Self-learning voice emergency call alarm device based on artificial intelligence

Abstract

The invention discloses a self-learning voice emergency call alarm device based on artificial intelligence, and the device comprises an indoor environment information collection module, an indoor anti-theft information collection module, a self-learning module, an alarm grading module, a controller, a voice alarm module, a GPS positioning module, and a database. The indoor environment information acquisition module and the indoor anti-theft information acquisition module are respectively connected with the self-learning module, the self-learning module is respectively connected with the database and the alarm grading module, the alarm grading module is connected with the controller, the controller is connected with the voice alarm module, and the voice alarm module is connected with the GPS positioning module. According to the invention, alarms of different degrees are given according to conditions of different levels, the alarm intelligence is improved, and the monitoring efficiency is improved through bidirectional monitoring of the indoor environment and indoor theft prevention.

Description

Technical Field

[0001] The invention relates to the technical field of voice emergency call alarm devices, and in particular to a self-learning voice emergency call alarm device based on artificial intelligence. Background Art

[0002] As the name implies, artificial intelligence self-learning systems are intelligent systems with self-learning capabilities. These systems rely on advanced technologies such as machine learning and deep learning, and use data as a driving force to extract and identify patterns, thereby optimizing their own decision-making processes. Its basic process includes data collection, data preprocessing, feature extraction, and model training. In this process, the system analyzes a large amount of historical data, identifies key features that can be used for prediction and decision-making, and ultimately generates an efficient intelligent model.

[0003] When the user is not at home, existing indoor monitoring mainly relies on installing cameras and security monitors, which consumes a lot of energy and is costly. Human negligence is inevitable. If someone breaks into the house to steal or the indoor flammable gas concentration is too high, it is difficult to detect it in time, and real-time notification and alarm cannot be achieved, so the safety factor is not high.

[0004] Therefore, in order to solve the above problems, a self-learning voice emergency call alarm device based on artificial intelligence is proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a self-learning voice emergency call alarm device based on artificial intelligence, comprising an indoor environment information collection module, an indoor anti-theft information collection module, a self-learning module, an alarm classification module, a controller, a voice alarm module, a GPS positioning module and a database, wherein the indoor environment information collection module and the indoor anti-theft information collection module are respectively connected to the self-learning module, the self-learning module is respectively connected to the database and the alarm classification module, the alarm classification module is connected to the controller, the controller is connected to the voice alarm module, and the voice alarm module is connected to the GPS positioning module.

[0006] Preferably, the indoor environment information acquisition module includes a smoke sensor, a temperature sensor and a combustible gas sensor.

[0007] Preferably, the indoor anti-theft information collection module includes a video monitoring unit, a door lock abnormality monitoring unit, and a feature recognition unit.

[0008] Preferably, the door lock abnormality monitoring unit is connected to the door lock, and can set a monitoring time to monitor abnormal door lock opening behavior within the monitoring time.

[0009] Preferably, the feature recognition unit includes two parts: facial feature recognition and behavioral feature recognition.

[0010] Preferably, the self-learning module can process the information collected by the indoor environment information collection module and the indoor anti-theft information collection module, and classify the alarms in combination with the information in the database, specifically:

[0011] Level 1 alarm unit: The indoor environment information collection module collects smoke concentration, ambient temperature, and combustible gas concentration that just exceeds the database standard threshold; the door lock abnormality monitoring unit of the indoor anti-theft information collection module has abnormal unlocking within the monitoring time, but the video monitoring unit does not monitor anyone entering the room. The above two situations are level 1 alarms;

[0012] Secondary alarm unit: The indoor environment information collection module collects smoke concentration, ambient temperature, and combustible gas concentration that exceeds the database standard threshold but does not reach the concentration extreme value; the door lock abnormality monitoring unit of the indoor anti-theft information collection module has abnormal unlocking within the monitoring time, and the video monitoring unit monitors someone entering the room, but the feature recognition unit recognizes that the face has appeared more than 5 times in a month. The above two situations are secondary alarms;

[0013] Level 3 alarm unit: The indoor environment information collection module detects that the smoke concentration, ambient temperature, and combustible gas concentration have reached the extreme concentration values; the door lock abnormality monitoring unit of the indoor anti-theft information collection module has abnormal unlocking within the monitoring time, and the feature recognition unit recognizes that the face has appeared less than 5 times in a month and has exhibited abnormal behavior. The above two situations are level 3 alarms.

[0014] Preferably, the voice alarm module includes a voice alarm unit, a text message sending unit, a user phone dialing unit and an alarm phone dialing unit.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention collects indoor environmental information and indoor anti-theft information respectively, and performs alarm classification on the collected information through a self-learning module. According to the alarm classification results, the controller controls the voice alarm module to perform graded alarms, and performs alarms of different degrees according to different levels of situations, thereby improving the intelligence of the alarm, and improving the monitoring efficiency by performing two-way monitoring of the indoor environment and indoor anti-theft. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a structural schematic diagram of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] As attached Figure 1 As shown, the present invention provides a self-learning voice emergency call alarm device based on artificial intelligence, including an indoor environment information collection module, an indoor anti-theft information collection module, a self-learning module, an alarm classification module, a controller, a voice alarm module, a GPS positioning module and a database, wherein the indoor environment information collection module and the indoor anti-theft information collection module are respectively connected to the self-learning module, the indoor environment information collection module includes a smoke sensor, a temperature sensor and a combustible gas sensor, the indoor anti-theft information collection module includes a video monitoring unit, a door lock abnormality monitoring unit, and a feature recognition unit, the door lock abnormality monitoring unit is connected to the door lock, can set the monitoring time, and monitor the abnormal opening of the door lock within the monitoring time, and the feature recognition unit includes two parts: face feature recognition and behavior feature recognition;

[0019] The self-learning module is connected to the database and the alarm classification module respectively, and the alarm classification module is connected to the controller. The self-learning module can process the information collected by the indoor environment information collection module and the indoor anti-theft information collection module, and perform alarm classification in combination with the information in the database, specifically:

[0020] Level 1 alarm unit: The indoor environment information collection module collects smoke concentration, ambient temperature, and combustible gas concentration that just exceeds the database standard threshold; the door lock abnormality monitoring unit of the indoor anti-theft information collection module has abnormal unlocking within the monitoring time, but the video monitoring unit does not monitor anyone entering the room. The above two situations are level 1 alarms;

[0021] Secondary alarm unit: The indoor environment information collection module collects smoke concentration, ambient temperature, and combustible gas concentration that exceeds the database standard threshold but does not reach the concentration extreme value; the door lock abnormality monitoring unit of the indoor anti-theft information collection module has abnormal unlocking within the monitoring time, and the video monitoring unit monitors someone entering the room, but the feature recognition unit recognizes that the face has appeared more than 5 times in a month. The above two situations are secondary alarms;

[0022] Level 3 alarm unit: The indoor environment information collection module collects smoke concentration, ambient temperature, and combustible gas concentration that have reached the extreme concentration value; the door lock abnormality monitoring unit of the indoor anti-theft information collection module has abnormal unlocking within the monitoring time; the feature recognition unit recognizes that the face has appeared less than 5 times in a month and has abnormal behavior. The above two situations are level 3 alarms;

[0023] The controller is connected to the voice alarm module, which includes a voice alarm unit, a text message sending unit, a user phone dialing unit and an alarm phone dialing unit, wherein the first-level alarm unit only performs voice alarm; the second-level alarm unit performs alarm text message sending and user phone dialing; the third-level alarm unit performs alarm text message sending, user phone dialing and alarm phone dialing;

[0024] The voice alarm module is connected to the GPS positioning module.

[0025] Embodiment 1:

[0026] The indoor environment information collection module collects smoke concentration, ambient temperature, and combustible gas concentration that just exceeds the database standard threshold; the door lock abnormality monitoring unit of the indoor anti-theft information collection module has abnormal unlocking within the monitoring time, but the video monitoring unit does not monitor anyone entering the room;

[0027] The smoke concentration, ambient temperature, and combustible gas concentration information are collected through the indoor environment information collection module, and the indoor anti-theft information collection module collects indoor video surveillance, door lock abnormalities, and character features. The information is transmitted to the self-learning module, and the self-learning module processes the information collected by the indoor environment information collection module and the indoor anti-theft information collection module, and divides the indoor alarm situation into first-level alarm situations in combination with the information in the database, and transmits the first-level alarm situation to the alarm classification module, and the controller controls the voice alarm module to issue a voice alarm.

[0028] Embodiment 2:

[0029] The indoor environment information collection module collects smoke concentration, ambient temperature, and combustible gas concentration that exceeds the database standard threshold but does not reach the concentration extreme value; the door lock abnormality monitoring unit of the indoor anti-theft information collection module has abnormal unlocking within the monitoring time, and the video monitoring unit monitors that someone enters the room, but the feature recognition unit recognizes that the face has appeared more than 5 times in a month;

[0030] The smoke concentration, ambient temperature, and combustible gas concentration information are collected through the indoor environment information collection module, and the indoor anti-theft information collection module collects indoor video surveillance, door lock abnormalities, and character features. The information is transmitted to the self-learning module, which processes the information collected by the indoor environment information collection module and the indoor anti-theft information collection module, and divides the indoor alarm situation into two levels of alarm situation based on the information in the database. The two-level alarm situation is transmitted to the alarm classification module, and the controller controls the voice alarm module to send alarm text messages and call the user.

[0031] Embodiment 3:

[0032] The indoor environment information collection module collects smoke concentration, ambient temperature, and combustible gas concentration that have reached the extreme concentration value; the door lock abnormality monitoring unit of the indoor anti-theft information collection module has abnormal unlocking within the monitoring time, and the feature recognition unit recognizes that the face has appeared less than 5 times in a month and has abnormal behavior;

[0033] The smoke concentration, ambient temperature, and combustible gas concentration information are collected through the indoor environment information collection module, and the indoor anti-theft information collection module collects indoor video surveillance, door lock abnormalities, and character features. The information is transmitted to the self-learning module, which processes the information collected by the indoor environment information collection module and the indoor anti-theft information collection module, and divides the indoor alarm conditions into three levels of alarm conditions based on the information in the database. The three levels of alarm conditions are transmitted to the alarm classification module, which is located by the GPS positioning module, and the controller controls the voice alarm module to send alarm text messages and dial the user's phone and the alarm phone dialing unit.

[0034] Utilizing the technical solution described in the present invention, or those skilled in the art designing a similar technical solution inspired by the technical solution of the present invention to achieve the above-mentioned technical effects, all fall within the protection scope of the present invention.

Claims

1. A self-learning voice emergency call alarm device based on artificial intelligence, characterized in that: It includes an indoor environment information collection module, an indoor anti-theft information collection module, a self-learning module, an alarm classification module, a controller, a voice alarm module, a GPS positioning module and a database. The indoor environment information collection module and the indoor anti-theft information collection module are respectively connected to the self-learning module, the self-learning module is respectively connected to the database and the alarm classification module, the alarm classification module is connected to the controller, the controller is connected to the voice alarm module, and the voice alarm module is connected to the GPS positioning module.

2. The self-learning voice emergency call alarm device based on artificial intelligence according to claim 1 is characterized in that: The indoor environment information acquisition module includes a smoke sensor, a temperature sensor and a combustible gas sensor.

3. The self-learning voice emergency call alarm device based on artificial intelligence according to claim 1 is characterized in that: The indoor anti-theft information collection module includes a video monitoring unit, a door lock abnormality monitoring unit, and a feature recognition unit.

4. The self-learning voice emergency call alarm device based on artificial intelligence according to claim 3 is characterized in that: The door lock abnormality monitoring unit is connected to the door lock, and can set a monitoring time to monitor abnormal door lock opening behavior within the monitoring time.

5. The self-learning voice emergency call alarm device based on artificial intelligence according to claim 3 is characterized in that: The feature recognition unit includes two parts: face feature recognition and behavior feature recognition.

6. The self-learning voice emergency call alarm device based on artificial intelligence according to claim 1, characterized in that: The self-learning module can process the information collected by the indoor environment information collection module and the indoor anti-theft information collection module, and classify the alarms in combination with the information in the database.

7. The self-learning voice emergency call alarm device based on artificial intelligence according to claim 1 is characterized in that: The voice alarm module includes a voice alarm unit, a short message sending unit, a user phone dialing unit and an alarm phone dialing unit.

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