283 results about "Fire smoke" patented technology

The invention discloses an expressway tunnel abnormal event recognition method based on multi-scale polarization fusion, relates to the technical field of intelligent recognition of road traffic videos, and is used for solving the problem of robust recognition of trailing collision, fire smoke and abnormal static behaviors in an expressway tunnel scene. The method comprises the following steps: acquiring polarization angle and polarization degree information of each pixel point in a vehicle driving process; then, the image is divided into a plurality of partitions according to longitudinal illumination changes, a time sequence locking window is established in each partition, and the difference between traffic flow reflection characteristics and background interference is extracted; and identifying a smoke area by constructing a disturbance graph and a direction texture graph, calibrating a trailing collision risk, and judging an abnormal static behavior. And finally, an event atlas is generated, full-process identification closed loop and response cooperation are ensured through structure fingerprints and version numbers, and a high-robustness identification means is provided for fire, trailing and abnormal static targets in a tunnel scene.

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 belongs to the technical field of tunnel catastrophe, and particularly relates to an intelligent feedback type tunnel catastrophe monitoring method, which comprises the following steps of: 1, deploying a tunnel monitoring system; a temperature sensor, a smoke sensor, an air velocity sensor and a gas concentration sensor are arranged in the tunnel; the temperature sensor is used for monitoring temperature changes in the tunnel. According to the intelligent feedback type tunnel catastrophe monitoring method, the safety and the emergency response capability of the tunnel are effectively improved through real-time data monitoring and analysis and an automatic control mechanism. Firstly, through temperature, smoke, gas concentration and air velocity sensors, the system can detect and identify potential catastrophe risks in a tunnel in time, such as fire, smoke diffusion and harmful gas leakage. Once an abnormality occurs, the system performs catastrophe prediction through an algorithm model, and performs accurate evaluation on a fire propagation path and smoke diffusion in combination with a simulation analysis result, thereby providing reliable data support for quick response.

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 sensors, in particular to an intelligent fire-fighting fire smoke particle detection method, which comprises the following steps: acquiring multiple frames of target images of a target area, and determining whether the smoke area in each frame of target image is a fire smoke area according to the gray value of the smoke area in each frame of target image; determining the actual brightness of each sub-region in the fire smoke region under the condition that the fire smoke region is the fire smoke region; determining the global concentration of the fire smoke area according to the original brightness, the actual brightness of each sub-area and the number of pixels, and determining the instantaneous acceleration of the smoke concentration based on the global concentration of the fire smoke area in the target image of the current frame and the global concentration of the fire smoke area in the target image of the previous frame; and determining a fire risk grade by using the instantaneous speed increase of the smoke concentration and triggering an alarm of the corresponding grade. Therefore, the accuracy and reliability of the detection result of the fire smoke particles are improved.

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 discloses fire smoke alarm equipment based on a satellite positioning function, and belongs to the technical field of fire smoke alarm systems. Comprising a smoke alarm and a base, and double interchangeable collecting cylinders are arranged in the smoke alarm. The first collecting cylinder is used for a high-dust environment, and 80% of coarse dust is pre-separated through a large aperture and a settling table. The second collecting cylinder is used for high-humidity environment, small aperture and chimney effect condensation prevention, and the ventilation rate is larger than or equal to 96%. A smoke channel is integrated in an inner cavity of the upper connecting disc, an annular spraying array is arranged on the outer ring of the lower connecting disc, and the integration of detection, positioning and fire extinguishing is achieved. The satellite baseband chip and the infrared maze share an antenna guiding assembly, NMEA coordinates are frozen when smoke exceeds a threshold value, the NMEA coordinates are directly sent to a platform through NB-IoT, the positioning error is smaller than or equal to 2 m, and a platform map is a second-level flash point. The drawer type smoke detection module can be disassembled quickly in 5s, double silica gel sealing and pulse water spraying hole cooling are adopted, and long-term maintenance-free under high-temperature, high-dust and high-humidity conditions is ensured.

The invention discloses a forest fire smoke particle adsorption degree prediction method, system and device and a medium, and belongs to the field of power systems, and the method comprises the steps: obtaining forest fire data of a to-be-predicted overhead transmission line under a forest fire condition in a preset time period; inputting the forest fire data into a simulation calculation model, so that the simulation calculation model constructs a simulation model corresponding to the overhead transmission line to be predicted according to the forest fire data, determining a corresponding relation between coordinate data of each smoke particle and each simulation area according to the simulation model, and calculating the number and quality of the smoke particles in each simulation area, and outputting an adsorption degree prediction result corresponding to the target simulation area, the simulation model comprising a plurality of simulation areas, and each simulation area being obtained by division according to the space field intensity of the to-be-predicted overhead transmission line, so that through implementation of the method, the adsorption degree of the smoke particles in the overhead transmission line can be accurately predicted, and the prediction accuracy of the adsorption degree of the smoke particles in the overhead transmission line is improved. And the safety of the power system is improved.

The invention discloses a fire smoke detection method based on an improved YOLOv8 network, and the method comprises the steps: carrying out the data preprocessing, and building a data set: building the data set through employing a fire smoke image, and enabling the data set to comprise two kinds of scene cities and forests; comprising annotation fire disasters and smog of two target categories, large targets and small targets of the fire disasters and the smog, and interference images without the fire disasters and the smog; establishing a target detection network which comprises a feature extraction network, a feature fusion network and a detection head; the feature extraction network generates a multi-scale primary feature map; the feature fusion network optimizes semantic and spatial information of the multi-scale primary feature map through cross-scale connection, and outputs an enhanced feature pyramid; the detection head executes fractional-scale dense prediction based on the pyramid, and outputs a detection result through non-maximum suppression; and sending the test set sample to a target detection network, and performing category classification and position regression on test data to obtain a final detection result.

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 invention discloses an intelligent temperature control axial flow type fire-fighting smoke exhaust fan, and belongs to the technical field of smoke exhaust fans. Blades of an impeller of the smoke exhaust fan comprise a connecting piece, a rotating piece and a connecting shaft, two sets of symmetrical thermal deformation metal pieces are arranged between the connecting piece and the rotating piece, the characteristic that the thermal deformation metal pieces contract or extend along with the temperature is utilized, the rotating piece is driven to deform bidirectionally so as to adjust the angle of the blades, intelligent temperature control is achieved, and the air volume of the impeller can be automatically adjusted. A heat dissipation and self-cleaning integrated component is further arranged on the machine shell, the functions of oscillation of cleaning liquid, heat dissipation and self-cleaning can be achieved, the smoke exhaust fan can be self-cleaned while heat dissipation is conducted on the whole smoke exhaust fan, a large amount of dust is prevented from standing and precipitating on blades, and the heat absorption and dissipation capacity of the whole smoke exhaust fan can be enhanced. Intelligent adjustment is achieved through mechanical structure linkage, complex electric control is not needed, and the smoke exhaust efficiency, operation stability and maintenance convenience are improved.

The invention relates to an assembly type integrated fire-fighting smoke exhaust fan room structure which comprises a machine room enclosure bulkhead cylinder body which 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 the two ends of the machine room enclosure bulkhead cylinder body in the horizontal direction are provided with a first opening end and a second opening end which are oppositely arranged correspondingly; 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; smoke suction and exhaust ports are formed in the first end cover and the second end cover and are used for being connected with a ventilation pipeline; the machine room access door is arranged on the first side wall or the second side wall and can be opened and closed; the fan is arranged in an internal space formed by the machine room enclosure bulkhead cylinder body, the first end cover and the second end cover; the machine room enclosure bulkhead cylinder body, the first end cover, the second end cover and the machine room access door are all of a prefabricated concrete structure. The fabricated integrated design is adopted, the cost is low, the self weight is light, fireproof performance is achieved, and the advantages of being stable, reusable, attractive and the like are achieved.

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 invention relates to the technical field of fire alarm, in particular to a method for preventing false alarm of a fire smoke detector in a high-frequency electromagnetic field environment. The method comprises the following steps: S1, acquiring a smoke scattered light intensity signal, an environment high-frequency electromagnetic field intensity signal and a temperature and humidity signal in real time through a multi-sensor synchronous acquisition module; s2, constructing an electromagnetic coupling feature set; s3, inputting the basic smoke characteristics and the electromagnetic coupling characteristics into a pre-trained random forest model; s4, aggregating the output probabilities of all decision trees by adopting a soft voting mechanism; s5, dynamically adjusting an alarm threshold value according to the real-time electromagnetic field intensity; and S6, judging whether fire alarm is triggered or not. According to the method, a diversified and robust decision tree set is constructed by using the random forest, and prediction of the trees is aggregated through soft voting, so that the signal identification accuracy of the fire smoke detector can be remarkably improved. According to the invention, the variance and deviation are effectively reduced, and the robustness of the model to noise and complex interference modes is enhanced.

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 utility model relates to the technical field of smoke alarms, and discloses a fire smoke alarm, which comprises an installation disc, and further comprises fixing frames which are symmetrically arranged at the bottom of the installation disc, installation plates are arranged in the two fixing frames, the bottoms of the two installation plates are fixedly connected with an alarm body, and the alarm body is fixedly connected with the installation disc. Heat dissipation holes are formed in the bottom of the alarm body at equal intervals, and smoke inlet grooves are formed in the outer portion of the alarm body at equal intervals. According to the utility model, through the arrangement of the installation assembly, workers can conveniently disassemble and assemble the alarm body, the disassembly and assembly efficiency of the alarm body is effectively improved, the workload of the workers is reduced, and through the arrangement of the dustproof assembly, the alarm body can be effectively subjected to dustproof protection treatment; impurities such as dust in the external environment are prevented from entering the alarm body through the heat dissipation holes and the smoke inlet groove, and the service life of the alarm body is effectively prolonged.

The invention relates to the technical field of fire smoke temperature composite detectors, in particular to an internet-based subway fire smoke temperature composite detector, which comprises a main body, the removing assembly is arranged at the bottom of the main body and comprises a mounting plate, a mounting groove is formed in the mounting plate, a moving plate is arranged in the mounting groove, a sliding plate is arranged on one side of the moving plate, a cleaning plate is arranged on one side of the sliding plate, a driving disc is arranged on one side of the mounting groove, and a connecting plate is arranged on one side of the driving disc; and the positioning plate is arranged on one side of the moving plate. Through mutual matching of a connecting plate, a connecting block and a spring of the removing assembly, a positioning plate and a cleaning plate can move, in this way, the device can clean the filter screen through shaking generated when the subway stops or starts, blockage of the filter screen is avoided, and the service life of the filter screen is prolonged. And by means of the swinging assembly, the device can effectively utilize shaking of starting or stopping of the subway to conduct streaming treatment on air, and the flue gas receiving efficiency of the device is effectively improved.

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 invention relates to a traffic wind suppression device for tunnel fire smoke control, which comprises fire-resistant baffles arranged in a tunnel, the fire-resistant baffles are arranged in the longitudinal direction of the tunnel at equal intervals according to the distance A, the fire-resistant baffles are rotatably fixed on a base through hinges, and the base is fixedly connected with a flue plate. The electric closer is arranged on the left side and the right side of the base and fixedly connected with the flue plate, the electric closer is provided with a C-shaped groove and a motor, a horizontal moving sliding block and a baffle vertical limiting block are embedded in the C-shaped groove, the baffle horizontal limiting block and the horizontal moving sliding block are connected with a connecting rod through a first hinge, and the connecting rod is connected with a fireproof baffle through a second hinge. The equipment control cabinet is connected with the motor to drive the fireproof baffle to rotate around the hinge. According to the method, traffic wind attenuation can be accelerated, the smoke spreading distance can be shortened, the reliability of a tunnel disaster prevention system is improved, a baffle interval design model is determined, and a basis is provided for design of baffles in a tunnel.

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.