognition coverage rate can be remarkably improved, dynamic correlation analysis of cross-modal data is achieved through the spatio-temporal feature fusion neural network, the disaster precursor feature capture sensitivity can be effectively improved, and the false alarm rate can be effectively reduced.