2565 results about "Fire protection" patented technology

The invention discloses an end-side cloud collaborative intelligent fire-fighting fire monitoring system based on image fusion, and relates to the technical field of intelligent fire-fighting, the system is composed of a plurality of functional modules, and the system comprises a multi-modal image fusion module which generates a dynamic scanning priority map based on prior data, distinguishes a natural heat source from an abnormal fire by using a dual-light fusion algorithm, and sends an image fusion result to a cloud server; a scanning area is divided according to the thermal risk grade, and the thermal imaging resolution is dynamically adjusted; the distributed edge computing module is used for carrying out space-time synchronization on cross-modal data through a multi-modal feature alignment network, and carrying out dynamic allocation on a CUDA core and CPU resources through adaptive computing scheduling; an improved artificial bee colony algorithm is adopted, the bandwidth of the multi-sensor data flow is dynamically allocated through a time-sharing multiplexing protocol, and three-dimensional path planning is carried out; and the end-side cloud collaborative decision module constructs a federated learning driven model sharing network, and each edge node trains a lightweight YOLOv5s pruning model based on local data.

The invention discloses an emergency fire-fighting hidden danger troubleshooting method based on a multi-modal AI large model identification technology, and relates to the field of artificial intelligence. The multi-modal hidden danger knowledge base is constructed by collecting multi-modal data such as images, texts and related laws and regulations actually recorded in the hidden danger checking process, the recognition and analysis ability of hidden danger information is improved based on the deep learning and multi-modal large model technology, the multi-hop reasoning and thinking chain technology is utilized, and the hidden danger checking efficiency is improved. A complex hidden danger positioning problem can be disassembled into a series of interpretable reasoning steps, and a user is helped to understand a hidden danger judgment basis. According to the method, the hidden danger in the image is analyzed from multiple angles and levels, different hypotheses or conditions can be verified step by step, so that the judgment accuracy is improved, the information of each dimension is comprehensively synthesized for comprehensive evaluation, and the comprehensiveness and accuracy of hidden danger investigation are ensured.

The invention, which relates to the technical field of fire protection and security management, discloses an intelligent fire protection and security integrated big data platform system comprising a data acquisition module, a data storage and preprocessing module, an intelligent analysis module and a linkage control module. The data acquisition module integrates fire-fighting and security sensors and equipment, and transmits data to the convergence unit in a wired and wireless communication mode, so that one-stop acquisition of fire-fighting and security basic data is realized; according to the invention, the intelligent analysis module can carry out fire prediction probability evaluation in combination with security video image features, carries out comprehensive analysis on security videos and time series data through CNN and LSTM technologies, analyzes the internal relation of fire protection and security data through an association rule mining algorithm, and generates a risk early warning report; according to the intelligent analysis method, the accuracy and timeliness of safety early warning are improved, potential safety threats can be found and processed in time, and safety accidents such as fire disasters and the like are effectively prevented.

The invention discloses a remote Internet of Things control management system and method based on fire fighting, and belongs to the technical field of Internet of Things. The system comprises an image recognition module which obtains a video stream of a fire scene through a monitoring camera, and carries out the real-time analysis and recognition of an image through image processing and a deep convolutional neural network; the gas recognition module is used for monitoring the gas concentration of a fire scene in real time and recognizing gas components by using a gas recognition algorithm; the data fusion analysis module is used for carrying out feature fusion on the data acquired by the image recognition module and the gas recognition module, and carrying out analysis and modeling on the fused data; the decision support module is used for performing fire risk assessment according to an analysis result of the data fusion analysis module; based on historical data and the scene model, performing simulation and prediction of a fire development trend; and the remote internet-of-things control module is used for providing data for checking fire scene conditions in real time, so that a user can remotely control all equipment and devices of the fire extinguishing system.

The invention relates to the technical field of transformer substation intelligent management, in particular to a modular prefabricated cabin transformer substation intelligent comprehensive management system with a multi-source data integration and collaborative management function. Comprising a multi-source data acquisition unit; the edge intelligent processing unit is used for carrying out local preprocessing, feature extraction and abnormal early warning on the acquired multi-source heterogeneous data of the transformer substation, and realizing data noise reduction, abnormal recognition and equipment health degree evaluation through a lightweight AI algorithm and a hybrid communication protocol carried by the edge computing terminal module; and a data integration collaboration unit. According to the invention, through an adaptive sampling strategy and a multi-modal feature fusion mechanism of the multi-source data acquisition unit, multi-dimensional data such as electric power parameters, power environment, fire protection and security protection and the like are incorporated into a monitoring system, feature layer association analysis is realized by depending on a Jousseme distance and a Dempster synthesis rule, the assessment limitation of single equipment and single-dimensional data in a traditional scheme is broken through, and the method has the advantages of high reliability and high reliability. And a more comprehensive state basis is provided for equipment health degree research and judgment.

The invention relates to the technical field of fire safety, in particular to an intelligent fire-fighting electrical fire monitoring method, device and equipment and a medium, and the method comprises the steps: obtaining electrical parameters; according to the electrical parameters, a fire hazard identification model is established by using an LSTM algorithm and a CNN algorithm, the operation state of the electrical equipment is predicted according to the fire hazard identification model, an operation state trend prediction result is obtained, and a potential fire hazard type is identified; according to a fire hazard type identification result, in combination with a use environment of electrical equipment and a threshold determination algorithm, performing quantitative evaluation on a fire hazard risk to obtain a corresponding risk level, and when the risk level exceeds a set multi-layer threshold, automatically starting a linkage control mechanism; therefore, the problems of response lagging, high labor cost, high intermittent fault omission ratio and the like in the prior art are solved.

The invention discloses a gradient welding strength control method and system for a welded galvanized steel pipe for fire fighting, particularly relates to the technical field of welding automation control, and aims to solve the problem of abnormal welding seam strength gradient caused by instantaneous unbalance of an electric field and a thermal field during dynamic parameter switching in the prior art. Electromagnetic distortion characteristic quantity is extracted through frequency domain energy analysis, and thermodynamic offset state quantity is deduced in combination with a thermal diffusion trend; on the basis of frequency band correlation mapping of electromagnetic and thermodynamic parameters, thermoelectric cooperative imbalance levels are divided through mutual information entropy evolution, and a self-adaptive harmonic attenuation weight tuning instruction is generated; analyzing a mismatching relation between transient disturbance of an environment magnetic field and arc voltage modulation distortion in real time, dynamically generating a magnetic field compensation factor and reversely superposing the magnetic field compensation factor to a control instruction; and in combination with the matching degree of molten pool oscillation energy and a harmonic frequency spectrum, correcting wire feeding rate calibration, reconstructing a multi-band harmonic energy proportion spectrum, outputting an anti-interference welding control signal, and realizing dynamic balance between arc stability and molten pool heat input.

The invention discloses a multistage fire-fighting and intelligent heat management combined system and method for an energy storage system, a battery cluster is provided with a single fire extinguishing nozzle, a composite detector monitors the state of the battery cluster in real time, and when any battery cluster meets a spraying condition, the fire extinguishing nozzle is triggered to spray a fire extinguishing material; the internal state of the energy storage cabin is monitored in real time through a composite detector, and when the interior of the energy storage cabin meets the spraying condition, a spraying nozzle is automatically started to continuously spray for preset spraying time; according to the centralized liquid cooling unit, a dual-redundancy compressor is combined with an ethylene glycol aqueous solution circulating system to conduct dynamic flow regulation and control, the opening degree of an electromagnetic valve of the dual-redundancy compressor is dynamically adjusted through a composite detector, and the internal temperature of an energy storage cabin is controlled; dynamically distributing flow according to the energy storage time period by adopting an intelligent temperature control algorithm; after the multi-stage fire-fighting module acts, the centralized liquid cooling unit is started for cooling; when the temperature detected by the composite detector exceeds a high-temperature threshold value, the fan is started for air replacement, and the multi-stage fire-fighting module is triggered to act.

The invention relates to the technical field of intelligent fire fighting, in particular to a building electrical fire identification method and system based on multi-source information fusion, and the method comprises the steps: firstly collecting the multi-source monitoring data of an electrical system in real time, then carrying out the preprocessing of the multi-source data, including noise filtering, time alignment and feature extraction, and constructing a dynamic weight fusion model; the weight of each data source is adaptively allocated based on the feature entropy, then fusion features are input to the fire risk grading model, a fire probability index and an early warning level are output, and when the early warning level exceeds a threshold value, a linkage control instruction is triggered and an alarm is given; according to the method, through dynamic fusion of multi-source information, the electrical fire identification precision is remarkably improved, multi-dimensional parameters such as current, temperature, smoke and arc are adaptively integrated by adopting an entropy weight assignment mechanism, the problems of false alarm and missing alarm of traditional single-threshold detection are solved, the missing alarm rate and the false alarm rate are remarkably reduced, and the reliability of fire early warning is ensured.

The invention relates to the technical field of fire protection and security, in particular to a security and disinfection integrated multi-modal fusion embedded edge calculation method and system, and provides a security and disinfection integrated multi-modal fusion embedded edge calculation method which comprises the following steps: constructing a data set; the AI visual recognition model uses an improved YOLOv8 model to train a data set and execute target detection, meanwhile, an optical flow method is adopted to extract motion features of flames or smog in continuous key frame images in a monitoring video, and a spreading prediction model is established to send out an early warning signal in advance; and the fusion processing module establishes a dynamic threshold adjustment model based on the environmental parameters to optimize an early warning trigger threshold, and transmits the early warning trigger threshold to the fire-fighting linkage control module to verify and trigger fire-fighting linkage operation. AI intelligent analysis and fire-fighting linkage disposal of fire hazards are realized, false alarm of early warning information is effectively prevented, the discovery and disposal efficiency of the fire hazards is improved, and the fire hazards are eliminated in the bud.

The invention discloses an intelligent fire evacuation system and method based on dynamic environment perception, and relates to the technical field of fire fighting and safety protection, and the method comprises the steps: collecting real-time data in a fire scene; dividing the evacuation area into a plurality of grid units by using a two-dimensional rasterization technology to form a real-time updated environment map; in combination with dynamic modeling data, an optimal evacuation path is generated by using an improved path planning algorithm; an evacuation path is transmitted to trapped people in real time in a visual and auditory mode, and the visual and auditory mode comprises the use of a dynamic indicator lamp, a marker lamp, an electronic screen and a voice broadcast system; the guidance content is adjusted in combination with real-time data, and the evacuation efficiency is optimized; fire fighting equipment is linked, and the evacuation path environment is optimized; and the evacuation state is monitored through a dynamic data feedback mechanism. According to the invention, an evacuation path is calculated and updated in real time by integrating a sensor network, fire scene dynamic modeling and an intelligent path planning algorithm, and a safe and efficient evacuation scheme is provided for trapped people in a fire.

The invention discloses a fire-fighting long-distance ad hoc network full-duplex voice communication system, which relates to the technical field of voice communication, and realizes whole-staff real-time voice acquisition through cooperative work of a microphone array module, a noise sensing module, a noise filtering module, a communication state evaluation module and a signal gain adjustment module. Two-way voice communication between firefighters and between the firefighters and a command center is ensured, in a fire rescue site, the noise sensing module can accurately recognize various background noise in a fire environment, such as explosive sound or equipment operation sound, and noise interference areas are classified and marked in time. The noise filtering module can dynamically adjust the noise suppression coefficient according to the noise type and intensity through a self-adaptive noise suppression algorithm, interference signals are effectively removed, and through real-time and dynamic noise suppression, firemen can clearly receive command information in a complex environment, and misunderstanding or communication faults caused by noise interference are reduced.

The invention relates to the technical field of fire-fighting facility detection, in particular to a fire-fighting pump room anti-freezing and moisture-proof system, which comprises a data acquisition module, a data processing module, a data processing module and a data processing module, and is characterized in that the data acquisition module is used for acquiring pump room environment parameters, outdoor environment parameters and indoor facility surface temperature parameters; the data processing module is used for preprocessing the pump room environment parameters, the outdoor environment parameters and the indoor facility surface temperature; the control decision module comprises an abnormity early warning unit which is used for calculating a freezing risk index and a moisture-proof risk threshold temperature, judging whether anti-freezing early warning or moisture-proof early warning exists or not and outputting an early warning result; and the automatic control unit is used for regulating and controlling the operation state of related equipment in the pump room according to the early warning result. According to the invention, through intelligent monitoring and dynamic adjustment of environment temperature and humidity and equipment surface temperature in the fire-fighting pump room, equipment in the fire-fighting pump room is effectively prevented from being damaged by freezing and humid environment.

The invention discloses a fire-fighting effect evaluation method and platform under digital modeling, and relates to the technical field of fire-fighting evaluation, and the method comprises the steps: carrying out the structural information collection of a target building, and obtaining the target structural information; performing digital modeling by adopting the target structure information to obtain a building three-dimensional model of the target building; performing interaction to obtain fire-fighting configuration data of the target building; performing fire-fighting equipment fitting on the building three-dimensional model to obtain a fire-fighting layout model; presetting a multi-stage fire risk scene, and obtaining a multi-stage fire protection simulation result; and performing fire-fighting response quantitative evaluation to obtain a fire-fighting effect evaluation result. The technical problems that in the prior art, the fire emergency capacity in a complex building environment is difficult to comprehensively evaluate, and the overall effect of a fire-fighting plan cannot be effectively verified are solved, and the technical effects that the spreading path and the smoke diffusion condition of a fire are accurately simulated, and the timeliness in an actual fire is effectively evaluated are achieved.

The invention discloses a fire pump station water supply regulation control system and method based on artificial intelligence, and the system comprises an obtaining module which is used for obtaining the real-time water supply parameters and environment state information of a fire pump station; the strategy generation module is used for generating an optimal water supply adjustment strategy based on a pre-trained artificial intelligence model according to the real-time water supply parameters and the environment state information; and the control module is used for executing the optimal water supply adjustment strategy to realize intelligent adjustment control of water supply of the fire pump station. The operation efficiency of the fire pump station can be greatly improved, the operation cost is reduced, the reliability and safety of the fire pump station are ensured, and therefore a more stable and efficient guarantee is provided for a fire fighting system.

The invention discloses a fire extinguishing system and method for accurate positioning of thermal runaway of a container type energy storage power station. The fire extinguishing system is composed of an energy storage power station, battery packs distributed in an array mode and a fire extinguishing system body. Each battery pack is provided with a ventilation safety valve and a fire extinguishing device, a hydrogen sensor array covering the whole area is arranged on the plane of the energy storage power station, the ventilation safety valves guide out hydrogen generated in the initial stage of thermal runaway, and the sensor array monitors the concentration of the whole area in real time. The industrial personal computer receives sensor data, constructs a gas concentration distribution diagram by combining pre-stored battery pack space distribution information, and displays a thermal runaway area on the display screen in real time. The positioning program analyzes a hydrogen concentration field based on gas diffusion characteristics, and after the position of a fault battery pack is accurately recognized, the industrial personal computer immediately triggers the fire extinguishing device in the corresponding pack to implement fixed-point fire extinguishing, so that an early fire extinguishing closed loop is formed. According to the system, through multi-sensor data fusion and gas distribution mapping technologies, rapid positioning and accurate suppression of a thermal runaway source are achieved, and the safety protection level of an energy storage power station is effectively improved.

The invention discloses an outdoor fire hydrant water pressure real-time monitoring system, and relates to the technical field of fire fighting. When the system operates, a data acquisition and preprocessing module performs efficient fusion of multi-source data, and provides accurate water pressure data Px (t); the correlation analysis module evaluates the relationship between adjacent fire hydrants by using the geographic position data and the correlation coefficient, and can discover potential risks in time and generate an early warning identifier; the anomaly detection and evaluation module dynamically analyzes the water pressure data and the early warning identifier to provide an accurate fire hydrant anomaly risk evaluation strategy scheme; the path analysis module accurately judges an abnormal propagation path by analyzing the abnormal index gradient Gxy (t) of the adjacent fire hydrants, and reveals a potential regional problem; according to the method, the effective regional exception handling strategy is generated and executed immediately, the response speed and the decision-making ability are enhanced, and particularly, when regional or systematic problems are handled, early warning can be performed in advance, and optimal countermeasures can be taken.

The invention relates to the technical field of emergency management, in particular to a power battery alarm handling strength scheduling method and system based on a fire-fighting large model, and the method comprises the following steps: carrying out text summarization through a large language model based on power battery parameter data, extracting material components and design structure information of various batteries, and carrying out data analysis; and analyzing the heat released by the multiple types of new energy batteries during combustion, the combustion rate and the combustion characteristics, and generating a power battery combustion model. According to the method, combustion characteristics of various types of new energy batteries are analyzed, fire diffusion and spreading processes in various external environments are simulated, flame propagation paths and battery fire characteristics are predicted, and the emergency degrees of various fire alarm conditions are evaluated and priority scores are calculated by analyzing historical alarm condition data. The efficiency and effectiveness of resource scheduling are optimized, the alarm response speed is improved, the number and type of required resources are predicted by analyzing the geographic position, the fire level and the environmental condition of the real-time fire, efficient deployment of fire-fighting power is carried out, and fire-fighting power waste and resource redundancy are reduced.

The present disclosure introduces an automated system designed for detecting and rectifying clashes in 3-dimensional (3D) mechanical, electrical, plumbing and fire protection (MEPF) service models. Comprising a computing device, the system receives a 3D model of a building project and various MEPF service models, including but not limited to HVAC, electrical, plumbing and fire protection services. An interconnected remote server, equipped with a non-transitory storage device, retains executable routines, a rule database with MEPF identifiers tied to specific rules and hierarchies, and a construction history database featuring 3D building templates depicting both clashed and resolved MEPF integrations. The central control unit retrieves the 3D models, constructs an AI model influenced by past construction data, and identifies clashes when overlaying the MEPF models on 3D depiction of the building. Post detection, the control unit employs AI-derived strategies to produce clash-free 3D models, which are subsequently displayed on the computing device.

The invention discloses a power distribution fire-fighting information management method and system based on the Internet of Things, and relates to the technical field of power distribution fire-fighting information management, and the method specifically comprises the following steps: analyzing the obtained transmission delay information of a current sensor, and generating a data integrity coefficient and a load disturbance index; and constructing a delay influence prediction model based on the generated data integrity coefficient and the load disturbance index, generating a delay prediction coefficient, carrying out analysis after generation, and predicting the influence degree of the delay of the current sensor data on the fault early warning of the power distribution equipment under the high-load operation condition. The influence degree is divided into a low influence degree, a medium influence degree and a high influence degree according to the prediction result; and implementing corresponding management measures for different influence degrees according to a prediction result. According to the method, the problem of inaccurate fault early warning caused by data delay of the current sensor under the condition of high-load operation is solved, the delay influence is accurately predicted, and a data acquisition and management strategy is dynamically optimized.

The invention relates to the technical field of data processing, in particular to a fire fighting equipment data reading and interaction method based on BIM lightweight. The method comprises the following steps: carrying out model format lightweight processing on fire fighting equipment in an original BIM model to obtain a fire fighting equipment BIM lightweight model; position data, working state data and maintenance record data of fire-fighting equipment are obtained in real time and synchronously updated to a fire-fighting equipment BIM lightweight model, so that a fire-fighting equipment interactive user interface is designed by using the fire-fighting equipment BIM lightweight model; and carrying out fire-fighting equipment data reading processing and fire-fighting equipment abnormity early warning problem interaction analysis on the fire-fighting equipment BIM lightweight model, carrying out state abnormity matching maintenance suggestion analysis, and generating a fire-fighting equipment state abnormity problem maintenance suggestion scheme so as to execute corresponding fire-fighting equipment state abnormity problem maintenance response work. The invention aims to optimize fire-fighting equipment data processing and improve user interaction experience.

The invention provides a full-automatic device for preventing fire spread of a new energy automobile of a roll-on-roll-off ship. The full-automatic device comprises a supporting module, a thrust module, fireproof cloth, a control module and a fire fighting module. The supporting module comprises a front supporting unit, a rear supporting unit, a trapezoidal connecting frame and a connecting rod. The thrust module comprises a main hydraulic cylinder and an auxiliary hydraulic cylinder. The control module comprises a temperature sensor, an electromagnet and a controller. The fire-fighting module comprises a fire-fighting sprayer and a fire alarm, and the fire-fighting sprayer and the fire alarm are fixedly installed on a base at the top of the vehicle cabin. According to the full-automatic device for preventing the fire spread of the roll-on-roll-off ship new energy automobile, the support can be pushed to be opened by means of the thrust of the hydraulic rod, a closed automobile cover is formed, unmanned operation can be achieved, and safety is higher.

Fire protection systems and methods having piping interconnections for connecting a fire protection device to a fluid source. The piping interconnections include a branch connector connected to a pipe header. The branch connector includes a tubular member and an internal annular seal member housed in an internal gasket chamber of the tubular member. The tubular member includes an internal stepless surface between a terminal end of the tubular member and the internal gasket chamber.

The invention discloses a deep defense protection method for a charging station, relates to the technical field of fire early warning and safety protection, and aims to solve the problems of high false alarm rate of fire early warning, delayed fire isolation and insufficient credibility of accident traceability data in the prior art. According to the method, a monitoring-disposal-traceability complete-cycle protection system is constructed, a temperature field, electrical parameters and environmental data are collected in a fusion mode through a multi-source sensor before a disaster, a self-adaptive safety threshold value is generated based on a dynamic game model, and a risk path is pre-judged in combination with digital twinborn deduction; a three-level response mechanism is adopted in the disaster; after the disaster, operation logs are stored in a fragmented mode through the block chain space-time anchoring technology, an accident evolution chain is reversely reconstructed through digital twinning, and tamper-resistant judicial evidence is generated. The early warning precision is improved through dynamic threshold optimization, the response time is shortened through multi-stage linkage control, the traceability credibility is guaranteed through the quantum evidence storage technology, and a closed-loop optimization system for charging station fire protection is formed.

The invention provides a high-order distributed fire-fighting unmanned aerial vehicle task allocation method and system, and relates to the technical field of unmanned aerial vehicle task allocation, and the method comprises the following steps: obtaining a thermal infrared image and necessary parameters; calculating the length and width of a thermal infrared image coverage area corresponding to a single pixel point; converting the thermal infrared image into a grey-scale map, carrying out binarization processing on the fire area, and calculating the area of the fire area; extracting a fire area boundary, establishing a local coordinate system, and calculating coordinates of the fire area boundary and the fire-fighting unmanned aerial vehicle; and carrying out distributed collaborative decision and task allocation. The method has the beneficial effects that the single-point fault problem in a centralized mode is avoided, the system reliability and robustness are high, the information interaction and cooperation are efficient, the decision process is simplified, the task repeated allocation is avoided, and the allocation strategy can be adjusted according to the dynamic change of the fire area.

The invention relates to the technical field of intelligent fire protection, and discloses an intelligent fire protection early warning system and an early warning method. The method comprises the following steps: acquiring environment data based on various sensors to generate a fire early warning data set, filtering abnormal data by using a preprocessing algorithm, performing multi-level confirmation on fire features through an image analysis module and a sound analysis module, finally generating a fire confirmation signal, triggering an alarm system and activating fire fighting equipment. In the prior art, a fire hazard early warning method only depends on a single sensor or a single data source, and especially under a complex and changeable environment condition, efficient and accurate fire hazard early warning cannot be realized. Due to the fact that multi-dimensional and intelligent fire detection is achieved through multi-source data fusion, convolutional neural network image recognition and fast Fourier transform sound analysis, the problem of false alarm or missing alarm caused by instability of a single data source is effectively avoided, and the accuracy and response speed of fire early warning are improved.

The invention discloses a garden fire early warning system based on GIS Internet, relates to the technical field of environmental protection, and comprises a terrain analysis unit, a node division unit, a fire judgment unit, an early warning classification unit and an early warning notification unit; the invention obtains garden distribution data from GIS Internet, calculates the fire spread coefficient according to terrain height data and vegetation distribution density data, and then delineates different monitoring areas according to the degree of fire spread, obtains real-time sensor data through a sensor group arranged at a monitoring node, generates a fire occurrence signal according to the real-time sensor data, calculates the fire spread rate in combination with the fire spread coefficient of the fire occurrence coordinates and real-time weather data, and arranges the monitoring nodes according to the distribution characteristics of the garden, thereby ensuring the effectiveness of monitoring while reducing the cost, accurately judging the fire spread rate when a fire occurs so as to take corresponding rescue measures, ensuring safety and being able to effectively regulate firefighting resources.

The present disclosure relates to a warehouse system having a fire protection system (650), the warehouse system providing space for a three-dimensional arrangement of storage bins. The warehouse system comprises a plurality of interconnected storage modules (200), wherein each storage module (200) comprises a storage area and a top level arranged above the storage area, wherein the storage area is adapted to accommodate a plurality of stacks of storage bins arranged in a horizontal two-dimensional grid at a bottom of the storage module (200), wherein, at the top level, at least one vehicle is movable in alignment with the two-dimensional grid to retrieve and place storage bins from and to the plurality of stacks, wherein the plurality of interconnected storage modules (200) comprises at least two levels of storage modules (200) placed one above the other in an individual room. The warehouse system comprises a fire protection system (650) providing a plurality of fire protected modules (200) among the plurality of storage modules (200), wherein, in each of the fire protected modules (200), a pipe system (654) for releasing extinguishing medium is installed.

The invention provides a power industry fire alarm control system which is provided with an environment monitoring module, a data processing module, a control module, a communication module and an alarm triggering module. Then the data is transmitted into a data processing module to be processed, and normalization processing, multi-parameter weighted fusion, fire risk index calculation and anomaly detection of the data are carried out; after power fire information is detected, related equipment is controlled through the control module, and the effect of extinguishing fire and protecting the equipment is achieved; the communication module transmits the system state and the alarm information to an external monitoring system or a remote control center; the alarm triggering module sends out an alarm signal to remind an operator on duty in time; according to the system, various environment monitoring sensors are integrated, and a weighted fusion algorithm, an anomaly detection mechanism and an automatic linkage control technology are adopted, so that efficient fire detection and emergency response functions are realized.

The invention provides an intelligent fire-fighting method and system for a photovoltaic power station based on the Internet of Things, and the method comprises the steps: collecting temperature data through a distributed optical fiber temperature measurement unit, avoiding electromagnetic interference through optical signal conversion, analyzing the spectral feature difference between electro-arc light and combustion flame through a spectral feature separation unit, and carrying out the analysis of the spectral feature difference. Correlating the particulate matter concentration with the specific gas component through the multi-source coupling smoke sensing unit to obtain anti-interference data; space-time probability fusion is executed, and fire confidence is generated through alignment; a trigger response is calculated according to the combination of the fire confidence coefficient, the temperature rise trend slope and the smoke diffusion speed; running a self-adaptive parameter adjustment engine, and generating a sensing layer calibration coefficient and a decision rule optimization instruction; the parameter optimization instruction is issued to the sensing device, the calibration effect is verified, the influence of dust, electromagnetic interference and other factors is effectively avoided through the collected anti-interference data, the response is determined in combination with temperature rise and delay diffusion, the probability of false triggering is effectively reduced, and the accuracy of fire detection is improved.