CN112153279A - Intelligent device false wake-up filtering method and system - Google Patents
Intelligent device false wake-up filtering method and system Download PDFInfo
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- CN112153279A CN112153279A CN202010841488.6A CN202010841488A CN112153279A CN 112153279 A CN112153279 A CN 112153279A CN 202010841488 A CN202010841488 A CN 202010841488A CN 112153279 A CN112153279 A CN 112153279A
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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
- H04N23/60—Control of cameras or camera modules
- H04N23/65—Control of camera operation in relation to power supply
- H04N23/651—Control of camera operation in relation to power supply for reducing power consumption by affecting camera operations, e.g. sleep mode, hibernation mode or power off of selective parts of the camera
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Abstract
The invention provides a method and a system for filtering false awakening of intelligent equipment in the technical field of computers, wherein the method comprises the following steps: step S10, after the low-power consumption MCU receives the trigger signal of the passive infrared sensor, the low-power consumption camera is started; s20, the low-power consumption MCU receives the collected content of the low-power consumption camera, analyzes the collected content and generates an analysis result; and step S30, the low-power consumption MCU wakes up the main equipment based on the analysis result. The invention has the advantages that: the power consumption of the intelligent device is greatly reduced.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a system for filtering false awakening of intelligent equipment.
Background
Along with the progress of science and technology, a large number of intelligent equipment with cameras appear in the fields of security protection, monitoring and the like, and a plurality of intelligent equipment are installed at the positions of inconvenient power connection such as the open air, so that the power is supplied by a battery. In order to prolong the working time of the intelligent device, the following method is conventionally adopted: the intelligent device is in a dormant state (most power is turned off) at ordinary times, and the intelligent device is awakened through a passive infrared sensor (PIR) or low-power-consumption WIFI.
However, the conventional method has the following disadvantages: 1. the passive infrared sensor is easily interfered by various heat sources, light sources and radio frequency radiation due to small signal amplitude, so that the infrared radiation of a human body is easily shielded, the sensitivity is reduced when the ambient temperature and the human body temperature are close to each other, and the detection capability of the passive infrared sensor on a radial moving object is poor due to the fact that the detection moving direction is transverse, so that the intelligent device is often awakened by mistake, and the overall power consumption is overhigh; 2. although the power consumption of the low-power-consumption WIFI is low, compared with a passive infrared sensor, the WIFI consumes power all the time, and the service time of a battery is reduced.
Therefore, how to provide a method and a system for filtering false wake-up of an intelligent device to reduce power consumption of the intelligent device becomes a problem to be solved urgently.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method and a system for filtering false wake-up of an intelligent device, so as to reduce the power consumption of the intelligent device.
In a first aspect, the present invention provides a method for filtering false wake-up of an intelligent device, including the following steps:
step S10, after the low-power consumption MCU receives the trigger signal of the passive infrared sensor, the low-power consumption camera is started;
s20, the low-power consumption MCU receives the collected content of the low-power consumption camera, analyzes the collected content and generates an analysis result;
and step S30, the low-power consumption MCU wakes up the main equipment based on the analysis result.
Further, the step S10 is specifically:
the low-power consumption MCU sets the induction sensitivity of a passive infrared sensor, judges whether the induction value of a trigger signal is matched with the induction sensitivity after receiving the trigger signal of the passive infrared sensor, and supplies power to the low-power consumption camera if the induction value of the trigger signal is matched with the induction sensitivity so as to start the low-power consumption camera; if not, the flow is ended.
Further, the step S20 is specifically:
and after the low-power consumption MCU receives the acquisition content of the preset duration or the preset size of the low-power consumption camera, the low-power consumption camera is closed, the acquisition content is analyzed by utilizing a machine learning technology, and an analysis result of whether a person or an object exists is generated.
Further, in step S20, the captured content is a photo, a video, or an audio.
Further, the step S30 is specifically:
the low-power-consumption MCU judges whether a person or an object exists or not based on the analysis result, if so, the MCU supplies power to the main equipment, and then awakens the main equipment; if not, the flow is ended.
In a second aspect, the present invention provides a system for filtering false wake-up of an intelligent device, including the following modules:
the passive infrared sensor sensing module is used for starting the low-power-consumption camera after the low-power-consumption MCU receives a trigger signal of the passive infrared sensor;
the acquisition content analysis module is used for receiving the acquisition content of the low-power-consumption camera by the low-power-consumption MCU, analyzing the acquisition content and generating an analysis result;
and the main equipment awakening module is used for awakening the main equipment by the low-power consumption MCU based on the analysis result.
Further, the passive infrared sensor sensing module specifically is:
the low-power consumption MCU sets the induction sensitivity of a passive infrared sensor, judges whether the induction value of a trigger signal is matched with the induction sensitivity after receiving the trigger signal of the passive infrared sensor, and supplies power to the low-power consumption camera if the induction value of the trigger signal is matched with the induction sensitivity so as to start the low-power consumption camera; if not, the flow is ended.
Further, the collected content analysis module specifically includes:
and after the low-power consumption MCU receives the acquisition content of the preset duration or the preset size of the low-power consumption camera, the low-power consumption camera is closed, the acquisition content is analyzed by utilizing a machine learning technology, and an analysis result of whether a person or an object exists is generated.
Further, in the collected content analysis module, the collected content is a photo, a video or an audio.
Further, the main device wake-up module specifically includes:
the low-power-consumption MCU judges whether a person or an object exists or not based on the analysis result, if so, the MCU supplies power to the main equipment, and then awakens the main equipment; if not, the flow is ended.
The invention has the advantages that:
because the passive infrared sensor does not emit any energy and only passively receives and detects infrared radiation from the environment, the trigger signal is sent to the low-power consumption MCU through the passive infrared sensor, the low-power consumption MCU restarts the low-power consumption camera to acquire the acquisition content, and the acquisition content is analyzed and judged by utilizing the machine learning technology to judge whether a person or an object exists, namely, the trigger signal of the passive infrared sensor is secondarily verified, a mistaken awakening event is filtered, when the person or the object is judged to exist actually, the main equipment is awakened again, frequent awakening of the main equipment is avoided, further, the power consumption of the intelligent equipment is greatly reduced, and the service life of the battery is greatly prolonged.
Drawings
The invention will be further described with reference to the following examples with reference to the accompanying drawings.
Fig. 1 is a flowchart of a method for filtering false wake-up of an intelligent device according to the present invention.
Fig. 2 is a schematic structural diagram of a false wake-up filtering system for an intelligent device according to the present invention.
Fig. 3 is a schematic block circuit diagram of an intelligent device of the present invention.
Description of the labeling:
1-main equipment, 2-low-power consumption MCU, 3-low-power consumption camera, 4-passive infrared sensor and 5-power module.
Detailed Description
The technical scheme in the embodiment of the application has the following general idea: because main equipment power consumption is big, consequently set up a low-power consumption MCU and a low-power consumption camera, after passive infrared sensor is triggered, low-power consumption MCU acquires the collection content of photo, video or audio through the low-power consumption camera, carries out the analysis to the collection content again, confirms that just start main equipment after the mistake awakens the incident, and then reduces intelligent device's consumption.
The invention needs to be applied to the intelligent equipment which comprises a main device 1, a low-power consumption MCU2, a low-power consumption camera 3, a passive infrared sensor 4 and a power module 5;
one end of the low-power consumption MCU2 is connected with the main device 1, and the other end is connected with the low-power consumption camera 3 and the passive infrared sensor 4; the low-power consumption MCU2, the low-power consumption camera 3 and the main device 1 are all connected with the power module 5.
The main device 1 is a main device of an intelligent device, and consumes most of electric energy of the power module 5; the low-power consumption MCU2 is configured to receive a trigger signal of the passive infrared sensor 4, control the low-power consumption camera 3 and the master device 1 to be turned on and off through the power module 5, receive the acquired content of the low-power consumption camera 3, and analyze the acquired content, and in specific implementation, the MCU capable of implementing this function is selected from the prior art, and is not limited to any model, such as RK2108, and the control program is well known to those skilled in the art, which is available to those skilled in the art without creative work; the low-power consumption camera 3 is used for collecting photos, videos or audios; the passive infrared sensor 4 is used for carrying out preliminary monitoring on whether people and objects exist; the power module 5 is used for supplying power to the intelligent equipment.
Referring to fig. 1 to fig. 3, a preferred embodiment of a method for filtering false wake-up of an intelligent device according to the present invention includes the following steps:
step S10, after the low-power consumption MCU receives the trigger signal of the passive infrared sensor, the low-power consumption camera is started; the passive infrared sensor does not emit any energy and only passively receives and detects infrared radiation from the environment, and has the advantages of good concealment, low power consumption, low price and the like;
s20, the low-power consumption MCU receives the collected content of the low-power consumption camera, analyzes the collected content and generates an analysis result;
step S30, the low-power consumption MCU wakes up the main device based on the analysis result; after the passive infrared sensor is triggered, secondary verification of the low-power consumption MCU is needed, the main equipment is awakened after the verification is passed, and the phenomenon that the electric energy is wasted due to frequent awakening of the main equipment is avoided.
The step S10 specifically includes:
the low-power consumption MCU sets the induction sensitivity of a passive infrared sensor, judges whether the induction value of a trigger signal is matched with the induction sensitivity after receiving the trigger signal of the passive infrared sensor, and supplies power to the low-power consumption camera through the power module if the induction value of the trigger signal is matched with the induction sensitivity so as to start the low-power consumption camera; if not, the flow is ended.
The sensing sensitivity is a sensing threshold interval of a sensing value of the passive infrared sensor, and only when the sensing value of the trigger signal is in the sensing threshold interval, the low-power-consumption camera is started, so that the situation that the low-power-consumption camera is frequently started to consume electric energy is avoided, and the power consumption of the intelligent device is further reduced.
The step S20 specifically includes:
and after the low-power consumption MCU receives the acquisition content of the preset duration or the preset size of the low-power consumption camera, the low-power consumption camera is closed, the acquisition content is analyzed by utilizing a machine learning technology, and an analysis result of whether a person or an object exists is generated.
The preset time length or the preset size which is enough for analysis is preset through the low-power consumption MCU, and the low-power consumption camera is closed after the preset time length or the preset size acquisition content is acquired by the low-power consumption camera, so that the waste of electric energy caused by long-time opening of the low-power consumption camera is avoided.
The machine learning technology is utilized to analyze the photo, the video or the audio, and whether a person or an object invades is judged to be the prior art. For example, after a large number of sample pictures are input into the neural network model for iterative training, pictures collected by the low-power-consumption camera are input into the trained model, and then whether people or objects exist can be immediately judged.
In step S20, the captured content is a photo, a video, or an audio.
The step S30 specifically includes:
the low-power-consumption MCU judges whether a person or an object exists or not based on the analysis result, if so, the power module supplies power to the main equipment, and then the main equipment is awakened; if not, the process is ended, and the main equipment is prevented from being frequently awakened.
The invention discloses a preferred embodiment of a false wake-up filtering system of intelligent equipment, which comprises the following modules:
the passive infrared sensor sensing module is used for starting the low-power-consumption camera after the low-power-consumption MCU receives a trigger signal of the passive infrared sensor; the passive infrared sensor does not emit any energy and only passively receives and detects infrared radiation from the environment, and has the advantages of good concealment, low power consumption, low price and the like;
the acquisition content analysis module is used for receiving the acquisition content of the low-power-consumption camera by the low-power-consumption MCU, analyzing the acquisition content and generating an analysis result;
the main equipment awakening module is used for awakening the main equipment by the low-power consumption MCU based on the analysis result; after the passive infrared sensor is triggered, secondary verification of the low-power consumption MCU is needed, the main equipment is awakened after the verification is passed, and the phenomenon that the electric energy is wasted due to frequent awakening of the main equipment is avoided.
The passive infrared sensor induction module specifically comprises:
the low-power consumption MCU sets the induction sensitivity of a passive infrared sensor, judges whether the induction value of a trigger signal is matched with the induction sensitivity after receiving the trigger signal of the passive infrared sensor, and supplies power to the low-power consumption camera through the power module if the induction value of the trigger signal is matched with the induction sensitivity so as to start the low-power consumption camera; if not, the flow is ended.
The sensing sensitivity is a sensing threshold interval of a sensing value of the passive infrared sensor, and only when the sensing value of the trigger signal is in the sensing threshold interval, the low-power-consumption camera is started, so that the situation that the low-power-consumption camera is frequently started to consume electric energy is avoided, and the power consumption of the intelligent device is further reduced.
The acquisition content analysis module specifically comprises:
and after the low-power consumption MCU receives the acquisition content of the preset duration or the preset size of the low-power consumption camera, the low-power consumption camera is closed, the acquisition content is analyzed by utilizing a machine learning technology, and an analysis result of whether a person or an object exists is generated.
The preset time length or the preset size which is enough for analysis is preset through the low-power consumption MCU, and the low-power consumption camera is closed after the preset time length or the preset size acquisition content is acquired by the low-power consumption camera, so that the waste of electric energy caused by long-time opening of the low-power consumption camera is avoided.
The machine learning technology is utilized to analyze the photo, the video or the audio, and whether a person or an object invades is judged to be the prior art. For example, after a large number of sample pictures are input into the neural network model for iterative training, pictures collected by the low-power-consumption camera are input into the trained model, and then whether people or objects exist can be immediately judged.
In the collected content analysis module, the collected content is a photo, a video or an audio.
The main equipment awakening module specifically comprises:
the low-power-consumption MCU judges whether a person or an object exists or not based on the analysis result, if so, the power module supplies power to the main equipment, and then the main equipment is awakened; if not, the process is ended, and the main equipment is prevented from being frequently awakened.
In summary, the invention has the advantages that:
because the passive infrared sensor does not emit any energy and only passively receives and detects infrared radiation from the environment, the trigger signal is sent to the low-power consumption MCU through the passive infrared sensor, the low-power consumption MCU restarts the low-power consumption camera to acquire the acquisition content, and the acquisition content is analyzed and judged by utilizing the machine learning technology to judge whether a person or an object exists, namely, the trigger signal of the passive infrared sensor is secondarily verified, a mistaken awakening event is filtered, when the person or the object is judged to exist actually, the main equipment is awakened again, frequent awakening of the main equipment is avoided, further, the power consumption of the intelligent equipment is greatly reduced, and the service life of the battery is greatly prolonged.
Although specific embodiments of the invention have been described above, it will be understood by those skilled in the art that the specific embodiments described are illustrative only and are not limiting upon the scope of the invention, and that equivalent modifications and variations can be made by those skilled in the art without departing from the spirit of the invention, which is to be limited only by the appended claims.
Claims (10)
1. A method for filtering false awakening of intelligent equipment is characterized by comprising the following steps: the method comprises the following steps:
step S10, after the low-power consumption MCU receives the trigger signal of the passive infrared sensor, the low-power consumption camera is started;
s20, the low-power consumption MCU receives the collected content of the low-power consumption camera, analyzes the collected content and generates an analysis result;
and step S30, the low-power consumption MCU wakes up the main equipment based on the analysis result.
2. The method for filtering false wake-up of intelligent equipment according to claim 1, wherein: the step S10 specifically includes:
the low-power consumption MCU sets the induction sensitivity of a passive infrared sensor, judges whether the induction value of a trigger signal is matched with the induction sensitivity after receiving the trigger signal of the passive infrared sensor, and supplies power to the low-power consumption camera if the induction value of the trigger signal is matched with the induction sensitivity so as to start the low-power consumption camera; if not, the flow is ended.
3. The method for filtering false wake-up of intelligent equipment according to claim 1, wherein: the step S20 specifically includes:
and after the low-power consumption MCU receives the acquisition content of the preset duration or the preset size of the low-power consumption camera, the low-power consumption camera is closed, the acquisition content is analyzed by utilizing a machine learning technology, and an analysis result of whether a person or an object exists is generated.
4. The method for filtering false wake-up of intelligent equipment according to claim 1, wherein: in step S20, the captured content is a photo, a video, or an audio.
5. The method for filtering false wake-up of intelligent equipment according to claim 1, wherein: the step S30 specifically includes:
the low-power-consumption MCU judges whether a person or an object exists or not based on the analysis result, if so, the MCU supplies power to the main equipment, and then awakens the main equipment; if not, the flow is ended.
6. The utility model provides a smart machine mistake awakens filtration system up which characterized in that: the system comprises the following modules:
the passive infrared sensor sensing module is used for starting the low-power-consumption camera after the low-power-consumption MCU receives a trigger signal of the passive infrared sensor;
the acquisition content analysis module is used for receiving the acquisition content of the low-power-consumption camera by the low-power-consumption MCU, analyzing the acquisition content and generating an analysis result;
and the main equipment awakening module is used for awakening the main equipment by the low-power consumption MCU based on the analysis result.
7. The smart device false wake-up filtering system of claim 6, wherein: the passive infrared sensor induction module specifically comprises:
the low-power consumption MCU sets the induction sensitivity of a passive infrared sensor, judges whether the induction value of a trigger signal is matched with the induction sensitivity after receiving the trigger signal of the passive infrared sensor, and supplies power to the low-power consumption camera if the induction value of the trigger signal is matched with the induction sensitivity so as to start the low-power consumption camera; if not, the flow is ended.
8. The smart device false wake-up filtering system of claim 6, wherein: the acquisition content analysis module specifically comprises:
and after the low-power consumption MCU receives the acquisition content of the preset duration or the preset size of the low-power consumption camera, the low-power consumption camera is closed, the acquisition content is analyzed by utilizing a machine learning technology, and an analysis result of whether a person or an object exists is generated.
9. The smart device false wake-up filtering system of claim 6, wherein: in the collected content analysis module, the collected content is a photo, a video or an audio.
10. The smart device false wake-up filtering system of claim 6, wherein: the main equipment awakening module specifically comprises:
the low-power-consumption MCU judges whether a person or an object exists or not based on the analysis result, if so, the MCU supplies power to the main equipment, and then awakens the main equipment; if not, the flow is ended.
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