Intelligent alarm method and device for doors and windows

Abstract

The invention relates to an intelligent alarm method and device for doors and windows, and belongs to the technical field of smart home, and the method comprises the following steps: 1, a sensing module obtains vibration data, acceleration data and magnetic force change data, and uploads the data to a control module; 2, the control module calculates a comprehensive safety coefficient by using a weighted average according to the vibration data, the acceleration data and the magnetic force change data; 3, the control module judges whether the comprehensive safety coefficient exceeds a safety threshold value or not, and gives an alarm when the judgment result is yes; the system can carry out multi-dimensional environment parameter comprehensive judgment alarm, and has the characteristic of high early warning accuracy.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of smart home, and particularly relates to a smart alarm method and device for doors and windows. BACKGROUND

[0002] With the rapid development of smart home technology, the door and window security system, as an important part of home protection, has gradually upgraded from traditional mechanical locks to intelligent devices with environmental perception capabilities Early intelligent door and window systems rely on single sensor detection, and complex multi-sensor fusion or introduction of machine learning model optimization alarm precision schemes often require complex algorithm support and higher edge computing resources. Therefore, Chinese Patent CN120526549B discloses a low-energy-consumption intelligent door and window security alarm method based on environmental perception, which includes an association computing module, an initial score calculation module, a monitoring alarm module, and a monitoring frequency updating module. The application significantly optimizes system energy efficiency through a double periodic scoring mechanism and a monitoring frequency dynamic adjustment strategy. The initial score generated based on user feature parameters establishes a basic energy consumption baseline, and then combined with the deviation analysis and time correction of short-period environmental monitoring data, a second importance score is generated to accurately quantify the risk value of each scene. This dynamic regulation mode keeps the device in an ultra-low power consumption state during the risk-free period, which can significantly reduce energy consumption compared to traditional fixed frequency, and is particularly suitable for long-term stable operation of battery-powered intelligent window control devices.

[0003] However, in the above-mentioned scheme, the main judgment method for determining whether to issue an alarm is to judge the scene risk and then adjust the data acquisition frequency. Although multi-dimensional environmental data (such as dynamic acceleration, glass breakage soundprint matching degree, and window deformation) are set, it is simply to take the maximum value of the normalized environmental data (i.e., for any alarm scene, the maximum value of the "abnormal score" of the monitoring parameter corresponding to the alarm scene is taken as the representative abnormal score of the current alarm scene), and it does not involve comprehensive judgment of multiple environmental parameters, so the judgment accuracy is not high. Therefore, a smart alarm method and device for doors and windows are needed, which can perform comprehensive judgment of multiple environmental parameters and have high early warning accuracy. SUMMARY

[0004] To solve the above-mentioned problems in the prior art, the application provides a smart alarm method and device for doors and windows, which has high early warning accuracy.

[0005] The purpose of the application can be achieved by the following technical solutions: A smart alarm method for doors and windows, comprising the following steps: Step one: the sensing module acquires vibration data, acceleration data, and magnetic force change data, and uploads them to the control module; Step two: the control module calculates the comprehensive safety coefficient by using weighted average according to the vibration data, acceleration data and magnetic force change data; Step three: the control module judges whether the comprehensive safety coefficient exceeds the safety threshold, and issues an alarm when the judgment result is yes.

[0006] As a preferred technical solution of the present application, the step one further comprises: the sensing module acquires vibration amplitude P, acceleration data A and magnetic force change data M and uploads them to the control module; the step two further comprises: the control module calculates the comprehensive safety coefficient N by using weighted average according to the vibration frequency f and amplitude P, acceleration data A and magnetic flux change data M, and judges whether it exceeds the safety threshold N0, wherein N=k1×P / P0+k2×A / A0+k3×M / M0, P0 is a pre-input amplitude threshold, A0 is a pre-input acceleration threshold, and M0 is a pre-input magnetic flux change threshold.

[0007] As a preferred technical solution of the present application, the step one further comprises: the sensing module acquires weather data and uploads them to the control module, and the control module has pre-input corresponding gears of weather types, the gears being gentle weather, severe weather and extreme weather; the step two further comprises: the control module increases the value of k1 in gentle weather, and the control module decreases the value of k1 in extreme weather.

[0008] As a preferred technical solution of the present application, the step one further comprises: the control module acquires the vibration data change rate in a month period and judges whether the change rate exceeds a second threshold; the step two further comprises: the control module reduces the weight of vibration data in the calculation of the comprehensive safety coefficient.

[0009] As a preferred technical solution of the present application, the step two further comprises: the control module generates an hourly vibration data average value, which is recorded as a vibration reference value, then the control module calculates the change rate b of the vibration reference value with time in a month period, and then adjusts k1 to A1 times of the original value, wherein A1=b / b0, and b0 is a pre-input change rate threshold.

[0010] As a preferred technical solution of the present application, the step one further comprises: the sensing module acquires low-frequency environmental noise decibel Fd and high-frequency environmental noise decibel Fg; the step two further comprises: the control module adjusts N0 to A2 times of the original value, wherein A2=Fd / Fd0×Fg0 / Fg, Fd0 is an environmental noise threshold, and Fg0 is a broken window noise threshold.

[0011] The application discloses an intelligent alarm device for doors and windows, which is suitable for the intelligent alarm method for doors and windows.

[0012] The application has the following beneficial effects: (1) The vibration data, acceleration data and magnetic force change data are detected by the sensing module, and the control module is used to calculate the comprehensive safety coefficient by using the vibration data, acceleration data and magnetic force change data, so that the multi-dimensional environmental parameter comprehensive judgment alarm is completed, and the early warning accuracy is improved. (2) The weather data are acquired by the sensing module, and the control module is used to adjust the vibration data weight according to the current weather grade, so that the false alarm caused by vibration triggered by the weather, a non-safety factor, is reduced, and the early warning accuracy is improved. (3) The low-frequency environmental noise and high-frequency environmental noise are acquired by the sensing module, when the low-frequency noise is high, which represents that the external weather or environmental disturbance is large, the threshold value is increased, and the probability of false alarm caused by vibration is reduced, when the high-frequency noise is high, which represents that there is a probability of window breaking, the threshold value is reduced, so that the system enters the alert state, and the early warning is more easily triggered. BRIEF DESCRIPTION OF DRAWINGS

[0013] In order to facilitate the understanding of those skilled in the art, the application will be further described below with reference to the drawings.

[0014] Figure 1 The application is a schematic diagram of the steps. DETAILED DESCRIPTION

[0015] In order to further illustrate the technical means and effects adopted by the application to achieve the predetermined application purposes, the specific embodiments, structures, features and effects according to the application are described in detail below with reference to the drawings and preferred embodiments.

[0016] Please refer to Figure 1 An intelligent alarm method for doors and windows comprises the following steps: Step one: the sensing module acquires vibration data, acceleration data and magnetic force change data, and uploads the data to the control module; Step two: the control module calculates the comprehensive safety coefficient by using the weighted average of the vibration data, acceleration data and magnetic force change data; Step three: the control module judges whether the comprehensive safety coefficient exceeds the safety threshold value, and sends an alarm when the result is yes.

[0017] Specifically, step one also includes: the sensing module acquires vibration amplitude P, acceleration data A and magnetic force change data M and uploads them to the control module; step two also includes: the control module calculates the comprehensive safety factor N using weighted average according to vibration amplitude P, acceleration data A and magnetic flux change data M, and judges whether it exceeds the safety threshold N0, wherein N=k1×P / P0+k2×A / A0+k3×M / M0, P0 is a pre-input amplitude threshold, A0 is a pre-input acceleration threshold, and M0 is a pre-input magnetic flux change threshold; The magnetic force change data refers to the magnetic flux change rate monitored by the sensor within a unit time; When the vibration amplitude is large, there is a probability that the intruder touches the window, or that foreign objects enter the window, at this time, the term k1×P / P0 representing vibration in N is large, which drives N to rise and exceed the safety threshold, triggering the alarm; When the acceleration data is large, there is a probability that the window is subjected to a violent impact or is rapidly opened and closed, which poses a safety risk, at this time, the term k2×A / A0 representing acceleration in N will significantly increase, thereby increasing the comprehensive safety factor N and triggering the alarm; When the magnetic flux change rate is large, it represents that the angle of the metal window frame changes rapidly, thereby causing the magnetic flux data to change, which poses a safety risk, at this time, the term k2×M / M0 representing magnetic flux in N increases, thereby increasing the comprehensive safety factor N and triggering the alarm; By setting the sensing module to detect vibration data, acceleration data and magnetic force change data, and making the control module use vibration data, acceleration data and magnetic force change data to calculate the comprehensive safety factor, multi-dimensional environmental parameter comprehensive judgment and alarm are completed, and the accuracy of early warning is improved; In the above process, there are other influencing factors that may interfere with the early warning, for example, sudden changes in weather conditions may cause slight deformation of the door and window structure, which is not caused by human intrusion, but may be misjudged as abnormal by the sensor, one example is that in extreme weather, strong winds may cause the window to vibrate slightly, thereby causing fluctuations in vibration data; Step one also includes: the sensing module acquires weather data and uploads it to the control module, and the control module pre-sets corresponding gears for weather types, the gears being gentle weather, severe weather and extreme weather, and step two also includes: the control module increases the value of k1 in gentle weather, and the control module reduces the value of k1 in extreme weather; For example, the control module is pre-inputted that sunny, cloudy and overcast are gentle weather, light rain, light snow and 5-8 wind force are severe weather, 9 and above wind force, typhoon, heavy rain and heavy snow are extreme weather, the control module automatically matches the weather gear after obtaining the weather forecast of the day, and rounds up to the weather gear with more serious weather when the weather of the day meets two gears at the same time, for example, the weather of a day is sunny but 6 wind force, which meets gentle weather and severe weather at the same time, then the control module takes severe weather as the gear; The weather data is obtained through the sensing module, and the control module adjusts the vibration data weight according to the current weather gear, which reduces the false alarm of vibration triggering caused by weather, a non-safety factor, and improves the warning accuracy.

[0018] After long-term use, the door and window may be slightly sunken or shaken due to deformation and loose hinge, generating a continuous vibration signal, when the vibration presents a slow but stable upward trend in a long term, it represents that the vibration sensor may be disturbed by structural loosening, the data reliability decreases, and the threshold needs to be relatively reduced, therefore, step one also includes: the control module obtains the vibration data change rate in a month and judges whether the change rate exceeds the second threshold; step two also includes: the control module reduces the weight of vibration data in the calculation of the comprehensive safety coefficient; Specifically, the control module generates the vibration data average value of each hour in step two, which is recorded as a vibration reference value, then the control module calculates the change rate b of the vibration reference value with time in a month, then adjusts k1 to A1 times of the original, where A1=b / b0, and b0 is a pre-inputted change rate threshold; For example, the control module calculates the average value of all vibration amplitude data received in the past one hour at each whole point, to obtain the vibration data average value of the past one hour, then the control module arranges the vibration data average value of each hour in the past one month in time sequence, and calculates the change rate, because there are 24 vibration data average values of each hour per day, and 30 days per month, therefore, there are 720 data in total when calculating the long-term change rate each time; By making the control module take the long-term change rate of vibration data, when the door and window can generate a continuous vibration signal due to deformation, it represents that the vibration sensor is disturbed by structural loosening, the data reliability decreases, and the threshold is relatively reduced, which reduces the interference of external factors on the warning; The threshold value needs to be adjusted according to different situations, for example, if there is strong wind, thunder or other interference source in the external environment, the safety threshold value needs to be increased to avoid false alarm caused by environmental noise; on the contrary, if there is glass breakage or human damage, the safety threshold value needs to be reduced to make the system enter a high alert state, so as to respond to potential threats faster, for this, step one further comprises: the sensor module acquires low-frequency environmental noise decibel Fd and high-frequency environmental noise decibel Fg, and step two further comprises: the control module adjusts N0 to A2 times of the original, wherein A2=Fd / Fd0xFg0 / Fg, Fd0 is an environmental noise threshold value, and Fg0 is a broken window noise threshold value. When the low-frequency environmental noise significantly increases, it may indicate that there is strong wind, thunder or other interference source in the external environment, at this time, the value of Fd / Fd0 is higher, A2 is increased, and the threshold value is increased; When the high-frequency environmental noise abnormally increases, it may indicate that there is glass breakage or human damage, and the safety threshold value needs to be reduced, at this time, the value of Fg0 / Fg is lower, A2 is reduced, and the threshold value is reduced; By making the sensor module acquire low-frequency environmental noise and high-frequency environmental noise, when the low-frequency noise is high, it represents that the external weather or environmental disturbance is large, the threshold value is increased, and the probability of false alarm caused by vibration is reduced; when the high-frequency noise is high, it represents that there is a probability of broken window, the threshold value is reduced, the system enters an alert state, and the pre-alarm is triggered more easily; The application further provides an intelligent alarm device for doors and windows, which is suitable for the intelligent alarm method for doors and windows and comprises a sensor module, an alarm module and a control module.

[0019] The above is only a preferred embodiment of the application, and does not limit the application in any form. Although the application has been disclosed as above, it is not intended to limit the application. Any person skilled in the art can make slight changes or modifications to the above disclosed technical content to obtain equivalent embodiments with equivalent changes, without departing from the technical solution of the application. Any modification, change, equivalent change and modification of the above embodiments, which does not depart from the technical solution of the application, are still within the scope of the technical solution of the application.

Claims

1. A smart alarm method for doors and windows, characterized in that: Includes the following steps: Step 1: The sensing module acquires vibration data, acceleration data, and magnetic force change data, and uploads them to the control module; Step 2: The control module calculates the comprehensive safety factor based on the vibration data, acceleration data, and magnetic force change data using a weighted average. Step 3: The control module determines whether the overall safety factor exceeds the safety threshold and issues an alarm if the result is yes.

2. The intelligent alarm method for doors and windows according to claim 1, characterized in that: Step one further includes: the sensing module acquires vibration amplitude P, acceleration data A, and magnetic flux change data M and uploads them to the control module; Step two further includes: the control module calculates a comprehensive safety factor N based on the vibration amplitude P, acceleration data A, and magnetic flux change data M using a weighted average, and determines whether the safety threshold N0 is exceeded, where N = k1 × P / P0 + k2 × A / A0 + k3 × M / M0, P0 is the pre-input amplitude threshold, A0 is the pre-input acceleration threshold, and M0 is the pre-input magnetic flux change threshold.

3. The intelligent alarm method for doors and windows according to claim 2, characterized in that: Step one further includes: the sensing module acquires weather data and uploads it to the control module. The control module has pre-input corresponding gears for different weather types, namely, calm weather, severe weather, and extreme weather. Step two further includes: the control module increases the value of k1 during calm weather and decreases the value of k1 during extreme weather.

4. The intelligent alarm method for doors and windows according to claim 3, characterized in that: Step one further includes: the control module acquiring the vibration data change rate on a monthly basis and determining whether the change rate exceeds a second threshold; Step two further includes: the control module reducing the weight of the vibration data in the calculation of the comprehensive safety factor.

5. The intelligent alarm method for doors and windows according to claim 4, characterized in that: Step two further includes: the control module generates an average vibration data value per hour, which is recorded as the vibration reference value. Then, the control module calculates the rate of change of the vibration reference value over time, b, on a monthly basis. Subsequently, k1 is adjusted to A1 times the original value, where A1 = b / b0, and b0 is a pre-inputted rate of change threshold.

6. The intelligent alarm method for doors and windows according to claim 5, characterized in that: Step one further includes: the sensing module acquiring the low-frequency ambient noise decibel Fd and the high-frequency ambient noise decibel Fg. Step two further includes: the control module adjusting N0 to A2 times the original value, where A2 = Fd / Fd0 × Fg0 / Fg, Fd0 is the ambient noise threshold, and Fg0 is the broken window noise threshold.

7. The intelligent alarm device for doors and windows according to claim 1, characterized in that: The intelligent alarm method for doors and windows according to any one of claims 1 to 6 includes a sensing module, an alarm module, and a control module. The sensing module and the alarm module are electrically connected to the control module, and the alarm module is communicatively connected to an alarm terminal. The alarm module issues an alarm through the alarm terminal.

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