CN104301680A - Cloud video agricultural monitoring and detecting method - Google Patents
Cloud video agricultural monitoring and detecting method Download PDFInfo
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Abstract
The invention provides a cloud video agricultural monitoring and detecting method and relates to the technical field of monitoring of crop growth. The cloud video agricultural monitoring and detecting method comprises the steps that an agricultural enterprise arranges video collecting devices on a production site, video information is packaged into an information packet, and the information packet is fed back to an operation platform through an information transmitting network; preliminary analysis is conducted on the collected video information, the collected video information is transmitted to a remote cloud computing center through the transmitting network; storage of a great number of video data is achieved by utilizing cloud computing processing capacity and cloud storage; characteristic information analysis is conducted on at least one video, so that overall feedback information is obtained, and the overall feedback information is transmitted to the operation platform of the production site through the transmitting network; the operation platform achieves optimal control over production according to the feedback information. According to the cloud video agricultural monitoring and detecting method, the application range is wide, hardware cost is reduced, operation and maintenance cost is reduced, workers can conveniently conduct maintenance and use, production cost is reduced, the utilization rate of resources is increased, the practicability is high, and popularization is easy.
Description
Technical field
The present invention relates to crop growth monitoring technique field, particularly relate to a kind of cloud video Agricultural Monitoring and Soil K+adsorption platform.
Background technology
Intensive manufacture is the important directions of agricultural development, and intensive manufacture refers in activity in production, by the raising of production factors quality, want the increase of cellulose content, key element throws people concentrates and the mode of production of benefit is promoted in the adjustment of factor combination mode.In brief, intensive is relative poor, and intensive management is recombinated to all key elements of operation for basic with benefit (Social benefit and economic benefit), realizes minimum cost and obtain maximum investment repayment.Along with the proportion of large-scale production in agricultural production accounts for increases gradually, information technology is also increasing in agricultural production, and computer vision technique is one of them important aspect.
Utilize computer vision technique can monitor crop growing state in agricultural production, infer according to plant-growth model analysis the data being most appropriate to produce, and then production is regulated and controled, reach the Optimal Production environment of plant growth, promote to produce.
The developing into solve the problem of cloud computing provides a kind of new thinking.Long-range cloud platform can provide distributed computational service for agribusiness, and agribusiness does not need to set up computing platform in this locality, as long as pay service fee just realize the analytical work to agriculture video image by cloud computing center.For agribusiness, utilize cloud computing technology to carry out agriculture video analysis, greatly can reduce production cost; The more important thing is, cloud platform makes enterprise need not waste excess resource in information construction, can be absorbed in agricultural production, for specification, fast intensive agricultural development provide new approach.
Summary of the invention
For the weak point existed in the problems referred to above, the invention provides a kind of cloud video Agricultural Monitoring and detection method, make it applied widely, reduce hardware cost, O&M cost, facilitate staff to safeguard use, save production cost, improve resource utilization, practical, be easy to promote.
In order to solve the problem, the invention provides a kind of cloud video Agricultural Monitoring and detection method, it is characterized in that, comprise the following steps:
S10, agribusiness arrange video acquisition device in production scene, the video information of video acquisition device measurand that Real-time Collection is made up of one or more farmland crops under the control of operating platform operational order, and video information is packaged into packets of information returns to operating platform by information transmission network;
S20, operating platform do initial analysis to the video information collected, and are transferred to long-range cloud computing center after carrying out feature extraction by transmission network;
S30, cloud computing center utilize cloud computing disposal ability and cloud storage to realize multitude of video data and store, and ensure that agricultural product production process can be watched in playback;
S40, the cloud computing center at least one road video to agribusiness of at least one place carries out characteristic information analysis, obtains global feedback information, is transferred to the operating platform of production scene by transmission network;
The operating platform of S50, production scene, according to feedback information, by manipulating external Controlling vertex, realizes the Optimal regulation and control to producing;
S60, network electricity business platform to be combined with cloud Video Supervision Technique, user to be connected with cloud computing center by network electricity business platform, to operate personal terminal enforcement remote monitoring and televideo, the viewing date can also be selected.
2, cloud video Agricultural Monitoring as claimed in claim 1 and detection method, it is characterized in that, in described step S10, described video information comprises: to be adjusted the distance at scene, farmland distance parameter that the nearest crops of video frequency pick-up head demarcate, the zoom magnification of the many groups farmland video image absorbed by described video frequency pick-up head and employing thereof and resolution parameter by Man Machine Interface input.
3, cloud video Agricultural Monitoring as claimed in claim 1 and detection method, it is characterized in that, in described step S10, described back-end operations platform receives described packets of information and deblocking, parse the video information of described measurand, obtains crops parameter according to carrying out analytical calculation to the basic colors of image pixel in described video information and preserves.
4, cloud video Agricultural Monitoring as claimed in claim 1 and detection method, is characterized in that, in described step S20, further comprising the steps of:
1) histogram equalization is done to image, image is evenly distributed in gray scale;
2) rim detection is done to image, obtain the image length of calibration line, contrast with the physical length of calibration line, obtain the engineer's scale of length in pixels and physical length;
3) Threshold segmentation is done to image, utilize the function library in OpenCV to calculate vegeto-animal relevant parameter, estimate length and the quality of production scene plant or animal according to calibration line; Wherein in the Operational preparation stage, training set is set up to the plant after Threshold segmentation or animal pattern, is sent to cloud computing center, obtain model of cognition by the training of SVM method;
4) obtain the characteristic information of frame of video through image procossing, be packaged into the information that data structure is 0-1 character string, send to cloud computing center, each character string represents a frame, and each character of character string represents a pixel.
5, cloud video Agricultural Monitoring as claimed in claim 1 and detection method, is characterized in that, in described step S40, further comprising the steps of:
S401, be the characteristic information of 0-1 character string by the data structure that ARM plate sends, be read as characteristic vector;
S402, characteristic vector are mated with training set, carry out feature identification and location according to plant or animal pattern to production scene different animals or plant, if target is animal enter step S3, if target is plant enter step S404;
S403, utilize particle filter method to carry out multiple target tracking to animal, and trace information is carried out recording and based on the survival condition of animal behavior model analysis animal, obtains the regulation and controlling of information that can meet animals comfortable degree;
The information such as S404, the area being obtained plant leaf blade by image characteristics extraction, length, texture, coupling plant leaf blade feature database, analyzes plant and is growth conditions and is met the regulation and controlling of information of plant growth.
Compared with prior art, the present invention has the following advantages:
The cloud computing platform consisted of large-scale computer cluster provides public computational service for agriculture video image, for agribusiness provides a kind of simple technology upgrading approach, avoid the input that agribusiness is excessive on unfamiliar computer hardware and hardware O&M; Applied widely, can be widely used in, in the animal feeding in agricultural production, plant cultivation, ensureing that animal and plant growth is in best production environment all the time; Reduce hardware cost, O&M cost, facilitate staff to safeguard use, save production cost, improve resource utilization, practical, be easy to promote.
Accompanying drawing explanation
Fig. 1 is schematic flow sheet of the present invention.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with accompanying drawing and example, the present invention is described in further detail, but example is not as a limitation of the invention.
As shown in Figure 1, embodiments of the invention comprise the following steps:
S10, agribusiness arrange video acquisition device in production scene, the video information of video acquisition device measurand that Real-time Collection is made up of one or more farmland crops under the control of operating platform operational order, and video information is packaged into packets of information returns to operating platform by information transmission network;
S20, operating platform do initial analysis to the video information collected, and are transferred to long-range cloud computing center after carrying out feature extraction by transmission network;
S30, cloud computing center utilize cloud computing disposal ability and cloud storage to realize multitude of video data and store, and ensure that agricultural product production process can be watched in playback;
S40, the cloud computing center at least one road video to agribusiness of at least one place carries out characteristic information analysis, obtains global feedback information, is transferred to the operating platform of production scene by transmission network;
The operating platform of S50, production scene, according to feedback information, by manipulating external Controlling vertex, realizes the Optimal regulation and control to producing;
S60, network electricity business platform to be combined with cloud Video Supervision Technique, user to be connected with cloud computing center by network electricity business platform, to operate personal terminal enforcement remote monitoring and televideo, the viewing date can also be selected.
Further, in described step S10, described video information comprises: to be adjusted the distance at scene, farmland distance parameter that the nearest crops of video frequency pick-up head demarcate, the zoom magnification of the many groups farmland video image absorbed by described video frequency pick-up head and employing thereof and resolution parameter by Man Machine Interface input.
Further, in described step S10, described back-end operations platform receives described packets of information and deblocking, parse the video information of described measurand, obtains crops parameter according to carrying out analytical calculation to the basic colors of image pixel in described video information and preserves.
Further, in described step S20, further comprising the steps of:
1) histogram equalization is done to image, image is evenly distributed in gray scale;
2) rim detection is done to image, obtain the image length of calibration line, contrast with the physical length of calibration line, obtain the engineer's scale of length in pixels and physical length;
3) Threshold segmentation is done to image, utilize the function library in OpenCV to calculate vegeto-animal relevant parameter, estimate length and the quality of production scene plant or animal according to calibration line; Wherein in the Operational preparation stage, training set is set up to the plant after Threshold segmentation or animal pattern, is sent to cloud computing center, obtain model of cognition by the training of SVM method;
4) obtain the characteristic information of frame of video through image procossing, be packaged into the information that data structure is 0-1 character string, send to cloud computing center, each character string represents a frame, and each character of character string represents a pixel.
Further, in described step S40, further comprising the steps of:
S401, be the characteristic information of 0-1 character string by the data structure that ARM plate sends, be read as characteristic vector;
S402, characteristic vector are mated with training set, carry out feature identification and location according to plant or animal pattern to production scene different animals or plant, if target is animal enter step S3, if target is plant enter step S404;
S403, utilize particle filter method to carry out multiple target tracking to animal, and trace information is carried out recording and based on the survival condition of animal behavior model analysis animal, obtains the regulation and controlling of information that can meet animals comfortable degree;
The information such as S404, the area being obtained plant leaf blade by image characteristics extraction, length, texture, coupling plant leaf blade feature database, analyzes plant and is growth conditions and is met the regulation and controlling of information of plant growth.
To the above-mentioned explanation of the disclosed embodiments, professional and technical personnel in the field are realized or uses the present invention.To be apparent for those skilled in the art to the multiple amendment of these embodiments, General Principle as defined herein can without departing from the spirit or scope of the present invention, realize in other embodiments.Therefore, the present invention can not be restricted to these embodiments shown in this article, but will meet the widest scope consistent with principle disclosed herein and features of novelty.
Claims (5)
1. cloud video Agricultural Monitoring as claimed in claim 1 and detection method, is characterized in that, comprise the following steps:
S10, agribusiness arrange video acquisition device in production scene, the video information of video acquisition device measurand that Real-time Collection is made up of one or more farmland crops under the control of operating platform operational order, and video information is packaged into packets of information returns to operating platform by information transmission network;
S20, operating platform do initial analysis to the video information collected, and are transferred to long-range cloud computing center after carrying out feature extraction by transmission network;
S30, cloud computing center utilize cloud computing disposal ability and cloud storage to realize multitude of video data and store, and ensure that agricultural product production process can be watched in playback;
S40, the cloud computing center at least one road video to agribusiness of at least one place carries out characteristic information analysis, obtains global feedback information, is transferred to the operating platform of production scene by transmission network;
The operating platform of S50, production scene, according to feedback information, by manipulating external Controlling vertex, realizes the Optimal regulation and control to producing;
S60, network electricity business platform to be combined with cloud Video Supervision Technique, user to be connected with cloud computing center by network electricity business platform, to operate personal terminal enforcement remote monitoring and televideo, the viewing date can also be selected.
2. cloud video Agricultural Monitoring as claimed in claim 1 and detection method, it is characterized in that, in described step S10, described video information comprises: to be adjusted the distance at scene, farmland distance parameter that the nearest crops of video frequency pick-up head demarcate, the zoom magnification of the many groups farmland video image absorbed by described video frequency pick-up head and employing thereof and resolution parameter by Man Machine Interface input.
3. cloud video Agricultural Monitoring as claimed in claim 1 and detection method, it is characterized in that, in described step S10, described back-end operations platform receives described packets of information and deblocking, parse the video information of described measurand, obtains crops parameter according to carrying out analytical calculation to the basic colors of image pixel in described video information and preserves.
4. cloud video Agricultural Monitoring as claimed in claim 1 and detection method, is characterized in that, in described step S20, further comprising the steps of:
1) histogram equalization is done to image, image is evenly distributed in gray scale;
2) rim detection is done to image, obtain the image length of calibration line, contrast with the physical length of calibration line, obtain the engineer's scale of length in pixels and physical length;
3) Threshold segmentation is done to image, utilize the function library in OpenCV to calculate vegeto-animal relevant parameter, estimate length and the quality of production scene plant or animal according to calibration line; Wherein in the Operational preparation stage, training set is set up to the plant after Threshold segmentation or animal pattern, is sent to cloud computing center, obtain model of cognition by the training of SVM method;
4) obtain the characteristic information of frame of video through image procossing, be packaged into the information that data structure is 0-1 character string, send to cloud computing center, each character string represents a frame, and each character of character string represents a pixel.
5. cloud video Agricultural Monitoring as claimed in claim 1 and detection method, is characterized in that, in described step S40, further comprising the steps of:
S401, be the characteristic information of 0-1 character string by the data structure that ARM plate sends, be read as characteristic vector;
S402, characteristic vector are mated with training set, carry out feature identification and location according to plant or animal pattern to production scene different animals or plant, if target is animal enter step S3, if target is plant enter step S404;
S403, utilize particle filter method to carry out multiple target tracking to animal, and trace information is carried out recording and based on the survival condition of animal behavior model analysis animal, obtains the regulation and controlling of information that can meet animals comfortable degree;
The information such as S404, the area being obtained plant leaf blade by image characteristics extraction, length, texture, coupling plant leaf blade feature database, analyzes plant and is growth conditions and is met the regulation and controlling of information of plant growth.
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| CN105898207A (en) * | 2015-01-26 | 2016-08-24 | 杭州海康威视数字技术股份有限公司 | Intelligent processing method and system of video data |
| CN106210623A (en) * | 2016-06-27 | 2016-12-07 | 石媛 | High in the clouds histogram distribution detection platform |
| CN108551473A (en) * | 2018-03-26 | 2018-09-18 | 武汉南博网络科技有限公司 | A kind of agricultural product communication method and device based on visual agricultural |
| CN113194275A (en) * | 2021-04-30 | 2021-07-30 | 重庆天智慧启科技有限公司 | Monitoring image preview system |
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