CN103576660A - Intelligent home monitoring system and method - Google Patents
Intelligent home monitoring system and method Download PDFInfo
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- CN103576660A CN103576660A CN201310565632.8A CN201310565632A CN103576660A CN 103576660 A CN103576660 A CN 103576660A CN 201310565632 A CN201310565632 A CN 201310565632A CN 103576660 A CN103576660 A CN 103576660A
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Abstract
The invention discloses an intelligent home monitoring system which comprises a monitoring terminal, a control platform and an information receiving terminal. The monitoring terminal comprises a digit camera and a voice collector and is used for collecting images and voice in a monitor environment and transmitting the collected data to the control platform. The control platform comprises an image processing system and a voice processing system and is used for processing the received image data and the voice data, judging whether an emergency exists or not and transmitting an alarming signal to the information receiving terminal. According to the intelligent home monitoring system, the voice and image processing technology is applied to all-around monitoring and nursing on the home environment and different requirements for home safety of life of people in modern times can be met. Multiple different manners are combined for processing and analyzing the data and accuracy and effectiveness of monitoring can be ensured.
Description
Technical field
The system that the present invention relates to a kind of Smart Home monitoring, relates in particular to a kind of system and method thereof of utilizing image and voice recognition to carry out Household monitor.
Background technology
Along with social development and progress, on sufficient material base, people start to pay close attention to a kind of more comfortable, convenient and intelligent life style and attitude.The concept of " Smart Home " embodies the pursuit of people to intelligentized comfortable life, meanwhile, people to the requirement of security also in continuous lifting.
Along with social development, demographic dividend fades away, aging population becomes increasingly conspicuous, and adds that more and more faster city life rhythm allows younger generation have to drop into more time and energy on work, and not free the old man of family and child are nursed and looked after.
Existing Intelligent home monitoring system is mostly by carrying out security monitoring at detection instruments such as door, window installation infrared lines.Its function singleness, can not meet home furnishings intelligent monitoring other demands such as nurse to kinsfolk, and its security is limited in addition, and lawless person is easy to detection instrument is removed and made supervisory system ineffective.
Summary of the invention
Technical matters to be solved by this invention is, a kind of Intelligent home monitoring system is provided, comprise that monitor terminal, control platform and information receiving terminal is characterized in that, described monitor terminal comprises digit camera and sound collector, and monitoring environment is carried out to image and sound gathers and the data that collect are sent to control platform; Described control platform comprises image processing system and sound processing system, and the image data set voice data receiving is processed, and judges whether to be in an emergency and sends alarm signal to information receiving terminal.
Further, described monitor terminal is intelligent robot, and described intelligent robot is equipped with sonar unit can the auxiliary intelligent monitoring to household of sensing surrounding environment.
Further, described monitor terminal can be fixing camera, by camera being installed in a plurality of corners of household, each corner of household is monitored.
Described method comprises:
S1 gathers the characteristic information of domestic environment and kinsfolk's picture;
Step S1 comprises:
S11 transfers the picture pixel of shooting to HSV color space pattern by rgb color space pattern, adopts the HSV can color combining information and textural characteristics, can improve widely discrimination power and can identification scope.
S12 is quantified as respectively 8,3,3 regions by H, S in HSV color space pattern, V, thereby the value of photo pixel is quantified as to 72 looks; The result that each pixel (H, S, V) of image is quantized be (H`, S`, V`), on HSV color space be quantified as 72 looks can reduce afterwards aberration on image ratio on impact and reduce the image processing time;
S13 is converted to planimetric coordinates by the picture pixel after quantizing, and transformation result is (H``, S``, V``).
S14 is used edge detection calculation to go out the variation tendency of X-axis and Y-axis the photo pixel value that is converted to planimetric coordinates.
Further, by step S14, obtain two vectors and calculate this two vectorial angle theta, can be used for judgement whether similar on the attribute at certain edge.
S15 obtains the microstructure features on photo, and its method is specially,
S151 is cut into several nonoverlapping square microstructure area by picture;
S152 compares the surrounding pixel point in each microstructure area and central pixel point;
S153 retains the surrounding pixel point identical with central pixel point, otherwise deletes;
S154 by the comparison position, center of microstructure area by centre turn right successively, under, bottom right moves a pixel, image is re-started and is cut apart, then carry out the determining step of (S53);
S155 merges the reservation pixel after above-mentioned four kinds of blocks cutting computing, obtains required microstructure features.
S156 compares surrounding pixel point in each microstructure unit region and central pixel point;
S157 retains the pixel identical with central pixel point, otherwise deletes.
The feature locations that S16 obtains step S15 combines with the color data that step S2 obtains
The feature that S17 obtains step S16 is used the proper vector of statistics with histogram picture,
Radius and the center of circle that the feature calculation that S171 is obtained by step S6 is published picture and looked like size and calculate minimum circumscribed circle;
S172 is overlapping by the circumscribed circle center of circle of polar center of circle and above-mentioned steps, and circumscribed circle is divided into the region that several concentric circless form;
S173 records and uses statistics with histogram by the corresponding characteristic in each region.
Finally, the picture feature vector and the picture feature vector in database that obtain are compared, utilize Euclidean distance to determine the Item Information of captured photo.
Wherein P and Q are respectively picture in database and the picture of shooting, and i and j represent the statistics number in each interval in histogram.
Further, the length that step S4 carries out calculating object after rim detection to planimetric coordinates is with wide, and by the central point of characteristic area and move to the central point after photo quantification.
In a three dimensions, if an axle is wherein fixed to (as z axle), through rotation arbitrarily, its parameter may change, but functional value remains unchanged, calculate object length and wide after can draw object center, with this, can accurately to it, carry out obtaining of feature when the object different rotation angle.
Further, in order further to improve accuracy rate and the identification range of identification, except obtaining the characteristic of former photo contrasts, also comprise that the upset of photo characteristic level, flip vertical and pixel shift are obtained to characteristic to be contrasted again.
S18 is by the proper vector storage of obtaining.
S2 monitors in real time to domestic environment;
During monitoring, adopt the method for S1 to gather the realtime image data of domestic environment, and the environment of data and storage and kinsfolk's feature are compared.
When appearring in S3, dangerous situation sends alarm signal to information receiving terminal;
Wherein, the people that the dangerous situation described in S3 includes non-kinsfolk occurs, the falling down and occur the sound that child crys of the toppling over of target furniture, old man's walking.
To the judgement of child's abnormal conditions, can judge by setting sound decibel and the threshold value of duration; Also can train again the sound of implementing to obtain is contrasted to judgement with it by the data of sound that child is cryed.
Further, real time data with storage Data Comparison comprise profile to the when contrast of height of C.G..
Wherein the calculation procedure of gravity center of human body's height comprises:
1, calculate the center of gravity of head and foot;
While calculating head and foot's center of gravity, task image need be divided into head zone and foot areas, wherein, described head zone height accounts for 20% of height, and described foot areas height accounts for 33% of height.
Further, head center of gravity is chosen 65% pixel downwards by the top of described head zone and is determined, head center of gravity is defined as this pixel to the distance of borderline each point of head with for minimum.
Foot's center of gravity is that foot areas bottom is upwards chosen 25% pixel and determined.
Preferably, consider that people squats down or the difference of other actions when standing, described foot center of gravity is that foot areas bottom is upwards chosen 12.5% pixel and determined.
2, calculate leg-of-mutton area and the height being formed by head and 3 of foots;
3, by triangle area, calculated at the leg-of-mutton end with high;
The present invention adopts SVM(support vector machine) train, preferably adopt Polynomial function to carry out identification, classification.
Further, for furniture topple over surrounding environment in the monitoring of people's face adopt the method for S1 to carry out feature extraction to image, and contrast and then judge furniture with the proper vector of storage and whether topple over and whether occurred strange face.
Further, when family window or balcony have abnormal people's turnover, also can trigger alarm, thereby effectively avoid burglar's turnover or family old man, child to occur accident.
Further, when sending alarm signal, information receiving terminal also sends real time picture.
Information receiving terminal of the present invention comprises especially mobile device of equipment that mobile phone, computer, panel computer, TV etc. can receive word, pictorial information.
Implement the present invention, there is following beneficial effect:
The present invention adopts sound and image processing techniques to carry out omnibearing monitoring and nurse to domestic environment, can meet the different requirements of modern's life to house security, and carry out data processing and analysis in conjunction with multitude of different ways, guarantee accuracy rate and the validity of monitoring.
Accompanying drawing explanation
Fig. 1 is first embodiment of the invention structural representation;
Fig. 2 is second embodiment of the invention structural representation.
Embodiment
For making the object, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing, the present invention is described in further detail.
As shown in Figure 1, system of the present invention comprises that mobile monitoring terminal, control platform and information receiving terminal are some, and in the present embodiment, information receiving terminal is 2, comprises mobile phone or apparatus such as computer.Described monitor terminal comprises digit camera and sound collector, the preferred intelligent robot of the present embodiment, and a plurality of domestic environments are carried out to image in described robot and sound gathers and the data that collect are sent to control platform; Described control platform comprises image processing system and sound processing system, and the image data set voice data receiving is processed, and judges whether to be in an emergency and sends alarm signal to information receiving terminal.
Fig. 2 is the another kind of implementation of the present invention, the difference of the implementation shown in itself and Fig. 1 is to adopt fixing monitor terminal to replace mobile monitoring terminal, the corresponding domestic environment of each fixing monitor terminal, domestic environment and fixing monitor terminal respectively have three in the present embodiment.
Embodiment 1
Adopt the present invention to carry out security monitoring to family, prevent that burglar from entering.Its main implementation is by gathering and store the characteristic information of domestic environment and kinsfolk's picture, when monitoring, the realtime graphic photographing is carried out to data processing, and calculate relatively by the characteristic of picture, thereby whether the people who judges in present monitoring range belongs to stranger, if so, as information receiving terminal, send alarm signal.
The principle that realizes of said method is:
S1 gathers the characteristic information of domestic environment and kinsfolk's picture;
Step S1 comprises,
S11 transfers the picture pixel of shooting to HSV color space pattern by rgb color space pattern, and the formula of conversion is
Wherein
with
fen Do As obtains the great Zhi With minimum value in RGB Se Cai Kong Inter, adopts the HSV can color combining information and textural characteristics, can improve widely discrimination power and can identification scope.
S12 is quantified as respectively 8,3,3 regions by H, S in HSV color space pattern, V, thereby the value of photo pixel is quantified as to 72 looks; The result that each pixel (H, S, V) of image is quantized be (H`, S`, V`), on HSV color space be quantified as 72 looks can reduce afterwards aberration on image ratio on impact and reduce the image processing time;
S13 is converted to planimetric coordinates by the picture pixel after quantizing, and transformation result is (H``, S``, V``), and its method is
S14 is used edge detection calculation to go out the variation tendency of X-axis and Y-axis the photo pixel value that is converted to planimetric coordinates, and the formula of detection is:
；
Further, by step S14, obtained two vectors and calculated this two vectorial angle theta, can be used for judgement whether similar on the attribute at certain edge, the computing formula of angle theta is:
S15 obtains the microstructure features on photo, and its method is specially,
S151 is cut into several nonoverlapping square microstructure area by picture;
S152 compares the surrounding pixel point in each microstructure area and central pixel point;
S153 retains the surrounding pixel point identical with central pixel point, otherwise deletes;
S154 by the comparison position, center of microstructure area by centre turn right successively, under, bottom right moves a pixel, image is re-started and is cut apart, then carry out the determining step of (S53);
S155 merges the reservation pixel after above-mentioned four kinds of blocks cutting computing, obtains required microstructure features.
S156 compares surrounding pixel point in each microstructure unit region and central pixel point;
S157 retains the pixel identical with central pixel point, otherwise deletes.
The feature locations that S16 obtains step S15 combines with the color data that step S2 obtains, and formula is:
Wherein, M (i, j) is architectural feature, and C (i, j) is the feature of HSV color space.
The feature that S17 obtains step S16 is used the proper vector of statistics with histogram picture,
Radius and the center of circle that the feature calculation that S171 is obtained by step S6 is published picture and looked like size and calculate minimum circumscribed circle;
S172 is overlapping by the circumscribed circle center of circle of polar center of circle and above-mentioned steps, and circumscribed circle is divided into the region that several concentric circless form;
S173 records and uses statistics with histogram by the corresponding characteristic in each region.
Finally, the picture feature vector and the picture feature vector in database that obtain are compared, utilize Euclidean distance to determine the Item Information of captured photo.
Particularly, by the characteristic quantification obtaining, be several intervals, be preferably 12, be divided into from inside to outside several concentric circless, be preferably 3, therefore in preferred version of the present invention, have 36 characteristic areas.
Radius and the center of circle that the feature calculation being obtained by step S16 is published picture and looked like size and calculate minimum circumscribed circle, again that the circumscribed circle center of circle of polar center of circle and above-mentioned steps is overlapping, finally the unique point obtaining is corresponded on polar coordinates, the feature record statistics in each polar coordinates interval is got up and added up with histogram.
The judgment formula of Euclidean distance is:
Wherein P and Q are respectively picture in database and the picture of shooting, and i and j represent the statistics number in each interval in histogram.
Further, the length that step S4 carries out calculating object after rim detection to planimetric coordinates is with wide, and by the central point of characteristic area and move to the central point after photo quantification.
In a three dimensions, if an axle is wherein fixed to (as z axle), through rotation arbitrarily, its parameter may change, but functional value remains unchanged, calculate object length and wide after can draw object center, with this, can accurately to it, carry out obtaining of feature when the object different rotation angle.
Further, in order further to improve accuracy rate and the identification range of identification, except obtaining the characteristic of former photo contrasts, also comprise that the upset of photo characteristic level, flip vertical and pixel shift are obtained to characteristic to be contrasted again.
S18 is by the proper vector storage of obtaining.
S2 monitors in real time to domestic environment;
During monitoring, adopt the method for S1 to gather the realtime image data of domestic environment, and the environment of data and storage and kinsfolk's feature are compared.
Embodiment 2
Another purposes of the present invention is that the old man in solely looking after the house is nursed, and signal gives the alarm when Falls Among Old People.
The mode of judgement Falls Among Old People is that while utilizing people to walk, the variation of center of gravity judges, the computing method of gravity center of human body's height are adopted to triangle core computing method, is specially:
1, calculate the center of gravity of head and foot;
While calculating head and foot's center of gravity, task image need be divided into head zone and foot areas, wherein, described head zone height accounts for 20% of height, and described foot areas height accounts for 33% of height.
Further, head center of gravity is chosen 65% pixel downwards by the top of described head zone and is determined, head center of gravity is defined as this pixel to the distance of borderline each point of head with for minimum.
Foot's center of gravity is that foot areas bottom is upwards chosen 25% pixel and determined.
Preferably, consider that people squats down or the difference of other actions when standing, described foot center of gravity is that foot areas bottom is upwards chosen 12.5% pixel and determined.
2, calculate leg-of-mutton area and the height being formed by head and 3 of foots;
3, by triangle area, calculated at the leg-of-mutton end with high;
After head is found out with three centers of gravity of both feet, three centers of gravity that utilization is found are out carried out the calculating of Vector triangle, judge in picture that personage is that to stand be also non-posture of standing, the method of judgement is that these three focus points are linked to be to a triangle, the center of gravity that makes head is A, and the center of gravity of bipod is B and C, and the limit that angle A is right is a, the limit that angle B is right is b, and the limit that angle C is right is c.With 2 range formulas, calculate after leg-of-mutton three length of side a, b and c, utilize formula (1) and (2) to calculate leg-of-mutton area, with area and a, calculate height again, calculate and adopt formula (3), the end BC drawing is the spacing of bipod center of gravity, the height of head center of gravity is h, calculate again the ratio v at high and the end, as formula (4), and then judge whether that the threshold value T that surpasses definition judges whether people stands, if value is greater than T and is judged to be and stands, be less than T and be judged to be non-standing.
（4）
The present invention adopts SVM(support vector machine) train, preferably adopt Polynomial function to carry out identification, classification.
By the image personage center-of-gravity value of Real-time Obtaining and threshold value T comparison, be greater than T for standing, being less than T is non-standing.
Preferably, described threshold value T is 3 ~ 3.5.
Embodiment 3
Toppling over of the especially large furniture of family furniture often means that unusual condition appears in domestic environment, for the monitoring method reference example 1 of furniture state, whether the angle that the image feature vector of the furniture image feature vector real-time monitoring and storage was contrasted and calculated the two can be judged furniture and topple over.
Preferably, can also whether the furniture of ad-hoc location be lost and be judged according to this method, important furniture is extracted separately to image feature vector storage.Realtime graphic and original image are carried out carrying out additive operation after binaryzation, and the proper vector of the distinguishing characteristics drawing and the important furniture of storage is identical represents that the furniture of this position loses, and now triggers alarm.
Embodiment 4
By the sound collector of monitor terminal, can collect monitor terminal sound around, when collecting child's sound, over certain decibel certain time, give the alarm.
Preferably, the sound of triggering alarm need be greater than 55 decibels.
Preferably, the sonar unit that described monitor terminal utilization is equipped with, the photo that can move and take to the sound source of triggering alarm the sound source of sounding is sent to described information receiving terminal.
Preferably, when being greater than the value that the frequency of setting decibel value and sending within a period of time is greater than setting, sound also can trigger above-mentioned alarm, as family is moved the noise that article send frequently after entering burglar.
The above is the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the premise without departing from the principles of the invention; can also make some improvements and modifications, these improvements and modifications are also considered as protection scope of the present invention.
Claims (9)
1. an Intelligent home monitoring system, comprise monitor terminal, control platform and information receiving terminal, it is characterized in that, described monitor terminal comprises digit camera and sound collector, and monitoring environment is carried out to image and sound gathers and the data that collect are sent to control platform; Described control platform comprises image processing system and sound processing system, and the image data set voice data receiving is processed, and judges whether to be in an emergency and sends alarm signal to information receiving terminal.
2. supervisory system according to claim 1, is characterized in that, described monitor terminal is intelligent robot.
3. supervisory system according to claim 2, is characterized in that, described intelligent robot is equipped with sonar unit.
4. supervisory system according to claim 1, is characterized in that, described monitor terminal is fixing camera.
5. a supervisory system Smart Home method for supervising described in employing claim 1, is characterized in that, described method comprises:
S1 gathers the characteristic information of domestic environment and kinsfolk's picture;
S2 monitors in real time to domestic environment;
When appearring in S3, dangerous situation sends alarm signal to information receiving terminal;
Wherein, the people that the dangerous situation described in S3 includes non-kinsfolk occurs, the falling down and occur the sound that child crys of the toppling over of target furniture, old man's walking.
6. method for supervising according to claim 5, is characterized in that, step S1 comprises,
S11 transfers the picture pixel of shooting to HSV color space pattern by rgb color space pattern;
S12 is quantified as respectively 8,3,3 regions by H, S in HSV color space pattern, V, thereby the value of photo pixel is quantified as to 72 looks;
S13 is converted to planimetric coordinates by the picture pixel after quantizing;
S14 is used edge detection calculation to go out the variation tendency of X-axis and Y-axis the photo pixel value that is converted to planimetric coordinates;
S15 obtains the microstructure features on photo;
The feature locations that S16 obtains step S15 combines with the color data that step S2 obtains;
The feature that S17 obtains step S16 is used the proper vector of statistics with histogram picture;
S18 is by the proper vector storage of obtaining.
7. according to the method for supervising described in claim 5 or 6, it is characterized in that, during monitoring, adopt the method for S1 to gather the realtime image data of domestic environment, and the environment of data and storage and kinsfolk's feature are compared.
8. method for supervising according to claim 7, is characterized in that, real time data with storage Data Comparison comprise profile to the when contrast of height of C.G..
9. method for supervising according to claim 5, is characterized in that, also sends real time picture when information receiving terminal sends alarm signal.
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Cited By (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104020745A (en) * | 2014-06-18 | 2014-09-03 | 吴林涛 | Intelligent household system |
| CN104519322A (en) * | 2014-12-24 | 2015-04-15 | 安徽科鸣三维科技有限公司 | Machine vision target tracking system |
| CN105554476A (en) * | 2016-02-04 | 2016-05-04 | 武克易 | IoT (Internet of Things) intelligent device with nursing function |
| CN105678958A (en) * | 2016-03-11 | 2016-06-15 | 深圳前海勇艺达机器人有限公司 | Robot-based human body tumble monitoring system |
| CN105681062A (en) * | 2014-11-18 | 2016-06-15 | 小米科技有限责任公司 | Safety monitoring method and apparatus |
| WO2016107006A1 (en) * | 2014-12-31 | 2016-07-07 | 中兴通讯股份有限公司 | Intelligent camera monitoring method and apparatus |
| CN106003047A (en) * | 2016-06-28 | 2016-10-12 | 北京光年无限科技有限公司 | Danger early warning method and device for intelligent robot |
| CN106027978A (en) * | 2016-06-21 | 2016-10-12 | 南京工业大学 | Smart home old age support video monitoring abnormal behavior system and method |
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| CN107186718A (en) * | 2017-06-06 | 2017-09-22 | 河池学院 | A kind of household robot control system and its control method |
| CN107734213A (en) * | 2016-08-11 | 2018-02-23 | 漳州立达信光电子科技有限公司 | Intelligent domestic electronic installation and system |
| CN108538035A (en) * | 2018-05-31 | 2018-09-14 | 南京博联智能科技有限公司 | Indoor security control method, electronic equipment, storage medium and system |
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| CN109147277A (en) * | 2018-09-30 | 2019-01-04 | 桂林海威科技股份有限公司 | A kind of old man care system and method |
| CN109194713A (en) * | 2018-08-01 | 2019-01-11 | 浙江深眸科技有限公司 | Client for robot detection alarm |
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| CN111811635A (en) * | 2020-07-07 | 2020-10-23 | 美钻石油钻采系统(上海)有限公司 | Underwater target monitoring device |
| TWI721885B (en) * | 2020-05-14 | 2021-03-11 | 雲云科技股份有限公司 | Visible-light-image physiological monitoring system with thermal detecting assistance |
| CN113552889A (en) * | 2021-07-29 | 2021-10-26 | 苏州森合知库机器人科技有限公司 | Inspection robot in roadway scene and navigation method thereof |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201037946Y (en) * | 2007-05-16 | 2008-03-19 | 李成龙 | Acoustic control household intelligent robot |
| CN202798812U (en) * | 2012-10-10 | 2013-03-13 | 南京铁道职业技术学院 | Intelligent household security system based on 3G cell phone control |
| CN103281223A (en) * | 2013-05-15 | 2013-09-04 | 五邑大学 | Modernized intelligent home security system |
| US20130253703A1 (en) * | 2012-03-20 | 2013-09-26 | Sony Corporation | Mobile robotic assistant for multipurpose applications |
| CN103383562A (en) * | 2013-06-26 | 2013-11-06 | 深圳市易图资讯有限公司 | Intelligent house management system |
-
2013
- 2013-11-13 CN CN201310565632.8A patent/CN103576660B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201037946Y (en) * | 2007-05-16 | 2008-03-19 | 李成龙 | Acoustic control household intelligent robot |
| US20130253703A1 (en) * | 2012-03-20 | 2013-09-26 | Sony Corporation | Mobile robotic assistant for multipurpose applications |
| CN202798812U (en) * | 2012-10-10 | 2013-03-13 | 南京铁道职业技术学院 | Intelligent household security system based on 3G cell phone control |
| CN103281223A (en) * | 2013-05-15 | 2013-09-04 | 五邑大学 | Modernized intelligent home security system |
| CN103383562A (en) * | 2013-06-26 | 2013-11-06 | 深圳市易图资讯有限公司 | Intelligent house management system |
Cited By (33)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104020745B (en) * | 2014-06-18 | 2016-08-24 | 吴林涛 | A kind of intelligent domestic system |
| CN104020745A (en) * | 2014-06-18 | 2014-09-03 | 吴林涛 | Intelligent household system |
| CN105681062A (en) * | 2014-11-18 | 2016-06-15 | 小米科技有限责任公司 | Safety monitoring method and apparatus |
| CN104519322A (en) * | 2014-12-24 | 2015-04-15 | 安徽科鸣三维科技有限公司 | Machine vision target tracking system |
| CN104519322B (en) * | 2014-12-24 | 2017-08-18 | 芜湖林一电子科技有限公司 | A kind of machine vision Target Tracking System |
| WO2016107006A1 (en) * | 2014-12-31 | 2016-07-07 | 中兴通讯股份有限公司 | Intelligent camera monitoring method and apparatus |
| CN105812723A (en) * | 2014-12-31 | 2016-07-27 | 中兴通讯股份有限公司 | Intelligent camera monitoring method and device |
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| CN109085761A (en) * | 2018-08-16 | 2018-12-25 | 夏琦 | A kind of detection device and the smart home system using the device |
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| CN111811635B (en) * | 2020-07-07 | 2021-06-15 | 美钻石油钻采系统(上海)有限公司 | Underwater target monitoring device |
| CN113552889A (en) * | 2021-07-29 | 2021-10-26 | 苏州森合知库机器人科技有限公司 | Inspection robot in roadway scene and navigation method thereof |
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