CN113538827A - Intelligent home monitoring system and method - Google Patents
Intelligent home monitoring system and method Download PDFInfo
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- CN113538827A CN113538827A CN202110783726.7A CN202110783726A CN113538827A CN 113538827 A CN113538827 A CN 113538827A CN 202110783726 A CN202110783726 A CN 202110783726A CN 113538827 A CN113538827 A CN 113538827A
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- person
- video
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B13/00—Burglar, theft or intruder alarms
- G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
- G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
- G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
- G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
Abstract
The invention discloses an intelligent home monitoring system and method. The monitoring unit is used for acquiring the monitoring video, the detection unit is used for determining whether a person exists according to the monitoring video, if the person exists, then determining whether the person in the monitoring video is an abnormal person, and when the person in the monitoring video is determined to be the abnormal person, the detection unit sends alarm information to the client. By adopting the system and the method, the system and the method can actively give an alarm to the user when potential danger exists, and the user can be warned in advance to take measures in time no matter whether the house is empty or not, or whether the house is a solitary female working outside or an old person living in the solitary all the year round, or whether the house is a family with babies or children.
Description
Technical Field
The invention relates to the technical field of home monitoring, in particular to an intelligent home monitoring system and method.
Background
At present, a lot of independent people who work outside exist, old people who live alone all the year round exist, and families with babies or children, and the people and the families are easily victims of crimes such as burglary, robbery and the like because of weak personal protection capability.
At present, science and technology in China is developing at a high speed, but the household safety monitoring is still not perfect enough, and most designs consider non-artificial factors such as fire, gas leakage and the like, and rarely deal with the artificial factors. In addition, the existing monitoring only records the state of a house, but cannot actively feed back to a user when in suspicious conditions, and the user cannot check the monitoring frequently in most of the time, so that the user cannot know potential dangers in time to take precautionary measures in advance.
Disclosure of Invention
The embodiment of the invention provides an intelligent home monitoring system and method, which are used for solving the problem that a monitoring system in the prior art cannot actively feed back to a user.
In one aspect, an embodiment of the present invention provides an intelligent home monitoring system, including: the system comprises a monitoring unit, a database unit, a detection unit and a client;
the monitoring unit is used for acquiring a monitoring video;
the database unit is used for storing the monitoring video;
the detection unit is used for determining whether a person exists according to the monitoring video, determining whether the person in the monitoring video is an abnormal person if the person exists, and sending alarm information to the client side when the person in the monitoring video is determined to be the abnormal person.
In a possible implementation manner, when it is determined that a person exists in a surveillance video, a detection unit first determines whether the person in the surveillance video is a family member, and if the person in the surveillance video is a family member, the detection unit continues to monitor the surveillance video; if the person in the monitoring video is not a family member, the detection unit determines whether the person in the monitoring video is an abnormal person.
In one possible implementation manner, when it is determined that the person in the surveillance video is not a family member, the detection unit acquires the surveillance image in the surveillance video, transmits the surveillance image to the database unit, and stores the surveillance image by the database unit.
In one possible implementation manner, the abnormal person includes a blacklist person, and when the detection unit determines that the person in the surveillance video is the blacklist person, the alarm information is immediately sent to the client.
In a possible implementation mode, the system further comprises an early warning unit, wherein abnormal persons comprise strangers; when the detection unit determines that the person in the monitoring video is a stranger, the early warning unit starts to monitor the monitoring video, and when the stranger in the monitoring video is determined to meet the early warning condition, the early warning unit sends warning information to the client.
In one possible implementation, the early warning condition is: and the time for strangers in the monitoring video to appear reaches a preset value.
In a possible implementation manner, the database unit includes a self-training module, the self-training module is configured to train a target detection model according to a picture transmitted by the client, and the detection unit determines whether a person in the surveillance video is an abnormal person by using the target detection model.
In a possible implementation manner, the database unit further includes a storage module, and the storage module is used for storing the monitoring video.
In a possible implementation mode, the system further comprises a warning unit, the warning unit is arranged on a door of a user family, and after the detection unit sends alarm information to the client, the detection unit further controls the warning unit to work.
On the other hand, the embodiment of the invention also provides an intelligent home monitoring method, which comprises the following steps:
acquiring a monitoring video;
storing the monitoring video;
and determining whether a person exists according to the monitoring video, if so, determining whether the person in the monitoring video is an abnormal person, and sending alarm information to the client when determining that the person in the monitoring video is the abnormal person.
The intelligent home monitoring system and the method have the following advantages that:
the alarm device can actively give an alarm to a user when potential danger exists, and the user can be warned in advance so as to take measures in time regardless of whether the user is a house without one person, or a solitary female who works outside or an old man living in a long-term, or a family with a baby or a child.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a functional block diagram of an intelligent home monitoring system according to an embodiment of the present invention;
fig. 2 is a flowchart of an intelligent home monitoring method according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a functional block diagram of an intelligent home monitoring system according to an embodiment of the present invention. The embodiment of the invention provides an intelligent home monitoring system, which comprises: the monitoring unit 100, the database unit 200, the detection unit 300 and the client 500;
the monitoring unit 100 is used for acquiring a monitoring video;
the database unit 200 is used for storing the monitoring video;
the detection unit 300 is configured to determine whether a person exists according to the surveillance video, determine whether the person in the surveillance video is an abnormal person if the person exists, and send alarm information to the client 500 by the detection unit 300 when the person in the surveillance video is determined to be the abnormal person.
Illustratively, the monitoring unit 100 is a camera, which is installed on a door of a home of the user, for acquiring a monitoring video of the doorway. The monitoring unit 100 has a wireless communication function, and can transmit the acquired monitoring video to the database unit 200 through a wireless communication technology such as WiFi.
The database unit 200 is a device having storage and processing functions, and for convenience of centralized management, the database unit 200 is a cloud server. In the embodiment of the present invention, the database unit 200 is a server using the arrzus technology. The database unit 200 has a storage module 210, the storage module 210 may use a cloud storage method, and the storage module 210 is used for storing the monitoring video acquired by the monitoring unit 100. The client 500 is dedicated software installed on an electronic device carried by a user, for example, APP (Application program) installed on a mobile phone, and the electronic device where the client 500 is located is in communication connection with the database unit 200 through a wireless communication technology at any time to view the monitoring video stored in the storage module 210 at any time and any place.
In the embodiment of the present invention, the detection unit 300 is a software program located on a cloud server, and the detection unit 300 may be located on the cloud server of the database unit 200, or may be located on different cloud servers respectively. After the storage module 210 stores the monitoring video, the detection unit 300 obtains the stored monitoring video in real time, and captures the monitoring image therein according to a set frequency, for example, 10 monitoring images per second. For the intercepted monitoring image, the detection unit 300 processes it to determine whether there is an abnormal person in the monitoring image.
In a possible embodiment, when determining that someone exists in the surveillance video, the detection unit 300 first determines whether the person in the surveillance video is a family member, and if so, the detection unit 300 continues to monitor the surveillance video; if the person in the surveillance video is not a family member, the detection unit 300 determines whether the person in the surveillance video is an abnormal person.
Illustratively, before the intelligent home monitoring system of the present invention starts working, the user is required to upload the family member photo to the database unit 200 through the client 500, and after the detection unit 300 extracts the features in the monitored image, the features are compared with the features of the family member photo, so as to determine whether the person in the monitored image is a family member. If the family member is determined, the detection unit 300 does not perform any operation, continues to acquire the monitoring video, and processes the monitoring video.
In one possible embodiment, when it is determined that the person in the surveillance video is not a family member, the detection unit 300 acquires the surveillance image in the surveillance video and transmits the surveillance image to the database unit 200 to be stored by the database unit 200.
Illustratively, if the person in the surveillance video is not a family member, there is a possibility that the person is an abnormal person, and the detection unit 300 transmits the intercepted surveillance image to the storage module 210 of the database unit 200 for the user to view.
In one possible embodiment, the abnormal person includes a blacklist person, and when the detection unit 300 determines that the person in the surveillance video is a blacklist person, an alarm message is immediately sent to the client 500.
Illustratively, when the user uploads the family member photo to the database unit 200 through the client 500, the blacklist photo can also be uploaded at the same time. The blacklist photo may be a photo stored on the mobile phone of the user, or a photo of a person whose shape is considered suspicious when the user views the monitoring video or the monitoring image transmitted from the detection unit 300 to the storage module 210. As with the identification of family members, the detection unit 300 may determine whether a person in the monitored image is a blacklist person by extracting features from the monitored image and comparing the extracted features with features of the blacklist photograph.
In the embodiment of the present invention, if the detection unit 300 determines that the person in the monitoring video belongs to the blacklist person, in addition to sending the alarm information to the client 500, a start instruction may also be sent to the warning unit installed on the user's home door, and the warning unit starts to work under the control of the start instruction, and sends an alarm to frighten the blacklist person at the door. The warning unit can be an LED lamp or a loudspeaker, the LED lamp can flash, light or highlight under the control of a starting instruction, and the loudspeaker can play buzzing sound, sound recorded by a user in advance and the like.
In a possible embodiment, the early warning unit 400 is further included, and the abnormal person includes strangers; when the detection unit 300 determines that a person in the surveillance video is a stranger, the early warning unit 400 starts monitoring the surveillance video, and when it is determined that the stranger in the surveillance video meets the early warning condition, the early warning unit 400 sends warning information to the client 500.
Illustratively, when the detection unit 300 determines that the person at the doorway does not belong to a family member or a blacklisted person, the person at the doorway is considered to be a stranger. Since strangers are not necessarily dangerous persons, continuous monitoring of strangers is required to determine whether they are dangerous.
In an embodiment of the present invention, the early warning condition is: and the time for strangers in the monitoring video to appear reaches a preset value. When the detection unit 300 determines that the person in the surveillance video is a stranger, the early warning unit 400 starts timing immediately and keeps tracking the person in the surveillance video, for example, tracking the stranger by using yolo (young Only Look one) V3 and OpenCV technology. When the time reaches a set value, for example, 5 minutes or 10 minutes, and a stranger is still in the monitoring video, the early warning unit 400 determines that the current stranger is dangerous, and immediately sends an alarm message to the client 500.
In a possible embodiment, the database unit 200 includes a self-training module 220, the self-training module 220 is configured to train a target detection model according to the pictures transmitted by the client 500, and the detection unit 300 determines whether the person in the surveillance video is an abnormal person using the target detection model.
Illustratively, the self-training module 220 trains the target detection model in a transfer learning manner after establishing the target detection model. In the embodiment of the present invention, the target detection model is a YOLOV3 network model, and the self-training module 320 takes the family member photos, the blacklist photos and the portrait pictures uploaded by the client as training pictures to train the target detection model. During training, the self-training module 220 labels the training pictures, where the labels are: family members, blacklists and strangers, then the self-training module 220 inputs the training pictures into the target detection model, and adjusts parameters of the target detection model according to the labels, so that the detection results output by the target detection model are consistent with the labels of the training pictures. After the training is completed, the test picture is input into the trained target detection model to determine whether the performance of the target detection model meets the requirements.
In the embodiment of the present invention, the user may manage, including adding and deleting, the family member photos and the blacklist photos uploaded to the database unit 200 through the client 500. The user can also manually control the warning unit to give an alarm, manually give an alarm and the like when checking the real-time monitoring video.
An embodiment of the present invention further provides an intelligent home monitoring method, as shown in fig. 2, the method includes:
s200, acquiring a monitoring video;
s201, storing the monitoring video;
s202, determining whether a person exists according to the monitoring video, determining whether the person in the monitoring video is an abnormal person if the person exists, and sending alarm information to the client 500 when the person in the monitoring video is determined to be the abnormal person.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. An intelligent home monitoring system, comprising: the system comprises a monitoring unit (100), a database unit (200), a detection unit (300) and a client (500);
the monitoring unit (100) is used for acquiring a monitoring video;
the database unit (200) is used for storing the monitoring video;
the detection unit (300) is used for determining whether a person exists according to the monitoring video, determining whether the person in the monitoring video is an abnormal person if the person exists, and sending alarm information to the client (500) by the detection unit (300) when the person in the monitoring video is determined to be the abnormal person.
2. The intelligent home monitoring system according to claim 1, wherein when determining that there is a person in the monitored video, the detection unit (300) first determines whether the person in the monitored video is a family member, and if so, the detection unit (300) continues to monitor the monitored video; if the person in the surveillance video is not a family member, the detection unit (300) determines whether the person in the surveillance video is an abnormal person.
3. An intelligent home monitoring system according to claim 2, wherein when it is determined that the person in the monitored video is not a member of the family, the detection unit (300) obtains the monitored image in the monitored video and transmits the monitored image to the database unit (200) for storage by the database unit (200).
4. An intelligent home monitoring system according to claim 1, wherein the abnormal person comprises a blacklisted person, and when the detection unit (300) determines that the person in the monitoring video is a blacklisted person, an alarm message is immediately sent to the client (500).
5. The intelligent home monitoring system according to claim 1, further comprising an early warning unit (400), wherein the abnormal person comprises a stranger;
when the detection unit (300) determines that the person in the surveillance video is a stranger, the early warning unit (400) starts to monitor the surveillance video, and when the stranger in the surveillance video is determined to meet an early warning condition, the early warning unit (400) sends warning information to the client (500).
6. The intelligent home monitoring system according to claim 5, wherein the early warning condition is: and the time of strangers in the monitoring video reaches a preset value.
7. The intelligent home monitoring system according to claim 1, wherein the database unit (200) comprises a self-training module (220), the self-training module (220) is configured to train a target detection model according to the pictures transmitted by the client (500), and the detection unit (300) determines whether the person in the monitoring video is an abnormal person by using the target detection model.
8. An intelligent home monitoring system according to claim 1, wherein the database unit (200) further comprises a storage module (210), and the storage module (210) is configured to store the monitoring video.
9. The intelligent home monitoring system according to claim 1, further comprising an alarm unit, wherein the alarm unit is disposed on a door of a home of a user, and when the detection unit (300) sends alarm information to the client (500), the detection unit (300) further controls the alarm unit to operate.
10. A method applied to the intelligent home monitoring system according to any one of claims 1-9, comprising:
acquiring a monitoring video;
storing the monitoring video;
and determining whether a person exists according to the monitoring video, if so, determining whether the person in the monitoring video is an abnormal person, and sending alarm information to a client (500) when determining that the person in the monitoring video is the abnormal person.
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| CN202110783726.7A CN113538827A (en) | 2021-07-12 | 2021-07-12 | Intelligent home monitoring system and method |
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| CN202110783726.7A CN113538827A (en) | 2021-07-12 | 2021-07-12 | Intelligent home monitoring system and method |
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Cited By (1)
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| CN115273369A (en) * | 2022-07-22 | 2022-11-01 | 常州星宇车灯股份有限公司 | Intelligent household security monitoring device and monitoring method thereof |
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