Kitchen fire hazard intelligent processing system
By deploying multi-sensor modules and intelligent data analysis modules in the kitchen, combined with the automatic control module to automatically close the main gas valve, the existing system's insufficient attention to the fire risks caused by long-term opening of the gas stove is solved, and more efficient fire warning and emergency response are achieved, which significantly improves home safety.
Patent Information
- Application Number
- CN202411696903.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-25
- Publication Date
- 2025-02-28
AI Technical Summary
The existing kitchen fire hazard intelligent handling system has shortcomings in gas leakage monitoring and fire early warning, especially inadequate attention to the fire risks caused by long-term opening of the gas stove and forgetting to turn off the fire. The system lacks comprehensiveness and intelligence, and insufficient emergency response.
An intelligent kitchen fire hazard processing system including multi-sensor module, intelligent data analysis module and automatic control module is designed. By integrating smoke sensors, temperature sensors, gas leakage sensors and human body sensing sensors, the kitchen environment is comprehensively monitored. The intelligent data analysis module evaluates sensor data in real time, and the automatic control module automatically closes the gas main valve when an abnormal situation is detected.
The system can effectively monitor and prevent fire risks caused by forgetting to close the gas stove, improves fire warning capabilities and emergency response efficiency, and significantly enhances home safety.
Smart Images
Figure CN119541126A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of smart home technology, and in particular to an intelligent system for handling kitchen fire hazards. Background Art
[0002] With the accelerated pace of life in modern society and the arrival of an aging society, the number of elderly people living alone is increasing, making kitchen safety issues particularly important. Especially for elderly people who go into the kitchen alone or busy family members, it is common for gas stoves to be left on for a long time due to negligence or forgetfulness, causing food in the pot to boil dry, which greatly increases the risk of fire. Such fires not only pose a serious threat to the user himself, but may also pose a potential serious hazard to the safety of the family and neighbors.
[0003] Although the existing intelligent kitchen fire hazard handling systems have made progress in gas leak monitoring and fire warning, these systems often have the following shortcomings: 1. Single monitoring direction: Traditional systems mostly focus on gas leak monitoring, but pay insufficient attention to the fire risk caused by leaving the gas stove on for a long time and forgetting to turn off the fire. Although some systems perform well in gas leaks, they are insufficient in monitoring the use status of gas stoves, personnel activities in the kitchen, and the length of time no one is in use. 2. Lack of comprehensiveness and intelligence: Existing systems often rely on a single type of sensor and fail to fully integrate data from different sensors. When faced with comprehensive safety issues, the intelligent response and processing capabilities of existing systems may not be comprehensive and efficient enough. 3. Inadequate emergency response: Existing systems are deficient in emergency response and emergency reminders after users leave the kitchen, and fail to effectively monitor and control fire risks. The system lacks comprehensive monitoring of fire and gas stove status and automatic shutdown, making it difficult to effectively prevent fires in the event of user negligence. Summary of the invention
[0004] The purpose of this application is to provide a kitchen fire hazard intelligent processing system, which can prevent the risk of fire caused by forgetting to turn off the gas stove and comprehensively enhance family safety.
[0005] To achieve the above objectives, this application provides the following solutions:
[0006] The present application provides a kitchen fire hazard intelligent processing system, comprising:
[0007] Multi-sensor modules and controllers;
[0008] The controller is equipped with an intelligent data analysis module and an automatic control module;
[0009] The intelligent data analysis module is connected to the multi-sensor module and the automatic control module respectively;
[0010] The multi-sensor module is arranged in the kitchen; the multi-sensor module is used to obtain kitchen environment parameters; the kitchen environment parameters include smoke, temperature, flame, whether there is a gas leak, whether there is someone and the length of time no one is there;
[0011] The intelligent data analysis module is used to determine whether there is an abnormal situation based on the kitchen environment parameters;
[0012] The automatic control module is connected to the main gas valve; the automatic control module closes the main gas valve when an abnormal situation occurs.
[0013] Optionally, the kitchen fire hazard intelligent processing system further includes: an alarm;
[0014] The alarm is connected to the intelligent data analysis module; the alarm is used to send out an alarm signal when an abnormal situation occurs.
[0015] Optionally, the intelligent data analysis module includes:
[0016] Intelligent data analysis unit and wireless transmission unit;
[0017] The intelligent data analysis unit is connected to the multi-sensor module, the automatic control module and the wireless transmission unit respectively; the intelligent data analysis unit is used to determine whether there is an abnormality according to the kitchen environment parameters;
[0018] The wireless transmission unit is connected to the remote terminal; the wireless transmission unit is used to send the kitchen environment parameters to the remote terminal and send an alarm signal to the remote terminal when an abnormal situation occurs.
[0019] Optionally, the multi-sensor module includes: a smoke sensor, a temperature collector, a gas leak sensor and a human body sensing sensor.
[0020] Optionally, the temperature collector includes: an infrared temperature sensor and an NTC (Negative Temperature Coefficient) sensor.
[0021] Optionally, the human body sensing adopts Doppler radar sensing technology.
[0022] Optionally, the kitchen fire hazard intelligent processing system further comprises: a brushless motor;
[0023] The brushless motor is connected to the automatic control module and the main gas valve respectively.
[0024] Optionally, the main gas valve is a safety electronic valve; the state of the main gas valve is controlled by a transmission mechanism of a brushless motor.
[0025] Optionally, the controller is provided with a plurality of analog acquisition quantity interfaces;
[0026] The analog acquisition quantity interface is used for connecting to an external acquisition device.
[0027] Optionally, the acquisition device includes a water immersion sensor and a light sensor.
[0028] According to the specific embodiments provided in this application, this application discloses the following technical effects:
[0029] The present application provides an intelligent kitchen fire hazard processing system, which comprehensively monitors various safety parameters in the kitchen by integrating multiple sensors (smoke sensors, temperature sensors, gas leak sensors, and human body sensing sensors based on Doppler radar technology). This configuration can detect the working status of the gas stove, the flame status of the stove, the activities of people in the kitchen, and the length of time without people in real time, thereby greatly improving the early warning capability of fire risks. Doppler radar technology avoids the problem of occlusion of traditional cameras in oil smoke environments, ensuring the accuracy and stability of monitoring; using intelligent data analysis modules, various sensor data are evaluated in real time. It can quickly identify abnormal situations (such as the gas stove has not been turned off for a long time or the stove flame is abnormal). Once a fire risk is detected, the system can automatically take control measures, such as closing the main gas valve, thereby reducing the possibility of fire. Intelligent response capabilities improve the system's efficiency in handling abnormal situations.
[0030] In addition, through the mobile phone application, the user can monitor the safety status of the kitchen in real time, receive early warning information and videos, and support remote adjustment of system settings and operations. This remote function enhances the convenience of the system, allowing users to respond to kitchen safety issues anytime and anywhere; when the gas stove is not turned off for a long time or the stove flame is abnormal, the sound and light alarm system is automatically triggered, and a notification is pushed through the mobile phone application. If it is confirmed that there is no one in the kitchen, the system will automatically close the main gas valve according to the preset strategy, thereby effectively preventing fires caused by user negligence. This automated emergency handling mechanism significantly improves the system's ability to prevent and control fire risks; the design provides a simple and intuitive user interface for users to easily set up and operate the system. At the same time, the system pays attention to privacy protection, ensures the security of users' personal information and monitoring data, and provides a good user experience; using brushless motors, all contactors use solid-state or switch tube components to avoid sparks during operation and improve gas safety. This design effectively reduces the safety hazards caused by electrical faults; an analog acquisition interface is reserved to support the configuration of other acquisition information in the future, such as water immersion, light, etc., to adapt to changing safety needs. BRIEF DESCRIPTION OF THE DRAWINGS
[0031] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0032] Figure 1 This is a schematic diagram of the structure of the intelligent kitchen fire hazard handling system in one embodiment of the present application. DETAILED DESCRIPTION
[0033] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0034] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.
[0035] In an exemplary embodiment, Figure 1 As shown, a kitchen fire hazard intelligent processing system is provided, including: a multi-sensor module and a controller; an intelligent data analysis module and an automatic control module are deployed on the controller; the intelligent data analysis module is connected to the multi-sensor module and the automatic control module respectively; the multi-sensor module is arranged in the kitchen; the multi-sensor module is used to obtain kitchen environmental parameters; the kitchen environmental parameters include smoke, temperature, flame, whether there is a gas leak, whether there is someone and the length of time no one is there; the intelligent data analysis module is used to determine whether there is an abnormal situation according to the kitchen environmental parameters; the automatic control module is connected to the main gas valve; the automatic control module closes the main gas valve when an abnormal situation exists. The kitchen fire hazard intelligent processing system also includes: an alarm; the alarm is connected to the intelligent data analysis module; the alarm is used to send an alarm signal when an abnormal situation exists.
[0036] The multi-sensor module includes: smoke sensor, temperature collector, gas leak sensor and human body induction sensor. The temperature collector includes: infrared temperature sensor and NTC sensor. The human body induction sensor adopts Doppler radar induction technology.
[0037] A variety of sensors are integrated: ① The smoke sensor is used to detect whether smoke is generated in the kitchen to determine the possibility of fire. ② The temperature collector is used to monitor the flame status of the stove to identify whether there is a risk that the gas stove has not been turned off for a long time. ③ The gas leak sensor is used to detect whether there is a gas leak in the kitchen to prevent fires caused by gas. ④ The human body sensing sensor uses Doppler radar sensing technology and is not affected by non-metallic objects. It overcomes the problem that traditional cameras are easily blocked in the kitchen fume environment to detect the activities of people in the kitchen and the length of time they are not occupied.
[0038] The intelligent data analysis module includes: an intelligent data analysis unit and a wireless transmission unit; the intelligent data analysis unit is connected to the multi-sensor module, the automatic control module and the wireless transmission unit respectively; the intelligent data analysis unit is used to determine whether there is an abnormal situation based on the kitchen environment parameters; the wireless transmission unit is connected to the remote terminal; the wireless transmission unit is used to send the kitchen environment parameters to the remote terminal, and send an alarm signal to the remote terminal when an abnormal situation occurs.
[0039] The intelligent data analysis module conducts real-time evaluation of the working status of the gas stove, the flame status of the stove, and the activities of personnel (whether there is anyone in the kitchen and how long no one has been in the kitchen) to determine whether there is a potential fire risk. When the automatic control module detects abnormal conditions such as the gas stove not being turned off or being turned on for a long time, it can automatically take measures to close the main gas valve to prevent fire. The automatic control module sets up an emergency processing module. When the system detects that the gas stove is not turned off and the stove flame is abnormal, it automatically triggers the sound and light alarm system and pushes a notification to the mobile phone of the emergency contact. If it is confirmed that there is no one in the kitchen, the main gas valve is automatically closed. Emergency contacts (such as children of elderly people living alone) can monitor the safety status of the kitchen in real time through the application in the mobile phone (remote terminal), receive warning information and videos, and adjust system settings and remotely operate. The application provides a simple and intuitive user interface to ensure the convenience of users in system settings and operations, and to ensure the security of personal information and monitoring data.
[0040] The kitchen fire hazard intelligent processing system also includes: a brushless motor; the brushless motor is connected to the automatic control module and the main gas valve. The main gas valve is a solid-state switch and a switch tube. The motor adopts a brushless motor, and all contactors adopt solid-state or switch tube components to avoid sparks during the operation process and ensure gas safety. The main gas valve is a safety electronic valve; the state of the main gas valve is controlled by the transmission mechanism of the brushless motor.
[0041] The controller is equipped with multiple analog acquisition interfaces, which are used to connect external acquisition devices. The acquisition devices include water immersion sensors and light sensors. The acquisition units of the system are minimized to simplify the installation complexity, reduce the power supply units, and reduce the difficulty of information transmission. At the same time, analog acquisition interfaces are reserved to support the subsequent addition of other acquisition information, such as water immersion, light, etc., to improve the applicability and flexibility of the system.
[0042] The working principle of the kitchen fire hazard intelligent processing system in this embodiment is as follows:
[0043] 1. System Installation:
[0044] Install smoke sensors, temperature sensors, gas leak sensors and human induction sensors (based on Doppler radar technology) at appropriate locations in the kitchen. Make sure these sensors can cover the gas stove and its surrounding areas to accurately monitor various safety parameters in the kitchen. The sensor installation location should be optimized according to the kitchen layout and equipment location to ensure the best monitoring effect.
[0045] 2. Intelligent data analysis:
[0046] The environmental data collected by the sensor is first transmitted to the intelligent data analysis module via wireless or wired transmission. Before the data enters the analysis process, the system will perform a series of preprocessing on the data, including data cleaning, standardization, and time series feature extraction. The purpose of data cleaning is to filter out incomplete or abnormal data points (such as invalid data caused by sensor failure) to reduce the interference of noise on the model; the standardization step normalizes different types of sensor data (such as temperature, smoke, gas concentration, etc.) to ensure that they are analyzed on the same scale and eliminate the impact of unit differences. Subsequently, the system performs time series feature extraction and extracts characteristic values (such as mean, maximum value, rate of change, etc.) to capture the trend and mutation of the data over time, providing strong support for subsequent risk identification.
[0047] After the data is preprocessed, the intelligent data analysis module uses a machine learning model to monitor and evaluate the usage status of the kitchen in real time. First, the system labels and collects normal kitchen data, and uses a supervised learning model (random forest) to build a baseline model of normal usage patterns, covering parameters such as normal flame status and personnel activities. For abnormal conditions that are difficult to label (such as accidental gas leaks or flame anomalies), the system uses an unsupervised learning method (k-means clustering) to identify abnormal conditions by learning data distribution and the degree of deviation from normal patterns. For example, if the system detects abnormal changes in the flame state for a long time, or the gas stove is still in operation when no one is active, the model will determine that the situation is abnormal. During the real-time analysis process, the usage status of the gas stove, the flame status of the stove, and the activities of personnel are continuously monitored.
[0048] The system can identify abnormal patterns (such as the gas stove not being turned off for a long time, abnormal stove flame, etc.) and generate early warning information and control instructions based on the analysis results.
[0049] 3. Automatic control:
[0050] The system is connected to the main gas valve through an automatic control module. When an abnormal situation is detected (such as the gas stove has not been turned off for a long time or the flame on the stove is abnormal), it automatically sends a closing command to the main gas valve to cut off the gas supply and reduce the risk of fire.
[0051] The control module automatically closes the main gas valve according to the preset strategy when no one is in the kitchen to prevent fire caused by user negligence.
[0052] 4. Remote monitoring and control:
[0053] Develop and deploy mobile applications through which users can view the kitchen safety status in real time and receive early warning information and real-time video from the system.
[0054] Users can adjust system settings through the app, such as adjusting sensor sensitivity, enabling or disabling alarm functions, etc., and perform remote operations.
[0055] 5. Emergency response mechanism:
[0056] The system has built-in sound and light alarm devices, which automatically trigger the alarm when a fire risk is detected to remind users and their families to pay attention to safety. The system pushes notifications to users and emergency contacts through mobile phone applications to ensure that they can respond to fire risks in a timely manner. At the same time, the system can automatically close the main gas valve according to the preset strategy when it is confirmed that no one is in the kitchen to prevent the occurrence of fire.
[0057] The system integrates multiple sensors (including smoke sensors, temperature collectors (infrared temperature and NTC), gas leakage sensors and human body sensing sensors, etc.), combines intelligent control technology and big data platform, and provides a comprehensive kitchen safety solution. The introduction of human body sensing sensors can detect the activities of people in the kitchen and the length of time no one is there in real time. Combined with intelligent data analysis, when the system detects that the gas stove is not turned off and has been turned on for a long time, resulting in abnormal flames on the stove, it can automatically close the main gas valve, effectively preventing the risk of fire caused by forgetting to turn off the gas stove, and comprehensively enhancing the safety of the family.
[0058] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0059] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.
Claims
1. A kitchen fire hazard intelligent processing system, characterized in that: include: Multi-sensor modules and controllers; The controller is equipped with an intelligent data analysis module and an automatic control module; The intelligent data analysis module is connected to the multi-sensor module and the automatic control module respectively; The multi-sensor module is arranged in the kitchen; the multi-sensor module is used to obtain kitchen environment parameters; the kitchen environment parameters include smoke, temperature, flame, whether there is a gas leak, whether there is someone and the length of time no one is there; The intelligent data analysis module is used to determine whether there is an abnormal situation based on the kitchen environment parameters; The automatic control module is connected to the main gas valve; the automatic control module closes the main gas valve when an abnormal situation occurs.
2. The kitchen fire hazard intelligent processing system according to claim 1 is characterized in that: The kitchen fire hazard intelligent processing system also includes: an alarm; The alarm is connected to the intelligent data analysis module; the alarm is used to send out an alarm signal when an abnormal situation occurs.
3. The kitchen fire hazard intelligent processing system according to claim 1 is characterized in that: The intelligent data analysis module includes: Intelligent data analysis unit and wireless transmission unit; The intelligent data analysis unit is connected to the multi-sensor module, the automatic control module and the wireless transmission unit respectively; the intelligent data analysis unit is used to determine whether there is an abnormality according to the kitchen environment parameters; The wireless transmission unit is connected to the remote terminal; the wireless transmission unit is used to send the kitchen environment parameters to the remote terminal and send an alarm signal to the remote terminal when an abnormal situation occurs.
4. The kitchen fire hazard intelligent processing system according to claim 1 is characterized in that: The multi-sensor module includes: a smoke sensor, a temperature collector, a gas leakage sensor and a human body sensing sensor.
5. The kitchen fire hazard intelligent processing system according to claim 4 is characterized in that: The temperature collector includes: an infrared temperature sensor and an NTC sensor.
6. The kitchen fire hazard intelligent processing system according to claim 4 is characterized in that: The human body sensing adopts Doppler radar sensing technology.
7. The kitchen fire hazard intelligent processing system according to claim 1 is characterized in that: The kitchen fire hazard intelligent processing system also includes: a brushless motor; The brushless motor is connected to the automatic control module and the main gas valve respectively.
8. The kitchen fire hazard intelligent processing system according to claim 1 is characterized in that: The main gas valve is a safety electronic valve; the state of the main gas valve is controlled by a transmission mechanism of a brushless motor.
9. The kitchen fire hazard intelligent processing system according to claim 1 is characterized in that: The controller is provided with a plurality of analog acquisition quantity interfaces; The analog acquisition quantity interface is used for connecting to an external acquisition device.
10. The kitchen fire hazard intelligent processing system according to claim 9, characterized in that: The acquisition device includes a water immersion sensor and a light sensor.