Fire alarm processing method and device based on engineering machinery vehicle and engineering machinery vehicle

Abstract

The invention discloses a fire alarm processing method and device based on an engineering machinery vehicle and the engineering machinery vehicle, and the method comprises the steps: collecting the fire monitoring data of the engineering machinery vehicle, the fire monitoring data being used for representing the current fire condition information; determining a fire risk assessment index according to the fire monitoring data; and according to the fire risk assessment index, determining a corresponding emergency operation and executing the emergency operation. Thus, the timeliness and accuracy of fire discovery are improved, the fire response capacity of the engineering machinery vehicle is improved, the risks of whole vehicle burnout, heavy economic loss and even casualties caused by untimely fire control are reduced, and the reliability and safety of the engineering machinery vehicle are further improved.

Description

Technical Field

[0001] This invention relates to the field of engineering machinery vehicle technology, and in particular to fire alarm handling methods, devices, and engineering machinery vehicles based on engineering machinery vehicles. Background Technology

[0002] Construction machinery vehicles, such as cranes, perform heavy operations in complex environments like construction sites and ports. Their electrical, hydraulic, and power systems operate under high loads for extended periods, posing a significant fire risk. Once a fire breaks out, it often spreads rapidly. Currently, the construction machinery industry primarily relies on two types of alarm systems: automatic alarm systems, which use integrated smoke and temperature detectors to monitor smoke and temperature changes in real time and automatically trigger an alarm when an anomaly is detected. However, this anomaly detection is usually based on fixed preset values. Another type is manual alarm systems, where the driver or operator triggers the alarm directly by pressing a button when they discover a fire. However, existing fire alarm systems are inaccurate in their assessments and are relatively delayed in detecting fires. Often, by the time an anomaly is detected manually or by a single integrated smoke and temperature detector, the fire has already developed to a considerable intensity, easily leading to the destruction of the entire vehicle, significant economic losses, and even casualties.

[0003] Therefore, how to solve the technical problem of inaccurate and untimely fire warnings in construction machinery vehicles, which makes it impossible to effectively contain fires in the early stages of fires, has become a challenge for existing technologies. Summary of the Invention

[0004] The purpose of this application is to provide a fire alarm handling method, device, construction machinery vehicle, and storage medium based on construction machinery vehicles, which can accurately and timely monitor fires in construction machinery vehicles, effectively reduce the phenomenon of complete vehicle burning caused by inaccurate and untimely fire warnings, and effectively contain fires in construction machinery vehicles in their early stages, thereby improving the reliability and safety of construction machinery vehicles.

[0005] To achieve the above objectives: In a first aspect, embodiments of this application provide a fire alarm handling method based on engineering machinery vehicles, including: Collect fire monitoring data from construction machinery vehicles, wherein the fire monitoring data is used to characterize the current fire situation information; Based on the fire monitoring data, a fire risk assessment index is determined; Based on the fire risk assessment index, the corresponding emergency operation is determined and the emergency operation is controlled and executed.

[0006] Optionally, the fire monitoring data includes at least one of the following: temperature data, smoke concentration data, video surveillance data, and abnormal condition data of specific components; The engineering machinery vehicle is equipped with: a temperature sensing device arranged in a first monitoring area of ​​the engineering machinery vehicle; a smoke concentration sensing device arranged in a second monitoring area of ​​the engineering machinery vehicle; a camera device installed in a third monitoring area of ​​the engineering machinery vehicle; and a sensing device for monitoring specific components; wherein, the first monitoring area includes at least one of the following: a monitoring point area divided into several monitoring points with independent identification marks along the main wiring harness path of the vehicle body, and an area where the fire occurrence frequency is higher than a frequency threshold; the second monitoring area includes at least one of the following: the driver's cab, the control room, and the engine compartment; the third monitoring area includes at least one of the following: the driver's cab, the control room, the area around the driver's cab, and the area around the control room; The collected fire monitoring data of engineering machinery vehicles includes at least one of the following: The temperature data of the first monitoring area is collected in real time through the temperature sensing device. The smoke concentration sensor collects real-time smoke concentration data of the second monitoring area. The camera device is used to collect video data of the third monitoring area in real time. Data on abnormal conditions of the specific component are collected using a sensing device for monitoring the specific component.

[0007] Optionally, determining the fire risk assessment index based on the fire monitoring data includes: The fire risk assessment index is determined based on at least one of the temperature data, the smoke concentration data, the video surveillance data, and the abnormal condition data of the specific component.

[0008] Optionally, determining the fire risk assessment index based on at least one of the temperature data, the smoke concentration data, the video surveillance data, and the specific component anomaly data includes: Obtain the first weight corresponding to the temperature data, the second weight corresponding to the smoke concentration data, the third weight of the video surveillance data, and the fourth weight of the abnormal condition data of the specific component; The fire risk assessment index is calculated based on the temperature data and the first weight, the smoke concentration data and the second weight, the video surveillance data and the third weight, and the abnormal situation data of specific components and the fourth weight.

[0009] Optionally, determining the corresponding emergency operation based on the fire risk assessment index and controlling the execution of the emergency operation includes: The fire risk level is determined based on the fire risk assessment index. Based on the fire alarm risk level, determine the emergency operation corresponding to the fire alarm risk level and execute the emergency operation corresponding to the risk level.

[0010] Optionally, determining the fire risk level based on the fire risk assessment index includes at least one of the following: If the fire risk assessment index is less than the first threshold, then the fire risk level is determined to be a level zero fire risk. If the fire risk assessment index is greater than or equal to the first threshold and less than the second threshold, then the fire risk level is determined to be a level one fire risk. If the fire risk assessment index is greater than the second threshold and less than the third threshold, then the fire risk level is determined to be a level two fire risk. If the fire risk assessment index is greater than or equal to the third threshold, then the fire risk level is determined to be a level three fire risk. Wherein, the third threshold is greater than the second threshold, and the second threshold is greater than the first threshold.

[0011] Optionally, determining and executing the emergency operation corresponding to the fire alarm risk level includes at least one of the following: If the fire alarm risk level is zero, then the emergency operation is determined to be normal operation and the engineering machinery vehicle is controlled to operate normally. If the fire alarm risk level is Level 1 fire alarm risk, then the emergency operation is determined to be a basic emergency operation, and the engineering machinery vehicle is controlled to issue an alarm prompt and / or adjust the vehicle speed. If the fire alarm risk level is level two, then the emergency operation is determined to be a medium-level emergency operation, and the engineering machinery vehicle is controlled to perform at least one of the following: engine shutdown, fuel supply valve cut-off, and engine intake shut-off valve shutdown. If the fire risk level is Level 3, then the emergency operation is determined to be an emergency operation, and the engineering machinery vehicle is controlled to shut down the vehicle's power supply and / or trigger the fire extinguishing device to perform automatic fire extinguishing.

[0012] Optionally, the method for adjusting vehicle speed includes: Obtain the current speed of the construction machinery vehicle; The adjusted vehicle speed is determined based on the current vehicle speed and the fire risk assessment index.

[0013] Optionally, the construction machinery vehicle is configured to monitor multiple areas; The fire extinguishing device is triggered to perform automatic fire extinguishing procedures, including: When a fire alarm risk level of three is triggered, the fire extinguishing devices in the monitored area will automatically extinguish the fire.

[0014] Optionally, the method further includes: Obtain the volume of the fire-starting chamber in the monitoring area corresponding to the fire risk level of Level III; Based on the fire risk assessment index of the fire chamber and the corresponding monitoring area, the extinguishing agent release amount of the fire extinguishing device is determined as the target release amount. The fire extinguishing devices within the monitoring area corresponding to a fire alarm risk level of three shall perform automatic fire extinguishing procedures, including: When a fire alarm risk level of three is triggered, the fire extinguishing device in the monitoring area releases the target amount of extinguishing agent to extinguish the fire.

[0015] Optionally, the method further includes: The system acquires fire situation information based on temperature data of the first monitoring area, smoke concentration data of the second monitoring area, video data of the third monitoring area, and fire risk assessment index corresponding to each monitoring area within a preset time period. Obtain the operating condition data and location data of the construction machinery vehicle within the preset time period; The operating data, location data, and fire situation information are uploaded to the Internet of Things platform via a wireless network.

[0016] Secondly, embodiments of this application provide a fire alarm handling device based on engineering machinery vehicles, comprising: a memory configured to store instructions; and a processor configured to retrieve the instructions from the memory and, when executing the instructions, to implement any of the aforementioned fire alarm handling methods based on engineering machinery vehicles.

[0017] Thirdly, embodiments of this application provide an engineering machinery vehicle that includes any of the aforementioned fire alarm handling devices.

[0018] Optionally, the construction machinery vehicle is equipped with: a temperature sensing device arranged in a first monitoring area of ​​the construction machinery vehicle; a smoke concentration sensing device arranged in a second monitoring area of ​​the construction machinery vehicle; a camera device installed in a third monitoring area of ​​the construction machinery vehicle; and a sensor device for monitoring specific components; wherein, the first monitoring area includes at least one of the following: a monitoring point area divided into several independently identifiable areas along the main wiring harness path of the vehicle body and an area where the frequency of fire occurrence is higher than a frequency threshold; the second monitoring area includes at least one of the following: the driver's cab, the control room, and the engine compartment; the third monitoring area includes at least one of the following: the driver's cab, the control room, the area surrounding the driver's cab, and the area surrounding the control room.

[0019] Fourthly, embodiments of this application provide a machine-readable storage medium storing instructions for causing a machine to execute any of the fire alarm processing methods described above.

[0020] This application provides a fire alarm handling method, device, construction machinery vehicle, and machine-readable storage medium based on construction machinery vehicles. The method includes: collecting fire monitoring data from the construction machinery vehicles, wherein the fire monitoring data is used to characterize the current fire situation; determining a fire alarm risk assessment index based on the fire monitoring data; and determining and controlling the execution of corresponding emergency operations based on the fire alarm risk assessment index. Thus, by collecting fire monitoring data that characterizes the current fire situation and determining a dynamic fire alarm risk assessment index accordingly, the inaccurate and untimely fire warnings caused by relying on fixed threshold judgments in existing technologies are reduced. Furthermore, by automatically determining and executing corresponding emergency operations based on the fire alarm risk assessment index, automatic intervention and execution of corresponding emergency operation control measures can be achieved before the fire is in its nascent stage. This solves the problem of delayed response caused by relying on manual discovery and intervention in existing technologies, providing a possibility for containing fires in their early stages. Thus, the fire alarm handling method for construction machinery vehicles provided in this application, through a coherent and automated control process from monitoring to assessment to decision-making and execution, not only solves the problems of inaccurate and untimely monitoring caused by single monitoring, but also fundamentally constructs an intelligent prevention and control system that can replace or assist manual judgment. This improves the timeliness and accuracy of fire detection, enhances the fire response capability of construction machinery vehicles, and reduces the risk of complete vehicle destruction, significant economic losses, or even casualties due to untimely fire control. Furthermore, it also improves the reliability and safety of construction machinery vehicles. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating a fire alarm handling method based on engineering machinery vehicles, provided in an embodiment of this application.

[0022] Figure 2 This is a schematic diagram illustrating an application scenario for fire alarm handling based on engineering machinery vehicles, provided in an embodiment of this application.

[0023] Figure 3 This is a schematic diagram of the system architecture for fire alarm processing based on engineering machinery vehicles, provided as an embodiment of this application.

[0024] Figure 4 Another schematic diagram of the fire alarm handling method based on engineering machinery vehicles provided in the embodiments of this application.

[0025] Figure 5 A schematic diagram illustrating the specific process of a fire alarm handling method based on engineering machinery vehicles provided in this application embodiment.

[0026] Figure 6 This is a structural block diagram of a fire alarm handling device based on engineering machinery vehicles provided in an embodiment of this application. Detailed Implementation

[0027] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the scope of the application.

[0028] Construction machinery vehicles can include cranes, excavators, mining dump trucks, and concrete pump trucks. In this example, construction machinery vehicles mainly refer to various types of vehicles used in complex and harsh environments. The following example uses a crane as an example of construction machinery vehicles.

[0029] As large-scale special equipment, engineering cranes are widely used in construction, ports, energy, and other fields. The safety of engineering cranes is directly related to the safety of personnel and property, as well as the progress of projects. In recent years, there have been frequent fire accidents involving engineering cranes. A typical characteristic of crane fire accidents is their suddenness and rapid spread of fire after it breaks out. Since crane operations are usually in relatively remote areas, once a fire occurs, by the time firefighters arrive, the vehicle has already been severely burned, or even completely destroyed, causing serious economic losses to customers. If the fire can be detected and extinguished in its early stages, the losses can be effectively avoided.

[0030] It is known that fires typically occur in five stages: the initial stage, the development stage, the intense stage, the decline stage, and the extinguishing stage. The initial stage is the easiest to extinguish; however, existing fire alarm systems for construction machinery vehicles often fail to detect fires in this initial phase. Therefore, it is necessary to seek a technology that can effectively detect potential fires in their early stages and contain them at the outset, thereby effectively preventing fires involving construction machinery vehicles and ensuring the safety of personnel and vehicle equipment.

[0031] It is known that fires in construction machinery vehicles, such as cranes, are generally caused by electrical system failures, hydraulic or fuel leaks, overheating due to friction, and improper operation. In fact, regardless of the cause of the fire, it will be accompanied by an increase in temperature and smoke concentration.

[0032] Based on this, the embodiments of this application provide a quick and effective method for detecting and analyzing fires and executing fire control. When an anomaly occurs, the controller of the engineering vehicle will take relevant measures according to the fire situation, thereby achieving accurate and timely fire monitoring and control of the entire vehicle. This effectively reduces the phenomenon of the entire vehicle being burned due to inaccurate or untimely fire warnings, and can effectively contain the fire of engineering machinery vehicles in the early stage of the fire, thereby improving the reliability and safety of engineering machinery vehicles.

[0033] See Figure 1 , Figure 1 This is a flowchart illustrating a fire alarm handling method based on engineering machinery vehicles provided in this application embodiment. This fire alarm handling method can be executed by a fire alarm handling device provided in this application embodiment. The fire alarm handling device can be implemented using software and / or hardware, such as a computer or server. In this embodiment, a computer (such as an onboard computer or mobile terminal) is taken as the executing entity of the fire alarm handling method. The fire alarm handling method based on engineering machinery vehicles provided in this embodiment includes: Step 101: Collect fire monitoring data of construction machinery vehicles, wherein the fire monitoring data is used to characterize the current fire situation information; Step 102: Determine the fire risk assessment index based on fire monitoring data; Step 103: Based on the fire risk assessment index, determine the corresponding emergency operations and control the execution of the emergency operations.

[0034] Fire monitoring data refers to raw data directly acquired from sensors and other data acquisition devices. Fire situation information provides a more intuitive representation of the fire monitoring data and assesses the severity of the fire, such as temperature point 3 reaching 85℃ and infrared images showing 80% overheating. The fire risk assessment index is a comprehensive, quantifiable value that scores the probability and severity of a localized or overall fire risk in the construction machinery vehicle. Emergency operation refers to the automatic triggering of different control commands and actions based on varying fire risk assessment indices.

[0035] It is important to understand that you should refer to [the relevant documentation / reference]. Figure 2 , Figure 2 This is a schematic diagram illustrating an application scenario for fire alarm handling based on engineering machinery vehicles, as provided in the embodiments of this application. Figure 2 As shown, the construction machinery vehicle integrates an intelligent fire alarm control system, which can be composed of a data acquisition system, a data processing system, other auxiliary systems, and an emergency execution system. The emergency execution system, as understood, is specifically integrated into the execution entity of the fire alarm handling method, such as the onboard computer of the construction machinery vehicle or a mobile terminal capable of controlling the construction machinery vehicle. Specifically, the data acquisition system is responsible for executing step 101, which involves collecting fire monitoring data from sensors throughout the vehicle, such as temperature and smoke data, for raw processing; the data processing system is responsible for determining the fire risk assessment index and emergency actions in step 102; and the emergency execution system is responsible for controlling and executing emergency actions, such as shutting down the transmitter and triggering the fire extinguishing device.

[0036] Thus, this application embodiment, by collecting fire monitoring data that characterizes the current fire situation and determining a dynamic fire risk assessment index accordingly, reduces the problems of inaccurate and untimely fire warnings caused by relying on fixed threshold judgments in existing technologies. Furthermore, by automatically determining and executing corresponding emergency operations based on the fire risk assessment index, it enables automatic intervention and implementation of appropriate emergency control measures before the fire is in its nascent or initial stage. This solves the problem of delayed response caused by reliance on manual detection and intervention in existing technologies, making it possible to contain fires in their early stages. In other words, the fire alarm handling method for engineering machinery vehicles provided in this application embodiment, through a coherent and automated control process from monitoring to assessment to decision-making and execution, not only solves the problems of inaccurate and untimely monitoring caused by single monitoring, but also fundamentally constructs an intelligent prevention and control system that can replace or assist manual judgment. This improves the timeliness and accuracy of fire detection, enhances the fire response capability of engineering machinery vehicles, and reduces the risk of vehicle destruction, significant economic losses, or even casualties due to untimely fire control. Furthermore, it has improved the reliability and safety of construction machinery vehicles.

[0037] In some embodiments, the fire monitoring data includes at least one of the following: temperature data, smoke concentration data, video surveillance data, and abnormal condition data of specific components; the engineering machinery vehicle is equipped with: a temperature sensing device arranged in a first monitoring area of ​​the engineering machinery vehicle; a smoke concentration sensor installed in a second monitoring area of ​​the engineering machinery vehicle; a camera device installed in a third monitoring area of ​​the engineering machinery vehicle; and a sensor for monitoring specific components; wherein, the first monitoring area includes at least one of the following: a monitoring point area divided into several independently identifiable areas along the main wiring harness path of the vehicle body and an area where the fire occurrence frequency is higher than a frequency threshold; the second monitoring area includes at least one of the following: the driver's cab, the control room, and the engine compartment; the third monitoring area includes at least one of the following: the driver's cab, the control room, the area surrounding the driver's cab, and the area surrounding the control room; In step 101, fire monitoring data of construction machinery vehicles is collected, including at least one of the following: Temperature data of the first monitoring area is collected in real time using a temperature sensing device. The smoke concentration data of the second monitoring area is collected in real time using a smoke concentration sensor. Video data of the third monitoring area is collected in real time using camera devices; Data on abnormal conditions of specific components are collected using sensors that monitor those components.

[0038] The temperature sensing devices here may include: temperature sensing cables installed along the main wiring harness path of the vehicle body, and / or temperature sensors installed in areas where the frequency of fires is higher than a frequency threshold.

[0039] The specific components mentioned here may include, but are not limited to, axles and / or braking systems. For example, in monitoring specific components, dedicated temperature and pressure sensors may be installed on specific components such as axles and braking systems that are prone to fire due to mechanical failure.

[0040] The perimeter of the cab may include, but is not limited to, at least one of the top, sides and bottom of the cab, and the perimeter of the control cab may include at least one of the top, sides and bottom of the control cab.

[0041] Please see Figure 3 , Figure 3 A schematic diagram of the system architecture for fire alarm processing based on engineering machinery vehicles provided in this application embodiment is shown below. Figure 3 As shown, the data acquisition system may include, but is not limited to, temperature detection systems, smoke concentration detection systems, visual monitoring systems, and other monitoring systems.

[0042] In practical applications, step S101 can be implemented through a data acquisition system. Specifically, temperature data for the first monitoring area is obtained through a temperature detection system, which receives temperature readings from monitoring points ID of temperature-sensing cables periodically or in real time, and / or temperature data from accessories of facilities where fires frequently occur. Specifically, smoke concentration detection system converts the analog or digital signals from smoke concentration sensors installed in the second monitoring area into smoke concentration percentage data. Specifically, a visual monitoring system analyzes the real-time video stream installed in the third monitoring area using an infrared imaging module to detect any abnormally high-temperature points. Specifically, other monitoring systems monitor in real time data from axle temperature sensors and / or air brake pressure sensors installed on specific components, such as axles and / or braking systems. If the readings exceed the normal operating threshold range, an anomaly is identified in the specific component, and abnormality data is obtained.

[0043] Specifically, the temperature detection system can deploy temperature-sensing cables along the main wiring harness path of the vehicle body, dividing this path into several monitoring points. Each monitoring point has an independent ID, and the system monitors and collects the temperature around each ID in real time, forming a temperature monitoring path from points to lines. Additional monitoring points are placed near high-frequency fire-generating mechanisms for simultaneous real-time temperature monitoring. This allows for monitoring of specific locations through adjustable temperature alarm thresholds, thus facilitating more effective monitoring of the temperature of high-frequency fire-generating mechanisms. Specifically, the temperature detection system can collect the temperature of the aforementioned areas, digitally convert the real-time collected temperature and its location ID into specific digital areas, and perform real-time monitoring of each area, forming a comprehensive temperature monitoring system for the vehicle's main wiring harness path and its equipment. The real-time temperature can be denoted as T (°C).

[0044] Among them, temperature-sensing cables are special cables with continuous temperature sensing capabilities. They are not only used to transmit power or signals, but also to sense temperature changes throughout the entire environment. It is understood that the embodiments of this application use temperature-sensing cables to detect uninterrupted temperature conditions along the entire path. Compared to existing technologies that install temperature sensors at one or a few points, this method can cover the wiring harness path most prone to electrical fires in a linear fashion, enabling early and accurate detection of potential hotspots, such as localized high temperatures caused by cable damage or poor contact. This solves the problem of monitoring blind spots existing with fixed sensors along wide wiring harness paths.

[0045] Understandably, temperature-sensitive cables typically contain two conductors with a special temperature-sensitive material, such as a negative temperature coefficient thermistor, filling the space between them. When the temperature changes at any point along the cable, the electrical properties of the sensitive material at that point, such as its resistance, will change accordingly. This allows for distributed, location-based, real-time monitoring of the temperature along the cable by monitoring changes in the overall electrical parameters of the entire cable or by locating the specific section where the change occurred using specific technologies.

[0046] Specifically, the smoke concentration detection system detects smoke concentration in real time by installing smoke concentration sensors in areas such as the driver's cab, control room, and engine compartment, and transmits the data to the data processing system. The real-time smoke concentration is recorded as S (%).

[0047] Specifically, the visual monitoring system monitors key fire prevention areas in real time by installing video recorders in, for example, the driver's cab, the control room, or the top of the control room. It also uses infrared temperature detection, and records any abnormal temperature conditions as V.

[0048] Specifically, other monitoring systems, through sensors installed on, for example, the axle and / or brake system accessories, monitor the axle operating temperature and / or air brake pressure in real time, and record any abnormality as H.

[0049] Thus, the implementation method of this application, by integrating multi-dimensional monitoring data such as temperature, smoke, video images, and the status of specific components, constructs a more comprehensive and complete fire monitoring network, overcomes the defects of false alarms and missed alarms of single sensors in the prior art, improves the accuracy and reliability of fire identification, and provides a solid data foundation for realizing early fire warning and precise prevention and control of engineering machinery vehicles.

[0050] In some implementations, step 102 involves determining a fire risk assessment index based on fire monitoring data, including: The fire risk assessment index is determined based on at least one of the following: temperature data, smoke concentration data, video surveillance data, and data on abnormal conditions of specific components.

[0051] For example, please refer to Figure 3 ,like Figure 3 As shown, the fire risk assessment index is calculated by using a data processing system to process at least one of the collected temperature data, smoke concentration data, video surveillance data, and abnormal condition data of specific components.

[0052] Thus, in this embodiment of the application, the system uses a comprehensive fire alarm risk assessment index to comprehensively and quantitatively assess various fire monitoring data, providing a favorable decision-making basis for subsequent precise emergency response operations.

[0053] In some implementations, a fire risk assessment index is determined based on at least one of temperature data, smoke concentration data, video surveillance data, and data on abnormal conditions of specific components, including: The first weight is obtained from temperature data, the second weight is obtained from smoke concentration data, the third weight is obtained from video surveillance data, and the fourth weight is obtained from abnormal condition data of specific components. The fire risk assessment index is calculated based on temperature data and its first weight, smoke data and its second weight, video surveillance data and its third weight, and abnormal condition data of specific components and its fourth weight.

[0054] The data processing system processes the data from the data acquisition system, specifically processing temperature data, smoke concentration data, video surveillance data, and abnormal situation data.

[0055] Specifically, the collected data is graded and weighted, with the input parameters assigned weight coefficients. The real-time temperature coefficient 'a' is the first weight, the smoke concentration system coefficient 'b' is the second weight, the video surveillance anomaly coefficient 'c' is the third weight, and the specific component anomaly coefficient 'd' is the fourth weight. Here, a + b + c + d = 1.

[0056] For example, the system sets safety thresholds according to the actual situation, such as T=80℃, S=15%, V=0 or 1, H=0 or 1.

[0057] We introduce the fire risk assessment index FRI ∈ [0, 1], which represents the probability of a fire; the higher the value, the greater the risk.

[0058]

[0059] The temperature sensing uses the temperature Sigmoid function:

[0060] Where, (T): real-time monitoring temperature (unit: ℃); (T_0): baseline trigger temperature (e.g., 80℃); (k): curve steepness coefficient (0.2); (S(T)): output normalized value [0,1]; when (T<50℃): (S(T) ≈ 0) (no response); when (T = T_0=80): (S(T) = 0.5) (early warning threshold); when (T>90℃): (S(T) ≈ 1) (full range trigger); where smoke sensor S(s) = (ΔS / S0)² smoke concentration change rate (S0 is the baseline value, here it is 15%).

[0061] The output value of the convolutional neural network for video surveillance c·S(v) infrared thermal imaging.

[0062] Other abnormal situations d, that is, the abnormal situations of the specific components mentioned above, are either 0 or 1. That is, if there is an abnormality, d needs to be added; if there is no abnormality, d does not need to be added.

[0063] Thus, in this embodiment of the application, by assigning different weights to different types of monitoring data, the differences in the actual contribution of various fire signs to risk assessment are fully considered, thereby making the final calculated fire risk assessment index more reasonable and reliable, thereby improving the accuracy and reliability of risk assessment.

[0064] In some implementations, please refer to Figure 4 , Figure 4 Another schematic diagram of the fire alarm handling method based on engineering machinery vehicles provided in the embodiments of this application is shown below. Figure 4 As shown, in step 103, based on the fire alarm risk assessment index, the corresponding emergency operations are determined and controlled for execution, including: Step 1031: Determine the fire risk level based on the fire risk assessment index; Step 1032: Based on the fire alarm risk level, determine the emergency operation corresponding to the fire alarm risk level and execute the emergency operation corresponding to the risk level.

[0065] For example, an emergency response decision logic is established based on the emergency plan provided by the data processing system.

[0066] For example, please refer to Figure 3 ,like Figure 3 As shown, the data processing system determines the emergency operations corresponding to the fire alarm risk level based on the fire alarm risk level, and the execution system executes the emergency operations corresponding to the risk level.

[0067] In this embodiment of the application, by establishing a graded response mechanism, precise control of emergency operations can be achieved. The system can execute differentiated measures from early warning to automatic fire extinguishing according to different risk levels, thereby minimizing unnecessary intervention while ensuring safety, and effectively balancing the contradiction between timely fire control and normal vehicle operation.

[0068] In some implementations, step 1031, determining the fire risk level based on the fire risk assessment index, includes at least one of the following: If the fire alarm risk assessment index is less than the first threshold, the fire alarm risk level is determined to be level zero fire alarm risk. If the fire alarm risk assessment index is greater than or equal to the first threshold and less than the second threshold, then the fire alarm risk level is determined to be Level 1 fire alarm risk. If the fire alarm risk assessment index is greater than the second threshold and less than the third threshold, the fire alarm risk level is determined to be a level two fire alarm risk. If the fire alarm risk assessment index is greater than or equal to the third threshold, the fire alarm risk level is determined to be level three fire alarm risk. Among them, the third threshold is greater than the second threshold, and the second threshold is greater than the first threshold.

[0069] For example, the first threshold may be 0.1, the second threshold may be 0.6, and the third threshold may be 0.8.

[0070] Here, by setting a fourth threshold, the primary emergency operation can be further divided into a first primary emergency operation and a second primary emergency operation, wherein the fourth threshold is greater than the first threshold and less than the second threshold. For example, the fourth threshold can be 0.3. If the fire risk level is Level 1, the emergency operation is determined to be a primary emergency operation, and the engineering machinery vehicle is controlled to issue an alarm notification and / or adjust its speed. This includes: if the fire risk level is Level 1 and the fire risk assessment index is greater than the first threshold but less than the fourth threshold, the engineering machinery vehicle is controlled to issue an alarm notification; if the fire risk level is Level 1 and is greater than or equal to the fourth threshold but less than the third threshold, the engineering vehicle is controlled to issue an alarm notification and its speed is adjusted. Thus, in this embodiment, the system uses a comprehensive fire risk assessment index to comprehensively and quantitatively assess fire risk from various fire monitoring data, providing a favorable decision-making basis for subsequent precise emergency operations.

[0071] In some implementations, step 1032 involves determining and executing emergency operations corresponding to the fire alarm risk level, including at least one of the following: If the fire alarm risk level is zero, then the emergency operation is determined to be normal operation and the construction machinery vehicles are controlled to operate normally. If the fire alarm risk level is Level 1, then the emergency operation is determined to be a basic emergency operation, and the construction machinery vehicle is controlled to issue an alarm prompt message and / or the vehicle speed is adjusted. If the fire alarm risk level is level two, the emergency operation is determined to be a medium-level emergency operation, and the engineering machinery vehicle is controlled to perform at least one of the following: engine shutdown, fuel supply valve cut-off, and engine intake shut-off valve closure. If the fire risk level is Level 3, the emergency operation is determined to be an emergency operation, and the engineering machinery vehicle is controlled to shut off the power supply to the entire vehicle and / or trigger the fire extinguishing device to perform automatic fire extinguishing.

[0072] The fire alert can be given to the driver or operator via voice announcement or by using LEDs to indicate the fire situation.

[0073] Adjusting the vehicle speed here means bringing it within a safe speed range.

[0074] Thus, in this embodiment of the application, by establishing a hierarchical emergency response mechanism from normal operation to emergency automatic fire extinguishing, precise intervention in the fire situation is achieved, ensuring that the vehicle continues to operate when the risk is low, and that controllable measures such as early warning and speed limit are implemented when the risk is medium, and that power outages and fire extinguishing are only implemented when the risk is high, thereby maximizing the continuity of vehicle operation while achieving the most effective control of the fire situation.

[0075] In some implementations, adjusting the vehicle speed includes: Obtain the current speed of the construction machinery vehicle; The adjusted vehicle speed is determined based on the current vehicle speed and the fire risk assessment index.

[0076] For example, given the current vehicle speed Vc and the fire risk assessment index FRI, the adjusted vehicle speed Vnew is calculated according to the following formula.

[0077]

[0078] For example, please refer to Figure 3 The execution system is connected to the vehicle control system, and the vehicle control system controls the vehicle speed adjustment.

[0079] Thus, the above implementation method achieves an optimized balance between safety and vehicle handling by dynamically linking vehicle speed adjustment with the real-time fire alarm risk index. The system can intelligently calculate a reasonable speed reduction based on the risk level, ensuring the effectiveness of risk control while avoiding secondary accidents caused by sudden braking or a sudden drop in speed, and guaranteeing a smooth transition for the vehicle in emergency situations.

[0080] In some implementations, the construction machinery vehicle is configured as multiple monitoring zones; Triggering the fire extinguishing system to perform automatic fire extinguishing procedures includes: When a fire alarm risk level of three is triggered, the fire extinguishing devices in the monitored area will automatically extinguish the fire.

[0081] It is important to understand that the multiple monitoring areas here can include multiple monitoring point areas, the area where the high-frequency fire occurs, the driver's cab, the control room, the area around the driver's cab, and the area around the control room, etc.

[0082] Different monitoring areas correspond to different calculated risk assessment indices. In response to a fire alarm risk level of three, the fire extinguishing devices in the monitoring area corresponding to a fire alarm risk level of three will be activated to perform automatic fire extinguishing. For example, if the current fire alarm risk level in the driver's cab is three, the fire extinguishing devices in the driver's cab will be automatically activated to perform fire extinguishing.

[0083] Thus, in this embodiment, by accurately associating the fire extinguishing action with the specifically identified fire risk area, location-based fire extinguishing is achieved, avoiding the waste of fire extinguishing caused by the indiscriminate fire extinguishing of the entire vehicle by the traditional system and the secondary damage to non-fired equipment, thereby improving fire extinguishing efficiency and maximizing the protection of vehicle assets.

[0084] In some embodiments, the method further includes: Obtain the volume of the burning chamber in the monitoring area corresponding to a fire risk level of three. Based on the volume of the burning chamber and the fire risk assessment index of the corresponding monitoring area, the extinguishing agent release amount of the fire extinguishing device is determined as the target release amount; When a fire alarm risk level of three is triggered, the fire extinguishing devices within the monitored area will automatically initiate fire suppression procedures, including: When a fire alarm risk level of three is triggered, the fire extinguishing devices within the monitored area will release the target amount of extinguishing agent to extinguish the fire.

[0085] For example, determining the target release amount of the extinguishing agent from the fire extinguishing device based on the volume of the burning chamber and the fire risk assessment index of the corresponding monitoring area may further include: Based on the volume of the burning chamber, the fire risk assessment index of the corresponding monitoring area, and the fire extinguishing efficiency coefficient of the fire extinguishing device, the extinguishing agent release amount of the fire extinguishing device is determined as the target release amount.

[0086] Specifically, the extinguishing agent release amount Q is calculated according to the following formula:

[0087] Where K is the fire extinguishing efficiency coefficient and A is the volume of the fire compartment (m3).

[0088] For example, please refer to Figure 3 The execution system is connected to the vehicle control system, which then performs the fire extinguishing process.

[0089] In this way, precise fire suppression is achieved by dynamically calculating the amount of extinguishing agent released. The system determines the optimal extinguishing agent dosage based on the actual volume of the fire area and the real-time severity of the fire (fire risk assessment index), which ensures effective fire suppression while minimizing the waste or insufficiency of extinguishing agent, thereby improving fire suppression efficiency and reducing fire suppression costs.

[0090] In some embodiments, the method further includes: Acquire fire situation information based on temperature data of the first monitoring area, smoke concentration data of the second monitoring area, video data of the third monitoring area, and fire risk assessment index corresponding to each monitoring area within a preset time period; Obtain operating condition data and location data of construction machinery vehicles within a preset time period; Operating data, location data, and fire information are uploaded to the Internet of Things platform via wireless network.

[0091] The IoT platform here can be the control and command center for construction machinery vehicles or the computers of the fleet. For example, operating condition data, location data, and fire situation information are uploaded to the IoT platform via a wireless network, and then visualized on the IoT platform. For instance, the operating condition data, location data, and fire situation information can be displayed in a digitized and graphical manner to enable the control center or fleet to analyze the cause of the vehicle fire and conduct timely rescue operations.

[0092] Here, the preset time period can be set in advance according to needs, such as 1 hour or half an hour.

[0093] For example, please refer to Figure 3 The execution system is connected to the data transmission network alarm system, which then uploads operating data, location data, and fire information to the Internet of Things platform via a wireless network.

[0094] Specifically, once a vehicle fire alarm is triggered, the alarm will be automatically triggered through the data network alarm system, and all operating conditions, locations and alarm information of the equipment within the past hour will be uploaded to the backend. This will facilitate subsequent analysis of the cause of the vehicle fire, realize comprehensive IoT intelligent control, improve the safety and timeliness of driver safety supervision, and the backend data can effectively digitize and visualize the process (including monitoring screens), greatly improving the reliability of the data.

[0095] Thus, the implementation method of this application constructs a complete fire data traceability chain by packaging and uploading multi-dimensional fire data, vehicle operating conditions, and location information to an IoT platform. This provides reliable data evidence for remote monitoring, accurate accident review, and liability determination, while supporting fire risk analysis and prediction based on historical data, thereby achieving an upgrade from single emergency response to full lifecycle safety management.

[0096] Based on the same inventive concept as the foregoing embodiments, the method provided by the foregoing embodiments will be illustrated by a specific example below, in which an engineering crane is used as an example of an engineering machinery vehicle.

[0097] It should be noted that the crane used in this project integrates the aforementioned intelligent fire alarm detection system. Please refer to [link / reference]. Figure 5 , Figure 5 A schematic diagram illustrating the specific process of the fire alarm handling method based on engineering machinery vehicles provided in this application embodiment is shown below. Figure 5As shown, the fire alarm handling method includes: Step 51: Power-on self-test of the equipment; Step 52: Check if the intelligent fire alarm detection system is working properly; if not, proceed to step 53; if it is working properly, proceed to step 54. Step 53: The system enters manual control mode; Step 54: The data acquisition system begins operation; That is, perform the above-mentioned step 101, and collect fire monitoring data through temperature detection system, smoke concentration detection system, video monitoring system and other monitoring systems; Step 55: The data processing system begins operation; That is, by performing steps 102 and 103 as described above, the fire alarm assessment index is calculated and emergency operations are determined through the data processing system.

[0098] Step 56: Execute system tasks; That is, perform the corresponding emergency operation in step 103 above.

[0099] Specifically, taking a first threshold of 0.1, a second threshold of 0.6, a third threshold of 0.8, and a fourth threshold of 0.3 as an example, the execution system establishes an emergency tiered response decision logic based on the emergency plan provided by the data processing system.

[0100] Step 561: In response to FRI < 0.1, normal operation is confirmed.

[0101] Step 562: In response to 0.1 ≤ FRI < 0.3, determine the emergency action for audible and visual alarm prompts; or Step 563: In response to 0.3 ≤ FRI < 0.6, determine the emergency action for audible and visual alarm prompts and limiting the vehicle speed to a safe value. Both of these are basic emergency actions.

[0102] Step 564: In response to 0.6 ≤ FRI < 0.8, determine the emergency operations of shutting down the engine, cutting off the vehicle fuel supply valve, and shutting off the engine intake cut-off valve.

[0103] Specifically, if T > 80℃ or S > 30%, an emergency operation signal will be output to stop the engine and shut off the engine fuel supply valve.

[0104] Step 565: 0.8≤ FRI, determine the emergency operation of the automatic fire extinguishing device, that is, trigger the fire extinguishing device in the corresponding area to automatically extinguish the fire based on the detected abnormal area.

[0105] Step 57: The vehicle controller is activated.

[0106] The vehicle controller executes the corresponding emergency operation based on the emergency operation.

[0107] Step 58: The data transmission network alarm system is activated.

[0108] Specifically, once a vehicle fire alarm is triggered, the alarm will be automatically triggered through the data network alarm system, and all operating conditions, locations, and alarm information of the equipment within the past hour will be uploaded to the backend.

[0109] In summary, the above embodiments have the following advantages compared to the prior art: This is the first integrated intelligent fire alarm system that combines fire monitoring (including temperature and smoke sensors, auxiliary monitoring, etc.), emergency execution (including engine shutdown, power cut-off, fuel supply cut-off, and air intake valve closure), intelligent fire extinguishing, and a background fire alarm data processing system. When construction machinery vehicles catch fire, it can intelligently and effectively handle emergency situations in stages and layers, enabling more precise and effective handling of fires, effectively reducing losses caused by fires, and greatly improving driving safety. In the event of a fire, the system can also assist in accident analysis and cause investigation through data uploaded from the background.

[0110] Figure 6 A structural block diagram of a fire alarm handling device based on engineering machinery vehicles provided in the embodiments of this application is shown below. Figure 6 As shown, the fire alarm processing device may include: a memory configured to store instructions; and a processor configured to retrieve instructions from the memory and, when executing the instructions, to implement the aforementioned fire alarm processing method. In the example, the fire alarm processing device may be, for example, an intelligent fire alarm detection system integrated into an engineering machinery vehicle or a separately configured mobile terminal with an intelligent fire alarm detection system.

[0111] This application also provides an engineering machinery vehicle, including the aforementioned fire alarm handling device. This engineering machinery vehicle may be, for example, a crane, excavator, bulldozer, or road roller, etc., and is not limited thereto.

[0112] In some embodiments, to implement the above-described fire alarm handling method, the construction machinery vehicle is further equipped with: a temperature sensing device arranged in a first monitoring area of ​​the construction machinery vehicle; a smoke concentration sensing device arranged in a second monitoring area of ​​the construction machinery vehicle; a camera device installed in a third monitoring area of ​​the construction machinery vehicle; and a sensing device for monitoring specific components, wherein the first monitoring area includes at least one of the following: a monitoring point area divided into several monitoring points with independent identification marks along the main road of the vehicle body and an area where the fire occurrence frequency is higher than a frequency threshold; the second monitoring area includes at least one of the following: the driver's cab, the control room, and the engine compartment; and the third monitoring area includes at least one of the following: the driver's cab, the control room, the area around the driver's cab, and the area around the control room.

[0113] This application also provides a machine-readable storage medium storing instructions that cause a machine to perform the fire alarm processing method described above.

[0114] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application takes the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0115] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer programs according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, executable by the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0116] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0117] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0118] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0119] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0120] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0121] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0122] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A fire alarm handling method based on engineering machinery vehicles, characterized in that, The method includes: Collect fire monitoring data from construction machinery vehicles, wherein the fire monitoring data is used to characterize the current fire situation information; Based on the fire monitoring data, a fire risk assessment index is determined; Based on the fire risk assessment index, the corresponding emergency operation is determined and the emergency operation is controlled and executed.

2. The method according to claim 1, characterized in that, The fire monitoring data includes at least one of the following: temperature data, smoke concentration data, video surveillance data, and data on abnormal conditions of specific components; The construction machinery vehicle is equipped with: a temperature sensing device located in a first monitoring area of ​​the construction machinery vehicle; a smoke concentration sensing device located in a second monitoring area of ​​the construction machinery vehicle; a camera device installed in a third monitoring area of ​​the construction machinery vehicle; and a sensor device for monitoring specific components; wherein, the first monitoring area includes at least one of the following: a monitoring point area divided into several independently identifiable areas along the main wiring harness path of the vehicle body, and an area where a mechanism with a fire occurrence frequency higher than a frequency threshold is located; the second monitoring area includes at least one of the following: the driver's cab, the control room, and the engine compartment; the third monitoring area includes at least one of the following: the driver's cab, the control room, the area surrounding the driver's cab, and the area surrounding the control room; The collected fire monitoring data of engineering machinery vehicles includes at least one of the following: The temperature data of the first monitoring area is collected in real time through the temperature sensing device. The smoke concentration sensor collects real-time smoke concentration data of the second monitoring area. The camera device is used to collect video data of the third monitoring area in real time. Data on abnormal conditions of the specific component are collected using a sensing device for monitoring the specific component.

3. The method according to claim 2, characterized in that, The step of determining the fire risk assessment index based on the fire monitoring data includes: The fire risk assessment index is determined based on at least one of the temperature data, the smoke concentration data, the video surveillance data, and the abnormal condition data of the specific component. The step of determining the corresponding emergency operation based on the fire risk assessment index and controlling the execution of the emergency operation includes: The fire risk level is determined based on the fire risk assessment index. Based on the fire alarm risk level, determine the emergency operation corresponding to the fire alarm risk level and execute the emergency operation corresponding to the risk level.

4. The method according to claim 3, characterized in that, The determination of the fire risk level based on the fire risk assessment index includes at least one of the following: If the fire risk assessment index is less than the first threshold, then the fire risk level is determined to be a level zero fire risk. If the fire risk assessment index is greater than or equal to the first threshold and less than the second threshold, then the fire risk level is determined to be a level one fire risk. If the fire risk assessment index is greater than the second threshold and less than the third threshold, then the fire risk level is determined to be a level two fire risk. If the fire risk assessment index is greater than or equal to the third threshold, then the fire risk level is determined to be a level three fire risk. Wherein, the third threshold is greater than the second threshold, and the second threshold is greater than the first threshold.

5. The method according to claim 4, characterized in that, The step of determining and executing emergency operations corresponding to the fire alarm risk level, based on the fire alarm risk level, includes at least one of the following: If the fire alarm risk level is zero, then the emergency operation is determined to be normal operation and the engineering machinery vehicle is controlled to operate normally. If the fire alarm risk level is Level 1, then the emergency operation is determined to be a basic emergency operation, and the construction machinery vehicle is controlled to issue an alarm prompt and / or adjust the vehicle speed; wherein, adjusting the vehicle speed includes: obtaining the current speed of the construction machinery vehicle; and determining the adjusted vehicle speed based on the current speed and the fire alarm risk assessment index; If the fire alarm risk level is level two, then the emergency operation is determined to be a medium-level emergency operation, and the engineering machinery vehicle is controlled to perform at least one of the following: engine shutdown, fuel supply valve cut-off, and engine intake shut-off valve closure. If the fire risk level is Level 3, then the emergency operation is determined to be an emergency operation, and the engineering machinery vehicle is controlled to shut down the vehicle's power supply and / or trigger the fire extinguishing device to perform automatic fire extinguishing.

6. The method according to claim 5, characterized in that, The construction machinery vehicles are configured to monitor multiple areas; The fire extinguishing device is triggered to perform automatic fire extinguishing procedures, including: When a fire alarm risk level of three is triggered, the fire extinguishing devices in the monitored area will automatically extinguish the fire.

7. The method according to claim 6, characterized in that, The method further includes: Obtain the volume of the fire-starting chamber in the monitoring area corresponding to the fire risk level of Level III; Based on the fire risk assessment index of the fire chamber and the corresponding monitoring area, the extinguishing agent release amount of the fire extinguishing device is determined as the target release amount. The fire extinguishing devices within the monitoring area corresponding to a fire alarm risk level of three shall perform automatic fire extinguishing procedures, including: When a fire alarm risk level of three is triggered, the fire extinguishing device in the monitoring area releases the target amount of extinguishing agent to extinguish the fire.

8. The method according to claim 2, characterized in that, The method further includes: The system acquires fire situation information based on temperature data of the first monitoring area, smoke concentration data of the second monitoring area, video data of the third monitoring area, and fire risk assessment index corresponding to each monitoring area within a preset time period. Obtain the operating condition data and location data of the construction machinery vehicle within the preset time period; The operating data, location data, and fire situation information are uploaded to the Internet of Things platform via a wireless network.

9. A fire alarm handling device based on engineering machinery vehicles, characterized in that, include: The memory is configured to store instructions; as well as The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the fire alarm processing method according to any one of claims 1-8.

10. An engineering machinery vehicle, characterized in that, Includes the fire alarm handling device as described in claim 12.

11. A machine-readable storage medium, characterized in that, include: The machine-readable storage medium stores instructions for causing the machine to perform the fire alarm handling method according to any one of claims 1 to 8.

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