Mobile terminal alarm device and method based on artificial intelligence

Abstract

The invention relates to the technical field of alarm devices, in particular to a mobile terminal alarm device and method based on artificial intelligence, and the method comprises the following steps: 1, initializing and configuring a system; step 2, real-time monitoring and data analysis; step 3, alarm triggering and notification; step 4, emergency response and intervention; 5, alarm recording and feedback are carried out; and step 6, optimizing and upgrading the system. According to the mobile terminal alarm device and method based on artificial intelligence, alarm information can be generated immediately, a video call or a voice call with an emergency contact can be started, so that the field condition can be known in real time, feedback suggestions can be collected, new technologies and functions are introduced, the intelligent level of the system is continuously improved, and the user experience is improved. The problems that mobile terminal alarm equipment in the prior art cannot monitor the surrounding environment in real time, intelligently analyze and quickly respond to the surrounding environment during actual use, and safer, more convenient and more efficient alarm service is provided for users are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of alarm devices, and in particular to a mobile terminal alarm device and method based on artificial intelligence. Background Art

[0002] Mobile terminal alarm is a system that combines mobile communication technology and security alarm functions. It aims to provide fast and convenient alarm services through mobile devices. Mobile terminal alarm refers to the use of smart phones, PDAs (personal digital assistants), wearable devices, and mobile terminals to achieve rapid alarm and help functions in emergency situations through built-in alarm software or applications. The system usually integrates multiple functions such as GPS positioning, voice communication, and text message sending. When the user encounters danger or emergency, the help signal can be quickly sent to the preset emergency contact, alarm center or security service agency to obtain rescue in time. The system usually integrates multiple functions such as GPS positioning, voice communication, and text message sending. When the user encounters danger or emergency, the help signal can be quickly sent to the preset emergency contact, alarm center or security service agency to obtain rescue in time. The mobile terminal alarm system relies on smart phone portable devices. Users can carry it anytime and anywhere, which is convenient for use in emergency situations. Using the mobile communication network, the alarm signal can be transmitted in real time to ensure that rescue personnel can respond quickly. Through the GPS positioning function, it can accurately provide the location information of the alarm person and provide accurate navigation for rescue personnel.

[0003] However, the mobile terminal alarm device in the prior art cannot monitor the surrounding environment in real time, perform intelligent analysis and respond quickly during actual use, and provide users with safer, more convenient and efficient alarm services. To address this problem, an artificial intelligence-based mobile terminal alarm device and method are provided. Summary of the invention

[0004] The purpose of the present invention is to provide a mobile terminal alarm device and method based on artificial intelligence to solve the problems raised in the above background technology. To achieve the above purpose, the present invention provides the following technical solutions: a mobile terminal alarm device and method based on artificial intelligence, comprising the following steps:

[0005] Step 1: System initialization and configuration;

[0006] Step 2: Real-time monitoring and data analysis;

[0007] Step 3: Alarm triggering and notification;

[0008] Step 4, emergency response and intervention;

[0009] Step 5: Alarm record and feedback;

[0010] Step six: system optimization and upgrade.

[0011] Preferably, the process steps of system initialization and configuration also include:

[0012] Step 1: Download and install the mobile alarm application, which has built-in AI algorithms and necessary sensor interfaces;

[0013] Step 2: Register and log in, set personal information and emergency contact information;

[0014] Step 3: Configure alarm rules according to your needs, including sound recognition keywords, image recognition patterns, and location trigger conditions. The AI ​​algorithm will learn and optimize based on these rules.

[0015] Preferably, the sensor interface includes a microphone, a camera, and a position sensor.

[0016] Preferably, the detection and data analysis process steps also include:

[0017] Step 1: The mobile terminal continuously monitors the surrounding environment, captures sound through a microphone, captures images through a camera, and records location information through a location sensor;

[0018] Step 2: The AI ​​algorithm analyzes the collected data in real time. For sound data, it uses voice recognition technology to identify keywords. For image data, it uses image recognition technology to detect abnormal behaviors or objects. For location data, it determines whether the user has entered a preset danger zone.

[0019] Step three: The AI ​​algorithm evaluates the analysis results according to the preset alarm rules to determine whether an alarm needs to be triggered. If an abnormal situation is detected, it proceeds to the next step.

[0020] Preferably, the process of alarm triggering and notification includes:

[0021] Step 1: The AI ​​algorithm confirms that an alarm needs to be triggered, and the system immediately generates an alarm message;

[0022] Step 2: Send the alarm information to the cloud server through an encrypted channel, and send text messages, phone calls or in-app notifications to the user's preset emergency contacts at the same time;

[0023] Step three: If the system has a two-way communication function, you can also start a video call or voice call with the emergency contact to understand the situation on the scene in real time.

[0024] Preferably, the alarm information includes the abnormality type, occurrence time, and location.

[0025] Preferably, the emergency response and intervention process includes:

[0026] Step 1: After receiving the alarm notification, the emergency contact takes corresponding measures according to the alarm information, such as contacting the police and going to the scene;

[0027] Step 2: If the system has an automatic intervention function, it can automatically execute preset intervention measures after confirming the alarm situation, such as playing an alarm, sending warning messages to surrounding devices, and starting camera recording.

[0028] Preferably, the process of alarm recording and feedback includes:

[0029] Step 1: The system records detailed information of each alarm, including triggering time, location, abnormality type, and processing results, and saves it in the cloud server or local database;

[0030] Step 2: You can view the alarm records in the app to understand the historical alarm situations and handling situations;

[0031] Step three: The system collects feedback, including evaluations on alarm accuracy, timeliness, and user experience, for subsequent system optimization and improvement.

[0032] Preferably, the process of system optimization and upgrading includes:

[0033] Step 1: Based on feedback and data analysis results, the system is regularly optimized and upgraded to improve the accuracy and efficiency of the AI ​​algorithm;

[0034] Step 2: Introduce new technologies and functions, such as more advanced speech recognition algorithms, image recognition technology, and deep learning models, to continuously improve the intelligence level of the system;

[0035] Step three: Adjust alarm rules and configuration options based on market demand and user feedback to provide more personalized and customized services.

[0036] The mobile terminal alarm device based on artificial intelligence includes multiple sensors and uses the methods of claims 1-9 to realize alarm.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] 1. Through system initialization and configuration, real-time monitoring and data analysis, alarm triggering and notification, emergency response and intervention, alarm recording and feedback, and system optimization and upgrading, it is possible to generate alarm information immediately, initiate video calls or voice calls with emergency contacts to understand the situation on the scene in real time, collect feedback, introduce new technologies and functions, and continuously improve the intelligence level of the system, solving the problem that the mobile terminal alarm equipment of the existing technology cannot monitor the surrounding environment in real time, intelligently analyze and respond quickly during actual use, and provide users with safer, more convenient and efficient alarm services. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a flowchart of the present invention;

[0040] Figure 2 A flowchart of initialization configuration of the system of the present invention;

[0041] Figure 3 It is a flowchart of the real-time monitoring and data analysis of the present invention;

[0042] Figure 4 It is a flowchart of the alarm triggering and notification of the present invention;

[0043] Figure 5 It is a flowchart of the emergency response and intervention of the present invention. DETAILED DESCRIPTION

[0044] 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 technical personnel in this field without creative work are within the scope of protection of the present invention.

[0045] See also Figures 1 to 5 The present invention provides a technical solution: a mobile terminal alarm device and method based on artificial intelligence, comprising the following steps:

[0046] Step 1: System initialization and configuration;

[0047] Step 2: Real-time monitoring and data analysis;

[0048] Step 3: Alarm triggering and notification;

[0049] Step 4, emergency response and intervention;

[0050] Step 5: Alarm record and feedback;

[0051] Step six: system optimization and upgrade.

[0052] In this embodiment, the process steps of system initialization and configuration also include:

[0053] Step 1: Download and install the mobile alarm application, which has built-in AI algorithms and necessary sensor interfaces;

[0054] Step 2: Register and log in, set personal information and emergency contact information;

[0055] Step 3: Configure alarm rules according to your needs, including sound recognition keywords, image recognition patterns, and location trigger conditions. The AI ​​algorithm will learn and optimize based on these rules.

[0056] In this embodiment, the sensor interface includes a microphone, a camera, and a position sensor.

[0057] In this embodiment, the detection and data analysis process steps also include:

[0058] Step 1: The mobile terminal continuously monitors the surrounding environment, captures sound through the microphone, captures images through the camera, and records location information through the location sensor. The microphone sensor can continuously capture the sound of the surrounding environment. The AI ​​algorithm can analyze these sound data and identify abnormal sounds (such as glass breaking, gunshots) or preset emergency signals to trigger alarms. The camera, as an image sensor, can capture real-time video streams. AI image recognition technology can analyze video content, detect abnormal behavior (such as intruders), environmental changes (such as smoke from fires), or specific objects (such as lost items). Accelerometers and gyroscopes can sense the movement and vibration of the device, which helps to identify abnormal physical activities, such as illegal movement of the device or abnormal vibration, which may indicate some kind of emergency. Although temperature and humidity sensors are not built-in in all alarm applications, temperature and humidity sensors can be used to monitor environmental changes in specific scenarios (such as warehouses and data centers) to prevent fires and flooding disasters. AI algorithms can learn and identify normal and abnormal environmental patterns. Through continuous data collection and analysis, the algorithm can distinguish between daily activities and potential emergencies. When sensor data deviates from the preset normal range or model, AI will mark it as abnormal and trigger further analysis or alarms. AI algorithms need It has the ability to process data in real time so as to respond quickly in emergency situations. The combined use of multiple sensor data can provide more comprehensive and accurate environmental monitoring. For example, the combination of sound sensors and image sensors can more accurately determine whether an intrusion has occurred. Sensor fusion technology reduces false alarm rates and improves the overall performance of the system by integrating information from different sensors. Mobile terminals communicate with remote servers through wireless networks (such as 4G / 5G, Wi-Fi) and upload monitoring data in real time. Users or monitoring centers can remotely access this data, view real-time video streams, receive alarm notifications, and perform remote intervention as needed. When conducting environmental monitoring, privacy protection regulations must be strictly observed to ensure the security and privacy of user data. Encrypted communications and permission control security measures are indispensable to prevent data leakage and illegal access;

[0059] Step 2: The AI ​​algorithm analyzes the collected data in real time. For sound data, voice recognition technology is used to identify keywords. For image data, image recognition technology is used to detect abnormal behavior or objects. For location data, it is used to determine whether the user has entered a preset danger zone. For sound data, the AI ​​algorithm mainly relies on voice recognition technology to identify keywords or specific sound patterns. These keywords or patterns can be preset emergency signals (such as fire alarms, cries for help), abnormal sounds (such as broken glass, gunshots), or specific sounds in daily activities (such as footsteps, conversations). The AI ​​algorithm learns to recognize preset keywords or phrases by training models. When the microphone captures the sound, the algorithm converts it into a digital signal and compares it with the trained model to identify whether it contains any keywords. In addition to keyword recognition, the AI ​​algorithm can also analyze the patterns and characteristics of the sound, such as volume, frequency, and duration, to distinguish different types of sounds. For example, by analyzing the frequency and waveform of the sound, the algorithm can distinguish between screams and normal conversations. The algorithm can recognize The AI ​​algorithm can also detect objects in the video and determine whether they are preset abnormal objects (such as intruders, lost items). This is usually achieved by training deep learning models. The models will learn to recognize the features of different objects and detect these features in new videos. In addition to object detection, AI algorithms can also analyze the behavior of people or animals in the video. For example, by analyzing the movement trajectory, posture and action, the algorithm can determine whether abnormal behavior has occurred (such as running, fighting). The algorithm can also detect environmental changes in the video, such as smoke and flooding caused by fire. This usually relies on image processing and computer vision technology to identify specific features or patterns in the image. Through the GPS module integrated in the mobile device, the AI ​​system can track the user's location in real time. These location data are regularly uploaded to the server and compared with the preset danger zone map. The algorithm will determine whether the user has entered the preset danger zone (such as prohibited areas and high-risk areas) based on the user's location information. If the user is detected to have entered a danger zone, the system will immediately trigger an alarm and notify the relevant emergency contacts or security service agencies.

[0060] Step three: The AI ​​algorithm evaluates the analysis results according to the preset alarm rules to determine whether an alarm needs to be triggered. If an abnormal situation is detected, it proceeds to the next step. According to actual needs and safety standards, a series of preset alarm rules are formulated. These rules may include multiple dimensions such as sound thresholds, image features, and location ranges. The preset alarm rules are configured in the AI ​​algorithm to ensure that the algorithm can evaluate the collected data according to these rules. The AI ​​algorithm processes the sound captured by the microphone in real time, identifies keywords or specific sound patterns, and compares the recognition results with the sound thresholds or keywords in the preset alarm rules. If the recognition results meet the alarm conditions, it proceeds to the next step. Image recognition processing is performed on the video stream captured by the camera to detect abnormal behavior or objects. The detection results are compared with the image features in the preset alarm rules. If abnormal behavior or objects are detected , and the alarm conditions are met, the next step is to obtain the location information of the user or device through the GPS positioning function, and compare the location information with the preset dangerous area map. If the user or device enters the preset dangerous area and meets the alarm conditions, the next step is to be processed. When the AI ​​algorithm detects an abnormal situation and determines that the preset alarm rules are met, an alarm will be triggered immediately. The alarm method may include sound prompts, pop-up window displays, SMS or email notifications. The system records detailed information about the abnormal situation, including the time, location, and type of abnormality, and automatically generates an alarm log for subsequent query and tracking. According to needs, other security systems (such as fire alarm systems, access control systems) can be linked or relevant personnel (such as security personnel, management personnel) can be notified. According to the severity and urgency of the abnormal situation, corresponding follow-up measures are formulated, such as on-site investigation, troubleshooting, and security reinforcement.

[0061] In this embodiment, the process of alarm triggering and notification includes:

[0062] Step 1: The AI ​​algorithm confirms that an alarm needs to be triggered, and the system immediately generates an alarm message. First, it collects basic information related to the alarm event, including the time and location of the event (such as GPS coordinates or specific address), the type of sensors involved (such as sound, image, location), and the initial judgment of the abnormal type (such as intrusion, fire, equipment failure). Based on the analysis results of the AI ​​algorithm, the system will generate a detailed description of the abnormal situation, which may include the recognized keywords, the characteristics of the abnormal image, and the trajectory of the position change, so that the recipient can quickly understand the nature and severity of the alarm event. The system will set the priority for the alarm information according to the preset rules or the judgment results of the AI ​​algorithm, which helps the recipient to sort and process the alarm according to the urgency of the alarm and give priority to responding to high-priority alarms. In order to improve the standardization and readability of the alarm information, the system usually applies preset alarm information templates. These templates contain the standard format of the alarm information and necessary fields, such as title, text, attachments (such as images, videos) , Based on the application template, the system can also be customized according to actual needs. For example, according to the identity or responsibilities of the recipient, the system can generate different versions of alarm information so that the recipient can better understand and handle it. The system will select the target personnel or systems that need to receive the alarm information based on the preset communication list or the judgment result of the AI ​​algorithm. These targets may include security personnel, management personnel, emergency contacts or other related security systems. In order to ensure that the alarm information can be quickly conveyed to the recipient, the system usually uses multiple communication channels for transmission. These channels may include SMS, email, instant messaging, voice calls, and APP push. According to the recipient's preferences and actual conditions, the system will select the most appropriate communication channel for transmission. During the transmission of the alarm information, the system will monitor in real time to ensure that the information can be successfully delivered to the recipient. If the transmission fails or the recipient does not respond, the system will take corresponding remedial measures, such as resending the alarm information or notifying other backup recipients;

[0063] Step 2: Send the alarm information to the cloud server through an encrypted channel, and send text messages, phone calls or in-app notifications to the user's preset emergency contacts at the same time. The client initiates a connection request with the cloud server and negotiates the encryption key through the SSL / TLS handshake process. The encrypted channel is established, and the client will encapsulate the alarm information in the agreed format, including the alarm type, time, location, and specific content key information. The encapsulated data is sent to the cloud server through an encrypted channel to ensure that it is not stolen or tampered with during transmission. After receiving the encrypted alarm information, the cloud server uses the same key to decrypt it and restore the original alarm information. The server processes the alarm information according to preset rules and logic, such as recording logs and triggering subsequent alarm actions;

[0064] Step three: If the system has a two-way communication function, you can also start a video call or voice call with the emergency contact to understand the situation on the scene in real time.

[0065] In this embodiment, the alarm information includes the abnormality type, occurrence time, and location.

[0066] In this embodiment, the emergency response and intervention process includes:

[0067] Step 1: After receiving the alarm notification, the emergency contact takes corresponding measures according to the alarm information, such as contacting the police and going to the scene;

[0068] Step 2: If the system has an automatic intervention function, it can automatically execute preset intervention measures after confirming the alarm situation, such as playing an alarm, sending warning messages to surrounding devices, and starting camera recording.

[0069] In this embodiment, the process of alarm recording and feedback includes:

[0070] Step 1: The system records detailed information of each alarm, including triggering time, location, abnormality type, and processing results, and saves it in the cloud server or local database;

[0071] Step 2: You can view the alarm records in the app to understand the historical alarm situations and handling situations;

[0072] Step three: The system collects feedback, including evaluations on alarm accuracy, timeliness, and user experience, for subsequent system optimization and improvement.

[0073] In this embodiment, the process of system optimization and upgrading includes:

[0074] Step 1: Based on feedback and data analysis results, the system is regularly optimized and upgraded to improve the accuracy and efficiency of the AI ​​algorithm;

[0075] Step 2: Introduce new technologies and functions, such as more advanced speech recognition algorithms, image recognition technology, and deep learning models, to continuously improve the intelligence level of the system;

[0076] Step three: Adjust alarm rules and configuration options based on market demand and user feedback to provide more personalized and customized services.

[0077] The mobile terminal alarm device based on artificial intelligence includes multiple sensors and uses the methods of claims 1-9 to realize alarm.

[0078] The above shows and describes the basic principles, main features and advantages of the present invention. Technical personnel in this industry should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not used to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. Mobile terminal alarm device and method based on artificial intelligence, It is characterized in that The steps include: Step 1: System initialization and configuration; Step 2: Real-time monitoring and data analysis; Step 3: Alarm triggering and notification; Step 4, emergency response and intervention; Step 5: Alarm record and feedback; Step six: system optimization and upgrade.

2. According to the artificial intelligence-based mobile terminal alarm device and method according to claim 1, Features: The process steps of system initialization and configuration also include: Step 1: Download and install the mobile alarm application, which has built-in AI algorithms and necessary sensor interfaces; Step 2: Register and log in, set personal information and emergency contact information; Step 3: Configure alarm rules according to your needs, including sound recognition keywords, image recognition patterns, and location trigger conditions. The AI ​​algorithm will learn and optimize based on these rules.

3. According to the artificial intelligence-based mobile terminal alarm device and method according to claim 2, Features: The sensor interface includes a microphone, a camera, and a position sensor.

4. According to claim 1, the mobile terminal alarm device and method based on artificial intelligence, Features: The detection and data analysis process steps also include: Step 1: The mobile terminal continuously monitors the surrounding environment, captures sound through a microphone, captures images through a camera, and records location information through a location sensor; Step 2: The AI ​​algorithm analyzes the collected data in real time. For sound data, it uses voice recognition technology to identify keywords. For image data, it uses image recognition technology to detect abnormal behaviors or objects. For location data, it determines whether the user has entered a preset danger zone. Step three: The AI ​​algorithm evaluates the analysis results according to the preset alarm rules to determine whether an alarm needs to be triggered. If an abnormal situation is detected, it proceeds to the next step.

5. According to claim 1, the mobile terminal alarm device and method based on artificial intelligence, Features: The process of alarm triggering and notification includes: Step 1: The AI ​​algorithm confirms that an alarm needs to be triggered, and the system immediately generates an alarm message; Step 2: Send the alarm information to the cloud server through an encrypted channel, and send text messages, phone calls or in-app notifications to the user's preset emergency contacts at the same time; Step three: If the system has a two-way communication function, you can also start a video call or voice call with the emergency contact to understand the situation on the scene in real time.

6. According to claim 5, the mobile terminal alarm device and method based on artificial intelligence, Features: The alarm information includes the abnormality type, occurrence time and location.

7. The mobile terminal alarm device and method based on artificial intelligence according to claim 1, Features: The emergency response and intervention process includes: Step 1: After receiving the alarm notification, the emergency contact takes corresponding measures according to the alarm information, such as contacting the police and going to the scene; Step 2: If the system has an automatic intervention function, it can automatically execute preset intervention measures after confirming the alarm situation, such as playing an alarm, sending warning messages to surrounding devices, and starting camera recording.

8. The mobile terminal alarm device and method based on artificial intelligence according to claim 1, Features: The process of alarm recording and feedback includes: Step 1: The system records detailed information of each alarm, including triggering time, location, abnormality type, and processing results, and saves it in the cloud server or local database; Step 2: You can view the alarm records in the app to understand the historical alarm situations and handling situations; Step three: The system collects feedback, including evaluations on alarm accuracy, timeliness, and user experience, for subsequent system optimization and improvement.

9. The mobile terminal alarm device and method based on artificial intelligence according to claim 1, Features: The system optimization and upgrade process includes: Step 1: Based on feedback and data analysis results, the system is regularly optimized and upgraded to improve the accuracy and efficiency of the AI ​​algorithm; Step 2: Introduce new technologies and functions, such as more advanced speech recognition algorithms, image recognition technology, and deep learning models, to continuously improve the intelligence level of the system; Step three: Adjust alarm rules and configuration options based on market demand and user feedback to provide more personalized and customized services.

10. Mobile terminal alarm device based on artificial intelligence, Features: The invention comprises a plurality of sensors and adopts the methods of claims 1 to 9 to realize alarm.

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