173 results about "Fire smoke" patented technology

The invention relates to the technical field of image recognition, in particular to a fire behavior recognition method and system based on video monitoring. The technical problem that the early warning reliability of a video monitoring system on fire smoke is insufficient is solved. The method comprises the following steps: acquiring a monitoring video stream of a monitoring area and time sequence data acquired by a sensor in the monitoring area; determining an evaluation value of the to-be-detected area based on the image feature and the morphological change of the to-be-detected area; determining a confidence factor based on the form change trend of the to-be-detected region and the change trend of the time series data; determining a smoke authenticity value based on the evaluation value and the confidence factor; and adjusting an alarm threshold value of the smoke alarm based on the smoke authenticity value. The method is used for fire smoke early warning and monitoring scenes.

The invention discloses an intelligent layering and guiding device for highway tunnel fire smoke and a control method, and relates to the technical field of tunnel fire safety, a smoke flow Froude number is introduced as a direct control target, the parameter represents the ratio of smoke flow inertia force to buoyancy force, the numerical value directly determines the stability of a layering interface, and the layering interface can be directly controlled. The Froude number of each subarea of the tunnel is calculated in real time through a sensing network and is compared with a critical value calibrated through an experiment, when a real-time value is lower than the critical value, it is indicated that inertia force is relatively insufficient, the buoyancy effect is dominant, and instability and entrainment are likely to happen to an interface between a smoke layer and lower cold air, and then according to a control algorithm, the smoke layer and the lower cold air are controlled. The micro jet fan applies directional inertia force to a smoke layer by adjusting the angle and the speed, the intelligent induction smoke outlet optimizes local pressure difference and flow by adjusting the opening degree and assists in maintaining flowing, the smoke flowing state is actively locked in a stable layered flow interval, and mixing and sedimentation caused by flow state instability are prevented.

The invention relates to the technical field of intelligent fire protection of a thermal power plant, and discloses an intelligent fire smoke detection method and system for intelligent fire protection of the thermal power plant, and the method comprises the steps: collecting a video stream of a fire protection monitoring region through video monitoring disposed in the fire protection monitoring region of the thermal power plant, and extracting a video frame in the video stream; performing spatial texture feature extraction and time change feature extraction on the video frames to obtain a fire smoke spatial texture feature map and a fire smoke time change feature map; performing feature fusion on the fire smoke space texture feature map and the fire smoke time change feature map to obtain fire smoke fusion features; identifying the fire smoke fusion feature through a pre-trained fire smoke identification model to determine a fire smoke identification result and identification confidence of the fire-fighting monitoring area; and acquiring sensor data acquired by a fire-fighting sensor deployed in the fire-fighting monitoring area, and determining a fire smoke detection result of the fire-fighting monitoring area based on the fire smoke identification result, the identification confidence and the sensor data.

The invention relates to a UHPC-based fabricated fire-fighting smoke exhaust fan room structure and a construction method thereof, the room structure comprises a main body structure, and the main body structure is prefabricated by adopting an ultra-high performance concrete UHPC material; a fan is arranged in the internal space of the main body structure; the main body structure is provided with a machine room enclosure bulkhead cylinder body and an end cover side wall. Wherein the machine room enclosure bulkhead cylinder body is provided with a bottom plate, a first side wall and a second side wall, the first side wall and the second side wall are connected with the bottom plate and vertically arranged in parallel, and a first opening end and a second opening end which are oppositely arranged are arranged at the two ends of the machine room enclosure bulkhead cylinder body in the horizontal direction respectively; the end cover side wall is provided with a first end cover and a second end cover which are respectively arranged at the first opening end and the second opening end; the first end cover and the second end cover are each provided with a smoke suction and exhaust port, and the smoke suction and exhaust ports are used for being connected with a ventilation pipeline. The UHPC shell is adopted, the advantages of being high in strength and good in fire resistance are achieved, the prefabricated assembly type structure is adopted, construction is convenient, and efficiency is high.

The embodiment of the invention provides a smoke shielding false alarm intelligent identification system and method, and is applied to the technical field of intelligent fire detection, and the method comprises the steps: synchronously collecting an imaging picture, radiant heat response data and a wind field state parameter of a suspected shielding region; the method comprises the following steps: identifying and identifying an abnormal shielding area in a picture; further analyzing the motion characteristics of the region along with the change of the wind field and the dynamic process of the thermal inertia change of the region; the core is to judge whether a time sequence lag relationship meeting a smoke diffusion physical rule exists between the two, so as to identify whether the shielding object is combustion smoke or not. And if the physical mechanism is not met, the alarm is inhibited, so that real fire smoke and non-fire interferents such as dust and steam are effectively distinguished, and the fire false alarm rate in a complex ventilation environment is remarkably reduced.

The invention discloses a forest fire smoke monitoring method and related device based on false detection feedback and model self-evolution, and the method comprises the steps: obtaining a video stream of a monitoring region, carrying out the preprocessing, inputting a target detection model and a scene understanding model, and judging whether a candidate alarm event is generated or not through consistency analysis; when a candidate alarm event is generated, a work order is generated for manual judgment, a real alarm executes a disposal process, and a false alarm is stored in a database; screening high-value false detection samples based on an information entropy priority strategy, storing the samples into a dynamic memory bank, selecting the samples to form an incremental training set, performing incremental training on a pre-training teacher model, and introducing low-rank constraint stability parameters; migrating the discrimination ability of the teacher model to the student model through knowledge distillation, wherein alignment of a channel dimension and a multi-scale space dimension is carried out; and redeploying the updated student model to execute target detection. The invention aims to solve the problems that the current monitoring system depends on manpower, the coverage capability is limited, the response is slow and the cost is high, and the traditional method is high in false alarm rate, easy to leak and misjudge, difficult in large-scale network edge deployment, limited in light-weight model discrimination capability, lack of linkage between alarm processing and model updating and the like, and more accurate and efficient forest fire smoke monitoring is realized.

The invention discloses a rapid fire smoke diffusion simulation method based on a grid Boltzmann technology, and relates to the technical field of fire safety simulation. Comprising the following steps: carrying out three-dimensional modeling inside and outside a semiconductor large-scale industrial factory building, gridding the three-dimensional modeling inside and outside the semiconductor large-scale factory building, dividing a calculation space by adopting a Boltzmann LBMD3Q19 model, setting a fire point, calculating a smoke substance proportion by adopting an incomplete combustion chemical reaction equation, and calculating combustion heat release according to the incomplete combustion chemical reaction equation. Calculating a high-temperature thermal plume region formed by chemical reaction heat release, calculating a microscopic particle collision process, calculating a microscopic particle migration process, processing boundary conditions, counting macroscopic quantity, and iteratively calculating flue gas concentration; according to the method, microscopic and macroscopic advantage complementation of the two can be realized, the resolving efficiency is improved, seamless coupling of flame chemistry-turbulence-heat transfer is completed, and a new method is provided for solving the problem of fire smoke spreading of complex plants.

The present application relates to a kind of fire smoke flow intelligent monitoring early warning device and early warning method, early warning device includes base, swivel seat, monitoring head, main control module, thermal imaging module, laser module and alarm module, swivel seat is horizontally rotated by drive mechanism one and is arranged on base, monitoring head is vertically rotated by drive mechanism two and is arranged on swivel seat, laser module and thermal imaging module are arranged on monitoring head, thermal imaging module is connected with main control module, main control module is used to calculate the movement direction of smoke, main control module is connected with drive mechanism one, drive mechanism two, laser module and alarm module, for according to the movement direction of smoke control drive mechanism one and drive mechanism two action, make laser module towards the movement track of smoke.The present application has higher identification efficiency, judgment accuracy and response speed, can provide key early warning for firemen before fire outbreak, so as to gain crucial emergency decision and evacuation time.

The present application relates to the technical field of smoke alarm, in particular to a kind of intelligent fire-fighting smoke sensing alarm method and system based on Internet of Things, comprising the following steps: installing spectrum analysis sensor in the key area of building, capture spectrum signal, according to preset time interval collection smoke spectrum data, and be transmitted to cloud platform by Internet of Things network node, unified data format, generate spectrum dataset.In the present application, by capturing and analyzing the spectral characteristic curve of smoke, different types of smoke can be distinguished, efficient differentiation between fire smoke and non-fire smoke is achieved, false alarm phenomenon is reduced, combined with real-time environmental data, dynamically adjust the sensitivity of the sensor and the alarm threshold, still can maintain high reliability in complex and variable environment, at the same time, it can trigger multiple device response synchronously, quickly start fire sprinkler, smoke exhaust equipment and other mechanisms, and real-time fire alarm signal is transmitted to relevant departments, shorten the response time, optimize the linkage effect of fire emergency handling.

The embodiment of the application provides a smoke shielding false alarm intelligent identification system and method, which is applied to the technical field of intelligent fire detection. The method synchronously collects imaging pictures, radiation heat response data and wind field state parameters of a suspected shielding area. Firstly, shielding abnormal areas in the pictures are identified and marked. Then, the motion characteristics of the areas with the change of the wind field and the dynamic process of the change of the heat inertia of the areas are analyzed. The core is to judge whether there is a time sequence lag relationship conforming to the physical law of smoke diffusion between the two, so as to identify whether the shielding object is burning smoke. If the physical mechanism is not met, the alarm is inhibited, so that the real fire smoke and non-fire interference objects such as dust and steam can be effectively distinguished, and the fire false alarm rate in a complex ventilation environment is significantly reduced.

The application discloses a power transmission line mountain fire smoke detection method and system, comprising the following steps: for the power transmission channel picture to be detected, a pre-trained semantic segmentation model is used to segment out the mountain fire smoke candidate area in the picture and calculate the semantic segmentation confidence score; for each mountain fire smoke candidate area, the shape similarity score is calculated through a shape matching method, the position confidence score is calculated through a position function, and the color confidence score is calculated through color distribution comparison; the semantic segmentation confidence score, the shape similarity score, the position confidence score and the color confidence score are weighted and summed to obtain the final smoke confidence score, which is compared with a preset threshold to determine whether the corresponding mountain fire smoke candidate area is mountain fire smoke. The technical scheme provided by the application can effectively identify the mountain fire smoke condition in the power transmission line channel picture, and significantly reduce the misidentification conditions such as pond smoke, chimney smoke and cloud and mist, and has a wide application scenario.

This invention discloses a method for detecting and locating the smoke front in a highway tunnel fire, comprising: S1. performing data augmentation processing on the acquired fire smoke images to obtain an image dataset; S2. inputting the image dataset into a fire smoke detection network model for network model training to obtain a trained detection network model; S3. inputting the fire smoke image to be detected into the trained detection network model and outputting the fire smoke target area; S4. determining the position of the smoke front in the fire smoke target area; S5. determining the longitudinal distance between the smoke front position and the monitoring position. This invention can obtain richer subsequent disaster information and has high fire detection accuracy and timeliness.

The utility model discloses a detection device for fire alarm equipment maintenance belongs to detection device for fire alarm equipment maintenance technical field, and its technical scheme main points include the smoke gun body, the surface fixedly connected with the protection subassembly of smoke gun body, the inside fixedly connected with auxiliary assembly of protection subassembly, protection subassembly includes the placement block, the inside fixedly connected with electric telescopic handle of placement block, the top fixedly connected with the shield cover of electric telescopic handle, can solve the detection device of most fire alarm equipment maintenance of current through the fire smoke gun and produce the smoke dust, then through the smoke dust and the fire alarm device that needs to detect contact, and this to fire alarm device detection, but the current lack of smoke dust shelter structure, the smoke dust that produces has certain smell, and some smoke dust according to need, and the smoke dust will contain harmful substance, lead to the influence to test personnel, and influence the working environment.

The invention discloses a map real-time construction and rescue path dynamic planning system oriented to a fire dense smoke scene, and relates to the technical field of fire rescue. The system comprises a data acquisition and processing module, an environment modeling and path construction module and a post-processing module, based on millimeter wave radar, laser radar and motion sensor data, multi-modal information is obtained, synchronized and converted, a semantic segmentation model is utilized to analyze environment perception data to generate a feasible space, and laser radar point cloud and motion sensor data are fused to realize real-time positioning, map construction and rescue path planning in a fire scene. The path is updated in real time according to fire scene environment change, and a generated result is visually presented through a post-processing module and communicates with a command platform for real-time interaction. The system has the advantages of long-distance sensing of the millimeter wave radar and short-distance high precision of the laser radar, can realize quasi-real-time and high-precision fire scene environment modeling and dynamic path generation, and provides reliable path reference for rapid action decision in fire rescue.

The application relates to the technical field of indoor positioning, in particular to an indoor personnel positioning method and system based on multi-modal perception. The application proposes the following scheme: by acquiring the ultra-wideband channel impulse response, millimeter wave radar data and thermal imaging data of each layer, combining building information for double-base geometric mapping, reconstructing an indoor ray path and generating an occupancy grid map. Further, the water mist distribution intensity generated by a spraying device is collected, phase correction and beam domain purification are performed on the millimeter wave data, and flow direction filtering and flicker suppression are performed on the thermal imaging data to obtain pretreatment data. On this basis, motion prior information and boundary constraint information are extracted, and fusion is realized through mass conservation update and normalization synthesis in the occupancy grid map, and finally the position information and motion direction of the object to be positioned are output. The application can maintain positioning stability and accuracy under the interference of fire smoke, water mist and multipath effect, and is suitable for high-risk scenes such as fire rescue.

The utility model discloses a fire-fighting smoke alarm device which comprises a sleeve, the inner wall of the sleeve is fixedly connected with a plurality of fixing rods, and the fixing rods are annularly and uniformly distributed on the inner wall of the sleeve. According to the utility model, a traditional installation mode depending on 3M glue and magnet adsorption is abandoned, the installation disc and the bolts are matched to fix the roof, and the plurality of bolts can greatly improve the fixing stability of the installation disc, thereby ensuring the stable installation of the sleeve, the fixed rod, the cylindrical block and the smoke alarm body; meanwhile, through unique cooperation of the fixing rod and the limiting groove in the surface of the cylindrical block and combination of upward acting force applied by the elastic assembly, the smoke alarm body is not prone to loosening and falling off due to external force collision, vibration or environment change after being installed, stable operation of the device in the long-term use process is effectively guaranteed, and reliable guarantee is provided for fire safety monitoring. The device has the advantages of being firm in installation and convenient to disassemble and assemble.

The invention discloses an adjacent tunnel fluid channeling ratio simulation test device and method combined with boundary conditions, the adjacent tunnel fluid channeling ratio simulation test device combined with the boundary conditions comprises an upstream tunnel model, a downstream tunnel model and a middle section road surface, and the side surface of the middle section road surface is provided with a crosswind simulation mechanism. And a full-spectrum lamp is arranged above the middle section of the road surface. The invention further relates to an adjacent tunnel fluid channeling ratio simulation test method in combination with the boundary conditions. According to the method, the sulfur hexafluoride (SF6) concentration is used as a basis for quantitatively calculating the fluid channeling ratio, fluid channeling analysis of traffic pollutants and high-temperature fire smoke can be combined, and a more accurate adjacent tunnel pollutant fluid channeling ratio is obtained by combining terrain wind environment boundary conditions and pavement thermal environment boundary conditions; and more reliable experimental data is provided for the design of adjacent tunnels and the type selection of ventilation and fire fighting equipment.

The application discloses a hospital fire emergency evacuation method and system based on Internet of Things, and relates to the technical field of emergency evacuation methods. A plurality of emergency evacuation paths are determined according to the indoor distribution map of the hospital and the regional position of the fire area. The best emergency evacuation path is determined based on the plurality of emergency evacuation paths, the current position of the hospitalized patient and the hospital fire state map. Therefore, the evacuation action instruction of the hospitalized patient is determined according to the node position of the plurality of emergency evacuation nodes, the corresponding fire smoke area and the action state of the hospitalized patient. The corresponding fire fighting event is determined according to the evacuation behavior of the hospitalized patient and the position of the fire fighting personnel. The plurality of fire fighting projects are determined according to the identification of the fire fighting event. The multi-level rescue event of the hospitalized patient is determined according to the plurality of fire fighting projects, the current position of the hospitalized patient and the fire change event of each fire area. The accuracy of the multi-level rescue event of the hospitalized patient is improved.

The utility model relates to the technical field of smoke exhaust fan, concretely is a kind of adjustable fire-fighting smoke exhaust fan of aluminium leaf, including smoke exhaust seat and the mounting plate of setting in the front side of smoke exhaust seat, the left side of smoke exhaust seat is respectively equipped with siren and pilot lamp, the back of smoke exhaust seat is respectively provided with smoke fire sensor, connecting block and moving groove, the top of connecting block is provided with adjusting motor, the opposite side surface of connecting block is respectively provided with adjusting screw rod and positioning rod, the inside of smoke exhaust seat is respectively provided with smoke exhaust fan and adjusting groove, the inside of adjusting groove is slidably provided with fire-retardant aluminium leaf, the left and right ends of fire-retardant aluminium leaf back side are all fixedly installed with adjusting block, and split mounting mechanism is arranged between mounting plate and smoke exhaust seat, by setting a kind of adjustable fire-fighting smoke exhaust fan of aluminium leaf, to utilize the structural design in split mounting mechanism, further played the purpose of split mounting and disassembly to smoke exhaust seat, subsequent maintenance is facilitated.

This invention discloses a method for assessing the fire status of a submersible compartment based on multi-source heterogeneous data fusion, comprising the following steps: 1) acquiring monitoring video streams of the compartment under natural light conditions; 2) dividing a acquired video into K segments, randomly selecting a small segment from each segment; inputting the selected small segment into a spatiotemporal dual-stream convolutional neural network to obtain category scores for different small segments, then fusing them to locate fire and smoke areas in the video stream; 3) acquiring a heat map of the monitored compartment area, and assessing the fire status of the compartment based on the thermal imaging image; 4) combining multiple heterogeneous fire early warning signal data for collaborative analysis and information fusion to provide accurate early warning of fire hazards in the compartment. This invention acquires monitoring video streams of the compartment under natural light conditions and designs a convolutional neural network model based on a temporal attention mechanism to process the video stream and detect and locate fire and smoke areas in the video stream.

The application discloses a forest and grassland fire smoke and fire point simultaneous detection method. The method obtains visible light and infrared band images of a target area, registers and synthesizes into multi-band synthetic data; the data is input into a pre-trained multi-modal smoke and fire simultaneous detection network for feature extraction, the network adopts a feature fidelity down-sampling module containing a fixed kernel low-pass filter and average pooling during down-sampling, and is combined with a cross-layer connected background suppression and smoke and fire focusing module, a multi-scale smoke and fire shape perception module and a smoke and fire space information rearrangement amplification module for joint processing; finally, according to the feature channel set, the smoke and the fire point area are respectively located, and a fire monitoring distribution map is generated by superposition. The application realizes the simultaneous detection and mutual verification of multi-modal features of smoke and fire, effectively overcomes the loss problem of small fire points and smoke plume details, and improves the accuracy of early fire warning.

The utility model discloses a fire-fighting smoke exhaust window capable of being opened by 70 degrees, and relates to the technical field of fire-fighting smoke exhaust windows. The aluminum alloy window comprises a latticed structure formed by aluminum alloy cross beams and aluminum alloy stand columns, and a plurality of opening windows are fixedly connected into grids formed by the aluminum alloy cross beams and the aluminum alloy stand columns. A plurality of steel pipes are fixedly connected to the intersection points of the aluminum alloy cross beams and the aluminum alloy stand columns in an inserted mode, a plurality of fixed windows are connected between the steel pipes through hardware, and a flat curtain wall is formed. The use of the aluminum alloy decorative pressing plate not only enhances the aesthetic degree of the curtain wall, but also provides a good protection effect, the arrangement of the opening window and the fixed window meets the requirements of ventilation, lighting and visual field of the curtain wall, the opening window can be produced in a pre-assembly mode and can be quickly mounted after arriving at the site, and the production cost is reduced. And a user can conveniently ventilate in the use process.

The invention discloses a detector shell and a fire smoke detector, and belongs to the technical field of smoke alarm, the detector shell comprises a shell body, a cover body, a sealing member, an upper cover and a supporting cover, the cover body is embedded in the shell body, the cover body is matched with the shell body, the edge of the cover body extends downwards and is tightly attached to the inner wall of the shell body, and the top surface of the cover body is flush with the top surface of the inner wall of the shell body; the sealing piece is placed on the cover body, the edge of the sealing piece abuts against the flange of the shell, the upper cover is placed on the sealing piece, the shell, the cover body, the sealing piece and the upper cover are tightly connected through screws, and the supporting cover is fixed to the cover body. According to the detector shell and the fire smoke detector, an embedded structure is adopted, the possibility that water vapor and dust enter the interior along shell gaps to erode the control assembly is effectively reduced, and disassembly and maintenance are convenient.

This utility model discloses a multi-dimensional composite fire detector, belonging to the field of fire detectors. It includes a front shell with a battery slot containing a battery, and a battery cover covering the battery. The multi-dimensional composite fire detector of this utility model, through its flame PCB and control board, allows for assembly by first installing a bracket onto a rear shell, causing magnets one and two to attract each other, and then installing the front shell into the rear shell to complete the installation. When the fire detector detects smoke reaching a predetermined threshold, an alarm sounds. The flame PCB enables timely detection of flame information, enhancing the safety performance of the fire detector. This fire detector effectively distinguishes between fire smoke and facilitates cleaning of dust covers, and enables multi-dimensional cross-verification in the early stages of a fire.

The invention discloses a forest fire smoke monitoring method based on cooperation of multiple unmanned aerial vehicles, and the method comprises the following steps: collecting a to-be-monitored forest region image based on the unmanned aerial vehicles, constructing a lightweight smoke detection model, inputting the collected forest region image into the lightweight smoke detection model, and obtaining the position and confidence of a smoke target; according to the position and the confidence coefficient of the smoke target, combining with air concentration data acquired by a sensor carried by an unmanned aerial vehicle, and performing fusion to generate a smoke concentration field; and calculating a concentration gradient according to the smoke concentration field, and dynamically adjusting the cruise trajectories of the plurality of unmanned aerial vehicles by taking the concentration gradient as guidance, so that the unmanned aerial vehicles collaboratively approach the fire source area to complete forest fire smoke monitoring. The intelligent level of early forest fire monitoring is improved at the same time in three dimensions of detection precision, real-time response and energy consumption efficiency.

The invention relates to the technical field of disaster prevention and reduction, in particular to a mixed reality experiment method and system for personnel evacuation influenced by fire smoke parameters. The method comprises the following steps: selecting fire smoke parameters to be researched, and setting a plurality of working condition levels; the method comprises the following steps: acquiring flue gas data through fire simulation, establishing a flue gas-visual equivalent model, and mapping the data into visual information; a virtual reality engine and a particle system are utilized to construct a high-reality-sense fire smoke virtual scene, and the scene is carried on mixed reality equipment for space registration to form an experimental environment; an experimenter wears equipment to carry out an evacuation experiment, and three-dimensional tracks and posture data of the experimenter are recorded in real time; performing double denoising on the data, and outputting effective time sequence data; and analyzing the effective time sequence data to obtain a fire smoke parameter and evacuation efficiency formula, and providing an evacuation model under the action of the fire smoke parameter. Experiments are designed according to fire smoke parameters, a high-reality fire smoke experimental environment is provided, and the influence mechanism of the fire smoke parameters on evacuation behaviors is researched.

The application relates to the technical field of image recognition, and particularly discloses a car washer construction real-time fire smoke detection and recognition system based on computer vision, which obtains a preprocessed image sequence through image enhancement processing on a real-time collected video stream; adopts dynamic background modeling combined with a predefined mask of inherent moving parts of the car washer to carry out foreground segmentation and extract a real motion foreground area; extracts a suspected flame area and a suspected smoke area from the motion foreground area based on color space analysis and a dark channel theory; extracts static texture features and dynamic shape change features of the flame area to form a flame feature vector, and extracts color statistical features and gradient direction features of the smoke area to form a smoke feature vector; inputs the feature vectors into a pre-trained classification model to obtain fire and smoke probability values, and outputs a structured recognition result containing category and position information when the probability values exceed a set threshold; and the application can effectively distinguish real fire from environmental interference.

The invention relates to a forest fire monitoring method and device and computer equipment. Comprising the following steps: shooting a monitored mountain to obtain an environment image corresponding to the monitored mountain, performing smoke identification on the environment image, and calculating to obtain a first identification result; when it is detected that smoke exists in the environment image, smoke recognition is carried out on the area where the environment image is located in the time dimension and the space dimension, and a multi-dimensional recognition result is obtained; acquiring temperature, humidity and rainfall of the corresponding area of the environment image in a preset time period, calculating to obtain a forest fire index of the corresponding area of the environment image, and obtaining a second recognition result according to the forest fire index; and obtaining a target recognition result according to the first recognition result, the multi-dimensional recognition result and the second recognition result, marking the environment image according to the target recognition result, uploading the marked environment image to a platform side, and determining a forest fire smoke recognition result of the environment image through the platform side. According to the invention, the false alarm rate of forest fire monitoring can be reduced.

This utility model relates to the field of forest belt construction technology, specifically an integrated automatic drip irrigation and monitoring device for biological firebreak forest belt construction. It includes a base, with a dosing tank fixedly installed on the upper left side of the base. The dosing tank has a dosing inlet on its upper left side. A stirring assembly, including a motor, is fixedly installed in the middle of the upper part of the dosing tank, and a stirring rod is fixedly connected to the motor's rotating shaft. A first connecting pipe is fixedly connected to the lower right side of the dosing tank, and the other end of the first connecting pipe is fixedly installed on a water pump. A smoke sensor detects early fire smoke, triggering an alarm and linking the irrigation system (such as emergency water spraying for cooling) to curb the spread of fire. In high fire risk periods or areas prone to lightning strikes, rapid response can prevent small fires from escalating into major disasters. A humidity sensor monitors soil moisture in real time, and a controller automatically controls the solenoid valve to achieve precise drip irrigation.

This invention discloses a collaborative intelligent control method for multiple smoke exhaust systems in tunnel fires based on MPC. It achieves synchronous iteration of simulation, control, and physical hardware by constructing a full-size FDS numerical model and a Python-FDS-hardware-in-the-loop three-in-one millisecond-level bidirectional coupling interface. A spatiotemporal topology of tunnel fire smoke evolution is constructed to quickly and accurately predict the spatiotemporal distribution of smoke throughout the tunnel. A two-layer deep MPC architecture combining global collaborative optimization and zoned rolling control is designed, integrating multi-objective optimization functions for evacuation safety, smoke risk, energy consumption, and adjustment smoothness, and embedding hard constraints such as equipment rating, differential pressure, and safety thresholds. Adaptive rolling time-domain optimization and adaptive reconfiguration mechanism for fan failures are introduced. Finally, distributed collaborative closed-loop intelligent control of multiple smoke exhaust fans is achieved through the coupling interface, outputting control commands and fire situation data, significantly improving response speed.