CN119155378A - Mobile terminal alarm device and method based on artificial intelligence - Google Patents
Mobile terminal alarm device and method based on artificial intelligence Download PDFInfo
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- CN119155378A CN119155378A CN202411223005.0A CN202411223005A CN119155378A CN 119155378 A CN119155378 A CN 119155378A CN 202411223005 A CN202411223005 A CN 202411223005A CN 119155378 A CN119155378 A CN 119155378A
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- 238000012544 monitoring process Methods 0.000 claims abstract description 12
- 230000004044 response Effects 0.000 claims abstract description 10
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- 230000002159 abnormal effect Effects 0.000 claims description 20
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
- H04M1/72418—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality for supporting emergency services
- H04M1/72421—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality for supporting emergency services with automatic activation of emergency service functions, e.g. upon sensing an alarm
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/08—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using communication transmission lines
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
- H04M1/72406—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality by software upgrading or downloading
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- Emergency Management (AREA)
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Alarm Systems (AREA)
Abstract
The invention relates to the technical field of alarm devices, in particular to mobile terminal alarm equipment and a method based on artificial intelligence, comprising the following steps of firstly, initializing and configuring a system; the method comprises the following steps of monitoring in real time and analyzing data, triggering and notifying an alarm, responding in emergency and intervening in step four, recording and feeding back an alarm, and optimizing and upgrading a system in step six. The mobile terminal alarm device and the method based on artificial intelligence can realize the immediate generation of alarm information, can also start video call or voice call with emergency contacts so as to know the site situation in real time, can collect feedback comments and introduce new technology and functions to continuously improve the intelligent level of the system, and solve the problems that the mobile terminal alarm device in the prior art cannot realize real-time monitoring, intelligent analysis and quick response to the surrounding environment when in actual use, and provides safer, more convenient and more efficient alarm service for users.
Description
Technical Field
The invention relates to the technical field of alarm devices, in particular to mobile terminal alarm equipment and a mobile terminal alarm method based on artificial intelligence.
Background
The mobile terminal alarm is a system combining mobile communication technology and safety alarm function, and aims to realize quick and convenient alarm service through mobile equipment, mobile terminal alarm means that a smart phone, a PDA (personal digital assistant) and a wearable equipment mobile terminal are utilized, and quick alarm and help seeking function under emergency condition is realized through built-in alarm software or application, the system is generally integrated with multiple functions of GPS positioning, voice communication and short message sending, can quickly send help seeking signals to preset emergency contacts, alarm centers or safety service mechanisms when a user encounters danger or emergency condition, so as to obtain the rescue in time the system is usually integrated with GPS positioning, voice communication and short message sending functions, can rapidly send help signals to preset emergency contacts, alarm centers or safety service mechanisms when users encounter danger or emergency, so as to obtain rescue in time, the mobile terminal alarm system depends on smart mobile phone portable equipment, users can carry the system at any time and any place, the system is convenient to use in emergency, the alarm signals can be transmitted in real time by utilizing a mobile communication network, the rescue personnel can be ensured to respond rapidly, and the position information of the alarm personnel can be accurately provided by the GPS positioning function, so that accurate navigation is provided for the rescue personnel.
However, the mobile terminal alarm device in the prior art cannot monitor the surrounding environment in real time, analyze intelligently and respond quickly when in actual use, so that safer, more convenient and efficient alarm service is provided for users, and the mobile terminal alarm device and method based on artificial intelligence are provided for solving the problem.
Disclosure of Invention
The invention aims to provide mobile terminal alarm equipment and method based on artificial intelligence so as to solve the problems in the background technology. In order to achieve the purpose, the invention provides the following technical scheme that the mobile terminal alarm equipment and the method based on artificial intelligence comprise the following steps:
step one, initializing and configuring a system;
Step two, monitoring and analyzing data in real time;
step three, alarm triggering and notification;
step four, emergency response and intervention;
Step five, alarming, recording and feeding back;
And step six, optimizing and upgrading the system.
Preferably, the system initializing and configuring process further includes:
step one, downloading and installing a mobile alarm application, and applying a built-in AI algorithm and a necessary sensor interface;
registering and logging in, and setting personal data and emergency contact information;
And thirdly, configuring alarm rules according to requirements, wherein the alarm rules comprise voice recognition keywords, image recognition modes and position triggering conditions. The AI algorithm will learn and optimize based on these rules.
Preferably, the sensor interface comprises a microphone, a camera and a position sensor.
Preferably, the detecting and data analyzing steps further include:
The method comprises the steps that firstly, a mobile terminal continuously monitors the surrounding environment, sound is captured through a microphone, an image is captured through a camera, and position information is recorded through a position sensor;
Secondly, the AI algorithm analyzes the collected data in real time, a voice recognition technology is used for recognizing keywords for voice data, an image recognition technology is used for detecting abnormal behaviors or objects for image data, and whether a user enters a preset dangerous area or not is judged for position data;
And thirdly, the AI algorithm evaluates the analysis result according to a preset alarm rule, judges whether an alarm needs to be triggered, and if an abnormal condition is detected, enters the next step.
Preferably, the alarm triggering and notifying process includes:
Firstly, an AI algorithm confirms that an alarm needs to be triggered, and a system immediately generates alarm information;
step two, sending alarm information to a cloud server through an encryption channel, and simultaneously sending a short message, a telephone or an in-application notification to an emergency contact preset by a user;
and step three, if the system has a two-way communication function, a video call or a voice call with the emergency contact person can be started so as to know the site situation in real time.
Preferably, the alarm information includes abnormality type, occurrence time and place.
Preferably, the emergency response and intervention procedure includes:
Step one, 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;
And step two, if the system has an automatic intervention function, a preset intervention measure can be automatically executed after the alarm condition is confirmed, such as playing alarm sound, sending warning information to surrounding equipment and starting camera video.
Preferably, the alarm recording and feedback process includes:
step one, the system records detailed information of each alarm, including triggering time, place, abnormal type and processing result, and stores the information in a cloud server or a local database;
step two, checking alarm records in the application to know the historical alarm condition and the processing condition;
and thirdly, collecting feedback comments by the system, wherein the feedback comments comprise evaluation on the aspects of alarm accuracy, timeliness and user experience, and the feedback comments are used for subsequent system optimization and improvement.
Preferably, the system optimizing and upgrading process includes:
based on feedback and data analysis results, the system performs optimization and upgrading regularly, and the accuracy and efficiency of an AI algorithm are improved;
Step two, introducing new technologies and functions, such as more advanced voice recognition algorithms, image recognition technologies and deep learning models, and continuously improving the intelligent level of the system;
And thirdly, adjusting alarm rules and configuration options according to market demands and user feedback, and providing more personalized and customized services.
An artificial intelligence based mobile terminal alarm device comprising a plurality of sensors for implementing an alarm using the method of claims 1-9.
Compared with the prior art, the invention has the beneficial effects that:
1. The system can generate alarm information immediately 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, video call or voice call with emergency contacts can be started so as to know on-site conditions in real time, feedback comments can be collected to introduce new technology and functions to continuously improve the intelligent level of the system, and the problem that the mobile terminal alarm equipment in the prior art cannot realize real-time monitoring, intelligent analysis and quick response to surrounding environment in actual use is solved, and safer, more convenient and efficient alarm service is provided for users.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a flow chart diagram of a system initialization configuration of the present invention;
FIG. 3 is a flow chart of the real-time monitoring and data analysis of the present invention;
FIG. 4 is a block diagram of the flow of alarm departure and notification of the present invention;
Fig. 5 is a block diagram of the emergency response and intervention flow of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which are obtained by a worker of ordinary skill in the art without creative efforts, are within the protection scope of the present invention based on the embodiments of the present invention.
Referring to fig. 1 to 5, the invention provides a technical scheme that mobile terminal alarm equipment and method based on artificial intelligence comprises the following steps:
step one, initializing and configuring a system;
Step two, monitoring and analyzing data in real time;
step three, alarm triggering and notification;
step four, emergency response and intervention;
Step five, alarming, recording and feeding back;
And step six, optimizing and upgrading the system.
In this embodiment, the system initialization and configuration process further includes:
step one, downloading and installing a mobile alarm application, and applying a built-in AI algorithm and a necessary sensor interface;
registering and logging in, and setting personal data and emergency contact information;
And thirdly, configuring alarm rules according to requirements, wherein the alarm rules comprise voice recognition keywords, image recognition modes and position triggering conditions. The AI algorithm will learn and optimize based on these rules.
In this embodiment, the sensor interface includes a microphone, a camera, and a position sensor.
In this embodiment, the detecting and data analyzing steps further include:
The mobile terminal continuously monitors the surrounding environment, sound is captured through a microphone, an image is captured by a camera, position information is recorded by a position sensor, the sound of the surrounding environment can be continuously captured by using the microphone sensor, the AI algorithm can analyze the sound data, abnormal sounds (such as glass breaking sounds and gunshot) or preset emergency signals are identified, so that an alarm is triggered, and the camera is used as the image sensor, so that a real-time video stream can be captured. The AI image recognition technology can analyze video content, detect abnormal behaviors (such as intruders), environmental changes (such as smoke generated by fire) or specific objects (such as lost objects), the accelerometer and the gyroscope can sense the movement and vibration of the equipment, so as to help to recognize abnormal physical activities, such as illegal movement or abnormal vibration of the equipment, possibly indicate an emergency, a temperature and humidity sensor is not built in, but can be used for monitoring environmental changes under specific scenes (such as warehouses and data centers) to prevent fire and water immersion disasters, the AI algorithm can learn and recognize normal and abnormal environmental modes, the algorithm can distinguish daily activities from potential emergency events through continuous data collection and analysis, when sensor data deviate from a preset normal range or model, AI will be marked as abnormal and trigger further analysis or alarm, AI algorithm needs to have the ability to process data in real time to react quickly in case of emergency, the combined use of various sensor data can provide more comprehensive and accurate environmental monitoring, for example, the combination of sound sensor and image sensor can more accurately judge whether an intrusion event occurs, sensor fusion technology reduces false alarm rate by integrating information of different sensors, improves the overall performance of the system, mobile terminal keeps communication with remote server through wireless network (such as 4G/5G, wi-Fi), real-time uploading monitoring data, user or monitoring center can access the data remotely, view real-time video stream, receive alarm notification, and perform remote intervention as required, when the environment monitoring is carried out, privacy protection regulations must be strictly complied with, the safety and privacy of user data are ensured, and encryption communication and authority control security measures are indispensable to prevent data leakage and illegal access;
Step two, the AI algorithm carries out real-time analysis on the collected data, uses voice recognition technology to recognize keywords, uses image recognition technology to detect abnormal behaviors or objects, uses image recognition technology to detect position data to judge whether a user enters a preset dangerous area, uses voice recognition technology to recognize keywords or specific voice modes which can be preset emergency signals (such as fire alarm sounds and distress sounds), abnormal sounds (such as glass breaking sounds and gunshot) or specific sounds in daily activities (such as footstep sounds and talking sounds) for voice data, uses a training model to learn and recognize preset keywords or phrases, uses a training model to convert the voice captured by a microphone into digital signals and compares the digital signals with the trained model, to identify whether any keywords are included, the AI algorithm can analyze patterns and features of sounds, such as volume, frequency, duration, to distinguish different types of sounds, e.g., by analyzing frequencies and waveforms of sounds, the algorithm can distinguish between spike sounds and normal conversation sounds, the algorithm can identify objects in a video and determine if they are preset abnormal objects (e.g., intruders, lost objects), which is typically accomplished by training a deep learning model that learns features identifying different objects and detects these features in a new video, the AI algorithm can analyze behaviors of people or animals in the video in addition to object detection, e.g., by analyzing motion trajectories, gestures, and actions, the algorithm can determine if abnormal behaviors occur (e.g., running, fight) the algorithm can also detect environmental changes in the video, such as smoke and water immersion generated by fire, which usually depend on image processing and computer vision techniques to identify specific features or modes in the image, through a GPS module integrated in the mobile device, the AI system can track the user's position in real time, these position data are uploaded to the server regularly and compared with a preset dangerous area map, the algorithm can judge whether it enters a preset dangerous area (such as an area where entry is prohibited, a high risk area) according to the user's position information, if it detects that the user enters a dangerous area, the system can trigger an alarm immediately and notify the relevant emergency contact or security service mechanism;
Step three, the AI algorithm evaluates the analysis result according to the preset alarm rules, judges whether to trigger an alarm, if an abnormal condition is detected, then enters the next step, and according to the actual requirement and the safety standard, a series of preset alarm rules are formulated, wherein the rules possibly comprise a sound threshold, image characteristics and a plurality of dimensions of a position range, the preset alarm rules are configured into the AI algorithm, the AI algorithm is ensured to evaluate the collected data according to the rules, the AI algorithm processes the sound captured by the microphone in real time, identifies keywords or specific sound modes, compares the identification result with the sound threshold or keywords in the preset alarm rules, if the identification result meets the alarm condition, then enters the next step, carries out image identification processing on the video stream captured by the camera, detects abnormal behaviors or objects, comparing the detection result with the image characteristics in the preset alarm rules, if abnormal behaviors or objects are detected and alarm conditions are met, entering the next process, acquiring the position information of a user or equipment through a GPS positioning function, comparing the position information with a preset dangerous area map, if the user or equipment enters the preset dangerous area and meets the alarm conditions, entering the next process, when the AI algorithm detects the abnormal conditions and determines that the preset alarm rules are met, immediately triggering an alarm, wherein the alarm mode may comprise voice prompt, popup window display, sending short messages or mail notification, the system records the detailed information of the abnormal conditions, including occurrence time, place and abnormal type, automatically generating an alarm log, facilitating the subsequent query and tracking, and being capable of linking other safety systems (such as a fire alarm system, a fire alarm system and the like according to requirements, access control system) or notify related personnel (such as security personnel and management personnel, and according to the severity and emergency degree of the abnormal situation, making corresponding subsequent treatment measures such as field investigation, fault investigation and security reinforcement.
In this embodiment, the alarm triggering and notifying process includes:
firstly, the AI algorithm confirms that the alarm needs to be triggered, the system immediately generates alarm information, firstly, basic information related to the alarm event is collected, including time, place (such as GPS coordinates or specific address) of the event, related sensor type (such as sound, image and position) and initially judged abnormal type (such as intrusion, fire and equipment fault), according to the analysis result of the AI algorithm, the system generates detailed description of abnormal condition, which may include identified keywords, characteristics of abnormal image and locus of position change, so that the receiver can quickly understand the nature and severity of the alarm event, the system sets priority for the alarm information according to the preset rule or judgment result of the AI algorithm, which is helpful for the receiver to perform sorting treatment according to the emergency degree of the alarm, and respond to the alarm with high priority, in order to improve the normalization and readability of the alarm information, the system will generally apply preset alarm information templates, where the templates include standard formats and necessary fields of the alarm information, such as titles, texts, and attachments (e.g. images and videos), and based on the application templates, the system may also perform personalized customization according to actual requirements, for example, according to the identity or responsibility of the receiver, the system may generate different versions of the alarm information, so that the receiver can better understand and process the alarm information, and the system may select, according to a preset communication list or a judgment result of an AI algorithm, a target person or system that needs to receive the alarm information, where the 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 receiver, the system generally adopts various communication channels for transmission, wherein the channels can comprise short messages, mails, instant messages, voice calls and APP pushing, the system can select the most suitable communication channel for transmission according to the preference and actual situation of a receiver, in the process of transmitting alarm information, the system can monitor in real time to ensure that the information can be successfully transmitted to the receiver, and if the transmission fails or the receiver does not respond, the system can take corresponding remedial measures, such as retransmitting the alarm information or notifying other standby receivers;
Step two, sending alarm information to a cloud server through an encryption channel, sending a short message, a telephone or an intra-application notification to an emergency contact preset by a user at the same time, enabling a client to initiate a connection request with the cloud server, negotiating an encryption key through an SSL/TLS handshake process, establishing the encryption channel, enabling the client to package the alarm information according to a stipulated format, including key information of alarm types, time, places and specific contents, sending the packaged data to the cloud server through the encryption channel, ensuring that the encrypted alarm information is not stolen or tampered in a transmission process, decrypting the encrypted alarm information by using the same key after the cloud server receives the encrypted alarm information, restoring original alarm information, and enabling the server to process the alarm information according to preset rules and logic, such as log recording and triggering subsequent alarm actions;
and step three, if the system has a two-way communication function, a video call or a voice call with the emergency contact person can be started so as to know the site situation in real time.
In this embodiment, the alarm information includes an abnormality type, occurrence time, and place.
In this embodiment, the emergency response and intervention procedure includes:
Step one, 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;
And step two, if the system has an automatic intervention function, a preset intervention measure can be automatically executed after the alarm condition is confirmed, such as playing alarm sound, sending warning information to surrounding equipment and starting camera video.
In this embodiment, the alarm recording and feedback process includes:
step one, the system records detailed information of each alarm, including triggering time, place, abnormal type and processing result, and stores the information in a cloud server or a local database;
step two, checking alarm records in the application to know the historical alarm condition and the processing condition;
and thirdly, collecting feedback comments by the system, wherein the feedback comments comprise evaluation on the aspects of alarm accuracy, timeliness and user experience, and the feedback comments are used for subsequent system optimization and improvement.
In this embodiment, the system optimization and upgrade process includes:
based on feedback and data analysis results, the system performs optimization and upgrading regularly, and the accuracy and efficiency of an AI algorithm are improved;
Step two, introducing new technologies and functions, such as more advanced voice recognition algorithms, image recognition technologies and deep learning models, and continuously improving the intelligent level of the system;
And thirdly, adjusting alarm rules and configuration options according to market demands and user feedback, and providing more personalized and customized services.
An artificial intelligence based mobile terminal alarm device comprising a plurality of sensors for implementing an alarm using the method of claims 1-9.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present invention, and are not intended to limit the invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as claimed. The scope of the invention is defined by the appended claims and their equivalents.
Claims (10)
1. The mobile terminal alarm device and method based on artificial intelligence are characterized by comprising the following steps:
step one, initializing and configuring a system;
Step two, monitoring and analyzing data in real time;
step three, alarm triggering and notification;
step four, emergency response and intervention;
Step five, alarming, recording and feeding back;
And step six, optimizing and upgrading the system.
2. The mobile terminal alarm device and method based on artificial intelligence according to claim 1, wherein the system initialization and configuration process further comprises:
step one, downloading and installing a mobile alarm application, and applying a built-in AI algorithm and a necessary sensor interface;
registering and logging in, and setting personal data and emergency contact information;
And thirdly, configuring alarm rules according to requirements, wherein the alarm rules comprise voice recognition keywords, image recognition modes and position triggering conditions. The AI algorithm will learn and optimize based on these rules.
3. The mobile terminal alarm device and method based on artificial intelligence according to claim 2, wherein the sensor interface comprises a microphone, a camera and a position sensor.
4. The mobile terminal alarm device and method based on artificial intelligence according to claim 1, wherein the detecting and data analyzing steps further comprise:
The method comprises the steps that firstly, a mobile terminal continuously monitors the surrounding environment, sound is captured through a microphone, an image is captured through a camera, and position information is recorded through a position sensor;
Secondly, the AI algorithm analyzes the collected data in real time, a voice recognition technology is used for recognizing keywords for voice data, an image recognition technology is used for detecting abnormal behaviors or objects for image data, and whether a user enters a preset dangerous area or not is judged for position data;
And thirdly, the AI algorithm evaluates the analysis result according to a preset alarm rule, judges whether an alarm needs to be triggered, and if an abnormal condition is detected, enters the next step.
5. The mobile terminal alarm device and method based on artificial intelligence according to claim 1, wherein the alarm triggering and notifying process comprises:
Firstly, an AI algorithm confirms that an alarm needs to be triggered, and a system immediately generates alarm information;
step two, sending alarm information to a cloud server through an encryption channel, and simultaneously sending a short message, a telephone or an in-application notification to an emergency contact preset by a user;
and step three, if the system has a two-way communication function, a video call or a voice call with the emergency contact person can be started so as to know the site situation in real time.
6. The mobile terminal alarm device and method based on artificial intelligence according to claim 5, wherein the alarm information includes abnormality type, occurrence time and place.
7. The mobile terminal alarm device and method based on artificial intelligence according to claim 1, wherein the emergency response and intervention procedure comprises:
Step one, 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;
And step two, if the system has an automatic intervention function, a preset intervention measure can be automatically executed after the alarm condition is confirmed, such as playing alarm sound, sending warning information to surrounding equipment and starting camera video.
8. The mobile terminal alarm device and method based on artificial intelligence according to claim 1, wherein the alarm recording and feedback process comprises:
step one, the system records detailed information of each alarm, including triggering time, place, abnormal type and processing result, and stores the information in a cloud server or a local database;
step two, checking alarm records in the application to know the historical alarm condition and the processing condition;
and thirdly, collecting feedback comments by the system, wherein the feedback comments comprise evaluation on the aspects of alarm accuracy, timeliness and user experience, and the feedback comments are used for subsequent system optimization and improvement.
9. The mobile terminal alarm device and method based on artificial intelligence according to claim 1, wherein the system optimizing and upgrading process comprises:
based on feedback and data analysis results, the system performs optimization and upgrading regularly, and the accuracy and efficiency of an AI algorithm are improved;
Step two, introducing new technologies and functions, such as more advanced voice recognition algorithms, image recognition technologies and deep learning models, and continuously improving the intelligent level of the system;
And thirdly, adjusting alarm rules and configuration options according to market demands and user feedback, and providing more personalized and customized services.
10. An artificial intelligence based mobile terminal alarm device is characterized by comprising a plurality of sensors and realizing alarm by adopting the method of claims 1-9.
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| CN119723836A (en) * | 2025-02-24 | 2025-03-28 | 济南本安科技发展有限公司 | Alarm location determination method, mobile terminal, product and medium |
| CN119942654A (en) * | 2025-04-08 | 2025-05-06 | 西安旭阳通讯设备有限公司 | Intelligent alarm method and system based on environmental perception |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN119418477A (en) * | 2024-12-31 | 2025-02-11 | 富盛科技股份有限公司 | Fixed-point alarm method and device based on map information |
| CN119676011A (en) * | 2025-02-20 | 2025-03-21 | 杭州哨邦科技有限公司 | A fire emergency broadcast system that automatically broadcasts the location of fire alarms |
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