CN112164167B - Safety monitoring system and method based on artificial intelligence - Google Patents
Safety monitoring system and method based on artificial intelligence Download PDFInfo
- Publication number
- CN112164167B CN112164167B CN202011189905.XA CN202011189905A CN112164167B CN 112164167 B CN112164167 B CN 112164167B CN 202011189905 A CN202011189905 A CN 202011189905A CN 112164167 B CN112164167 B CN 112164167B
- Authority
- CN
- China
- Prior art keywords
- information
- module
- current
- vehicle
- safety
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/20—Individual registration on entry or exit involving the use of a pass
- G07C9/22—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder
- G07C9/25—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition
- G07C9/257—Individual registration on entry or exit involving the use of a pass in combination with an identity check of the pass holder using biometric data, e.g. fingerprints, iris scans or voice recognition electronically
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/20—Individual registration on entry or exit involving the use of a pass
- G07C9/27—Individual registration on entry or exit involving the use of a pass with central registration
-
- 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
- G08B25/016—Personal emergency signalling and security systems
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Human Computer Interaction (AREA)
- Traffic Control Systems (AREA)
- Alarm Systems (AREA)
Abstract
The invention relates to the technical field of parking lot monitoring, and particularly discloses a safety monitoring system and a method based on artificial intelligence, wherein the system comprises an image acquisition module, a safety monitoring module and a safety monitoring module, wherein the image acquisition module is used for acquiring a current image at a barrier gate when a vehicle exits from a parking lot; the recognition module is used for extracting current license plate information and current portrait information from a current image; the device also comprises a communication module and a control module; the communication module is used for receiving the basic information of the vehicle owner and the safety mode setting information, and the recognition module is also used for matching preset license plate information based on the current license plate information and matching preset face information based on the current face information; when the image matching is successful, the identification module further judges whether the current time is in the safe mode starting time, if so, the identification module is further used for judging whether the current image comprises an alarm indicating behavior, and if so, alarm information is generated. By adopting the technical scheme of the invention, the condition that the vehicle is not pulled out of the parking lot by the vehicle owner can be identified.
Description
Technical Field
The invention relates to the technical field of parking lot monitoring, in particular to a safety monitoring system and method based on artificial intelligence.
Background
At present, in a parking lot system, the identity of a vehicle owner is generally determined by swiping an IC card or recognizing a license plate by a camera, a barrier gate is automatically controlled to be opened, and vehicles are released; the IC card swiping method needs a car owner to manually swipe the card, so that the operation is troublesome, and in addition, if the IC card is lost, the car owner can pass through the IC card after the IC card is processed by a manager, so that the IC card swiping method is very inconvenient; if the vehicle in the parking lot is stolen, the vehicle can be freely driven out of the parking lot as long as the stolen person has the IC card; similarly, the license plate is identified by the camera, so that the vehicle can be identified without identifying people, and the effective theft prevention cannot be realized.
To this end, chinese patent publication No. CN103390300A discloses a parking lot management system, which includes a gateway installed at an entrance/exit of a parking lot, a camera for capturing video images at the entrance/exit of the parking lot, an alarm device for emitting an audible and visual alarm signal, and a control system for analyzing and processing vehicle information and face information of vehicles entering/exiting the parking lot captured by the camera and matching the vehicle information of the vehicles exiting the parking lot with the vehicle information and face information of the vehicles entering the parking lot. The parking lot management system matches the vehicle information of the vehicles running out of the parking lot with the vehicle information of the vehicles entering the parking lot and the face information, keeps the barrier pulled up to let the vehicles pass through when matching is successful, and does not need actions such as releasing the brakes, swiping a card and pulling the brakes, so that the parking lot management system has the advantages of being fast and efficient, and the vehicles in the parking lot can be effectively prevented from being stolen through face recognition.
However, in the above scheme, as long as the owner can be captured the face by the camera, it is determined that there is no safety risk, but the owner cannot recognize the situation that the owner is not willing to move the vehicle out of the parking lot, such as being clamped, and it is difficult to ensure the safety of the owner and the vehicle comprehensively.
Therefore, there is a need for an artificial intelligence based security monitoring system and method that can recognize that the owner of a vehicle will not intend to move the vehicle out of the parking lot.
Disclosure of Invention
The invention provides a safety monitoring system and a safety monitoring method based on artificial intelligence, which can identify the condition that an owner does not intend to drive a vehicle out of a parking lot.
In order to solve the technical problem, the present application provides the following technical solutions:
a safety monitoring system based on artificial intelligence comprises an image acquisition module, a safety monitoring module and a safety monitoring module, wherein the image acquisition module is used for acquiring a current image at a barrier when a vehicle exits a parking lot; the recognition module is used for extracting current license plate information and current portrait information from a current image;
the device also comprises a communication module and a control module;
the communication module is used for receiving vehicle owner basic information and safety mode setting information, wherein the vehicle owner basic information comprises preset license plate information and preset face information; the safety mode setting information comprises safety mode starting time and alarm indicating behaviors;
the recognition module is also used for matching preset license plate information based on the current license plate information and matching preset face information based on the current face information; when the image matching is successful, the identification module further judges whether the current time is in the safe mode starting time, if so, the identification module is further used for judging whether the current image comprises an alarm indicating behavior, and if not, a release instruction is generated; if yes, generating alarm information;
the control module is used for controlling the opening of the barrier when receiving the release instruction.
The basic scheme principle and the beneficial effects are as follows:
in the scheme, the received basic information of the vehicle owner and the setting information of the safety mode can be known about the setting of the opening time of the safety mode and the alarm indicating behavior of the vehicle owner.
When a vehicle is about to exit from a parking lot, a current image at a barrier gate is collected, current license plate information and current portrait information in the current image are extracted based on a mode recognition principle in artificial intelligence, and are respectively matched with preset license plate information and preset face information, so that a result can be quickly obtained. When the two are successfully matched, if the image is in the safe mode opening time, whether the current image comprises the alarm indicating behavior is judged. If the car owner is not self intention at this moment and drives the vehicle out of the parking lot, the car owner can make the alarm signaling behavior, the safety mode setting information is only known by the car owner, and other people cannot know the alarm signaling behavior, so that the car owner can not be aware of the alarm signaling behavior. In other words, the alarm action can be completed in the absence of noise, the safety of the car owner is effectively guaranteed, and meanwhile, the others are prevented from being surprised.
To sum up, this scheme can discern the condition that the car owner does not self wish to roll the vehicle out of the parking area to in time report to the police, the degree of safety is high.
Further, the identification module is used for judging whether the current position of the vehicle owner is in the driver seat or not when the current face information is successfully matched with the preset face information, and generating a get-off verification instruction if the current position of the vehicle owner is not in the driver seat;
the system also comprises a display module used for displaying get-off reminding information after receiving the get-off verification instruction.
When the car owner is not in the driver's seat, the possibility that the vehicle is driven out of the parking lot by non-self intentions such as being held by the arms is higher, the getting-off reminding information is displayed, the car owner can get off to verify, and if the car owner has danger at the moment, the car owner can get off to give the chance that the car owner escapes.
Further, the safety mode setting information also comprises alarm indicating voice;
the intelligent alarm system is characterized by further comprising an interaction module, wherein the interaction module is used for collecting current voice information of the vehicle owner after the vehicle owner gets off, judging whether the current voice information contains alarm indicating voice, and if the current voice information contains the alarm indicating voice, generating alarm information.
If the owner is clamped, the owner can speak out the alarm indicating voice when the owner gets off and carries out face verification again, and the purpose of alarming is achieved. The warning signal voice is only known by the vehicle owner, and other people cannot know the warning signal voice, so that the warning action of the vehicle owner cannot be perceived.
Further, the interaction module is further used for collecting portrait information within a preset distance, matching the portrait information within the preset distance with preset face information, and if matching is successful and the current voice information does not contain alarm indicating voice, generating a release instruction.
Only the portrait information within the preset distance is collected, and the vehicle owner has to get off the vehicle to perform face recognition.
Further, the basic information of the vehicle owner also comprises a reserved communication mode, the recognition module is also used for generating verification information when the matching of the current face information and the preset face information fails, and the communication module also sends the verification information based on the reserved communication mode;
the identification module also judges whether the communication module receives the reply information within a preset time, and if the reply information is not received, alarm information is generated; if the reply information is received, the identification module is also used for analyzing the content of the reply information, if the content contains the releasing keyword, a releasing instruction is generated, and if the content contains the alarming keyword, alarming information is generated.
The car owner still has the condition of borrowing the car for friend, if must the car owner just can open the banister at the scene, very inconvenient. Therefore, when the owner borrows the vehicle to other persons voluntarily, the authorization can be carried out in a mode of replying the information.
Further, the interaction module is also used for judging whether an alarm input signal is received or not, and if so, generating alarm information.
The vehicle owner can also alarm in a mode of directly inputting the alarm input signal, and the alarm modes are multiple, so that the vehicle owner can conveniently select according to the actual condition.
Further, the preset distance is 20-40 cm.
A safety monitoring method based on artificial intelligence uses the safety monitoring system based on artificial intelligence.
In the scheme, the received basic information of the vehicle owner and the setting information of the safety mode can be known about the setting of the opening time of the safety mode and the alarm indicating behavior of the vehicle owner.
When a vehicle is about to exit from a parking lot, the current image at the barrier gate is collected, the current license plate information and the current portrait information in the current image are extracted based on the principle of mode recognition in artificial intelligence, and are respectively matched with the preset license plate information and the preset face information, so that the result can be quickly obtained. When the two are successfully matched, if the image is in the safe mode opening time, whether the current image comprises the alarm indicating behavior is judged. If the car owner is not self intention at this moment and drives the vehicle out of the parking lot, the car owner can make the alarm signaling behavior, the safety mode setting information is only known by the car owner, and other people cannot know the alarm signaling behavior, so that the car owner can not be aware of the alarm signaling behavior. In other words, the alarm action can be completed in the absence of noise, the safety of the car owner is effectively guaranteed, and meanwhile, the others are prevented from being surprised.
To sum up, this scheme can discern the condition that the car owner does not self wish to roll the vehicle out of the parking area to in time report to the police, the degree of safety is high.
Drawings
Fig. 1 is a logic block diagram of an artificial intelligence based security monitoring system according to an embodiment.
Detailed Description
The following is further detailed by way of specific embodiments:
example one
As shown in fig. 1, the safety monitoring system based on artificial intelligence of the present embodiment includes a communication module, an image acquisition module, an identification module, a control module, a display module, and an interaction module.
The communication module is used for receiving vehicle owner basic information and safety mode setting information, wherein the vehicle owner basic information comprises a reserved communication mode, preset license plate information and preset face information; the security mode setting information includes security mode opening time, alarm signaling behavior, and alarm signaling voice.
In this embodiment, the owner's basic information and the security mode setting information may be entered by the owner on his/her mobile phone and sent to the communication module. In this embodiment, the alert gesture means a specific gesture or gesture, such as placing a hand around the neck, stroking "OK" with a hand, etc., and the alert gesture voice means a specific word or sentence, such as "i am somewhat uncomfortable".
In this embodiment, the image acquisition module adopts the camera, fixes at the parking area access & exit, and the image acquisition module is used for when the vehicle exits the parking area, gathers the current image of banister department. Of course, the image acquisition module may also acquire an image of the barrier when the vehicle enters the parking lot, and this part is not the key point of this embodiment and is not described herein again.
The identification module is used for extracting current license plate information and current portrait information from a current image; matching preset license plate information based on the current license plate information and matching preset face information based on the current face information; when the vehicle owner is successfully matched with the vehicle owner, the identification module also judges whether the current position of the vehicle owner is in a driver seat, and if the current position of the vehicle owner is not in the driver seat, a get-off verification instruction is generated; if the driver seat is in the driving seat, the identification module is also used for judging whether the current time is in the safe mode starting time or not, if so, the identification module is also used for judging whether the current image comprises an alarm indicating behavior or not, and if not, a release instruction is generated; and if the alarm information is contained, generating alarm information.
The display module is used for displaying get-off reminding information after receiving the get-off verification instruction. In this embodiment, the get-off reminding information is: if the human face cannot be identified, the vehicle is required to be identified again. If dangerous condition happens, people in the vehicle can be puzzled, and the vehicle owner can be put away and get off the vehicle.
The interaction module is used for collecting the current voice information of the vehicle owner after the vehicle owner gets off, judging whether the current voice information contains alarm indicating voice or not, and if yes, generating alarm information. In this embodiment, the interactive module is an interactive terminal arranged beside the barrier gate, and is equipped with a camera, a microphone, a touch screen and an alarm button.
The interaction module is also used for collecting portrait information within a preset distance, matching the portrait information within the preset distance with preset face information, and if the matching is successful and the current voice information does not contain alarm indicating voice, generating a release instruction. In this embodiment, the predetermined distance is 20-40 cm.
The interaction module is also used for judging whether an alarm input signal is received or not, and if so, generating alarm information. The alarm input signal can be input by the owner in the touch screen or can be generated after the owner presses the alarm button.
The identification module is further used for generating verification information when the matching of the current face information and the preset face information fails, and the communication module is further used for sending the verification information based on a reserved communication mode. The reserved communication mode can be a reserved mobile phone number, the corresponding sent verification information is a mobile phone short message, the corresponding sent verification information can also be bound social software such as WeChat, QQ and nailing, and the corresponding sent verification information is a WeChat message, QQ message or nailing message.
The identification module also judges whether the communication module receives the reply information within the preset time, and generates alarm information if the communication module does not receive the reply information; if the reply information is received, the identification module is also used for analyzing the content of the reply information, if the content contains the releasing keyword, a releasing instruction is generated, and if the content contains the alarming keyword, alarming information is generated. In this embodiment, the preset time is 2 minutes. The release keywords are, for example: agreeing to release, opening a barrier, agreeing, and the like; alarm keywords are for example: theft, alarm, etc.
The control module is used for controlling the opening of the barrier when receiving the release instruction.
In this embodiment, still include the management terminal that parking area security personnel used, communication module still is used for sending alarm information to management terminal. And after receiving the alarm information, security personnel can process the alarm information in time.
The safety monitoring method based on artificial intelligence in this embodiment adopts the safety monitoring system based on artificial intelligence.
Example two
The difference between this embodiment and the first embodiment is that, in the safety monitoring system based on artificial intelligence of this embodiment, the safety mode setting information further includes a safety schematic confirming behavior.
The identification module is used for judging whether the vehicle owner makes a safety schematic behavior based on the current image after the display module displays the getting-off reminding information, if the safety schematic behavior is made, the identification module is also used for calculating whether the time from the display of the getting-off reminding information to the occurrence of the safety schematic behavior exceeds a threshold value, and if the time does not exceed the threshold value, the identification module is marked to meet a first condition; the threshold value is 3-6 seconds, and in this embodiment the threshold value is 5 seconds.
The identification module also judges whether the vehicle owner communicates with other personnel in the vehicle before making a safety schematic behavior based on the current image, and if the vehicle owner does not communicate with other personnel in the vehicle, the identification module is marked to meet a second condition;
and when the condition one and the condition two are simultaneously met, the identification module generates a release instruction. And when the condition I and the condition II cannot be simultaneously met, generating the get-off verification instruction again.
Under the condition that the owner is in safety, if the owner is not in the driver's seat, such as a copilot position, the owner is required to get off the vehicle for verification, and the owner is very cumbersome. There is therefore a need for a method of eliminating the alighting verification step while ensuring security. In this embodiment, the owner may set in advance a safety signaling confirmation behavior to indicate that the owner is currently in a safe state.
However, in a scene that the owner of the vehicle is forced by a person, other persons may apply pressure to the owner of the vehicle, so that the owner of the vehicle may voluntarily make the safety indication confirmation. The pressure applied to the vehicle owner by other personnel in the vehicle can be eliminated, and the situation that the vehicle owner is hesitant when the external pressure is applied can also be eliminated.
The safety monitoring method based on artificial intelligence in this embodiment adopts the safety monitoring system based on artificial intelligence.
The above are merely examples of the present invention, and the present invention is not limited to the field related to this embodiment, and the common general knowledge of the known specific structures and characteristics in the schemes is not described herein too much, and those skilled in the art can know all the common technical knowledge in the technical field before the application date or the priority date, can know all the prior art in this field, and have the ability to apply the conventional experimental means before this date, and those skilled in the art can combine their own ability to perfect and implement the scheme, and some typical known structures or known methods should not become barriers to the implementation of the present invention by those skilled in the art in light of the teaching provided in the present application. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (7)
1. A safety monitoring system based on artificial intelligence comprises an image acquisition module, a safety monitoring module and a safety monitoring module, wherein the image acquisition module is used for acquiring a current image at a barrier when a vehicle exits a parking lot; the recognition module is used for extracting current license plate information and current portrait information from a current image;
the system is characterized by also comprising a communication module and a control module;
the communication module is used for receiving vehicle owner basic information and safety mode setting information, wherein the vehicle owner basic information comprises preset license plate information and preset face information; the safety mode setting information comprises safety mode starting time and alarm indicating behaviors;
the recognition module is also used for matching preset license plate information based on the current license plate information and matching preset face information based on the current face information; when the image matching is successful, the identification module further judges whether the current time is in the safe mode starting time, if so, the identification module is further used for judging whether the current image comprises an alarm indicating behavior, and if not, a release instruction is generated; if yes, generating alarm information;
the control module is used for controlling the barrier gate to be opened when receiving the release instruction;
the recognition module is used for judging whether the current position of the vehicle owner is in the driver seat or not when the current face information is successfully matched with the preset face information, and generating a get-off verification instruction if the current position of the vehicle owner is not in the driver seat;
the system also comprises a display module used for displaying get-off reminding information after receiving the get-off verification instruction;
the security mode setting information further includes a security schematic behavior;
the identification module is used for judging whether the vehicle owner makes a safety schematic behavior based on the current image after the display module displays the getting-off reminding information, if the safety schematic behavior is made, the identification module is also used for calculating whether the time from the display of the getting-off reminding information to the occurrence of the safety schematic behavior exceeds a threshold value, and if the time does not exceed the threshold value, the identification module is marked to meet a first condition;
the identification module also judges whether the vehicle owner communicates with other personnel in the vehicle before making a safety schematic behavior based on the current image, and if the vehicle owner does not communicate with other personnel in the vehicle, the identification module is marked to meet a second condition;
when the condition I and the condition II are simultaneously met, the identification module generates a release instruction; and when the condition I and the condition II cannot be simultaneously met, generating the get-off verification instruction again.
2. The artificial intelligence based security monitoring system of claim 1, wherein: the safety mode setting information also comprises alarm indicating voice;
the intelligent alarm system is characterized by further comprising an interaction module, wherein the interaction module is used for collecting current voice information of the vehicle owner after the vehicle owner gets off, judging whether the current voice information contains alarm indicating voice, and if the current voice information contains the alarm indicating voice, generating alarm information.
3. The artificial intelligence based security monitoring system of claim 2, wherein: the interaction module is further used for collecting portrait information within a preset distance, matching the portrait information within the preset distance with preset face information, and if matching is successful and the current voice information does not contain alarm indicating voice, generating a release instruction.
4. The artificial intelligence based security monitoring system of claim 3, wherein: the vehicle owner basic information further comprises a reserved communication mode, the recognition module is further used for generating verification information when the matching of the current face information and the preset face information fails, and the communication module is further used for sending the verification information based on the reserved communication mode;
the identification module also judges whether the communication module receives the reply information within the preset time, and generates alarm information if the communication module does not receive the reply information; if the reply information is received, the identification module is also used for analyzing the content of the reply information, if the content contains the releasing keyword, a releasing instruction is generated, and if the content contains the alarming keyword, alarming information is generated.
5. The artificial intelligence based security monitoring system of claim 4, wherein: the interaction module is also used for judging whether an alarm input signal is received or not, and if so, generating alarm information.
6. The artificial intelligence based security monitoring system of claim 5, wherein: the preset distance is 20-40 cm.
7. An artificial intelligence based security monitoring method, characterized by using the artificial intelligence based security monitoring system of any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011189905.XA CN112164167B (en) | 2020-10-30 | 2020-10-30 | Safety monitoring system and method based on artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011189905.XA CN112164167B (en) | 2020-10-30 | 2020-10-30 | Safety monitoring system and method based on artificial intelligence |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112164167A CN112164167A (en) | 2021-01-01 |
| CN112164167B true CN112164167B (en) | 2022-08-05 |
Family
ID=73865211
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011189905.XA Active CN112164167B (en) | 2020-10-30 | 2020-10-30 | Safety monitoring system and method based on artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112164167B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2600297Y (en) * | 2002-12-09 | 2004-01-21 | 陈涛 | Anti-hijack vehicle safety monitoring device |
| CN104346897A (en) * | 2013-07-23 | 2015-02-11 | 深圳市赛格导航科技股份有限公司 | Vehicle-mounted terminal eyeball identification alarm system and method |
| CN106394492A (en) * | 2015-07-21 | 2017-02-15 | 百利得汽车主动安全系统（苏州）有限公司 | Vehicle dynamic face identification safety control system and control method thereof |
| US10507793B1 (en) * | 2018-08-17 | 2019-12-17 | Felipe Boris De Moura Partika | Alarm, safety device and device for expelling attackers for motor vehicles |
| CN111476981A (en) * | 2019-01-23 | 2020-07-31 | 上海博泰悦臻电子设备制造有限公司 | In-vehicle personnel monitoring device and method |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU2003900048A0 (en) * | 2003-01-07 | 2003-01-23 | Stratech Systems Limited | Automated vehicle inspection system |
| CN103914886A (en) * | 2013-01-09 | 2014-07-09 | 深圳市中联创新自控系统有限公司 | Parking lot management method and system |
| CN104794795B (en) * | 2015-04-30 | 2017-07-04 | 深圳市车易泊技术股份有限公司 | Intelligent anti-theft shutdown system and its vehicles management method |
| CN106218581A (en) * | 2016-08-26 | 2016-12-14 | 张培 | A kind of vehicle-mounted antitheft security system |
| CN109360304B (en) * | 2018-09-20 | 2020-12-25 | 智慧互通科技有限公司 | Method and device for vehicle passing in parking lot |
| CN110077415A (en) * | 2019-04-23 | 2019-08-02 | 朱进军 | New-energy automobile safety monitoring system |
| CN111681399A (en) * | 2020-05-27 | 2020-09-18 | 北京卓奥世鹏科技有限公司 | Multi-dimensional three-dimensional safety prevention and control method, device and system |
-
2020
- 2020-10-30 CN CN202011189905.XA patent/CN112164167B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2600297Y (en) * | 2002-12-09 | 2004-01-21 | 陈涛 | Anti-hijack vehicle safety monitoring device |
| CN104346897A (en) * | 2013-07-23 | 2015-02-11 | 深圳市赛格导航科技股份有限公司 | Vehicle-mounted terminal eyeball identification alarm system and method |
| CN106394492A (en) * | 2015-07-21 | 2017-02-15 | 百利得汽车主动安全系统（苏州）有限公司 | Vehicle dynamic face identification safety control system and control method thereof |
| US10507793B1 (en) * | 2018-08-17 | 2019-12-17 | Felipe Boris De Moura Partika | Alarm, safety device and device for expelling attackers for motor vehicles |
| CN111476981A (en) * | 2019-01-23 | 2020-07-31 | 上海博泰悦臻电子设备制造有限公司 | In-vehicle personnel monitoring device and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112164167A (en) | 2021-01-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR100778060B1 (en) | Vehicle emergency preventive terminal device and internet system using facial recognition technology | |
| KR101610657B1 (en) | Three-dimensional virtual entrance control and communicable disease control system and method based on entrance control data | |
| CN107554483A (en) | A kind of VATS Vehicle Anti-Theft System based on human face expression action recognition | |
| CN109118617B (en) | Access control system applied to transformer substation and identification method thereof | |
| CN113076856B (en) | Bus safety guarantee system based on face recognition | |
| JP2007094935A (en) | Information processing device, method, system, and program, and recording medium | |
| CN110517449A (en) | A kind of intelligent air control system for net about vehicle, taxi | |
| CN109741573B (en) | Human safety monitoring method, system and device based on face recognition | |
| CN109291793A (en) | Net about vehicle passenger warning device and method | |
| KR101879444B1 (en) | Method and apparatus for operating CCTV(closed circuit television) | |
| CN111698215A (en) | Security prevention and control method, device and system based on biological feature recognition | |
| CN112164167B (en) | Safety monitoring system and method based on artificial intelligence | |
| KR20160028542A (en) | an emergency management and crime prevention system for cars and the method thereof | |
| JP5280272B2 (en) | MONITORING APPARATUS AND MONITORING SYSTEM | |
| CN111724573B (en) | Vehicle interior monitoring method and related device thereof | |
| CN113306563A (en) | Emergency stop method, device, electronic equipment and storage medium | |
| CN111640263B (en) | Information interaction method and device, automatic teller machine and medium | |
| KR101437406B1 (en) | an emergency management and crime prevention system for cars and the method thereof | |
| CN114999041A (en) | Intelligent parking safety monitoring system and method based on artificial intelligence | |
| TW202125419A (en) | Construction site management system and method thereof | |
| CN210222996U (en) | Intelligent wind control system for taxi booking and taxis | |
| CN112309127B (en) | AI-based parking management system and method | |
| CN108556629B (en) | Driving safety auxiliary system and method | |
| CN110239345A (en) | A kind of vehicle security drive precaution device | |
| CN110126723B (en) | Lock control system, method and device, storage medium and electronic device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |