Fire safety warning system

Abstract

The invention belongs to the field of fire safety warning, and provides a fire safety warning system which comprises a fire detection module used for detecting fire signals in an environment, a data acquisition module used for acquiring images and temperature data of a fire scene, a data analysis module used for analyzing the data acquired by the data acquisition module, and a risk assessment module. The risk assessment module is used for assessing a fire risk level according to a result of the data analysis module, and the alarm decision module is used for deciding whether to send out an alarm signal according to an assessment result of the risk assessment module; the comprehensive fire safety warning system provided by the invention remarkably improves the accuracy of fire detection, can comprehensively cover the environment of a large building or a complex structure, effectively eliminates the blind area of fire detection, ensures that the fire can be detected in time at the initial stage of the fire, and improves the safety of the fire. Therefore, precious time is gained for early response and control of the fire.

Description

Technical Field

[0001] The invention belongs to the field of fire safety warning, in particular to a fire safety warning system. Background Art

[0002] With the acceleration of urbanization and the increase in building density, fire safety issues are becoming increasingly prominent. Fire, as a sudden and destructive disaster, poses a serious threat to people's lives and property. Traditional fire safety warning systems mostly rely on simple smoke or temperature sensors. Although these systems can detect the occurrence of fire to a certain extent, there are some problems in their use.

[0003] Traditional systems rely on a single smoke or temperature sensor, which limits the detection range and creates blind spots in fire detection, thus affecting subsequent detection and analysis, resulting in incomplete fire judgment and analysis, and causing great inconvenience.

[0004] Therefore, those skilled in the art have proposed a fire safety warning system to solve the problems raised by the background technology. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a fire safety warning system to solve the problem that the prior art lacks the collection of intuitive data such as fire scene images, resulting in incomplete fire judgment and analysis, and insufficient analysis capabilities of existing data analysis modules.

[0006] A fire safety warning system includes a fire detection module for obtaining fire signals in an environment;

[0007] A data acquisition module, used to receive images and temperature data of the fire scene;

[0008] A data analysis module, used for analyzing the image data and temperature data collected by the data collection module, so as to obtain analysis results;

[0009] A risk assessment module, used to assess the fire risk level according to the results of the data analysis module and make an assessment result;

[0010] An alarm decision module is used to receive the assessment result of the risk assessment module and decide whether to issue an alarm signal;

[0011] The information release module is used to generate alarm information when the alarm decision module decides to send out an alarm signal.

[0012] Preferably, the fire detection module is used to process the ambient temperature data and the smoke concentration in the environment through a signal processing algorithm, and the formula is: Where S represents the processed signal strength, T represents the received temperature reading, and T0 Indicates the reference temperature of the environment, T max Indicates the highest temperature that the received temperature can detect, S m Indicates the acceptable smoke density reading, S m0 Indicates the baseline value of smoke density, S mmax Indicates the acceptable smoke concentration, which is the highest smoke concentration that can be detected.

[0013] Preferably, the data acquisition module is used to receive image data of the fire scene and obtain temperature data of the fire scene; and preprocess the image data and the temperature data through a data preprocessing algorithm, the formula of which is: Where D p represents the preprocessed data, I represents the image data collected by the image sensor, μ I represents the mean of the image data, σ I represents the standard deviation of the image data, T represents the temperature data collected by the received temperature, μ T represents the mean of temperature data, σ T Represents the standard deviation of the temperature data.

[0014] Preferably, the data analysis module uses an image processing algorithm to process the image data collected by the image sensor. The image algorithm adopts the following formula: Among them I P represents the processed image data, I represents the original image data, and I 0 represents a preset threshold value used to enhance the fire features in the image;

[0015] The data analysis module also includes a temperature data analysis algorithm for analyzing the received temperature data collected using the following algorithm formula: Where T a represents the analyzed temperature data, T represents the original temperature data, and T b represents the baseline temperature, T ab Indicates the sensitivity to temperature changes.

[0016] Preferably, the risk assessment module is used to assess the fire risk level using an image processing algorithm and a temperature data analysis algorithm, using the following formula for assessment: Where R represents the risk level, I p Represents the processed image data, I pmax Indicates the maximum value of image data, T a Represents the analyzed temperature data, T amax Indicates the maximum value of temperature data.

[0017] Preferably, the alarm decision module includes a decision algorithm for deciding whether to issue an alarm signal according to the result of the risk assessment algorithm, wherein the formula of the decision algorithm is: Where D represents the decision result, R represents the risk level, and R th Indicates the preset risk threshold.

[0018] Preferably, the information release module includes an information release algorithm for releasing the alarm information signal in real time when the decision algorithm determines that an alarm signal needs to be issued. The information release algorithm adopts the following formula:

[0019] Where P represents the alarm information released, D represents the decision result, X represents the location of the fire, and Y represents the time when the fire occurred.

[0020] Preferably, the system also includes a communication module for transmitting the alarm information to a designated receiving device, which uses a data encapsulation algorithm to encapsulate the alarm information into a format suitable for network transmission, and its formula is, M = e(P) = JSON(P, T), wherein M represents the encapsulated message, P represents the alarm information, T represents the transmission time, JSON represents a function for converting data into JSON format, and e represents the encryption algorithm of the alarm information.

[0021] Preferably, the communication protocol also includes an encryption algorithm for ensuring the transmission security of the alarm information. The encryption algorithm formula is: E represents the encrypted information, M represents the message to be encrypted, K represents the encryption key, ⊕ represents the bitwise XOR operation, and k represents the encryption key.

[0022] Preferably, the encryption algorithm also includes a key management algorithm for generating and managing encryption keys, and its formula is K=l(S)=H(S), wherein K represents the generated key, S represents the system security policy, and H represents the hash function.

[0023] Through the above technical solution,

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] Technical Effects of Right 1

[0026] The present invention provides a comprehensive fire safety warning system by integrating multiple sensors and advanced data analysis technologies, which significantly improves the accuracy of fire detection. The system can fully cover the environment of large buildings or complex structures, effectively eliminate the blind spots of fire detection, and ensure that fires can be detected in time at the early stages of their occurrence, thereby winning precious time for early response and control of fires. This multi-dimensional data collection method makes fire risk assessment more accurate and effectively reduces the possibility of false alarms and missed alarms. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flowchart of the fire detection module in the present invention;

[0028] Figure 2 The system module flow chart of the present invention is DETAILED DESCRIPTION

[0029] The following is a further detailed description of the embodiments of the present invention in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0030] Embodiment 1: As shown in the attached Figure 1 As shown: The present invention provides a fire safety warning system, including a fire detection module, which is used to detect fire signals in the environment. The module can quickly identify the initial signs of fire by real-time monitoring of the fire signals in the environment. Compared with the prior art, the module can provide earlier fire warnings, reduce response time, and reduce the damage caused by fire, providing a basis for the entire system to quickly respond to fires, so that subsequent data collection and analysis can be carried out based on accurate fire signals;

[0031] Data acquisition module, used to collect images and temperature data of the fire scene. By collecting images and temperature data, the system can obtain more comprehensive fire scene information. Compared with systems that rely on a single data source, this module provides more accurate fire analysis and evaluation, reduces false alarms and missed alarms, provides a rich data source for the data analysis module, and enhances the system's understanding and response capabilities to fire situations;

[0032] The data analysis module is used to analyze the data collected by the data acquisition module and conduct in-depth analysis of the collected data to identify fire characteristics and trends, thereby improving the accuracy of fire risk assessment, enabling the system to more accurately predict the development of fires, providing a scientific basis for the risk assessment module, and making alarm decisions more reasonable and effective;

[0033] The risk assessment module is used to evaluate the fire risk level according to the results of the data analysis module. The fire risk level is dynamically assessed to make the alarm decision more scientific and accurate. Compared with the static threshold, this module can adapt to different fire situations, improve the accuracy and timeliness of the alarm, and provide key risk assessment information for the alarm decision module, making the alarm more accurate and effective;

[0034] The alarm decision module is used to decide whether to issue an alarm signal based on the evaluation results of the risk assessment module. It makes intelligent decisions on whether to issue an alarm based on the risk assessment results, reduces false alarms and missed alarms, improves the reliability and efficiency of the alarm system, and ensures that the alarm can be issued in time when it is really needed. As the core decision-making unit of the system, it ensures the accuracy and timeliness of the alarm information and improves the response efficiency of the overall system;

[0035] The information release module is used to release alarm information when the alarm decision module decides to send out an alarm signal. It can quickly release alarm information to ensure that relevant personnel can take timely actions. Compared with delayed or inaccurate information release, this module can reduce fire response time and improve personnel evacuation and rescue efficiency. As the last link of the system, it ensures that the alarm information can be quickly conveyed to the personnel in need, thereby improving the practicality and effectiveness of the overall system.

[0036] As can be seen from the above, this system realizes the automatic management of the whole process from fire signal detection to alarm information release by integrating key modules such as fire detection, data collection, data analysis, risk assessment, alarm decision and information release. The advantage of this system is that it comprehensively utilizes multiple sensor data such as received temperature, received smoke concentration, image sensor, etc., as well as advanced data processing and analysis algorithms, thereby improving the accuracy and response speed of fire detection, ensuring that risks can be quickly and accurately assessed and alarm information can be released when a fire occurs, effectively improving the efficiency and effectiveness of fire safety management.

[0037] Embodiment 2: As shown in the attached Figure 1-2 As shown: This embodiment is basically the same as the previous embodiment, except that the fire detection module can be implemented by two classes: the TemperatureSensor class is used to obtain the ambient temperature data, including the method readTemperature(), which simulates reading the temperature value of the current environment from the hardware interface; the SmokeSensor class is used to obtain the smoke concentration in the environment, including the method readSmokeLevel(), which simulates reading the smoke concentration value of the current environment from the hardware interface

[0038] The specific code can be:

[0039]

[0040] By integrating temperature and received smoke concentration, the system can monitor fire signals from multiple dimensions, improve the accuracy and reliability of fire detection, reduce the false alarms that may be generated by a single sensor, provide the system with more comprehensive fire monitoring capabilities, and enhance the system's ability to identify early signs of fire;

[0041] The fire detection module also includes a signal processing algorithm for processing the above-mentioned sensor signals, and its formula is, where S represents the signal strength after processing, T represents the received temperature reading, represents the reference temperature of the environment, represents the maximum temperature that can be detected by the received temperature, represents the received smoke concentration reading, represents the reference value of the smoke concentration, and represents the maximum smoke concentration that can be detected by the received smoke concentration. This formula converts the temperature and smoke concentration readings into standardized signal strengths of 0-100 for further processing. Through the standardized processing algorithm, the system can convert the readings of different sensors into a unified signal strength for easy comparison and analysis, providing standardized data for subsequent data collection and analysis, and improving the data consistency and analysis accuracy of the entire system.

[0042] Furthermore, the data acquisition module can be implemented by two classes: the ImageSensor class is used to receive the image data of the fire scene. This class contains a method captureImage(), which obtains the real-time image data of the fire scene from the hardware interface; the TemperatureSensor class is used to obtain the temperature data of the fire scene. This class contains a method readTemperature(), which simulates obtaining the real-time temperature data of the fire scene from the hardware interface. The specific algorithm code can be

[0043]

[0044] The data acquisition module is used to preprocess the collected image data and temperature data through the data preprocessing algorithm. The formula is: Where D p represents the preprocessed data, I represents the image data collected by the image sensor, μ I represents the mean of the image data, σ I represents the standard deviation of the image data, T represents the temperature data collected by the received temperature, μ T represents the mean of temperature data, σ T Represents the standard deviation of temperature data. The preprocessing algorithm can denoise and standardize the collected data to improve data quality, provide high-quality data input for the data analysis module, and improve the performance and reliability of the entire system.

[0045] Preferably, the data analysis module uses an image processing algorithm to process the image data collected by the image sensor. The image algorithm uses the following formula: Among them I P represents the processed image data, I represents the original image data, and I 0Represents a preset threshold value, which is used to enhance the fire features in the image. The image processing algorithm can identify and enhance the fire features in the image, improve the accuracy of fire identification, provide more accurate fire feature information for the risk assessment module, and improve the accuracy of fire risk assessment;

[0046] The data analysis module also includes a temperature data analysis algorithm for analyzing the received temperature data collected. The specific algorithm formula is as follows: Where T a represents the analyzed temperature data, T represents the original temperature data, and T b represents the baseline temperature, T ab Indicates the sensitivity of temperature changes. The temperature data analysis algorithm can identify temperature anomalies, provide an important basis for fire risk assessment, provide accurate temperature anomaly information for the risk assessment module, and enhance the system's ability to identify fire risks.

[0047] Furthermore, the risk assessment module includes a risk assessment algorithm for assessing the fire risk level based on the results of the image processing algorithm and the temperature data analysis algorithm, using the following formula for assessment: Where R represents the risk level, I p Represents the processed image data, I pmax Indicates the maximum value of image data, T a Represents the analyzed temperature data, T amax It represents the maximum value of temperature data. The risk assessment algorithm that integrates image and temperature data can provide a more comprehensive fire risk assessment and provide a comprehensive risk assessment result for the alarm decision module, making the alarm decision more scientific and reasonable.

[0048] From the above, we can see that by integrating temperature, received smoke concentration and a signal processing algorithm, the detection accuracy and response speed of fire signals are improved, the collection and preprocessing of image and temperature data are increased, and a more comprehensive and accurate data basis is provided for subsequent analysis. At the same time, through image processing and temperature data analysis algorithms, the capabilities of the data analysis module are enhanced, enabling the system to more accurately identify fire characteristics and assess fire conditions.

[0049] Embodiment 3: As shown in the attached Figure 1 As shown: Based on the first embodiment, the alarm decision module includes a decision algorithm for deciding whether to issue an alarm signal according to the result of the risk assessment algorithm, wherein the formula of the decision algorithm is: Where D represents the decision result, R represents the risk level, and R th Represents the preset risk threshold. The decision algorithm can intelligently decide whether to alarm based on the risk level, reducing false alarms and missed alarms, ensuring the accuracy and timeliness of alarm information, and improving the response efficiency of the overall system.

[0050] Preferably, the information release module includes an information release algorithm for releasing the alarm information signal in real time when the decision algorithm determines that an alarm signal needs to be issued. The information release algorithm adopts the following formula: Where P represents the alarm information released, D represents the decision result, X represents the location of the fire, and Y represents the time of the fire. The information release algorithm can quickly release the alarm information to ensure that relevant personnel can take timely actions and ensure that the alarm information can be quickly conveyed to the personnel in need, thereby improving the practicality and effectiveness of the overall system.

[0051] Preferably, the system also includes a communication module for transmitting the alarm information to a designated receiving device. The communication module includes a communication protocol for transmitting the alarm information to a designated receiving device. The communication protocol also includes a data encapsulation algorithm for encapsulating the alarm information into a format suitable for network transmission. The formula is M=e(P)=JSON(P,T), wherein M represents the encapsulated message, P represents the alarm information, T represents the transmission time, JSON represents a function for converting data into a JSON format, and e represents an encryption algorithm for the alarm information. By using the data encapsulation algorithm, the system can encapsulate the alarm information into a standardized JSON format, thereby improving the readability and compatibility of the information. The data encapsulation algorithm enables the alarm information to be quickly and accurately parsed and processed by the receiving device, thereby improving the response speed and reliability of the entire system.

[0052] Preferably, the communication protocol also includes an encryption algorithm for ensuring the transmission security of the alarm information. The encryption algorithm formula is: E represents the encrypted information, M represents the message to be encrypted, K represents the encryption key, ⊕ represents the bitwise XOR operation, and k represents the encryption key. The use of the encryption algorithm ensures the security of the alarm information during transmission and prevents sensitive information from being accessed or tampered with without authorization. The encryption algorithm enhances the security of the system, ensures the integrity and confidentiality of the alarm information, and improves the overall security of the system and the trust of users.

[0053] Specifically, the encryption algorithm also includes a key management algorithm for generating and managing encryption keys, and its formula is K=l(S)=H(S), where K represents the generated key, S represents the system security policy, and H represents the hash function. The key management algorithm can dynamically generate and manage encryption keys according to the system security policy, thereby improving the flexibility and security of the system. The key management algorithm enables the system to adapt to different security requirements and environmental changes, ensuring long-term and continuous communication security and enhancing the adaptability and security of the system.

[0054] From the above, we can see that a communication module is introduced to ensure that the alarm information can be safely and efficiently transmitted to the designated receiving device through the data encapsulation algorithm. The security of the communication protocol is enhanced through the encryption algorithm to protect the alarm information from unauthorized access or tampering during transmission. At the same time, by setting the key management algorithm to generate and manage encryption keys, the security of the system communication is further enhanced, the reliability and security of the system during the transmission of alarm information are improved, and the rapid and accurate communication of information in emergency situations is ensured.

[0055] The embodiments of the present invention are provided for the purpose of illustration and description. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present invention. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A fire safety warning system, characterized in that: include: A fire detection module, used to obtain fire signals in the environment; A data acquisition module, used for receiving image data and temperature data of the fire scene; A data analysis module, used for analyzing the image data and the temperature data to obtain an analysis result; A risk assessment module, used to assess the fire risk level according to the analysis results and make an assessment result; An alarm decision module is used to receive the evaluation result and decide whether to issue an alarm signal; The information release module is used to generate alarm information when the alarm decision module decides to send out an alarm signal.

2. A fire safety warning system as claimed in claim 1, characterized in that: The fire detection module is used to process the ambient temperature data and the smoke concentration in the environment through a signal processing algorithm, and its formula is: Where S represents the processed signal strength, T represents the received temperature reading, T0 represents the ambient reference temperature, and T max Indicates the highest temperature that the received temperature can detect, S m Indicates the acceptable smoke density reading, S m0 Indicates the baseline value of smoke density, S mmax Indicates the acceptable smoke concentration, which is the highest smoke concentration that can be detected.

3. A fire safety warning system as claimed in claim 2, characterized in that: The data acquisition module is used to receive the image data of the fire scene and obtain the temperature data of the fire scene; and pre-process the image data and the temperature data through a data pre-processing algorithm, and the formula is: Where D p represents the preprocessed data, I represents the image data collected by the image sensor, μ I represents the mean of the image data, σ I represents the standard deviation of the image data, T represents the temperature data collected by the received temperature, μ T represents the mean of temperature data, σ T Represents the standard deviation of the temperature data.

4. A fire safety warning system as claimed in claim 3, characterized in that: The data analysis module is used to process the image data using an image processing algorithm. The image algorithm uses the following formula Among them I P represents the processed image data, I represents the original image data, and I0 represents a preset threshold value used to enhance the fire features in the image; The data analysis module is also used to analyze the received temperature data using a temperature data analysis algorithm, using the following algorithm formula Where T a represents the analyzed temperature data, T represents the original temperature data, and T b represents the baseline temperature, T ab Indicates the sensitivity to temperature changes.

5. A fire safety warning system as claimed in claim 4, characterized in that: The risk assessment module is used to assess the fire risk level using an image processing algorithm and a temperature data analysis algorithm, and the following formula is used for assessment Where R represents the risk level, I p Represents the processed image data, I pmax Indicates the maximum value of image data, T a Represents the analyzed temperature data, T amax Indicates the maximum value of temperature data.

6. A fire safety warning system as claimed in claim 5, characterized in that: The alarm decision module includes a decision algorithm for deciding whether to issue an alarm signal according to the result of the risk assessment algorithm, wherein the formula of the decision algorithm is: Where D represents the decision result, R represents the risk level, and R th Indicates the preset risk threshold.

7. A fire safety warning system as claimed in claim 6, characterized in that: The information release module includes an information release algorithm, which is used to release the alarm information signal in real time when the decision algorithm determines that an alarm signal needs to be issued. The information release algorithm adopts the following formula: Where P represents the alarm information released, D represents the decision result, X represents the location of the fire, and Y represents the time when the fire occurred.

8. A fire safety warning system as claimed in claim 1, characterized in that: The system also includes a communication module for transmitting the alarm information to a designated receiving device, which uses a data encapsulation algorithm to encapsulate the alarm information into a format suitable for network transmission. The formula is M=e(P)=JSON(P,T), wherein M represents the encapsulated message, P represents the alarm information, T represents the transmission time, JSON represents a function for converting data into JSON format, and e represents an encryption algorithm for the alarm information.

9. A fire safety warning system as claimed in claim 8, characterized in that: The communication protocol also includes an encryption algorithm, the encryption algorithm formula is: E represents the encrypted information, M represents the message to be encrypted, and K represents the encryption key. represents a bitwise XOR operation, and k represents the encryption key.

10. A fire safety warning system as claimed in claim 9, characterized in that: The encryption algorithm also includes a key management algorithm for generating and managing encryption keys, and its formula is K=l(S)=H(S), where K represents the generated key, S represents the system security policy, and H represents the hash function.

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