4274results about "Emergency/hazardous communication service" patented technology

A decentralized event detection and geolocation system is disclosed, utilizing a dynamically adaptable Spontaneously Emergent Geolocation Network (SEGNet) comprising mobile, stationary, and other devices equipped with multi-sensor capabilities. The system operates by obtaining sensor data from distributed devices, applying trained models to detect potential events of interest (EOIs), and dynamically forming device networks for collaborative geolocation and event validation. The system employs synchronization mechanisms and geolocation techniques, including Time Difference of Arrival (TDOA) and / or Angle of Arrival (AoA), to determine event locations through multimodal data fusion and iterative validation processes. The architecture supports multiple operational modes, including decentralized, centralized, and hybrid configurations, enabling operation in connectivity-limited environments and enhanced processing when server access is available. The system is designed to accommodate dynamic task delegation and real-time threshold adjustments based on environmental conditions, providing reliable event detection and geolocation across diverse scenarios.

The invention discloses a multi-hop communication node intelligent scheduling method and system, and relates to the technical field of communication networks. The method is used for solving the scheduling and switching problems of multi-hop relay nodes in disaster emergency communication. Residual energy, channel fading parameters and link load data of an unmanned aerial vehicle and a ground terminal are collected, a communication potential index is calculated in combination with dynamic weight fusion, and the relay capability of a node in a complex environment is accurately evaluated. A relay node selection threshold is set according to the disaster type, nodes with communication potential indexes higher than the disaster adaptation threshold are preferentially selected, an initial hybrid topology structure with preferential survivability is constructed, and the network stability and survivability are improved. An autonomous game agent model is adopted, a multi-target reward function is designed based on local channel quality, residual energy and task emergency degree, it is ensured that the network achieves collaborative optimization of energy consumption balance, transmission real-time performance and survivability under the condition of dynamic topology and node failure, and efficient and continuous optimization of the disaster emergency communication network is achieved.

The invention discloses a self-adaptive packet data transmission system and method based on Beidou short messages, the system is composed of eight core modules such as a serial port communication module, a protocol conversion module and a configuration module, multi-link communication is established through an RS232 serial port and a Beidou director, and Baud rate self-adaptive adjustment and multi-serial port parallel processing are supported. The protocol conversion module adopts a finite-state machine to analyze a BDS-3 protocol, data fragmentation and recombination are achieved in combination with a sliding window algorithm, and the compression rate reaches 3: 1. The method comprises the following seven stages of flows: evaluating channel quality by detecting a message, and dynamically switching a BDS-3 anti-interference mode; implementing flow control by adopting a token bucket algorithm, and dividing three levels of QoS guarantee emergency instructions; and terminal health management is realized through a heartbeat detection and diagnosis instruction set. According to the method, instruction execution is delayed by 1.2 seconds in emergency communication, the bit error rate is controlled to be 0.0005%, the transmission efficiency is improved by 40% compared with a traditional scheme, and the method can be widely applied to the fields of Internet of Things, intelligent transportation and the like.

The invention provides a wireless communication network method and system of a mobile first-aid station. The method comprises the following steps: monitoring and evaluating a surrounding environment in real time, selecting an optimal working frequency band, and adjusting a frequency band switching strategy to obtain a self-adaptive multi-frequency-band access mechanism; the bandwidth and the connection priority of the wireless communication network are dynamically adjusted, the task priority is evaluated, and a dynamic resource allocation strategy is generated; deploying a distributed cache and synchronization system, realizing balanced distribution and rapid positioning of data, and generating a distributed temporary data cache pool; establishing an intelligent routing algorithm of deep reinforcement learning, calculating an optimal transmission path from a source to a destination, and finally generating an intelligent routing planning scheme; a redundant path is preset on the path, and a redundant path planning scheme is generated according to a dynamic resource allocation strategy and an intelligent routing planning result. According to the technical scheme provided by the invention, the reliability and the response speed of the wireless communication network of the mobile first-aid station are improved.

The invention relates to the technical field of artificial intelligence rescue, and discloses an unmanned aerial vehicle and robot dog rescue emergency system and method, and the system comprises an unmanned aerial vehicle cluster module which is used for air data collection, communication guarantee and emergency material distribution; the robot dog cluster module is used for ground environment detection, sample collection and special task execution; the communication cooperation module is used for ensuring information intercommunication and task cooperation between air-ground equipment; the central control module provides task instructions for the unmanned aerial vehicle cluster and the robot dog cluster; the human-computer interaction interface module is used for realizing effective communication between rescue workers and the system; the modules work cooperatively, multi-source data acquisition, three-dimensional scene reconstruction, semantic segmentation, risk assessment, fire spreading prediction and decision support information generation of a disaster site are realized, and a reliable basis is provided for rescue command decision.

The invention provides an emergency command converged communication system resource dynamic scheduling method based on artificial intelligence. The method comprises the following steps: S1, acquiring a plurality of sensors and log data of an emergency command system; constructing a dynamic graph neural network optimization communication topology, and selecting an optimal communication path; combining resource prediction and the optimized communication topology to formulate a global optimal resource scheduling strategy, and generating an optimal resource allocation scheme for each task; the resource pool comprises available computing resources and communication bandwidth; dynamically adjusting resource allocation and a communication path in a task execution process, and generating task execution feedback of a corresponding task; the system state is monitored in real time, and resource prediction, topology adjustment and scheduling strategies are optimized based on execution error feedback of task execution feedback. According to the method, efficient and intelligent dynamic resource scheduling is realized in an emergency command converged communication system through resource prediction of self-supervised learning, self-adaptive topological optimization of a variable topological graph neural network and global scheduling of reinforcement learning driving.

The present invention relates to an intelligent, context-aware battery management system embedded within a mobile device that dynamically allocates power resources based on real-time user behavior, system state, and environmental context. It incorporates a smart recognition engine that analyzes sensor-derived telemetry data to compute behavioral deviation scores, enabling the system to anticipate abnormal or emergency-prone conditions. A continuous activity classification module contextualizes user motion and geolocation to inform power policy decisions. Upon detecting significant behavioral anomalies or critically low battery conditions, an emergency mode subsystem is triggered, restricting device operations to essential functionalities while preserving energy for critical communication and navigation tasks. The system also establishes a secure, lightweight emergency communication tunnel for relaying essential metadata, including GPS and behavioral indicators, to predefined response servers.

The invention discloses a bidirectional short message communication method used in a network-free scene, relates to the technical field of communication, and is used for solving the problem of poor communication in a network disconnection scene. Through multi-source environment perception and link state fusion modeling, real-time evaluation of communication environment accessibility is realized, the stability of a public network link is dynamically judged, and support is provided for channel switching; a scheduling scoring model is constructed in combination with a link state and task characteristics, so that the terminal preferentially transmits a high-emergency and high-adaptation task under a link limited condition, and the resource utilization efficiency is improved; a multi-time-scale risk integral mechanism is introduced, the recognition capability of sudden states such as falling, static and air pressure sudden change is improved, an emergency short message is automatically generated without human intervention, and quick uploading of SOS information and position is realized, so that the stability, safety and adaptability of communication in a network-free scene are improved.

The invention discloses an offshore platform emergency control method based on a Beidou satellite system and related equipment, and relates to the technical field of Beidou satellites.The offshore platform emergency control method based on the Beidou satellite system comprises the steps that Beidou satellite time service signals and real-time meteorological data are obtained, the method comprises the following steps: synchronously acquiring structural deformation parameters, marine environment dynamic parameters and personnel positioning information of an offshore platform, and constructing multi-dimensional data of the offshore platform; fusing and analyzing the multidimensional data of the offshore platform, extracting space-time correlation characteristics through a pre-trained dynamic risk prediction model, constructing a multi-factor causal chain, and determining a platform risk level and accident type prediction result; and triggering graded emergency response according to the accident type prediction result, encrypting and transmitting a corresponding early warning instruction to a preset terminal through a Beidou short message, and executing a corresponding emergency control method. According to the invention, risk prediction and emergency response are carried out through the multi-dimensional data of time-space synchronization, so that the offshore platform can carry out timely emergency control.

The invention relates to the technical field of power system management, in particular to a Beidou-based power grid emergency wireless communication monitoring system, which comprises a Beidou No.3 communication subsystem for realizing power business data encryption transmission, positioning and long message processing through a Beidou data transmission terminal and a handheld terminal; the short-wave communication subsystem establishes a communication link by using an autonomous frequency selection technology when no public network coverage exists; the Tiantong satellite communication subsystem provides voice and real-time data transmission service by means of a Tiantong satellite terminal; the converged communication control module dynamically switches communication links according to the channel quality, the service priority and the energy consumption index; the protocol conversion module realizes mutual conversion between electric power meter reading and a Beidou protocol; and the unmanned aerial vehicle relay extension module constructs an air relay link with the ground relay base station through the unmanned aerial vehicle group to extend Beidou signal coverage. According to the invention, efficient, reliable and wide power grid emergency communication is realized, and remarkable creativity and practicability are achieved.

The invention provides an intelligent short message link efficient detection method and system. According to the method, unmanned aerial vehicle cluster deployment is used for forming a dynamic communication topology, and the dynamic communication topology is used for monitoring the time delay mutation rate and the packet loss rate of a damaged short message link in real time and generating a state fluctuation sequence. When it is detected that the transmission time delay gradient exceeds an emergency communication threshold value, an abnormal marking mechanism is triggered, and abnormal association clusters and the space-time coupling relation of the abnormal association clusters are recognized by analyzing the data. Then, the information is bound with timestamps, and a block chain state change event is generated by using a multi-node parallel evidence storage technology; and adjusting the distribution density of the unmanned aerial vehicle according to a verification result, and generating a topology reconstruction factor so as to update a short message transmission path and optimize a communication network. According to the technical scheme provided by the invention, the stability and reliability of efficient detection of the short message link can be improved.

The invention provides a control method and system for an unmanned aerial vehicle to check and hit a ground station. The method comprises the following steps: firstly, acquiring real-time image data, carrying out terrain contour comparison, identifying a disaster risk area, secondly, generating a task mark file, compressing the task mark file into an encrypted data packet with a geographic label, then sending the encrypted data packet to a ground station, simultaneously receiving a rescue priority instruction, and adjusting the hovering height and the inspection navigational speed of the unmanned aerial vehicle. The method comprises the steps of receiving a device ready state code, sending the device ready state code to a ground station, verifying the integrity of the device ready state code to generate an action authorization identifier, controlling an unmanned aerial vehicle to fly to a safe coordinate, controlling the unmanned aerial vehicle to execute a task when a positioning signal transmitter receives a synchronous verification signal, and automatically deleting data after the task is completed; according to the technical scheme provided by the invention, rapid response, accurate execution and data closed-loop management of the unmanned aerial vehicle to the multi-target area in a disaster rescue scene are realized.

The invention relates to the technical field of logistics storage, and discloses an edge-cloud collaborative 5G logistics storage anomaly detection device and method. The device comprises a logistics data acquisition module, an edge preprocessing module, a lightweight model reasoning module, a cloud collaborative analysis module and a dynamic strategy generation module. The logistics data acquisition module acquires multi-source heterogeneous logistics storage data; the edge preprocessing module performs cleaning and dimension reduction on the related data to generate a standardized edge feature vector; the lightweight model reasoning module constructs a model based on an AutoML framework to perform real-time reasoning; the cloud collaborative analysis module fuses the data to generate a global abnormal event positioning map; and the dynamic strategy generation module generates an instruction and an alarm signal according to the result and issues the instruction and the alarm signal through 5G network slicing. According to the invention, multi-source heterogeneous data can be efficiently processed, real-time abnormal detection, accurate positioning and rapid response are realized, the intelligent level and operation efficiency of logistics warehouse management are improved, and the cost and the cargo loss risk are reduced.

The invention relates to the technical field of power system management, in particular to a Beidou-based power grid emergency wireless command system, which comprises a Beidou positioning communication terminal, a multi-source data fusion terminal, an intelligent decision-making terminal, a heterogeneous communication terminal and a visual command terminal. The Beidou positioning communication module accurately obtains the position of the power equipment and transmits an encryption instruction; the multi-source data fusion module integrates power, weather and geographic information, and provides support for decision making through data cleaning and space-time correlation analysis; the intelligent decision-making module generates a multi-target optimization decision by applying an improved multi-target genetic algorithm based on a digital twinborn dynamic plan library and a deep reinforcement learning algorithm; the heterogeneous communication module integrates various communication units, realizes mode dynamic switching and bandwidth aggregation, and ensures stable communication. And the visual command terminal displays the power grid situation and efficiently issues an instruction by means of augmented reality and multi-level authority management. The power grid emergency response and command efficiency is greatly improved, and power supply stability is powerfully guaranteed.

The invention relates to the technical field of Beidou positioning, and discloses a Beidou positioning inspection method and system. The method comprises the following steps: acquiring geographic information and equipment state parameters of an inspection area, and generating a structured task queue according to dimensions such as equipment types and fault levels; constructing a Beidou positioning dynamic model containing a position axis, a time axis and an environment factor axis; determining an initial inspection constraint condition according to the equipment type and the fault level, and performing path planning simulation to generate an initial inspection route; detecting a route anomaly, and adjusting an abnormal node by using a hybrid optimization algorithm to generate a stable route; model parameters are updated in combination with real-time environment data, and a final inspection instruction set containing information such as equipment moving time sequence is generated. The system comprises a data processing module, a model construction module, a constraint determination module, a path planning module, an anomaly detection module, an optimization adjustment module and the like. The inspection efficiency and precision are improved, the stability and reliability are enhanced, and the inspection requirements of complex environments can be effectively met.

The invention provides a real-time map route construction method and system. The method comprises the following steps: installing various sensors on an unmanned aerial vehicle to obtain multi-modal data of an environment; converting the multi-modal features into a high-dimensional embedding space, and constructing a real-time three-dimensional environment model based on a multi-modal point cloud reconstruction algorithm; deploying edge computing nodes, and distributing computing tasks to the edge computing nodes; planning a cooperative path among the multiple unmanned aerial vehicles; constructing a multi-unmanned aerial vehicle cooperative global adaptive adjustment mechanism to dynamically adjust the flight path of the unmanned aerial vehicle; and performing priority ranking on the tasks of the flight path of the unmanned aerial vehicle, constructing a path adjustment optimization mechanism according to the real-time flight condition to minimize the task failure risk, and updating the task priority and the scheduling strategy according to the feedback after each task is executed. According to the invention, a plurality of key problems in the prior art are effectively solved, and a technical guarantee is provided for successful application of the unmanned aerial vehicle in more complex application scenes.

The invention discloses an integrated multi-network integration satellite portable station, which belongs to the technical field of wireless communication networks, and comprises the following steps: a radio frequency module acquires satellite link signal quality and ad hoc network node distribution parameters, and generates a network original parameter set; the parameter processing module generates a network state feature vector through multi-dimensional feature extraction, and dynamically calculates a fusion weight value of the satellite and the ad hoc network based on a multi-target optimization model; the data receiving unit generates a multi-network modal scheduling instruction and a coding path according to the weight value, and receives production data and an emergency video stream; the data encapsulation unit encapsulates data in a mixed manner of framing compression and quantum key encryption; and the routing distribution module dynamically distributes the transmission proportion according to the weight. According to the invention, dynamic fusion weight calculation, a closed-loop power adaptive algorithm and a multi-protocol coding path selection mechanism are adopted, so that real-time optimal distribution of network resources, dynamic adaptation of transmitting power and efficient and safe transmission of mixed data streams can be realized.

The invention relates to the technical field of network monitoring, in particular to a method for constructing a dynamic self-adaptive alarm monitoring network based on LoRa and Ad-hoc ad hoc network technology, which comprises the following steps: (1) integrating a dynamic Ad-hoc ad hoc network routing protocol on each LoRa node, so that each node can automatically discover neighbor nodes, establish and maintain a dynamic routing table, and automatically discover the neighbor nodes; a non-centralized network architecture is realized; (2) through a multi-hop communication mode, the alarm information can be flexibly transmitted among the nodes, the coverage range of the network is expanded, and the system adapts to a complex geographical environment; and (3) by utilizing the characteristics of low power consumption and long-distance transmission of the LoRa technology, stable communication between the nodes in a large range is ensured, meanwhile, the energy consumption is reduced, and the working life of the nodes is prolonged. Through the dynamic self-adaptive Ad-hoc routing protocol, the network can automatically adjust the routing according to the node state and the environment change, the dynamic change of the network topology is adapted, and the reliable transmission of the alarm information is ensured.

The invention discloses an offshore platform anti-collision device and method based on multi-mode BEV perception, and the device comprises a three-dimensional fusion distance measurement module, a UWB distance measurement module, a ship navigation state monitoring module, a platform marine environment monitoring module, and a central processing unit. The three-dimensional fusion ranging module comprises a holder, a laser radar and a camera, and is used for performing 360-degree three-dimensional scanning on the periphery of the offshore platform; the UWB distance measuring modules are installed on the periphery of a ship and pile legs of an offshore platform. The ship navigation state monitoring module is used for acquiring ship position, navigational speed and course information in real time; the platform marine environment monitoring module collects wind wave data and weather data near the offshore platform and route information of passing ships through network communication. The invention discloses an offshore platform anti-collision device with real-time monitoring and collision risk assessment functions, the anti-collision safety of an offshore platform is improved, and the occurrence rate of collision accidents is reduced.

The invention provides a first-aid method and system based on 5G communication and an edge device. The method comprises the following steps: determining a communication protocol target adaptation protocol with a 5G base station based on the edge device; obtaining multi-modal data according to the target adaptation protocol based on the edge device, and performing priority classification on the multi-modal data to obtain a priority classification result; evaluating the 5G network resources of the edge device, determining a resource evaluation result, and determining a cloud transmission strategy based on the resource evaluation result and the priority classification result; performing association analysis on the vital sign data, the medical image data and the voice record data to obtain a calculation task and task complexity, processing the calculation task based on the task complexity and a cloud transmission strategy, and determining a data processing result; and data processing results are transmitted to the first-aid smart center and the mobile terminal in a grading manner. According to the method and the device, the compatibility problem caused by non-uniformity of device interfaces is solved, and the edge device processing capability is improved.

The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. Embodiments herein provide methods for handling disaster roaming service in network by UE. The method includes determining whether the UE receives a NAS message without integrity protection from a combination of first PLMN and second PLMN upon sending a registration request message to combination of first PLMN and second PLMN after expiry of a timer. In an embodiment, the method includes determining a count of attempt to combination of first PLMN and second PLMN meets a predefined threshold and determining that first PLMN is genuine network in which UE is not allowed to get disaster roaming service and blocking to retry on combination of first PLMN and second PLMN in response to receiving NAS message without integrity protection from combination of first PLMN and second PLMN upon sending a registration request message to the combination of first PLMN and second PLMN after expiry of timer.

The invention discloses a base station coverage anomaly detection method based on big data analysis, and belongs to the technical field of base station coverage detection in the technical field of communication. Aiming at the problems that the existing base station coverage anomaly detection is insufficient in accuracy and cannot adapt to dynamic environment change, the method comprises the following steps of: acquiring operation data such as received signal strength indication values of all base stations in a target area for continuous 1-30 days and 10-60 minutes, performing dimension reduction processing, and calculating a coverage characteristic value obtained by multi-dimensional index linear weighting; the method comprises the following steps: acquiring a coverage anomaly probability value, inputting the coverage anomaly probability value into an isolated forest model which is trained by historical data and can be dynamically updated, outputting the coverage anomaly probability value, and when the coverage anomaly probability value is in an interval greater than 0.7 and less than or equal to 0.9, marking a corresponding base station position on an electronic map as a coverage anomaly area. The method can accurately position the abnormal coverage area of the base station, is suitable for real-time monitoring and abnormity identification of the coverage state of the base station in communication network maintenance, and improves the network optimization efficiency and the service quality.

An integrated system for detecting dam breaches, as an early warning system and for evacuation assistance, consisting of: A geoinformatics analysis module comprising a modeling processor with a graphics processing unit, configured to: analyze spatial, hydrological, and topographic data of a dam and its downstream area; generate hydrological models using probable maximum rainfall (PMP) data to determine probable maximum flood discharge (PMF); generate hydraulic models to simulate flood propagation and determine flood depth, flood extent, flow velocity, and flood arrival time; create flood vulnerability models, vulnerability models, and flood hotspot models using a multi-criteria decision-making (MCDM) framework; and generate evacuation plans for high-risk zones based on the models. A sensor monitoring subsystem includes: a distributed fiber optic sensor (DFOS) configured to monitor the structural load and deformation of a dam, and a radar level gauge configured to measure the water level in the reservoir; a microcontroller unit configured to receive and process sensor data from the sensor monitoring subsystem, to detect dam breaches based on abnormal structural movements detected by the DFOS or sudden drops in water level below predefined thresholds detected by the radar level gauge; a communication module configured to transmit warning messages when dam breaches are detected; a warning system configured to: send SMS notifications to residents in downstream high-risk zones via a GSM communication module, generate real-time alerts via an IoT platform on user devices, and activate siren systems in villages to issue loud alarms and voice announcements; and an evacuation assistance platform configured to provide real-time evacuation assistance in emergencies due to dam breaks, displaying site maps with nearby emergency shelters, evacuation routes, hospitals, government buildings and aid centers, showing hydrological layers including flood extent, water depth, flow velocity and arrival time of the water, and enabling real-time location tracking in relation to safety zones and flood-prone areas.

The invention relates to an unmanned aerial vehicle emergency communication spectrum scheduling method and system based on dynamic entropy optimization, and the method comprises the steps: 1, constructing an emergency communication system, and calculating the gain of a received signal; 2, constructing a spectrum sensing and user access model; step 3, evaluating the channel quality in the emergency communication system; 4, establishing a state, an action and a reward of deep reinforcement learning according to spectrum sensing, a user access model and channel quality evaluation; 5, constructing a deep reinforcement learning model, and performing training to obtain a trained deep reinforcement learning model; and step 6, obtaining an optimal strategy of unmanned aerial vehicle emergency communication spectrum scheduling in a spectrum environment by using the trained deep reinforcement learning model, and realizing multi-user aggregation spectrum access. According to the invention, through intelligent distributed spectrum management, the problems of limited spectrum resources and energy, multi-user dynamic competition and the like in a disaster rescue scene are solved, and the spectrum utilization efficiency and the communication reliability are remarkably improved.

The invention provides a smart city split emergency management method and system based on an Internet of Things large model, and the method is executed by an emergency supervision management platform of the system, and comprises the steps: determining at least one accident based on target data; determining a data criticality based on the target data, the data basic features and the at least one accident; determining a data emergency feature based on the target data, the data abnormal feature and the data criticality; determining at least one target sub-platform based on the target data, the data exception features and the division conditions; determining emergency parameters based on the emergency type, the emergency degree and the data emergency characteristics; determining working parameters of the emergency vehicle based on the emergency degree, the emergency parameters and the data emergency characteristics; and based on the emergency parameters and the working parameters, generating and sending a scheduling instruction, and controlling the emergency vehicle to drive to the geographic area to work. According to the method and the system, accurate determination and dynamic allocation of emergency resources can be realized, and the overall efficiency of urban emergency management is improved.

The invention provides a multimode communication network dynamic scheduling system fused with AI computing power, which belongs to the technical field of communication equipment and artificial intelligence hardware fusion, and is characterized in that based on a four-layer hardware architecture of'core control-computing power support-multimode communication-high-speed interconnection ', an interconnection layer is constructed by adopting high-speed interfaces such as PCIe / SGMII + and the like, and inter-module fault is realized; 10ms low-delay data transmission is realized; the AI computing power module integrated with the 8TOPS NPU is deeply coupled with the multi-mode communication module, and the AI computing power module is quantized and compressed through an LSTM / Transform model and then solidified to an NPU special storage to realize scene self-adaptive scheduling; a'acquisition-identification-decision-feedback 'hardware closed loop is established, the communication interruption rate is reduced in an emergency scene, the overall power consumption is reduced, and AI reasoning is delayed. Through breakthrough hardware architecture design, AI computing power and a multi-mode communication module are deeply integrated, an intelligent communication resource scheduling system is constructed, and dynamic optimal configuration of communication resources in multiple scenes can be realized.

The invention particularly relates to an emergency broadcast intelligent early warning system applied to disaster prevention and reduction, and relates to the technical field of communication. The redundant communication and self-adaptive switching module is configured to establish a multi-mode communication network, monitor link states in real time and realize intelligent switching and load balancing of communication links based on a dynamic algorithm; an intelligent decision-making and precise broadcasting module; and the emergency broadcast terminal is connected with the offline execution module. According to the invention, a multi-mode communication architecture is established, each link monitors parameters such as signal strength, delay, packet loss rate and the like in real time, and intelligent switching and load balancing are carried out through a dynamic routing algorithm; and meanwhile, on the basis of memory thermal characteristic analysis, link faults are pre-judged in advance, switching is triggered, the success rate of early warning information transmission under extreme disasters is ensured, and the problem of transmission interruption of traditional single link communication under the scenes of power failure, base station damage and the like is solved.

The invention discloses a fire-fighting fireproof door alarm information transmission device and method based on the Internet of Things, and relates to the technical field of fire-fighting alarm, and the method comprises the following steps: carrying out the multi-band continuous scanning of a wireless communication environment of a fireproof door alarm device deployment region after a fire emergency mode is started, identifying a target communication protocol frequency band used by the fireproof door alarm device, and obtaining spectrum parameter information of each frequency band to form a to-be-analyzed communication frequency band set; and extracting a working frequency band used by the peripheral wireless equipment based on a pre-established environment wireless equipment frequency band database. Frequency spectrum mapping is constructed through frequency spectrum scanning and an environment database, intelligent interference prediction is realized in combination with a support vector machine, coding parameters are dynamically adjusted based on interference intensity, the transmission reliability of key alarm information in a high-interference environment is improved, feedforward recognition and closed-loop regulation and control capabilities are achieved, and the method is suitable for popularization and application. And the problems of slow response and unstable transmission of a traditional system are effectively solved.

An aspect of this disclosure includes a method of a communication apparatus. The method includes sending a message. The message includes a request to send information. The information includes at least one of: an identifier of a user equipment (UE); a location information where the UE locates; video information around the UE; photo information around the UE; sound information around the UE; temperature information around the UE; vital information of a user of the UE; and contact information of the UE. The method includes receiving the information after sending the message.